Discovery of recessive effect of human polymerase δ proofreading deficiency through mutational analysis of POLD1-mutated normal and cancer cells.

Constitutional heterozygous pathogenic variants in the exonuclease domain of POLE and POLD1, which affect the proofreading activity of the corresponding polymerases, cause a cancer predisposition syndrome characterized by increased risk of gastrointestinal polyposis, colorectal cancer, endometrial cancer and other tumor types. The generally accepted explanation for the connection between the disruption of the proofreading activity of polymerases epsilon and delta and cancer development is through an increase in the somatic mutation rate. Here we studied an extended family with multiple members heterozygous for the pathogenic POLD1 variant c.1421T>C p.(Leu474Pro), which segregates with the polyposis and cancer phenotypes. Through the analysis of mutational patterns of patient-derived fibroblasts colonies and de novo mutations obtained by parent-offspring comparisons, we concluded that heterozygous POLD1 L474P just subtly increases the somatic and germline mutation burden. In contrast, tumors developed in individuals with a heterozygous mutation in the exonuclease domain of POLD1, including L474P, have an extremely high mutation rate (>100 mut/Mb) associated with signature SBS10d. We solved this contradiction through the observation that tumorigenesis involves somatic inactivation of the wildtype POLD1 allele. These results imply that exonuclease deficiency of polymerase delta has a recessive effect on mutation rate.

A hybrid pathway for self-sustained luminescence.

The fungal bioluminescence pathway can be reconstituted in other organisms allowing luminescence imaging without exogenously supplied substrate. The pathway starts from hispidin biosynthesis-a step catalyzed by a large fungal polyketide synthase that requires a posttranslational modification for activity. Here, we report identification of alternative compact hispidin synthases encoded by a phylogenetically diverse group of plants. A hybrid bioluminescence pathway that combines plant and fungal genes is more compact, not dependent on availability of machinery for posttranslational modifications, and confers autonomous bioluminescence in yeast, mammalian, and plant hosts. The compact size of plant hispidin synthases enables additional modes of delivery of autoluminescence, such as delivery with viral vectors.

Using AlphaFold to predict the impact of single mutations on protein stability and function.

AlphaFold changed the field of structural biology by achieving three-dimensional (3D) structure prediction from protein sequence at experimental quality. The astounding success even led to claims that the protein folding problem is "solved". However, protein folding problem is more than just structure prediction from sequence. Presently, it is unknown if the AlphaFold-triggered revolution could help to solve other problems related to protein folding. Here we assay the ability of AlphaFold to predict the impact of single mutations on protein stability (ΔΔG) and function. To study the question we extracted the pLDDT and metrics from AlphaFold predictions before and after single mutation in a protein and correlated the predicted change with the experimentally known ΔΔG values. Additionally, we correlated the same AlphaFold pLDDT metrics with the impact of a single mutation on structure using a large scale dataset of single mutations in GFP with the experimentally assayed levels of fluorescence. We found a very weak or no correlation between AlphaFold output metrics and change of protein stability or fluorescence. Our results imply that AlphaFold may not be immediately applied to other problems or applications in protein folding.

Relation Between the Number of Peaks and the Number of Reciprocal Sign Epistatic Interactions.

Empirical essays of fitness landscapes suggest that they may be rugged, that is having multiple fitness peaks. Such fitness landscapes, those that have multiple peaks, necessarily have special local structures, called reciprocal sign epistasis (Poelwijk et al. in J Theor Biol 272:141-144, 2011). Here, we investigate the quantitative relationship between the number of fitness peaks and the number of reciprocal sign epistatic interactions. Previously, it has been shown (Poelwijk et al. in J Theor Biol 272:141-144, 2011) that pairwise reciprocal sign epistasis is a necessary but not sufficient condition for the existence of multiple peaks. Applying discrete Morse theory, which to our knowledge has never been used in this context, we extend this result by giving the minimal number of reciprocal sign epistatic interactions required to create a given number of peaks.

Heterogeneity of the GFP fitness landscape and data-driven protein design.

Studies of protein fitness landscapes reveal biophysical constraints guiding protein evolution and empower prediction of functional proteins. However, generalisation of these findings is limited due to scarceness of systematic data on fitness landscapes of proteins with a defined evolutionary relationship. We characterized the fitness peaks of four orthologous fluorescent proteins with a broad range of sequence divergence. While two of the four studied fitness peaks were sharp, the other two were considerably flatter, being almost entirely free of epistatic interactions. Mutationally robust proteins, characterized by a flat fitness peak, were not optimal templates for machine-learning-driven protein design - instead, predictions were more accurate for fragile proteins with epistatic landscapes. Our work paves insights for practical application of fitness landscape heterogeneity in protein engineering.

Chromosome-encoded IpaH ubiquitin ligases indicate non-human enteroinvasive Escherichia.

Until recently, Shigella and enteroinvasive Escherichia coli were thought to be primate-restricted pathogens. The base of their pathogenicity is the type 3 secretion system (T3SS) encoded by the pINV virulence plasmid, which facilitates host cell invasion and subsequent proliferation. A large family of T3SS effectors, E3 ubiquitin-ligases encoded by the ipaH genes, have a key role in the Shigella pathogenicity through the modulation of cellular ubiquitination that degrades host proteins. However, recent genomic studies identified ipaH genes in the genomes of Escherichia marmotae, a potential marmot pathogen, and an E. coli extracted from fecal samples of bovine calves, suggesting that non-human hosts may also be infected by these strains, potentially pathogenic to humans. We performed a comparative genomic study of the functional repertoires in the ipaH gene family in Shigella and enteroinvasive Escherichia from human and predicted non-human hosts. We found that fewer than half of Shigella genomes had a complete set of ipaH genes, with frequent gene losses and duplications that were not consistent with the species tree and nomenclature. Non-human host IpaH proteins had a diverse set of substrate-binding domains and, in contrast to the Shigella proteins, two variants of the NEL C-terminal domain. Inconsistencies between strains phylogeny and composition of effectors indicate horizontal gene transfer between E. coli adapted to different hosts. These results provide a framework for understanding of ipaH-mediated host-pathogens interactions and suggest a need for a genomic study of fecal samples from diseased animals.

Rates of SARS-CoV-2 transmission and vaccination impact the fate of vaccine-resistant strains.

Vaccines are thought to be the best available solution for controlling the ongoing SARS-CoV-2 pandemic. However, the emergence of vaccine-resistant strains may come too rapidly for current vaccine developments to alleviate the health, economic and social consequences of the pandemic. To quantify and characterize the risk of such a scenario, we created a SIR-derived model with initial stochastic dynamics of the vaccine-resistant strain to study the probability of its emergence and establishment. Using parameters realistically resembling SARS-CoV-2 transmission, we model a wave-like pattern of the pandemic and consider the impact of the rate of vaccination and the strength of non-pharmaceutical intervention measures on the probability of emergence of a resistant strain. As expected, we found that a fast rate of vaccination decreases the probability of emergence of a resistant strain. Counterintuitively, when a relaxation of non-pharmaceutical interventions happened at a time when most individuals of the population have already been vaccinated the probability of emergence of a resistant strain was greatly increased. Consequently, we show that a period of transmission reduction close to the end of the vaccination campaign can substantially reduce the probability of resistant strain establishment. Our results suggest that policymakers and individuals should consider maintaining non-pharmaceutical interventions and transmission-reducing behaviours throughout the entire vaccination period.

The limits of normal approximation for adult height.

Adult height inspired the first biometrical and quantitative genetic studies and is a test-case trait for understanding heritability. The studies of height led to formulation of the classical polygenic model, that has a profound influence on the way we view and analyse complex traits. An essential part of the classical model is an assumption of additivity of effects and normality of the distribution of the residuals. However, it may be expected that the normal approximation will become insufficient in bigger studies. Here, we demonstrate that when the height of hundreds of thousands of individuals is analysed, the model complexity needs to be increased to include non-additive interactions between sex, environment and genes. Alternatively, the use of log-normal approximation allowed us to still use the additive effects model. These findings are important for future genetic and methodologic studies that make use of adult height as an exemplar trait.

Author Correction: Plants with genetically encoded autoluminescence.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A Method for Identification of the Methylation Level of CpG Islands From NGS Data.

In the course of sample preparation for Next Generation Sequencing (NGS), DNA is fragmented by various methods. Fragmentation shows a persistent bias with regard to the cleavage rates of various dinucleotides. With the exception of CpG dinucleotides the previously described biases were consistent with results of the DNA cleavage in solution. Here we computed cleavage rates of all dinucleotides including the methylated CpG and unmethylated CpG dinucleotides using data of the Whole Genome Sequencing datasets of the 1000 Genomes project. We found that the cleavage rate of CpG is significantly higher for the methylated CpG dinucleotides. Using this information, we developed a classifier for distinguishing cancer and healthy tissues based on their CpG islands statuses of the fragmentation. A simple Support Vector Machine classifier based on this algorithm shows an accuracy of 84%. The proposed method allows the detection of epigenetic markers purely based on mechanochemical DNA fragmentation, which can be detected by a simple analysis of the NGS sequencing data.

Plants with genetically encoded autoluminescence.

Autoluminescent plants engineered to express a bacterial bioluminescence gene cluster in plastids have not been widely adopted because of low light output. We engineered tobacco plants with a fungal bioluminescence system that converts caffeic acid (present in all plants) into luciferin and report self-sustained luminescence that is visible to the naked eye. Our findings could underpin development of a suite of imaging tools for plants.

HypercubeME: two hundred million combinatorially complete datasets from a single experiment.

MOTIVATION: Epistasis, the context-dependence of the contribution of an amino acid substitution to fitness, is common in evolution. To detect epistasis, fitness must be measured for at least four genotypes: the reference genotype, two different single mutants and a double mutant with both of the single mutations. For higher-order epistasis of the order n, fitness has to be measured for all 2n genotypes of an n-dimensional hypercube in genotype space forming a "combinatorially complete dataset". So far, only a handful of such datasets have been produced by manual curation. Concurrently, random mutagenesis experiments have produced measurements of fitness and other phenotypes in a high-throughput manner, potentially containing a number of combinatorially complete datasets. RESULTS: We present an effective recursive algorithm for finding all hypercube structures in random mutagenesis experimental data. To test the algorithm, we applied it to the data from a recent HIS3 protein dataset and found all 199,847,053 unique combinatorially complete genotype combinations of dimensionality ranging from two to twelve. The algorithm may be useful for researchers looking for higher-order epistasis in their high-throughput experimental data. AVAILABILITY: https://github.com/ivankovlab/HypercubeME.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An experimental assay of the interactions of amino acids from orthologous sequences shaping a complex fitness landscape.

Characterizing the fitness landscape, a representation of fitness for a large set of genotypes, is key to understanding how genetic information is interpreted to create functional organisms. Here we determined the evolutionarily-relevant segment of the fitness landscape of His3, a gene coding for an enzyme in the histidine synthesis pathway, focusing on combinations of amino acid states found at orthologous sites of extant species. Just 15% of amino acids found in yeast His3 orthologues were always neutral while the impact on fitness of the remaining 85% depended on the genetic background. Furthermore, at 67% of sites, amino acid replacements were under sign epistasis, having both strongly positive and negative effect in different genetic backgrounds. 46% of sites were under reciprocal sign epistasis. The fitness impact of amino acid replacements was influenced by only a few genetic backgrounds but involved interaction of multiple sites, shaping a rugged fitness landscape in which many of the shortest paths between highly fit genotypes are inaccessible.

Genetically encodable bioluminescent system from fungi.

Bioluminescence is found across the entire tree of life, conferring a spectacular set of visually oriented functions from attracting mates to scaring off predators. Half a dozen different luciferins, molecules that emit light when enzymatically oxidized, are known. However, just one biochemical pathway for luciferin biosynthesis has been described in full, which is found only in bacteria. Here, we report identification of the fungal luciferase and three other key enzymes that together form the biosynthetic cycle of the fungal luciferin from caffeic acid, a simple and widespread metabolite. Introduction of the identified genes into the genome of the yeast Pichia pastoris along with caffeic acid biosynthesis genes resulted in a strain that is autoluminescent in standard media. We analyzed evolution of the enzymes of the luciferin biosynthesis cycle and found that fungal bioluminescence emerged through a series of events that included two independent gene duplications. The retention of the duplicated enzymes of the luciferin pathway in nonluminescent fungi shows that the gene duplication was followed by functional sequence divergence of enzymes of at least one gene in the biosynthetic pathway and suggests that the evolution of fungal bioluminescence proceeded through several closely related stepping stone nonluminescent biochemical reactions with adaptive roles. The availability of a complete eukaryotic luciferin biosynthesis pathway provides several applications in biomedicine and bioengineering.

Negative selection in tumor genome evolution acts on essential cellular functions and the immunopeptidome.

BACKGROUND: Natural selection shapes cancer genomes. Previous studies used signatures of positive selection to identify genes driving malignant transformation. However, the contribution of negative selection against somatic mutations that affect essential tumor functions or specific domains remains a controversial topic. RESULTS: Here, we analyze 7546 individual exomes from 26 tumor types from TCGA data to explore the portion of the cancer exome under negative selection. Although we find most of the genes neutrally evolving in a pan-cancer framework, we identify essential cancer genes and immune-exposed protein regions under significant negative selection. Moreover, our simulations suggest that the amount of negative selection is underestimated. We therefore choose an empirical approach to identify genes, functions, and protein regions under negative selection. We find that expression and mutation status of negatively selected genes is indicative of patient survival. Processes that are most strongly conserved are those that play fundamental cellular roles such as protein synthesis, glucose metabolism, and molecular transport. Intriguingly, we observe strong signals of selection in the immunopeptidome and proteins controlling peptide exposition, highlighting the importance of immune surveillance evasion. Additionally, tumor type-specific immune activity correlates with the strength of negative selection on human epitopes. CONCLUSIONS: In summary, our results show that negative selection is a hallmark of cell essentiality and immune response in cancer. The functional domains identified could be exploited therapeutically, ultimately allowing for the development of novel cancer treatments.

Self-consistency test reveals systematic bias in programs for prediction change of stability upon mutation.

Motivation: Computational prediction of the effect of mutations on protein stability is used by researchers in many fields. The utility of the prediction methods is affected by their accuracy and bias. Bias, a systematic shift of the predicted change of stability, has been noted as an issue for several methods, but has not been investigated systematically. Presence of the bias may lead to misleading results especially when exploring the effects of combination of different mutations. Results: Here we use a protocol to measure the bias as a function of the number of introduced mutations. It is based on a self-consistency test of the reciprocity the effect of a mutation. An advantage of the used approach is that it relies solely on crystal structures without experimentally measured stability values. We applied the protocol to four popular algorithms predicting change of protein stability upon mutation, FoldX, Eris, Rosetta and I-Mutant, and found an inherent bias. For one program, FoldX, we manage to substantially reduce the bias using additional relaxation by Modeller. Authors using algorithms for predicting effects of mutations should be aware of the bias described here. Availability and implementation: All calculations were implemented by in-house PERL scripts. Supplementary information: Supplementary data are available at Bioinformatics online. Note: The article 10.1093/bioinformatics/bty348, published alongside this paper, also addresses the problem of biases in protein stability change predictions.

Saturation of recognition elements blocks evolution of new tRNA identities.

Understanding the principles that led to the current complexity of the genetic code is a central question in evolution. Expansion of the genetic code required the selection of new transfer RNAs (tRNAs) with specific recognition signals that allowed them to be matured, modified, aminoacylated, and processed by the ribosome without compromising the fidelity or efficiency of protein synthesis. We show that saturation of recognition signals blocks the emergence of new tRNA identities and that the rate of nucleotide substitutions in tRNAs is higher in species with fewer tRNA genes. We propose that the growth of the genetic code stalled because a limit was reached in the number of identity elements that can be effectively used in the tRNA structure.

Local fitness landscape of the green fluorescent protein.

Fitness landscapes depict how genotypes manifest at the phenotypic level and form the basis of our understanding of many areas of biology, yet their properties remain elusive. Previous studies have analysed specific genes, often using their function as a proxy for fitness, experimentally assessing the effect on function of single mutations and their combinations in a specific sequence or in different sequences. However, systematic high-throughput studies of the local fitness landscape of an entire protein have not yet been reported. Here we visualize an extensive region of the local fitness landscape of the green fluorescent protein from Aequorea victoria (avGFP) by measuring the native function (fluorescence) of tens of thousands of derivative genotypes of avGFP. We show that the fitness landscape of avGFP is narrow, with 3/4 of the derivatives with a single mutation showing reduced fluorescence and half of the derivatives with four mutations being completely non-fluorescent. The narrowness is enhanced by epistasis, which was detected in up to 30% of genotypes with multiple mutations and mostly occurred through the cumulative effect of slightly deleterious mutations causing a threshold-like decrease in protein stability and a concomitant loss of fluorescence. A model of orthologous sequence divergence spanning hundreds of millions of years predicted the extent of epistasis in our data, indicating congruence between the fitness landscape properties at the local and global scales. The characterization of the local fitness landscape of avGFP has important implications for several fields including molecular evolution, population genetics and protein design.

Massively parallel enzyme kinetics reveals the substrate recognition landscape of the metalloprotease ADAMTS13.

Proteases play important roles in many biologic processes and are key mediators of cancer, inflammation, and thrombosis. However, comprehensive and quantitative techniques to define the substrate specificity profile of proteases are lacking. The metalloprotease ADAMTS13 regulates blood coagulation by cleaving von Willebrand factor (VWF), reducing its procoagulant activity. A mutagenized substrate phage display library based on a 73-amino acid fragment of VWF was constructed, and the ADAMTS13-dependent change in library complexity was evaluated over reaction time points, using high-throughput sequencing. Reaction rate constants (kcat/KM) were calculated for nearly every possible single amino acid substitution within this fragment. This massively parallel enzyme kinetics analysis detailed the specificity of ADAMTS13 and demonstrated the critical importance of the P1-P1' substrate residues while defining exosite binding domains. These data provided empirical evidence for the propensity for epistasis within VWF and showed strong correlation to conservation across orthologs, highlighting evolutionary selective pressures for VWF.