Protein tolerance to random amino acid change

Transcript errors generate amyloid-like proteins in huwman cells

Aging is characterized by the accumulation of proteins that display amyloid-like behavior. However, the molecular mechanisms by which these proteins arise remain unclear. Here, we demonstrate that amyloid-like proteins are produced in a variety of human cell types, including stem cells, brain organoids and fully differentiated neurons by mistakes that occur in messenger RNA molecules. Some of these mistakes generate mutant proteins already known to cause disease, while others generate proteins that have not been observed before. Moreover, we show that these mistakes increase when cells are exposed to DNA damage, a major hallmark of human aging. When taken together, these experiments suggest a mechanistic link between the normal aging process and age-related diseases.

Enriching productive mutational paths accelerates enzyme evolution

Darwinian evolution has given rise to all the enzymes that enable life on Earth. Mimicking natural selection, scientists have learned to tailor these biocatalysts through recursive cycles of mutation, selection and amplification, often relying on screening large protein libraries to productively modulate the complex interplay between protein structure, dynamics and function. Here we show that by removing destabilizing mutations at the library design stage and taking advantage of recent advances in gene synthesis, we can accelerate the evolution of a computationally designed enzyme. In only five rounds of evolution, we generated a Kemp eliminase-an enzymatic model system for proton transfer from carbon-that accelerates the proton abstraction step >108-fold over the uncatalyzed reaction. Recombining the resulting variant with a previously evolved Kemp eliminase HG3.17, which exhibits similar activity but differs by 29 substitutions, allowed us to chart the topography of the designer enzyme's fitness landscape, highlighting that a given protein scaffold can accommodate several, equally viable solutions to a specific catalytic problem.

Unsupervised evolution of protein and antibody complexes with a structure-informed language model

Large language models trained on sequence information alone can learn high-level principles of protein design. However, beyond sequence, the three-dimensional structures of proteins determine their specific function, activity, and evolvability. Here, we show that a general protein language model augmented with protein structure backbone coordinates can guide evolution for diverse proteins without the need to model individual functional tasks. We also demonstrate that ESM-IF1, which was only trained on single-chain structures, can be extended to engineer protein complexes. Using this approach, we screened about 30 variants of two therapeutic clinical antibodies used to treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We achieved up to 25-fold improvement in neutralization and 37-fold improvement in affinity against antibody-escaped viral variants of concern BQ.1.1 and XBB.1.5, respectively. These findings highlight the advantage of integrating structural information to identify efficient protein evolution trajectories without requiring any task-specific training data.

Utilization of low-stability variants in protein evolutionary engineering

Evolutionary engineering involves repeated mutations and screening and is widely used to modify protein functions. However, it is important to diversify evolutionary pathways to eliminate the bias and limitations of the variants by using traditionally unselected variants. In this study, we focused on low-stability variants that are commonly excluded from evolutionary processes and tested a method that included an additional restabilization step. The esterase from the thermophilic bacterium Alicyclobacillus acidocaldarius was used as a model protein, and its activity at its optimum temperature of 65 °C was improved by evolutionary experiments using random mutations by error-prone PCR. After restabilization using low-stability variants with low-temperature (37 °C) activity, several re-stabilizing variants were obtained from a large number of variant libraries. Some of the restabilized variants achieved by removing the destabilizing mutations showed higher activity than that of the wild-type protein. This implies that low-stability variants with low-temperature activity can be re-evolved for future use. This method will enable further diversification of evolutionary pathways.

Computational scoring and experimental evaluation of enzymes generated by neural networks

In recent years, generative protein sequence models have been developed to sample novel sequences. However, predicting whether generated proteins will fold and function remains challenging. We evaluate a set of 20 diverse computational metrics to assess the quality of enzyme sequences produced by three contrasting generative models: ancestral sequence reconstruction, a generative adversarial network and a protein language model. Focusing on two enzyme families, we expressed and purified over 500 natural and generated sequences with 70-90% identity to the most similar natural sequences to benchmark computational metrics for predicting in vitro enzyme activity. Over three rounds of experiments, we developed a computational filter that improved the rate of experimental success by 50-150%. The proposed metrics and models will drive protein engineering research by serving as a benchmark for generative protein sequence models and helping to select active variants for experimental testing.

Scaling up Functional Analyses of the G Protein-Coupled Receptor Rhodopsin

Eukaryotic cells use G protein-coupled receptors (GPCRs) to convert external stimuli into internal signals to elicit cellular responses. However, how mutations in GPCR-coding genes affect GPCR activation and downstream signaling pathways remain poorly understood. Approaches such as deep mutational scanning show promise in investigations of GPCRs, but a high-throughput method to measure rhodopsin activation has yet to be achieved. Here, we scale up a fluorescent reporter assay in budding yeast that we engineered to study rhodopsin's light-activated signal transduction. Using this approach, we measured the mutational effects of over 1200 individual human rhodopsin mutants, generated by low-frequency random mutagenesis of the GPCR rhodopsin (RHO) gene. Analysis of the data in the context of rhodopsin's three-dimensional structure reveals that transmembrane helices are generally less tolerant to mutations compared to flanking helices that face the lipid bilayer, which suggest that mutational tolerance is contingent on both the local environment surrounding specific residues and the specific position of these residues in the protein structure. Comparison of functional scores from our screen to clinically identified rhodopsin disease variants found many pathogenic mutants to be loss of function. Lastly, functional scores from our assay were consistent with a complex counterion mechanism involved in ligand-binding and rhodopsin activation. Our results demonstrate that deep mutational scanning is possible for rhodopsin activation and can be an effective method for revealing properties of mutational tolerance that may be generalizable to other transmembrane proteins.

Structure of the space of folding protein sequences defined by large language models

Proteins populate a manifold in the high-dimensional sequence space whose geometrical structure guides their natural evolution. Leveraging recently-developed structure prediction tools based on transformer models, we first examine the protein sequence landscape as defined by an effective energy that is a proxy of sequence foldability. This landscape shares characteristics with optimization challenges encountered in machine learning and constraint satisfaction problems. Our analysis reveals that natural proteins predominantly reside in wide, flat minima within this energy landscape. To investigate further, we employ statistical mechanics algorithms specifically designed to explore regions with high local entropy in relatively flat landscapes. Our findings indicate that these specialized algorithms can identify valleys with higher entropy compared to those found using traditional methods such as Monte Carlo Markov Chains. In a proof-of-concept case, we find that these highly entropic minima exhibit significant similarities to natural sequences, especially in critical key sites and local entropy. Additionally, evaluations through Molecular Dynamics suggests that the stability of these sequences closely resembles that of natural proteins. Our tool combines advancements in machine learning and statistical physics, providing new insights into the exploration of sequence landscapes where wide, flat minima coexist alongside a majority of narrower minima.

Sequence-activity mapping via depletion reveals striking mutational tolerance and elucidates functional motifs in Tur1a antimicrobial peptide

Proline-rich antimicrobial peptides (PrAMPs) are attractive antibiotic candidates that target gram-negative bacteria ribosomes. We elucidated the sequence-function landscape of 43 000 variants of a recently discovered family member, Tur1a, using the validated SAMP-Dep platform that measures intracellular AMP potency in a high-throughput manner via self-depletion of the cellular host. The platform exhibited high replicate reproducibility (ρ = 0.81) and correlation between synonymous genetic variants (R2 = 0.93). Only two segments within Tur1a exhibited stringent mutational requirements to sustain potency: residues 9YLP11 and 19FP20. This includes the aromatic residue in the hypothesized binding domain but not the PRP domain. Along with unexpected mutational tolerance of PRP, the data contrast hypothesized importance of the 1RRIR4 motif and arginines in general. In addition to mutational tolerance of residue segments with presumed significance, 77% of mutations are functionally neutral. Multimutant performance mainly shows compounding effects from removed combinations of prolines and arginines in addition to the two segments of residues showing individual importance. Several variants identified as active from SAMP-Dep were externally produced and maintained activity when applied to susceptible species exogenously.

Inverse folding of protein complexes with a structure-informed language model enables unsupervised antibody evolution

Large language models trained on sequence information alone are capable of learning high level principles of protein design. However, beyond sequence, the three-dimensional structures of proteins determine their specific function, activity, and evolvability. Here we show that a general protein language model augmented with protein structure backbone coordinates and trained on the inverse folding problem can guide evolution for diverse proteins without needing to explicitly model individual functional tasks. We demonstrate inverse folding to be an effective unsupervised, structure-based sequence optimization strategy that also generalizes to multimeric complexes by implicitly learning features of binding and amino acid epistasis. Using this approach, we screened ~30 variants of two therapeutic clinical antibodies used to treat SARS-CoV-2 infection and achieved up to 26-fold improvement in neutralization and 37-fold improvement in affinity against antibody-escaped viral variants-of-concern BQ.1.1 and XBB.1.5, respectively. In addition to substantial overall improvements in protein function, we find inverse folding performs with leading experimental success rates among other reported machine learning-guided directed evolution methods, without requiring any task-specific training data.

A porphyrin-based molecular cage guided by designed local-electric field is highly selective and efficient

The present work outlines a general methodology for designing efficient catalytic machineries that can easily be tweaked to meet the demands of the target reactions. This work utilizes a principle of the designed local electric field (LEF) as the driver for an efficient catalyst. It is demonstrated that by tweaking the LEF, we can catalyze the desired hydroxylation products with enantioselectivity that can be changed at will. Using computation tools, we caged a synthetic analog of heme porphyrin (HM1) and investigated the pharmaceutically relevant conversion of tetralin to tetralol, inside the modified supramolecular cage. The QM/MM calculations demonstrate a resulting catalytic efficiency with virtually absolute R-selectivity for the tetralin hydroxylation. Our calculations show that the LEF of the supramolecular cage and HM1 exert a strong electric field along the Fe-O reaction axis, which is the main driving force for enhanced reactivity. At the same time, the supramolecular cage applies a lateral LEF that regulates the enantioselectivity. We further demonstrate that swapping the charged/polar substitution in the supramolecular cage switches the lateral LEF which changes the enantioselectivity of hydroxylation from R to S.

ASCARIS: Positional feature annotation and protein structure-based representation of single amino acid variations

Background

Genomic variations may cause deleterious effects on protein functionality and perturb biological processes. Elucidating the effects of variations is critical for developing novel treatment strategies for diseases of genetic origin. Computational approaches have been aiding the work in this field by modeling and analyzing the mutational landscape. However, new approaches are required, especially for accurate representation and data-centric analysis of sequence variations.

Method

In this study, we propose ASCARIS (Annotation and StruCture-bAsed RepresentatIon of Single amino acid variations), a method for the featurization (i.e., quantitative representation) of single amino acid variations (SAVs), which could be used for a variety of purposes, such as predicting their functional effects or building multi-omics-based integrative models. ASCARIS utilizes the direct and spatial correspondence between the location of the SAV on the sequence/structure and 30 different types of positional feature annotations (e.g., active/lipidation/glycosylation sites; calcium/metal/DNA binding, inter/transmembrane regions, etc.), along with structural features and physicochemical properties. The main novelty of this method lies in constructing reusable numerical representations of SAVs via functional annotations.

Results

We statistically analyzed the relationship between these features and the consequences of variations and found that each carries information in this regard. To investigate potential applications of ASCARIS, we trained variant effect prediction models that utilize our SAV representations as input. We carried out an ablation study and a comparison against the state-of-the-art methods and observed that ASCARIS has a competing and complementary performance against widely-used predictors. ASCARIS can be used alone or in combination with other approaches to represent SAVs from a functional perspective. ASCARIS is available as a programmatic tool at https://github.com/HUBioDataLab/ASCARIS and as a web-service at https://huggingface.co/spaces/HUBioDataLab/ASCARIS.

LibGENiE - A bioinformatic pipeline for the design of information-enriched enzyme libraries

Enzymes are potent catalysts with high specificity and selectivity. To leverage nature's synthetic potential for industrial applications, various protein engineering techniques have emerged which allow to tailor the catalytic, biophysical, and molecular recognition properties of enzymes. However, the many possible ways a protein can be altered forces researchers to carefully balance between the exhaustiveness of an enzyme screening campaign and the required resources. Consequently, the optimal engineering strategy is often defined on a case-by-case basis. Strikingly, while predicting mutations that lead to an improved target function is challenging, here we show that the prediction and exclusion of deleterious mutations is a much more straightforward task as analyzed for an engineered carbonic acid anhydrase, a transaminase, a squalene-hopene cyclase and a Kemp eliminase. Combining such a pre-selection of allowed residues with advanced gene synthesis methods opens a path toward an efficient and generalizable library construction approach for protein engineering. To give researchers easy access to this methodology, we provide the website LibGENiE containing the bioinformatic tools for the library design workflow.

Translation regulation by a guanidine-II riboswitch is highly tunable in sensitivity, dynamic range, and apparent cooperativity

Riboswitches function as important translational regulators in bacteria. Comprehensive mutational analysis of transcriptional riboswitches has been used to probe the energetic intricacies of interplay between the aptamer and expression platform, but translational riboswitches have been inaccessible to massively parallel techniques. The guanidine-II (gdm-II) riboswitch is an exclusively translational class. We have integrated RelE cleavage with next-generation sequencing to quantify ligand-dependent changes in translation initiation for all single and double mutations of the Pseudomonas aeruginosa gdm-II riboswitch, a total of more than 23,000 variants. This extensive mutational analysis is consistent with the prominent features of the bioinformatic consensus. These data indicate, unexpectedly, that direct sequestration of the Shine-Dalgarno sequence is dispensable for riboswitch function. Additionally, this comprehensive data set reveals important positions not identified in previous computational and crystallographic studies. Mutations in the variable linker region stabilize alternate conformations. The double mutant data reveal the functional importance of the previously modeled P0b helix formed by the 5' and 3' tails that serves as the basis for translational control. Additional mutations to GU wobble base pairs in both P1 and P2 reveal how the apparent cooperativity of the system involves an intricate network of communication between the two binding sites. This comprehensive examination of a translational riboswitch's expression platform illuminates how the riboswitch is precisely tuned and tunable with regard to ligand sensitivity, the amplitude of expression between ON and OFF states, and the cooperativity of ligand binding.

Mapping the neutralizing specificity of human anti-HIV serum by deep mutational scanning

Understanding the specificities of human serum antibodies that broadly neutralize HIV can inform prevention and treatment strategies. Here, we describe a deep mutational scanning system that can measure the effects of combinations of mutations to HIV envelope (Env) on neutralization by antibodies and polyclonal serum. We first show that this system can accurately map how all functionally tolerated mutations to Env affect neutralization by monoclonal antibodies. We then comprehensively map Env mutations that affect neutralization by a set of human polyclonal sera that neutralize diverse strains of HIV and target the site engaging the host receptor CD4. The neutralizing activities of these sera target different epitopes, with most sera having specificities reminiscent of individual characterized monoclonal antibodies, but one serum targeting two epitopes within the CD4-binding site. Mapping the specificity of the neutralizing activity in polyclonal human serum will aid in assessing anti-HIV immune responses to inform prevention strategies.

Protein-Inspired Control over Synthetic Polymer Folding for Structured Functional Nanoparticles in Water

The folding of proteins into functional nanoparticles with defined 3D structures has inspired chemists to create simple synthetic systems mimicking protein properties. The folding of polymers into nanoparticles in water proceeds via different strategies, resulting in the global compaction of the polymer chain. Herein, we review the different methods available to control the conformation of synthetic polymers and collapse/fold them into structured, functional nanoparticles, such as hydrophobic collapse, supramolecular self-assembly, and covalent cross-linking. A comparison is made between the design principles of protein folding to synthetic polymer folding and the formation of structured nanocompartments in water, highlighting similarities and differences in design and function. We also focus on the importance of structure for functional stability and diverse applications in complex media and cellular environments.

Mapping the neutralizing specificity of human anti-HIV serum by deep mutational scanning

Understanding the specificities of human serum antibodies that broadly neutralize HIV can inform prevention and treatment strategies. Here we describe a deep mutational scanning system that can measure the effects of combinations of mutations to HIV envelope (Env) on neutralization by antibodies and polyclonal serum. We first show that this system can accurately map how all functionally tolerated mutations to Env affect neutralization by monoclonal antibodies. We then comprehensively map Env mutations that affect neutralization by a set of human polyclonal sera known to target the CD4-binding site that neutralize diverse strains of HIV. The neutralizing activities of these sera target different epitopes, with most sera having specificities reminiscent of individual characterized monoclonal antibodies, but one sera targeting two epitopes within the CD4 binding site. Mapping the specificity of the neutralizing activity in polyclonal human serum will aid in assessing anti-HIV immune responses to inform prevention strategies.

Efficient Exploration of Sequence Space by Sequence-Guided Protein Engineering and Design

The rapid growth of sequence databases over the past two decades means that protein engineers faced with optimizing a protein for any given task will often have immediate access to a vast number of related protein sequences. These sequences encode information about the evolutionary history of the protein and the underlying sequence requirements to produce folded, stable, and functional protein variants. Methods that can take advantage of this information are an increasingly important part of the protein engineering tool kit. In this Perspective, we discuss the utility of sequence data in protein engineering and design, focusing on recent advances in three main areas: the use of ancestral sequence reconstruction as an engineering tool to generate thermostable and multifunctional proteins, the use of sequence data to guide engineering of multipoint mutants by structure-based computational protein design, and the use of unlabeled sequence data for unsupervised and semisupervised machine learning, allowing the generation of diverse and functional protein sequences in unexplored regions of sequence space. Altogether, these methods enable the rapid exploration of sequence space within regions enriched with functional proteins and therefore have great potential for accelerating the engineering of stable, functional, and diverse proteins for industrial and biomedical applications.

Analyses of Mutation Displacements from Homology Models

Evaluation of the structural perturbations introduced by a single amino acid mutation is the main issue for protein structural biology. We propose here to present some recent advances in methods, allowing the splitting of distortion between the actual substitution effect and the contribution of the local flexibility of the position where the mutation occurs. Its main drawback is the need of many structures with a single mutation in each of them. To bypass this difficulty, we propose to use molecular modeling tools, with several software enabling us to build a model from a template, given the sequence. As a proof of concept, we rely on a gold standard, the human lysozyme. Both wild-type and three mutant structures are available in the PDB. Two of these mutations result in amyloid fibril formation, and the last one is neutral. As a conclusion, irrespective of the algorithm used for modeling, side chain conformations at the site of mutation are reliable, although long-range effects are out of reach of these tools.

Conflicting effects of recombination on the evolvability and robustness in neutrally evolving populations

Understanding the benefits and costs of recombination under different scenarios of evolutionary adaptation remains an open problem for theoretical and experimental research. In this study, we focus on finite populations evolving on neutral networks comprising viable and unfit genotypes. We provide a comprehensive overview of the effects of recombination by jointly considering different measures of evolvability and mutational robustness over a broad parameter range, such that many evolutionary regimes are covered. We find that several of these measures vary non-monotonically with the rates of mutation and recombination. Moreover, the presence of unfit genotypes that introduce inhomogeneities in the network of viable states qualitatively alters the effects of recombination. We conclude that conflicting trends induced by recombination can be explained by an emerging trade-off between evolvability on the one hand, and mutational robustness on the other. Finally, we discuss how different implementations of the recombination scheme in theoretical models can affect the observed dependence on recombination rate through a coupling between recombination and genetic drift.

Ancestral library identifies conserved reprogrammable liver motif on AAV capsid

Gene therapy is emerging as a modality in 21st-century medicine. Adeno-associated viral (AAV) gene transfer is a leading technology to achieve efficient and durable expression of a therapeutic transgene. However, the structural complexity of the capsid has constrained efforts to engineer the particle toward improved clinical safety and efficacy. Here, we generate a curated library of barcoded AAVs with mutations across a variety of functionally relevant motifs. We then screen this library in vitro and in vivo in mice and nonhuman primates, enabling a broad, multiparametric assessment of every vector within the library. Among the results, we note a single residue that modulates liver transduction across all interrogated models while preserving transduction in heart and skeletal muscles. Moreover, we find that this mutation can be grafted into AAV9 and leads to profound liver detargeting while retaining muscle transduction-a finding potentially relevant to preventing hepatoxicities seen in clinical studies.

Engineering functional thermostable proteins using ancestral sequence reconstruction

Natural proteins are often only slightly more stable in the native state than the denatured state, and an increase in environmental temperature can easily shift the balance toward unfolding. Therefore, the engineering of proteins to improve protein stability is an area of intensive research. Thermostable proteins are required to withstand industrial process conditions, for increased shelf-life of protein therapeutics, for developing robust 'biobricks' for synthetic biology applications, and for research purposes (e.g., structure determination). In addition, thermostability buffers the often destabilizing effects of mutations introduced to improve other properties. Rational design approaches to engineering thermostability require structural information, but even with advanced computational methods, it is challenging to predict or parameterize all the relevant structural factors with sufficient precision to anticipate the results of a given mutation. Directed evolution is an alternative when structures are unavailable but requires extensive screening of mutant libraries. Recently, however, bioinspired approaches based on phylogenetic analyses have shown great promise. Leveraging the rapid expansion in sequence data and bioinformatic tools, ancestral sequence reconstruction can generate highly stable folds for novel applications in industrial chemistry, medicine, and synthetic biology. This review provides an overview of the factors important for successful inference of thermostable proteins by ancestral sequence reconstruction and what it can reveal about the determinants of stability in proteins.

Structural variation between neuropeptide isoforms affects function in the lobster cardiac system

Neuronal responses to peptide signaling are determined by the specific binding of a peptide to its receptor(s). For example, isoforms of the same peptide family can drive distinct responses in the same circuit by having different affinities for the same receptor, by having each isoform bind to a different receptor, or by a combination of these scenarios. Small changes in peptide composition can alter the binding kinetics and overall physiological response to a given peptide. In the American lobster (Homarus americanus), native isoforms of C-type allatostatins (AST-Cs) usually decrease heartbeat frequency and alter contraction force. However, one of the three AST-C isoforms, AST-C II, drives a cardiac response distinct from the response elicited by the other two. To investigate the aspects of the peptide that might be responsible for these differential responses, we altered various features of each peptide sequence. Although the presence of an amide group at the end of a peptide sequence (amidation) is often essential for determining physiological function, we demonstrate that C-terminal amidation does not dictate the AST-C response in the lobster cardiac system. However, single amino acid substitution within the consensus sequence did account for many of the differences in specific response characteristics (e.g. contraction frequency or force).

Paleoproteomics

Paleoproteomics, the study of ancient proteins, is a rapidly growing field at the intersection of molecular biology, paleontology, archaeology, paleoecology, and history. Paleoproteomics research leverages the longevity and diversity of proteins to explore fundamental questions about the past. While its origins predate the characterization of DNA, it was only with the advent of soft ionization mass spectrometry that the study of ancient proteins became truly feasible. Technological gains over the past 20 years have allowed increasing opportunities to better understand preservation, degradation, and recovery of the rich bioarchive of ancient proteins found in the archaeological and paleontological records. Growing from a handful of studies in the 1990s on individual highly abundant ancient proteins, paleoproteomics today is an expanding field with diverse applications ranging from the taxonomic identification of highly fragmented bones and shells and the phylogenetic resolution of extinct species to the exploration of past cuisines from dental calculus and pottery food crusts and the characterization of past diseases. More broadly, these studies have opened new doors in understanding past human-animal interactions, the reconstruction of past environments and environmental changes, the expansion of the hominin fossil record through large scale screening of nondiagnostic bone fragments, and the phylogenetic resolution of the vertebrate fossil record. Even with these advances, much of the ancient proteomic record still remains unexplored. Here we provide an overview of the history of the field, a summary of the major methods and applications currently in use, and a critical evaluation of current challenges. We conclude by looking to the future, for which innovative solutions and emerging technology will play an important role in enabling us to access the still unexplored "dark" proteome, allowing for a fuller understanding of the role ancient proteins can play in the interpretation of the past.

Non-Equilibrium Protein Folding and Activation by ATP-Driven Chaperones

Recent experimental studies suggest that ATP-driven molecular chaperones can stabilize protein substrates in their native structures out of thermal equilibrium. The mechanism of such non-equilibrium protein folding is an open question. Based on available structural and biochemical evidence, I propose here a unifying principle that underlies the conversion of chemical energy from ATP hydrolysis to the conformational free energy associated with protein folding and activation. I demonstrate that non-equilibrium folding requires the chaperones to break at least one of four symmetry conditions. The Hsp70 and Hsp90 chaperones each break a different subset of these symmetries and thus they use different mechanisms for non-equilibrium protein folding. I derive an upper bound on the non-equilibrium elevation of the native concentration, which implies that non-equilibrium folding only occurs in slow-folding proteins that adopt an unstable intermediate conformation in binding to ATP-driven chaperones. Contrary to the long-held view of Anfinsen's hypothesis that proteins fold to their conformational free energy minima, my results predict that some proteins may fold into thermodynamically unstable native structures with the assistance of ATP-driven chaperones, and that the native structures of some chaperone-dependent proteins may be shaped by their chaperone-mediated folding pathways.

Ancestral sequence reconstruction of a cytochrome P450 family involved in chemical defence reveals the functional evolution of a promiscuous, xenobiotic-metabolizing enzyme in vertebrates

The cytochrome P450 family 1 enzymes (CYP1s) are a diverse family of hemoprotein monooxygenases, which metabolize many xenobiotics including numerous environmental carcinogens. However, their historical function and evolution remain largely unstudied. Here we investigate CYP1 evolution via the reconstruction and characterization of the vertebrate CYP1 ancestors. Younger ancestors and extant forms generally demonstrated higher activity toward typical CYP1 xenobiotic and steroid substrates than older ancestors, suggesting significant diversification away from the original CYP1 function. Caffeine metabolism appears to be a recently evolved trait of the CYP1A subfamily, observed in the mammalian CYP1A lineage, and may parallel the recent evolution of caffeine synthesis in multiple separate plant species. Likewise, the aryl hydrocarbon receptor agonist, 6-formylindolo[3,2-b]carbazole (FICZ) was metabolized to a greater extent by certain younger ancestors and extant forms, suggesting that activity toward FICZ increased in specific CYP1 evolutionary branches, a process that may have occurred in parallel to the exploitation of land where UV-exposure was higher than in aquatic environments. As observed with previous reconstructions of P450 enzymes, thermostability correlated with evolutionary age; the oldest ancestor was up to 35 °C more thermostable than the extant forms, with a ¹⁰T₅₀ (temperature at which 50% of the hemoprotein remains intact after 10 min) of 71 °C. This robustness may have facilitated evolutionary diversification of the CYP1s by buffering the destabilizing effects of mutations that conferred novel functions, a phenomenon which may also be useful in exploiting the catalytic versatility of these ancestral enzymes for commercial application as biocatalysts.

Evolutionary Landscapes of Host-Virus Arms Races

Vertebrate immune systems suppress viral infection using both innate restriction factors and adaptive immunity. Viruses mutate to escape these defenses, driving hosts to counterevolve to regain fitness. This cycle recurs repeatedly, resulting in an evolutionary arms race whose outcome depends on the pace and likelihood of adaptation by host and viral genes. Although viruses evolve faster than their vertebrate hosts, their proteins are subject to numerous functional constraints that impact the probability of adaptation. These constraints are globally defined by evolutionary landscapes, which describe the fitness and adaptive potential of all possible mutations. We review deep mutational scanning experiments mapping the evolutionary landscapes of both host and viral proteins engaged in arms races. For restriction factors and some broadly neutralizing antibodies, landscapes favor the host, which may help to level the evolutionary playing field against rapidly evolving viruses. We discuss the biophysical underpinnings of these landscapes and their therapeutic implications.

Mutant libraries reveal negative design shielding proteins from supramolecular self-assembly and relocalization in cells

Genetic mutations fuel organismal evolution but can also cause disease. As proteins are the cell’s workhorses, the ways in which mutations can disrupt their structure, stability, function, and interactions have been studied extensively. However, proteins evolve and function in a cellular context, and our ability to relate changes in protein sequence to cell-level phenotypes remains limited. In particular, the molecular mechanism underlying most disease-associated mutations is unknown. Here, we show that mutations changing a protein’s surface chemistry can dramatically impact its supramolecular self-assembly and localization in the cell. These results highlight the complex nature of genotype–phenotype relationships with a simple system.

Understanding the molecular consequences of mutations in proteins is essential to map genotypes to phenotypes and interpret the increasing wealth of genomic data. While mutations are known to disrupt protein structure and function, their potential to create new structures and localization phenotypes has not yet been mapped to a sequence space. To map this relationship, we employed two homo-oligomeric protein complexes in which the internal symmetry exacerbates the impact of mutations. We mutagenized three surface residues of each complex and monitored the mutations’ effect on localization and assembly phenotypes in yeast cells. While surface mutations are classically viewed as benign, our analysis of several hundred mutants revealed they often trigger three main phenotypes in these proteins: nuclear localization, the formation of puncta, and fibers. Strikingly, more than 50% of random mutants induced one of these phenotypes in both complexes. Analyzing the mutant’s sequences showed that surface stickiness and net charge are two key physicochemical properties associated with these changes. In one complex, more than 60% of mutants self-assembled into fibers. Such a high frequency is explained by negative design: charged residues shield the complex from self-interacting with copies of itself, and the sole removal of the charges induces its supramolecular self-assembly. A subsequent analysis of several other complexes targeted with alanine mutations suggested that such negative design is common. These results highlight that minimal perturbations in protein surfaces’ physicochemical properties can frequently drive assembly and localization changes in a cellular context.

OUP accepted manuscript

It is known that methods to estimate the rate of adaptive evolution, which are based on the McDonald–Kreitman test, can be biased by changes in effective population size. Here, we demonstrate theoretically that changes in population size can also generate an artifactual correlation between the rate of adaptive evolution and any factor that is correlated to the strength of selection acting against deleterious mutations. In this context, we have investigated whether several site-level factors influence the rate of adaptive evolution in the divergence of humans and chimpanzees, two species that have been inferred to have undergone population size contraction since they diverged. We find that the rate of adaptive evolution, relative to the rate of mutation, is higher for more exposed amino acids, lower for amino acid pairs that are more dissimilar in terms of their polarity, volume, and lower for amino acid pairs that are subject to stronger purifying selection, as measured by the ratio of the numbers of nonsynonymous to synonymous polymorphisms (p_N/p_S). All of these correlations are opposite to the artifactual correlations expected under contracting population size. We therefore conclude that these correlations are genuine.

Design of a Superpositively Charged Enzyme: Human Carbonic Anhydrase II Variant with Ferritin Encapsulation and Immobilization

Supercharged proteins exhibit high solubility and other desirable properties, but no engineered superpositively charged enzymes have previously been made. Superpositively charged variants of proteins such as green fluorescent protein have been efficiently encapsulated within Archaeoglobus fulgidus thermophilic ferritin (AfFtn). Encapsulation by supramolecular ferritin can yield systems with a variety of sequestered cargo. To advance applications in enzymology and green chemistry, we sought a general method for supercharging an enzyme that retains activity and is compatible with AfFtn encapsulation. The zinc metalloenzyme human carbonic anhydrase II (hCAII) is an attractive encapsulation target based on its hydrolytic activity and physiologic conversion of carbon dioxide to bicarbonate. A computationally designed variant of hCAII contains positively charged residues substituted at 19 sites on the protein's surface, resulting in a shift of the putative net charge from -1 to +21. This designed hCAII(+21) exhibits encapsulation within AfFtn without the need for fusion partners or additional reagents. The hCAII(+21) variant retains esterase activity comparable to the wild type and spontaneously templates the assembly of AfFtn 24mers around itself. The AfFtn-hCAII(+21) host-guest complex exhibits both greater activity and thermal stability when compared to hCAII(+21). Upon immobilization on a solid support, AfFtn-hCAII(+21) retains enzymatic activity and exhibits an enhancement of activity at elevated temperatures.

Silencing of the ER and Integrative Stress Responses in the Liver of Mice with Error-Prone Translation

Translational errors frequently arise during protein synthesis, producing misfolded and dysfunctional proteins. Chronic stress resulting from translation errors may be particularly relevant in tissues that must synthesize and secrete large amounts of secretory proteins. Here, we studied the proteostasis networks in the liver of mice that express the Rps2-A226Y ribosomal ambiguity (ram) mutation to increase the translation error rate across all proteins. We found that Rps2-A226Y mice lack activation of the eIF2 kinase/ATF4 pathway, the main component of the integrated stress response (ISR), as well as the IRE1 and ATF6 pathways of the ER unfolded protein response (ER-UPR). Instead, we found downregulation of chronic ER stress responses, as indicated by reduced gene expression for lipogenic pathways and acute phase proteins, possibly via upregulation of Sirtuin-1. In parallel, we observed activation of alternative proteostasis responses, including the proteasome and the formation of stress granules. Together, our results point to a concerted response to error-prone translation to alleviate ER stress in favor of activating alternative proteostasis mechanisms, most likely to avoid cell damage and apoptotic pathways, which would result from persistent activation of the ER and integrated stress responses.

Saturation Mutagenesis of the Transmembrane Region of HokC in Escherichia coli Reveals Its High Tolerance to Mutations

Cells adapt to different stress conditions, such as the antibiotics presence. This adaptation sometimes is achieved by changing relevant protein positions, of which the mutability is limited by structural constrains. Understanding the basis of these constrains represent an important challenge for both basic science and potential biotechnological applications. To study these constraints, we performed a systematic saturation mutagenesis of the transmembrane region of HokC, a toxin used by Escherichia coli to control its own population, and observed that 92% of single-point mutations are tolerated and that all the non-tolerated mutations have compensatory mutations that reverse their effect. We provide experimental evidence that HokC accumulates multiple compensatory mutations that are found as correlated mutations in the HokC family multiple sequence alignment. In agreement with these observations, transmembrane proteins show higher probability to present correlated mutations and are less densely packed locally than globular proteins; previous mutagenesis results on transmembrane proteins further support our observations on the high tolerability to mutations of transmembrane regions of proteins. Thus, our experimental results reveal the HokC transmembrane region high tolerance to loss-of-function mutations that is associated with low sequence conservation and high rate of correlated mutations in the HokC family sequences alignment, which are features shared with other transmembrane proteins.

Mistranslation can promote the exploration of alternative evolutionary trajectories in enzyme evolution

Darwinian evolution preferentially follows mutational pathways whose individual steps increase fitness. Alternative pathways with mutational steps that do not increase fitness are less accessible. Here, we show that mistranslation, the erroneous incorporation of amino acids into nascent proteins, can increase the accessibility of such alternative pathways and, ultimately, of high fitness genotypes. We subject populations of the beta‐lactamase TEM‐1 to directed evolution in Escherichia coli under both low‐ and high‐mistranslation rates, selecting for high activity on the antibiotic cefotaxime. Under low mistranslation rates, different evolving TEM‐1 populations ascend the same high cefotaxime‐resistance peak, which requires three canonical DNA mutations. In contrast, under high mistranslation rates they ascend three different high cefotaxime‐resistance genotypes, which leads to higher genotypic diversity among populations. We experimentally reconstruct the adaptive DNA mutations and the potential evolutionary paths to these high cefotaxime‐resistance genotypes. This reconstruction shows that some of the DNA mutations do not change fitness under low mistranslation, but cause a significant increase in fitness under high‐mistranslation, which helps increase the accessibility of different high cefotaxime‐resistance genotypes. In addition, these mutations form a network of pairwise epistatic interactions that leads to mutually exclusive evolutionary trajectories towards different high cefotaxime‐resistance genotypes. Our observations demonstrate that protein mistranslation and the phenotypic mutations it causes can alter the evolutionary exploration of fitness landscapes and reduce the predictability of evolution.

Abundance Imparts Evolutionary Constraints of Similar Magnitude on the Buried, Surface, and Disordered Regions of Proteins

An understanding of the forces shaping protein conservation is key, both for the fundamental knowledge it represents and to allow for optimal use of evolutionary information in practical applications. Sequence conservation is typically examined at one of two levels. The first is a residue-level, where intra-protein differences are analyzed and the second is a protein-level, where inter-protein differences are studied. At a residue level, we know that solvent-accessibility is a prime determinant of conservation. By inverting this logic, we inferred that disordered regions are slightly more solvent-accessible on average than the most exposed surface residues in domains. By integrating abundance information with evolutionary data within and across proteins, we confirmed a previously reported strong surface-core association in the evolution of structured regions, but we found a comparatively weak association between disordered and structured regions. The facts that disordered and structured regions experience different structural constraints and evolve independently provide a unique setup to examine an outstanding question: why is a protein’s abundance the main determinant of its sequence conservation? Indeed, any structural or biophysical property linked to the abundance-conservation relationship should increase the relative conservation of regions concerned with that property (e.g., disordered residues with mis-interactions, domain residues with misfolding). Surprisingly, however, we found the conservation of disordered and structured regions to increase in equal proportion with abundance. This observation implies that either abundance-related constraints are structure-independent, or multiple constraints apply to different regions and perfectly balance each other.

Exploring mutable conserved sites and fatal non-conserved sites by random mutation of esterase from Sulfolobus tokodaii and subtilisin from Thermococcus kodakarensis

Homologous proteins differ in their amino acid sequences at several positions. Generally, conserved sites are recognized as not suitable for amino acid substitution, and thus in evolutionary protein engineering, non-conserved sites are often selected as mutation sites. However, there have also been reports of possible mutations in conserved sites. In this study, we explored mutable conserved sites and immutable non-conserved sites by testing random mutations of two thermostable proteins, an esterase from Sulfolobus tokodaii (Sto-Est) and a subtilisin from Thermococcus kodakarensis (Tko-Sub). The subtilisin domain of Tko-Sub needs Ca²⁺ ions and the propeptide domain for stability, folding and maturation. The results from the two proteins showed that about one-third of the mutable sites were detected in conserved sites and some non-conserved sites lost enzymatic activity at high temperatures due to mutation. Of the conserved sites in Sto-Est, the sites on the loop, on the surface, and far from the active site are more resistant to mutation. In Tko-Sub, the sites flanking Ca²⁺-binding sites and propeptide were undesirable for mutation. The results presented here serve as an index for selecting mutation sites and contribute to the expansion of available sequence range by introducing mutations at conserved sites.

Mining and Statistical Modeling of Natural and Variant Class IIa Bacteriocins Elucidate Activity and Selectivity Profiles across Species

Class IIa bacteriocin antimicrobial peptides (AMPs) are a compelling alternative to current antimicrobials because of potential specific activity toward antibiotic-resistant bacteria, including vancomycin-resistant enterococci. Engineering of these molecules would be enhanced by a better understanding of AMP sequence-activity relationships to improve efficacy in vivo and limit effects of off-target activity. Toward this goal, we experimentally evaluated 210 natural and variant class IIa bacteriocins for antimicrobial activity against six strains of enterococci. Inhibitory activity was ridge regressed to AMP sequence to predict performance, achieving an area under the curve of 0.70 and demonstrating the potential of statistical models for identifying and designing AMPs. Active AMPs were individually produced and evaluated against eight enterococcus strains and four Listeria strains to elucidate trends in susceptibility. It was determined that the mannose phosphotransferase system (manPTS) sequence is informative of susceptibility to class IIa bacteriocins, yet other factors, such as membrane composition, also contribute strongly to susceptibility. A broadly potent bacteriocin variant (lactocin DT1) from a Lactobacillus ruminis genome was identified as the only variant with inhibitory activity toward all tested strains, while a novel enterocin variant (DT2) from an Enterococcus faecium genome demonstrated specificity toward Listeria strains. Eight AMPs were evaluated for proteolytic stability to trypsin, chymotrypsin, and pepsin, and three C-terminal disulfide-containing variants, including divercin V41, were identified as compelling for future in vivo studies, given their high potency and proteolytic stability.IMPORTANCE Class IIa bacteriocin antimicrobial peptides (AMPs), an alternative to traditional small-molecule antibiotics, are capable of selective activity toward various Gram-positive bacteria, limiting negative side effects associated with broad-spectrum activity. This selective activity is achieved through targeting of the mannose phosphotransferase system (manPTS) of a subset of Gram-positive bacteria, although factors affecting this mechanism are not entirely understood. Peptides identified from genomic data, as well as variants of previously characterized AMPs, can offer insight into how peptide sequence affects activity and selectivity. The experimental methods presented here identify promising potent and selective bacteriocins for further evaluation, highlight the potential of simple computational modeling for prediction of AMP performance, and demonstrate that factors beyond manPTS sequence affect bacterial susceptibility to class IIa bacteriocins.

Phylogenetic and biochemical analysis of calsequestrin structure and association of its variants with cardiac disorders

Calsequestrin is among the most abundant proteins in muscle sarcoplasmic reticulum and displays a high capacity but a low affinity for Ca²⁺ binding. In mammals, calsequestrin is encoded by two genes, CASQ1 and CASQ2, which are expressed almost exclusively in skeletal and cardiac muscles, respectively. Phylogenetic analysis indicates that calsequestrin is an ancient gene in metazoans, and that the duplication of the ancestral calsequestrin gene took place after the emergence of the lancelet. CASQ2 gene variants associated with catecholaminergic polymorphic ventricular tachycardia (CPVT) in humans are positively correlated with a high degree of evolutionary conservation across all calsequestrin homologues. The mutations are distributed in diverse locations of the calsequestrin protein and impart functional diversity but remarkably manifest in a similar phenotype in humans.

Mutational resilience of antiviral restriction favors primate TRIM5α in host-virus evolutionary arms races

Host antiviral proteins engage in evolutionary arms races with viruses, in which both sides rapidly evolve at interaction interfaces to gain or evade immune defense. For example, primate TRIM5α uses its rapidly evolving 'v1' loop to bind retroviral capsids, and single mutations in this loop can dramatically improve retroviral restriction. However, it is unknown whether such gains of viral restriction are rare, or if they incur loss of pre-existing function against other viruses. Using deep mutational scanning, we comprehensively measured how single mutations in the TRIM5α v1 loop affect restriction of divergent retroviruses. Unexpectedly, we found that the majority of mutations increase weak antiviral function. Moreover, most random mutations do not disrupt potent viral restriction, even when it is newly acquired via a single adaptive substitution. Our results indicate that TRIM5α's adaptive landscape is remarkably broad and mutationally resilient, maximizing its chances of success in evolutionary arms races with retroviruses.

Genome-wide and structural analyses of pseudokinases encoded in the genome of Arabidopsis thaliana provide functional insights

Protein Kinase-Like Non-Kinases (PKLNKs), commonly known as "pseudokinases", are homologous to eukaryotic Ser/Thr/Tyr protein kinases (PKs) but lack the crucial aspartate residue in the catalytic loop, indispensable for phosphotransferase activity. Therefore, they are predicted to be "catalytically inactive" enzyme homologs. Analysis of protein-kinase like sequences from Arabidopsis thaliana led to the identification of more than 120 pseudokinases lacking catalytic aspartate, majority of which are closely related to the plant-specific receptor-like kinase family. These pseudokinases engage in different biological processes, enabled by their diverse domain architectures and specific subcellular localizations. Structural comparison of pseudokinases with active and inactive conformations of canonical PKs, belonging to both plant and animal origin, revealed unique structural differences. The currently available crystal structures of pseudokinases show that the loop topologically equivalent to activation segment of PKs adopts a distinct-folded conformation, packing against the pseudoenzyme core, in contrast to the extended and inhibitory geometries observed for active and inactive states, respectively, of catalytic PKs. Salt-bridge between ATP-binding Lys and DFG-Asp as well as hydrophobic interactions between the conserved nonpolar residue C-terminal to the equivalent DFG motif and nonpolar residues in C-helix mediate such a conformation in pseudokinases. This results in enhanced solvent accessibility of the pseudocatalytic loop in pseudokinases that can possibly serve as an interacting surface while associating with other proteins. Specifically, our analysis identified several residues that may be involved in pseudokinase regulation and hints at the repurposing of pseudocatalytic residues to achieve mechanistic control over noncatalytic functions of pseudoenzymes.

Identification of Cancer Biomarkers in Human Body Fluids by Using Enhanced Physicochemical-incorporated Evolutionary Conservation Scheme

OBJECTIVE

Cancer is one of the most serious diseases affecting human health. Among all current cancer treatments, early diagnosis and control significantly help increase the chances of cure. Detecting cancer biomarkers in body fluids now is attracting more attention within oncologists. In-silico predictions of body fluid-related proteins, which can be served as cancer biomarkers, open a door for labor-intensive and time-consuming biochemical experiments.

METHODS

In this work, we propose a novel method for high-throughput identification of cancer biomarkers in human body fluids. We incorporate physicochemical properties into the weighted observed percentages (WOP) and position-specific scoring matrices (PSSM) profiles to enhance their attributes that reflect the evolutionary conservation of the body fluid-related proteins. The least absolute selection and shrinkage operator (LASSO) feature selection strategy is introduced to generate the optimal feature subset.

RESULTS

The ten-fold cross-validation results on training datasets demonstrate the accuracy of the proposed model. We also test our proposed method on independent testing datasets and apply it to the identification of potential cancer biomarkers in human body fluids.

CONCLUSION

The testing results promise a good generalization capability of our approach.

Directed evolution methods for overcoming trade-offs between protein activity and stability

Engineered proteins are being widely developed and employed in applications ranging from enzyme catalysts to therapeutic antibodies. Directed evolution, an iterative experimental process composed of mutagenesis and library screening, is a powerful technique for enhancing existing protein activities and generating entirely new ones not observed in nature. However, the process of accumulating mutations for enhanced protein activity requires chemical and structural changes that are often destabilizing, and low protein stability is a significant barrier to achieving large enhancements in activity during multiple rounds of directed evolution. Here we highlight advances in understanding the origins of protein activity/stability trade-offs for two important classes of proteins (enzymes and antibodies) as well as innovative experimental and computational methods for overcoming such trade-offs. These advances hold great potential for improving the generation of highly active and stable proteins that are needed to address key challenges related to human health, energy and the environment.

The Impact of Protein Architecture on Adaptive Evolution

Adaptive mutations play an important role in molecular evolution. However, the frequency and nature of these mutations at the intramolecular level are poorly understood. To address this, we analyzed the impact of protein architecture on the rate of adaptive substitutions, aiming to understand how protein biophysics influences fitness and adaptation. Using Drosophila melanogaster and Arabidopsis thaliana population genomics data, we fitted models of distribution of fitness effects and estimated the rate of adaptive amino-acid substitutions both at the protein and amino-acid residue level. We performed a comprehensive analysis covering genome, gene, and protein structure, by exploring a multitude of factors with a plausible impact on the rate of adaptive evolution, such as intron number, protein length, secondary structure, relative solvent accessibility, intrinsic protein disorder, chaperone affinity, gene expression, protein function, and protein-protein interactions. We found that the relative solvent accessibility is a major determinant of adaptive evolution, with most adaptive mutations occurring at the surface of proteins. Moreover, we observe that the rate of adaptive substitutions differs between protein functional classes, with genes encoding for protein biosynthesis and degradation signaling exhibiting the fastest rates of protein adaptation. Overall, our results suggest that adaptive evolution in proteins is mainly driven by intermolecular interactions, with host-pathogen coevolution likely playing a major role.

Effect of cadmium on mRNA mistranslation in Saccharomyces cerevisiae

Although highly accurate molecular processes and various messenger RNA (mRNA) quality control and ribosome proofreading mechanisms are used by organisms to transcribe their genes and maintain the fidelity of genetic information, errors are inherent in all biological systems. Low-level translation errors caused by an imbalance of homologous and nonhomologous amino acids caused by stress conditions are particularly common. Paradoxically, advantageous phenotypic diversity can be generated by such errors in eukaryotes through unknown molecular processes. Here, we found that the significant cadmium-resistant phenotype was correlated with an increased mistranslation rate of the mRNA in Saccharomyces cerevisiae. This phenotypic change was also related to endogenous sulfur amino acid starvation. Compared with the control, the mistranslation rate caused by cadmium was significantly increased (p < .01). With the increase of cysteine contents in medium, the mistranslation rate of WT(BY4742a) decreased significantly (p < .01). This demonstrates that cadmium treatment and sulfur amino acid starvation both can induce translation errors. Although cadmium uptake is independent of the Sul1 transporter, cadmium-induced mRNA mistranslation is dependent on the sulfate uptake of the Sul1p transporter. Furthermore, cadmium-induced translation errors depend on methionine biosynthesis. Taken together, cadmium causes endogenous sulfur starvation, leading to an increase in the mRNA mistranslation, which contributes to the resistance of yeast cells to cadmium. We provide a new pathway mediating the toxicity of cadmium, and we propose that altering mRNA mistranslation may portray a different form of environmental adaptation.

A Novel 'Candidatus Liberibacter asiaticus'-Encoded Sec-Dependent Secretory Protein Suppresses Programmed Cell Death in Nicotiana benthamiana

'Candidatus Liberibacter asiaticus' (CLas) is one of the causal agents of citrus Huanglongbing (HLB), a bacterial disease of citrus trees that greatly reduces fruit yield and quality. CLas strains produce an array of currently uncharacterized Sec-dependent secretory proteins. In this study, the conserved chromosomally encoded protein CLIBASIA_03875 was identified as a novel Sec-dependent secreted protein. We show that CLIBASIA_03875 contains a putative Sec- secretion signal peptide (SP), a 29 amino acid residue located at the N-terminus, with a mature protein (m3875) of 22 amino acids found to localize in multiple subcellular components of the leaf epidermal cells of Nicotiana benthamiana. When overexpressed via a Potato virus X (PVX)-based expression vector in N. benthamiana, m3875 suppressed programmed cell death (PCD) and the H2O2 accumulation triggered by the pro-apoptotic mouse protein BAX and the Phytophthora infestans elicitin INF1. Overexpression also resulted in a phenotype of dwarfing, leaf deformation and mosaics, suggesting that m3875 has roles in plant immune response, growth, and development. Substitution mutagenesis of the charged amino acid (D7, R9, R11, and K22) with alanine within m3875 did not recover the phenotypes for PCD and normal growth. In addition, the transiently overexpressed m3875 regulated the transcriptional levels of N. benthamiana orthologs of CNGCs (cyclic nucleotide-gated channels), BI-1 (Bax-inhibitor 1), and WRKY33 that are involved in plant defense mechanisms. To our knowledge, m3875 is the first PCD suppressor identified from CLas. Studying the function of this protein provides insight as to how CLas attenuates the host immune responses to proliferate and cause Huanglongbing disease in citrus plants.

3D spatial organization and network-guided comparison of mutation profiles in Glioblastoma reveals similarities across patients

Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor. Molecular heterogeneity is a hallmark of GBM tumors that is a barrier in developing treatment strategies. In this study, we used the nonsynonymous mutations of GBM tumors deposited in The Cancer Genome Atlas (TCGA) and applied a systems level approach based on biophysical characteristics of mutations and their organization in patient-specific subnetworks to reduce inter-patient heterogeneity and to gain potential clinically relevant insights. Approximately 10% of the mutations are located in "patches" which are defined as the set of residues spatially in close proximity that are mutated across multiple patients. Grouping mutations as 3D patches reduces the heterogeneity across patients. There are multiple patches that are relatively small in oncogenes, whereas there are a small number of very large patches in tumor suppressors. Additionally, different patches in the same protein are often located at different domains that can mediate different functions. We stratified the patients into five groups based on their potentially affected pathways that are revealed from the patient-specific subnetworks. These subnetworks were constructed by integrating mutation profiles of the patients with the interactome data. Network-guided clustering showed significant association between the groups and patient survival (P-value = 0.0408). Also, each group carries a set of signature 3D mutation patches that affect predominant pathways. We integrated drug sensitivity data of GBM cell lines with the mutation patches and the patient groups to analyze the possible therapeutic outcome of these patches. We found that Pazopanib might be effective in Group 3 by targeting CSF1R. Additionally, inhibiting ATM that is a mediator of PTEN phosphorylation may be ineffective in Group 2. We believe that from mutations to networks and eventually to clinical and therapeutic data, this study provides a novel perspective in the network-guided precision medicine.

tRNA Deregulation and Its Consequences in Cancer

The expression of transfer RNAs (tRNAs) is deregulated in cancer cells but the mechanisms and functional meaning of such deregulation are poorly understood. The proteome of cancer cells is not fully encoded by their transcriptome, however, the contribution of mRNA translation to such diversity remains to be elucidated. We review data supporting the hypothesis that tRNA expression deregulation and translational error rate is an important contributor to proteome diversity and cell population heterogeneity, genome instability, and drug resistance in tumors. This hypothesis is aligned with recent data in various model organisms, showing unanticipated adaptive roles of translational errors (adaptive mistranslation), expression control of specific gene subsets by tRNAs, and proteome diversification by elevation of translational error rates in tumors.

Non-digestible proteins and protease inhibitors: implications for defense of the colored eggs of the freshwater apple snailPomacea canaliculata

Apple snails (Pomacea Perry, 1810) are successful invaders that cause ecological perturbations, economic losses, and medical issues. A peculiar trait of this snail is a high biological potential, related to the absence of predators of their eggs. Eggs show protease inhibitor (PI) activity, originally ascribed to PcOvo perivitellin in the apple snail Pomacea canaliculata (Lamarck, 1822) but absent in PmPV1, the orthologoue of PcOvo, in eggs of the apple snail Pomacea maculata Perry, 1810. As egg fluid diminishes rat growth rate, an antidigestive effect, similar to plant defenses against herbivory, was hypothesized. However, PI activity has not been characterized in apple snail eggs. Here we identify and partially characterize P. canaliculata egg PI and improve our knowledge of the quaternary structure and evolution of PcOvo. Through N-terminal, transcriptomic or proteomic sequencing, and biochemical validation, we identified a Kunitz-type and a Kazal-type inhibitor that, though at low concentration in the egg, exhibit strong PI activity against trypsin, chymotrypsin, elastase, and subtilisin. Additionally, we report three new subunits for the non-digestible storage protein PcOvo. They are likely products of ancient gene duplication, as their sequences exhibit moderate similarity (30%). To our knowledge, this is the first report of Kazal-type inhibition among invertebrate eggs. Inhibiting varied proteases, PI seems an efficient adaptive trait that limits predator’s capacity to digest egg nutrients.