Structured States of Disordered Proteins from Genomic Sequences.

Protein flexibility ranges from simple hinge movements to functional disorder. Around half of all human proteins contain apparently disordered regions with little 3D or functional information, and many of these proteins are associated with disease. Building on the evolutionary couplings approach previously successful in predicting 3D states of ordered proteins and RNA, we developed a method to predict the potential for ordered states for all apparently disordered proteins with sufficiently rich evolutionary information. The approach is highly accurate (79%) for residue interactions as tested in more than 60 known disordered regions captured in a bound or specific condition. Assessing the potential for structure of more than 1,000 apparently disordered regions of human proteins reveals a continuum of structural order with at least 50% with clear propensity for three- or two-dimensional states. Co-evolutionary constraints reveal hitherto unseen structures of functional importance in apparently disordered proteins.

The Rab5 effector FERRY links early endosomes with mRNA localization.

Localized translation is vital to polarized cells and requires precise and robust distribution of different mRNAs and ribosomes across the cell. However, the underlying molecular mechanisms are poorly understood and important players are lacking. Here, we discovered a Rab5 effector, the five-subunit endosomal Rab5 and RNA/ribosome intermediary (FERRY) complex, that recruits mRNAs and ribosomes to early endosomes through direct mRNA-interaction. FERRY displays preferential binding to certain groups of transcripts, including mRNAs encoding mitochondrial proteins. Deletion of FERRY subunits reduces the endosomal localization of transcripts in cells and has a significant impact on mRNA levels. Clinical studies show that genetic disruption of FERRY causes severe brain damage. We found that, in neurons, FERRY co-localizes with mRNA on early endosomes, and mRNA loaded FERRY-positive endosomes are in close proximity of mitochondria. FERRY thus transforms endosomes into mRNA carriers and plays a key role in regulating mRNA distribution and transport.

CD-CODE: crowdsourcing condensate database and encyclopedia.

The discovery of biomolecular condensates transformed our understanding of intracellular compartmentalization of molecules. To integrate interdisciplinary scientific knowledge about the function and composition of biomolecular condensates, we developed the crowdsourcing condensate database and encyclopedia ( cd-code.org ). CD-CODE is a community-editable platform, which includes a database of biomolecular condensates based on the literature, an encyclopedia of relevant scientific terms and a crowdsourcing web application. Our platform will accelerate the discovery and validation of biomolecular condensates, and facilitate efforts to understand their role in disease and as therapeutic targets.

Low-frequency inherited complement receptor variants are associated with purpura fulminans.

ABSTRACT: Extreme disease phenotypes can provide key insights into the pathophysiology of common conditions, but studying such cases is challenging due to their rarity and the limited statistical power of existing methods. Herein, we used a novel approach to pathway-based mutational burden testing, the rare variant trend test (RVTT), to investigate genetic risk factors for an extreme form of sepsis-induced coagulopathy, infectious purpura fulminans (PF). In addition to prospective patient sample collection, we electronically screened over 10.4 million medical records from 4 large hospital systems and identified historical cases of PF for which archived specimens were available to perform germline whole-exome sequencing. We found a significantly increased burden of low-frequency, putatively function-altering variants in the complement system in patients with PF compared with unselected patients with sepsis (P = .01). A multivariable logistic regression analysis found that the number of complement system variants per patient was independently associated with PF after controlling for age, sex, and disease acuity (P = .01). Functional characterization of PF-associated variants in the immunomodulatory complement receptors CR3 and CR4 revealed that they result in partial or complete loss of anti-inflammatory CR3 function and/or gain of proinflammatory CR4 function. Taken together, these findings suggest that inherited defects in CR3 and CR4 predispose to the maladaptive hyperinflammation that characterizes severe sepsis with coagulopathy.

Fitness Effects of Phenotypic Mutations at Proteome-Scale Reveal Optimality of Translation Machinery.

Errors in protein translation can lead to non-genetic, phenotypic mutations, including amino acid misincorporations. While phenotypic mutations can increase protein diversity, the systematic characterization of their proteome-wide frequencies and their evolutionary impact has been lacking. Here, we developed a mechanistic model of translation errors to investigate how selection acts on protein populations produced by amino acid misincorporations. We fitted the model to empirical observations of misincorporations obtained from over a hundred mass spectrometry datasets of E. coli and S. cerevisiae. We found that on average 20% to 23% of proteins synthesized in the cell are expected to harbor at least one amino acid misincorporation, and that deleterious misincorporations are less likely to occur. Combining misincorporation probabilities and the estimated fitness effects of amino acid substitutions in a population genetics framework, we found 74% of mistranslation events in E. coli and 94% in S. cerevisiae to be neutral. We further show that the set of available synonymous tRNAs is subject to evolutionary pressure, as the presence of missing tRNAs would increase codon-anticodon cross-reactivity and misincorporation error rates. Overall, we find that the translation machinery is likely optimal in E. coli and S. cerevisiae and that both local solutions at the level of codons and a global solution such as the tRNA pool can mitigate the impact of translation errors. We provide a framework to study the evolutionary impact of codon-specific translation errors and a method for their proteome-wide detection across organisms and conditions.

deTELpy: Python package for high-throughput detection of amino acid substitutions in mass spectrometry datasets.

MOTIVATION: Errors in the processing of genetic information during protein synthesis can lead to phenotypic mutations, such as amino acid substitutions, e.g. by transcription or translation errors. While genetic mutations can be readily identified using DNA sequencing, and mutations due to transcription errors by RNA sequencing, translation errors can only be identified proteome-wide using mass spectrometry. RESULTS: Here, we provide a Python package implementation of a high-throughput pipeline to detect amino acid substitutions in mass spectrometry datasets. Our tools enable users to process hundreds of mass spectrometry datasets in batch mode to detect amino acid substitutions and calculate codon-specific and site-specific translation error rates. deTELpy will facilitate the systematic understanding of amino acid misincorporation rates (translation error rates), and the inference of error models across organisms and under stress conditions, such as drug treatment or disease conditions. AVAILABILITY: deTELpy is implemented in Python 3 and is freely available with detailed documentation and practical examples at https://git.mpi-cbg.de/tothpetroczylab/detelpy and https://pypi.org/project/deTELpy/ and can be easily installed via pip install deTELpy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Simple yet functional phosphate-loop proteins.

Abundant and essential motifs, such as phosphate-binding loops (P-loops), are presumed to be the seeds of modern enzymes. The Walker-A P-loop is absolutely essential in modern NTPase enzymes, in mediating binding, and transfer of the terminal phosphate groups of NTPs. However, NTPase function depends on many additional active-site residues placed throughout the protein's scaffold. Can motifs such as P-loops confer function in a simpler context? We applied a phylogenetic analysis that yielded a sequence logo of the putative ancestral Walker-A P-loop element: a ß-strand connected to an α-helix via the P-loop. Computational design incorporated this element into de novo designed ß-α repeat proteins with relatively few sequence modifications. We obtained soluble, stable proteins that unlike modern P-loop NTPases bound ATP in a magnesium-independent manner. Foremost, these simple P-loop proteins avidly bound polynucleotides, RNA, and single-strand DNA, and mutations in the P-loop's key residues abolished binding. Binding appears to be facilitated by the structural plasticity of these proteins, including quaternary structure polymorphism that promotes a combined action of multiple P-loops. Accordingly, oligomerization enabled a 55-aa protein carrying a single P-loop to confer avid polynucleotide binding. Overall, our results show that the P-loop Walker-A motif can be implemented in small and simple ß-α repeat proteins, primarily as a polynucleotide binding motif.

novoCaller: a Bayesian network approach for de novo variant calling from pedigree and population sequence data.

MOTIVATION: De novo mutations (i.e. newly occurring mutations) are a pre-dominant cause of sporadic dominant monogenic diseases and play a significant role in the genetics of complex disorders. De novo mutation studies also inform population genetics models and shed light on the biology of DNA replication and repair. Despite the broad interest, there is room for improvement with regard to the accuracy of de novo mutation calling. RESULTS: We designed novoCaller, a Bayesian variant calling algorithm that uses information from read-level data both in the pedigree and in unrelated samples. The method was extensively tested using large trio-sequencing studies, and it consistently achieved over 97% sensitivity. We applied the algorithm to 48 trio cases of suspected rare Mendelian disorders as part of the Brigham Genomic Medicine gene discovery initiative. Its application resulted in a significant reduction in the resources required for manual inspection and experimental validation of the calls. Three de novo variants were found in known genes associated with rare disorders, leading to rapid genetic diagnosis of the probands. Another 14 variants were found in genes that are likely to explain the phenotype, and could lead to novel disease-gene discovery. AVAILABILITY AND IMPLEMENTATION: Source code implemented in C++ and Python can be downloaded from https://github.com/bgm-cwg/novoCaller. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The EVcouplings Python framework for coevolutionary sequence analysis.

SUMMARY: Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The framework enables generation of sequence alignments, calculation and evaluation of evolutionary couplings (ECs), and de novo prediction of structure and mutation effects. The combination of an easy to use, flexible command line interface and an underlying modular Python package makes the full power of coevolutionary analyses available to entry-level and advanced users. AVAILABILITY AND IMPLEMENTATION: https://github.com/debbiemarkslab/evcouplings.

An Ancient Fingerprint Indicates the Common Ancestry of Rossmann-Fold Enzymes Utilizing Different Ribose-Based Cofactors.

Nucleoside-based cofactors are presumed to have preceded proteins. The Rossmann fold is one of the most ancient and functionally diverse protein folds, and most Rossmann enzymes utilize nucleoside-based cofactors. We analyzed an omnipresent Rossmann ribose-binding interaction: a carboxylate side chain at the tip of the second ß-strand (ß2-Asp/Glu). We identified a canonical motif, defined by the ß2-topology and unique geometry. The latter relates to the interaction being bidentate (both ribose hydroxyls interacting with the carboxylate oxygens), to the angle between the carboxylate and the ribose, and to the ribose's ring configuration. We found that this canonical motif exhibits hallmarks of divergence rather than convergence. It is uniquely found in Rossmann enzymes that use different cofactors, primarily SAM (S-adenosyl methionine), NAD (nicotinamide adenine dinucleotide), and FAD (flavin adenine dinucleotide). Ribose-carboxylate bidentate interactions in other folds are not only rare but also have a different topology and geometry. We further show that the canonical geometry is not dictated by a physical constraint--geometries found in noncanonical interactions have similar calculated bond energies. Overall, these data indicate the divergence of several major Rossmann-fold enzyme classes, with different cofactors and catalytic chemistries, from a common pre-LUCA (last universal common ancestor) ancestor that possessed the ß2-Asp/Glu motif.

Systematic Mapping of Protein Mutational Space by Prolonged Drift Reveals the Deleterious Effects of Seemingly Neutral Mutations.

Systematic mappings of the effects of protein mutations are becoming increasingly popular. Unexpectedly, these experiments often find that proteins are tolerant to most amino acid substitutions, including substitutions in positions that are highly conserved in nature. To obtain a more realistic distribution of the effects of protein mutations, we applied a laboratory drift comprising 17 rounds of random mutagenesis and selection of M.HaeIII, a DNA methyltransferase. During this drift, multiple mutations gradually accumulated. Deep sequencing of the drifted gene ensembles allowed determination of the relative effects of all possible single nucleotide mutations. Despite being averaged across many different genetic backgrounds, about 67% of all nonsynonymous, missense mutations were evidently deleterious, and an additional 16% were likely to be deleterious. In the early generations, the frequency of most deleterious mutations remained high. However, by the 17th generation, their frequency was consistently reduced, and those remaining were accepted alongside compensatory mutations. The tolerance to mutations measured in this laboratory drift correlated with sequence exchanges seen in M.HaeIII's natural orthologs. The biophysical constraints dictating purging in nature and in this laboratory drift also seemed to overlap. Our experiment therefore provides an improved method for measuring the effects of protein mutations that more closely replicates the natural evolutionary forces, and thereby a more realistic view of the mutational space of proteins.

Correlated occurrence and bypass of frame-shifting insertion-deletions (InDels) to give functional proteins.

Short insertions and deletions (InDels) comprise an important part of the natural mutational repertoire. InDels are, however, highly deleterious, primarily because two-thirds result in frame-shifts. Bypass through slippage over homonucleotide repeats by transcriptional and/or translational infidelity is known to occur sporadically. However, the overall frequency of bypass and its relation to sequence composition remain unclear. Intriguingly, the occurrence of InDels and the bypass of frame-shifts are mechanistically related - occurring through slippage over repeats by DNA or RNA polymerases, or by the ribosome, respectively. Here, we show that the frequency of frame-shifting InDels, and the frequency by which they are bypassed to give full-length, functional proteins, are indeed highly correlated. Using a laboratory genetic drift, we have exhaustively mapped all InDels that occurred within a single gene. We thus compared the naive InDel repertoire that results from DNA polymerase slippage to the frame-shifting InDels tolerated following selection to maintain protein function. We found that InDels repeatedly occurred, and were bypassed, within homonucleotide repeats of 3-8 bases. The longer the repeat, the higher was the frequency of InDels formation, and the more frequent was their bypass. Besides an expected 8A repeat, other types of repeats, including short ones, and G and C repeats, were bypassed. Although obtained in vitro, our results indicate a direct link between the genetic occurrence of InDels and their phenotypic rescue, thus suggesting a potential role for frame-shifting InDels as bridging evolutionary intermediates.

Protein insertions and deletions enabled by neutral roaming in sequence space.

Backbone modifications via insertions and deletions (InDels) may exert dramatic effects, for better (mediating new functions) and for worse (causing loss of structure and/or function). However, contrary to point mutations (substitutions), our knowledge of the evolution and structural-functional effects of InDels is limited and so is our capability to engineer them. We sought to assess how deleterious InDels are relative to point mutations and understand the mechanisms that mediate their acceptance. Analysis of the evolution of InDels in orthologous protein phylogenies indicated that their rate of purging is 9- to 100-fold higher than for point mutations. In yeast, for example, the substitutions-to-InDels ratio is approximately 14-fold higher in protein coding than in noncoding regions. The incorporation of InDels relative to substitutions is not only slow but also nonlinear. On average, ≥50 substitutions accumulate before the appearance of the first InDel. We also found enriched substitutions in sequential and spatial proximity to InDels, suggesting that certain substitutions are correlated with InDels. As indicated by the lag in InDels accumulation, some of these correlated substitutions may have occurred first, as apparently neutral mutations, and later enabled the accumulation of InDels that would be otherwise purged. Thus, compensatory substitutions may follow InDels in an "adaptive walk" as traditionally assumed, but might also accumulate first, by "neutral roaming." The dynamics of InDels accumulation also depends on their genomic frequencies-InDels in flies are 4-fold more frequent than in yeast and tend to be compensated rather than enabled.

Slow protein evolutionary rates are dictated by surface-core association.

Why do certain proteins evolve much slower than others? We compared not only rates per protein, but also rates per position within individual proteins. For ∼90% of proteins, the distribution of positional rates exhibits three peaks: a peak of slow evolving residues, with average log(2)[normalized rate], log(2)µ, of ca. -2, corresponding primarily to core residues; a peak of fast evolving residues (log(2)µ ∼ 0.5) largely corresponding to surface residues; and a very fast peak (log(2)µ ∼ 2) associated with disordered segments. However, a unique fraction of proteins that evolve very slowly exhibit not only a negligible fast peak, but also a peak with a log(2)µ ∼ -4, rather than the standard core peak of -2. Thus, a "freeze" of a protein's surface seems to stop core evolution as well. We also observed a much higher fraction of substitutions in potentially interacting residues than expected by chance, including substitutions in pairs of contacting surface-core residues. Overall, the data suggest that accumulation of surface substitutions enables the acceptance of substitutions in core positions. The underlying reason for slow evolution might therefore be a highly constrained surface due to protein-protein interactions or the need to prevent misfolding or aggregation. If the surface is inaccessible to substitutions, so becomes the core, thus resulting in very slow overall rates.

Environment modulates protein heterogeneity through transcriptional and translational stop codon readthrough.

Stop codon readthrough events give rise to longer proteins, which may alter the protein's function, thereby generating short-lasting phenotypic variability from a single gene. In order to systematically assess the frequency and origin of stop codon readthrough events, we designed a library of reporters. We introduced premature stop codons into mScarlet, which enabled high-throughput quantification of protein synthesis termination errors in E. coli using fluorescent microscopy. We found that under stress conditions, stop codon readthrough may occur at rates as high as 80%, depending on the nucleotide context, suggesting that evolution frequently samples stop codon readthrough events. The analysis of selected reporters by mass spectrometry and RNA-seq showed that not only translation but also transcription errors contribute to stop codon readthrough. The RNA polymerase was more likely to misincorporate a nucleotide at premature stop codons. Proteome-wide detection of stop codon readthrough by mass spectrometry revealed that temperature regulated the expression of cryptic sequences generated by stop codon readthrough in E. coli. Overall, our findings suggest that the environment affects the accuracy of protein production, which increases protein heterogeneity when the organisms need to adapt to new conditions.

DeMAG predicts the effects of variants in clinically actionable genes by integrating structural and evolutionary epistatic features.

Despite the increasing use of genomic sequencing in clinical practice, the interpretation of rare genetic variants remains challenging even in well-studied disease genes, resulting in many patients with Variants of Uncertain Significance (VUSs). Computational Variant Effect Predictors (VEPs) provide valuable evidence in variant assessment, but they are prone to misclassifying benign variants, contributing to false positives. Here, we develop Deciphering Mutations in Actionable Genes (DeMAG), a supervised classifier for missense variants trained using extensive diagnostic data available in 59 actionable disease genes (American College of Medical Genetics and Genomics Secondary Findings v2.0, ACMG SF v2.0). DeMAG improves performance over existing VEPs by reaching balanced specificity (82%) and sensitivity (94%) on clinical data, and includes a novel epistatic feature, the 'partners score', which leverages evolutionary and structural partnerships of residues. The 'partners score' provides a general framework for modeling epistatic interactions, integrating both clinical and functional information. We provide our tool and predictions for all missense variants in 316 clinically actionable disease genes (demag.org) to facilitate the interpretation of variants and improve clinical decision-making.

Phenotypic mutations contribute to protein diversity and shape protein evolution.

Errors in DNA replication generate genetic mutations, while errors in transcription and translation lead to phenotypic mutations. Phenotypic mutations are orders of magnitude more frequent than genetic ones, yet they are less understood. Here, we review the types of phenotypic mutations, their quantifications, and their role in protein evolution and disease. The diversity generated by phenotypic mutation can facilitate adaptive evolution. Indeed, phenotypic mutations, such as ribosomal frameshift and stop codon readthrough, sometimes serve to regulate protein expression and function. Phenotypic mutations have often been linked to fitness decrease and diseases. Thus, understanding the protein heterogeneity and phenotypic diversity caused by phenotypic mutations will advance our understanding of protein evolution and have implications on human health and diseases.

Adventures on the Routes of Protein Evolution-In Memoriam Dan Salah Tawfik (1955-2021).

Understanding how proteins evolved not only resolves mysteries of the past, but also helps address challenges of the future, particularly those relating to the design and engineering of new protein functions. Here we review the work of Dan S. Tawfik, one of the pioneers of this area, highlighting his seminal contributions in diverse fields such as protein design, high throughput screening, protein stability, fundamental enzyme-catalyzed reactions and promiscuity, that underpin biology and the origins of life. We discuss the influence of his work on how our models of enzyme and protein function have developed and how the main driving forces of molecular evolution were elucidated. The discovery of the rugged routes of evolution has enabled many practical applications, some which are now widely used.