Insight into structure and assembly of the nuclear pore complex by utilizing the genome of a eukaryotic thermophile.

Despite decades of research, the structure and assembly of the nuclear pore complex (NPC), which is composed of ∼30 nucleoporins (Nups), remain elusive. Here, we report the genome of the thermophilic fungus Chaetomium thermophilum (ct) and identify the complete repertoire of Nups therein. The thermophilic proteins show improved properties for structural and biochemical studies compared to their mesophilic counterparts, and purified ctNups enabled the reconstitution of the inner pore ring module that spans the width of the NPC from the anchoring membrane to the central transport channel. This module is composed of two large Nups, Nup192 and Nup170, which are flexibly bridged by short linear motifs made up of linker Nups, Nic96 and Nup53. This assembly illustrates how Nup interactions can generate structural plasticity within the NPC scaffold. Our findings therefore demonstrate the utility of the genome of a thermophilic eukaryote for studying complex molecular machines.

FLAMS: Find Lysine Acylations and other Modification Sites.

SUMMARY: Today, hundreds of post-translational modification (PTM) sites are routinely identified at once, but the comparison of new experimental datasets to already existing ones is hampered by the current inability to search most PTM databases at the protein residue level. We present FLAMS (Find Lysine Acylations and other Modification Sites), a Python3-based command line and web-tool that enables researchers to compare their PTM sites to the contents of the CPLM, the largest dedicated protein lysine modification database, and dbPTM, the most comprehensive general PTM database, at the residue level. FLAMS can be integrated into PTM analysis pipelines, allowing researchers to quickly assess the novelty and conservation of PTM sites across species in newly generated datasets, aiding in the functional assessment of sites and the prioritization of sites for further experimental characterization. AVAILABILITY AND IMPLEMENTATION: FLAMS is implemented in Python3, and freely available under an MIT license. It can be found as a command line tool at https://github.com/hannelorelongin/FLAMS, pip and conda; and as a web service at https://www.biw.kuleuven.be/m2s/cmpg/research/CSB/tools/flams/.

DARTpaths, an in silico platform to investigate molecular mechanisms of compounds.

SUMMARY: Xpaths is a collection of algorithms that allow for the prediction of compound-induced molecular mechanisms of action by integrating phenotypic endpoints of different species; and proposes follow-up tests for model organisms to validate these pathway predictions. The Xpaths algorithms are applied to predict developmental and reproductive toxicity (DART) and implemented into an in silico platform, called DARTpaths. AVAILABILITY AND IMPLEMENTATION: All code is available on GitHub https://github.com/Xpaths/dartpaths-app under Apache license 2.0, detailed overview with demo is available at https://www.vivaltes.com/dartpaths/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Molecular Evolution of Aryl Hydrocarbon Receptor Signaling Pathway Genes.

The Aryl hydrocarbon receptor is an ancient transcriptional factor originally discovered as a sensor of dioxin. In addition to its function as a receptor of environmental toxicants, it plays an important role in development. Although a significant amount of research has been carried out to understand the AHR signal transduction pathway and its involvement in species' susceptibility to environmental toxicants, none of them to date has comprehensively studied its evolutionary origins. Studying the evolutionary origins of molecules can inform ancestral relationships of genes. The vertebrate genome has been shaped by two rounds of whole-genome duplications (WGD) at the base of vertebrate evolution approximately 600 million years ago, followed by lineage-specific gene losses, which often complicate the assignment of orthology. It is crucial to understand the evolutionary origins of this transcription factor and its partners, to distinguish orthologs from ancient non-orthologous homologs. In this study, we have investigated the evolutionary origins of proteins involved in the AHR pathway. Our results provide evidence of gene loss and duplications, crucial for understanding the functional connectivity of humans and model species. Multiple studies have shown that 2R-ohnologs (genes and proteins that have survived from the 2R-WGD) are enriched in signaling components relevant to developmental disorders and cancer. Our findings provide a link between the AHR pathway's evolutionary trajectory and its potential mechanistic involvement in pathogenesis.

Genomics of an endemic cystic fibrosis Burkholderia multivorans strain reveals low within-patient evolution but high between-patient diversity.

Burkholderia multivorans is a member of the Burkholderia cepacia complex (Bcc), notorious for its pathogenicity in persons with cystic fibrosis. Epidemiological surveillance suggests that patients predominantly acquire B. multivorans from environmental sources, with rare cases of patient-to-patient transmission. Here we report on the genomic analysis of thirteen isolates from an endemic B. multivorans strain infecting four cystic fibrosis patients treated in different pediatric cystic fibrosis centers in Belgium, with no evidence of cross-infection. All isolates share an identical sequence type (ST-742) but whole genome analysis shows that they exhibit peculiar patterns of genomic diversity between patients. By combining short and long reads sequencing technologies, we highlight key differences in terms of small nucleotide polymorphisms indicative of low rates of adaptive evolution within patient, and well-defined, hundred kbps-long segments of high enrichment in mutations between patients. In addition, we observed large structural genomic variations amongst the isolates which revealed different plasmid contents, active roles for transposase IS3 and IS5 in the deactivation of genes, and mobile prophage elements. Our study shows limited within-patient B. multivorans evolution and high between-patient strain diversity, indicating that an environmental microdiverse reservoir must be present for this endemic strain, in which active diversification is taking place. Furthermore, our analysis also reveals a set of 30 parallel adaptations across multiple patients, indicating that the specific genomic background of a given strain may dictate the route of adaptation within the cystic fibrosis lung.

Molecular dynamics shows complex interplay and long-range effects of post-translational modifications in yeast protein interactions.

Post-translational modifications (PTMs) play a vital, yet often overlooked role in the living cells through modulation of protein properties, such as localization and affinity towards their interactors, thereby enabling quick adaptation to changing environmental conditions. We have previously benchmarked a computational framework for the prediction of PTMs' effects on the stability of protein-protein interactions, which has molecular dynamics simulations followed by free energy calculations at its core. In the present work, we apply this framework to publicly available data on Saccharomyces cerevisiae protein structures and PTM sites, identified in both normal and stress conditions. We predict proteome-wide effects of acetylations and phosphorylations on protein-protein interactions and find that acetylations more frequently have locally stabilizing roles in protein interactions, while the opposite is true for phosphorylations. However, the overall impact of PTMs on protein-protein interactions is more complex than a simple sum of local changes caused by the introduction of PTMs and adds to our understanding of PTM cross-talk. We further use the obtained data to calculate the conformational changes brought about by PTMs. Finally, conservation of the analyzed PTM residues in orthologues shows that some predictions for yeast proteins will be mirrored to other organisms, including human. This work, therefore, contributes to our overall understanding of the modulation of the cellular protein interaction networks in yeast and beyond.

Integrated Multi-Omics Analysis of Mechanisms Underlying Yeast Ethanol Tolerance.

For yeast cells, tolerance to high levels of ethanol is vital both in their natural environment and in industrially relevant conditions. We recently genotyped experimentally evolved yeast strains adapted to high levels of ethanol and identified mutations linked to ethanol tolerance. In this study, by integrating genomic sequencing data with quantitative proteomics profiles from six evolved strains (data set identifier PXD006631) and construction of protein interaction networks, we elucidate exactly how the genotype and phenotype are related at the molecular level. Our multi-omics approach points to the rewiring of numerous metabolic pathways affected by genomic and proteomic level changes, from energy-producing and lipid pathways to differential regulation of transposons and proteins involved in cell cycle progression. One of the key differences is found in the energy-producing metabolism, where the ancestral yeast strain responds to ethanol by switching to respiration and employing the mitochondrial electron transport chain. In contrast, the ethanol-adapted strains appear to have returned back to energy production mainly via glycolysis and ethanol fermentation, as supported by genomic and proteomic level changes. This work is relevant for synthetic biology where systems need to function under stressful conditions, as well as for industry and in cancer biology, where it is important to understand how the genotype relates to the phenotype.

Resurrected Protein Interaction Networks Reveal the Innovation Potential of Ancient Whole-Genome Duplication.

The evolution of plants is characterized by whole-genome duplications, sometimes closely associated with the origin of large groups of species. The gamma (γ) genome triplication occurred at the origin of the core eudicots, which comprise ∼75% of flowering plants. To better understand the impact of whole-genome duplication, we studied the protein interaction network of MADS domain transcription factors, which are key regulators of reproductive development. We reconstructed, synthesized, and tested the interactions of ancestral proteins immediately before and closely after the triplication and directly compared these ancestral networks to the extant networks of Arabidopsis thaliana and tomato (Solanum lycopersicum). We found that gamma expanded the MADS domain interaction network more strongly than subsequent genomic events. This event strongly rewired MADS domain interactions and allowed for the evolution of new functions and installed robustness through new redundancy. Despite extensive rewiring, the organization of the network was maintained through gamma. New interactions and protein retention compensated for its potentially destructive impact on network organization. Post gamma, the network evolved from an organization around the single hub SEP3 to a network organized around multiple hubs and well-connected proteins lost, rather than gained, interactions. The data provide a resource for comparative developmental biology in flowering plants.

Unraveling Protein Interactions between the Temperate Virus Bam35 and Its Bacillus Host Using an Integrative Yeast Two Hybrid-High Throughput Sequencing Approach.

Bacillus virus Bam35 is the model Betatectivirus and member of the family Tectiviridae, which is composed of tailless, icosahedral, and membrane-containing bacteriophages. Interest in these viruses has greatly increased in recent years as they are thought to be an evolutionary link between diverse groups of prokaryotic and eukaryotic viruses. Additionally, betatectiviruses infect bacteria of the Bacillus cereus group, which are known for their applications in industry and notorious since it contains many pathogens. Here, we present the first protein-protein interactions (PPIs) network for a tectivirus-host system by studying the Bam35-Bacillus thuringiensis model using a novel approach that integrates the traditional yeast two-hybrid system and high-throughput sequencing (Y2H-HTS). We generated and thoroughly analyzed a genomic library of Bam35's host B. thuringiensis HER1410 and screened interactions with all the viral proteins using different combinations of bait-prey couples. Initial analysis of the raw data enabled the identification of over 4000 candidate interactions, which were sequentially filtered to produce 182 high-confidence interactions that were defined as part of the core virus-host interactome. Overall, host metabolism proteins and peptidases were particularly enriched within the detected interactions, distinguishing this host-phage system from the other reported host-phage PPIs. Our approach also suggested biological roles for several Bam35 proteins of unknown function, including the membrane structural protein P25, which may be a viral hub with a role in host membrane modification during viral particle morphogenesis. This work resulted in a better understanding of the Bam35-B. thuringiensis interaction at the molecular level and holds great potential for the generalization of the Y2H-HTS approach for other virus-host models.

Integrative omics analysis of Pseudomonas aeruginosa virus PA5oct highlights the molecular complexity of jumbo phages.

Pseudomonas virus vB_PaeM_PA5oct is proposed as a model jumbo bacteriophage to investigate phage-bacteria interactions and is a candidate for phage therapy applications. Combining hybrid sequencing, RNA-Seq and mass spectrometry allowed us to accurately annotate its 286,783 bp genome with 461 coding regions including four non-coding RNAs (ncRNAs) and 93 virion-associated proteins. PA5oct relies on the host RNA polymerase for the infection cycle and RNA-Seq revealed a gradual take-over of the total cell transcriptome from 21% in early infection to 93% in late infection. PA5oct is not organized into strictly contiguous regions of temporal transcription, but some genomic regions transcribed in early, middle and late phases of infection can be discriminated. Interestingly, we observe regions showing limited transcription activity throughout the infection cycle. We show that PA5oct upregulates specific bacterial operons during infection including operons pncA-pncB1-nadE involved in NAD biosynthesis, psl for exopolysaccharide biosynthesis and nap for periplasmic nitrate reductase production. We also observe a downregulation of T4P gene products suggesting mechanisms of superinfection exclusion. We used the proteome of PA5oct to position our isolate amongst other phages using a gene-sharing network. This integrative omics study illustrates the molecular diversity of jumbo viruses and raises new questions towards cellular regulation and phage-encoded hijacking mechanisms.

Effects of Acetylation and Phosphorylation on Subunit Interactions in Three Large Eukaryotic Complexes.

Protein post-translational modifications (PTMs) have an indispensable role in living cells as they expand chemical diversity of the proteome, providing a fine regulatory layer that can govern protein-protein interactions in changing environmental conditions. Here we investigated the effects of acetylation and phosphorylation on the stability of subunit interactions in purified Saccharomyces cerevisiae complexes, namely exosome, RNA polymerase II and proteasome. We propose a computational framework that consists of conformational sampling of the complexes by molecular dynamics simulations, followed by Gibbs energy calculation by MM/GBSA. After benchmarking against published tools such as FoldX and Mechismo, we could apply the framework for the first time on large protein assemblies with the aim of predicting the effects of PTMs located on interfaces of subunits on binding stability. We discovered that acetylation predominantly contributes to subunits' interactions in a locally stabilizing manner, while phosphorylation shows the opposite effect. Even though the local binding contributions of PTMs may be predictable to an extent, the long range effects and overall impact on subunits' binding were only captured because of our dynamical approach. Employing the developed, widely applicable workflow on other large systems will shed more light on the roles of PTMs in protein complex formation.

The Genome of the Plant-Associated Lactic Acid Bacterium Lactococcus lactis KF147 Harbors a Hybrid NRPS-PKS System Conserved in Strains of the Dental Cariogenic Streptococcus mutans.

Lactococcus lactis subsp. lactis KF147 as a non-dairy strain from lactic acid bacteria (LAB) can inhabit plant tissues. It can grow on complex carbohydrates derived from plant cell walls. Its genome size is one of the largest among the sequenced lactococcal strains, possessing many genes that do not have homologues in the published genome sequences of dairy-associated L. lactis strains. In silico analysis has identified a gene cluster encoding a hybrid NRPS-PKS system (composed of non-ribosomal peptide synthetases and polyketide synthases) in the L. lactis KF147 genome, as first example of a LAB possessing such hybrid mega-enzymes. Hybrid systems produce hybrid NRP-PK secondary metabolites (natural products) in a wide variety of bacteria, fungi, and plants. In the hybrid NRPS-PKS system of L. lactis KF147, a total of 21 NRPS and 8 PKS domains were identified that are arranged into 6 NRPS modules, 3 PKS modules, and two single functional domains (trans-acyl-transferase "transAT" and thioesterase). We found homologous hybrid systems having similar gene, module, and domain organization in six other L. lactis strains and 25 strains of the dental cariogenic Streptococcus mutans. This study mainly aimed to predict the structure and function of the hybrid NRP-PK product of L. lactis KF147 using comparative genomics techniques, and included a detailed analysis of the regulatory system. Various bioinformatical approaches were used to predict the substrate specificity of the six A domains and the iterative transAT domain. Functional conservation of the A domains within different-niche-associated strains supported the prediction of the primary core structure of the putative hybrid natural product to be Leu-DLeu-Asp-DAsn-Gly-MC-MC-MC-DAsp (MC = Malonyl-CoA). Oxidative stress resistance and biofilm formation are the most probable functions of this hybrid system. The need for such a system in two different niches is argued, as an adaptation of L. lactis and S. mutans to adhere to plant tissues and human teeth, respectively, in an oxidative environment.

Catabolic task division between two near-isogenic subpopulations co-existing in a herbicide-degrading bacterial consortium: consequences for the interspecies consortium metabolic model.

Variovorax sp. WDL1 mediates hydrolysis of the herbicide linuron into 3,4-dichloroaniline (DCA) and N,O-dimethylhydroxylamine in a tripartite bacterial consortium with Comamonas testosteroni WDL7 and Hyphomicrobium sulfonivorans WDL6. Although strain WDL1 contains the dcaQTA1A2B operon for DCA oxidation, this conversion is mainly performed by WDL7. Phenotypic diversification observed in WDL1 cultures and scrutiny of the WDL1 genome suggest that WDL1 cultures consist of two dedicated subpopulations, i.e., a linuron-hydrolysing subpopulation (Lin + DCA-) and a DCA-oxidizing subpopulation (Lin-DCA+). Whole genome analysis of strains representing the respective subpopulations revealed that they are identical, aside from the presence of hylA (in Lin + DCA- cells) and the dcaQTA1A2B gene cluster (in Lin-DCA+ cells), and that these catabolic gene modules replace each other at exactly the same locus on a 1380 kb extra-chromosomal element that shows plasmid gene functions including genes for transferability by conjugation. Both subpopulations proliferate in consortium biofilms fed with linuron, but Lin + DCA- cells compose the main WDL1 subpopulation. Our observations instigated revisiting the interactions within the consortium and suggest that the physical separation of two essential linuron catabolic gene clusters in WDL1 by mutually exclusive integration in the same mobile genetic element is key to the existence of WDL1 in a consortium mode.

Evolutionary conservation of Ebola virus proteins predicts important functions at residue level.

MOTIVATION: The recent outbreak of Ebola virus disease (EVD) resulted in a large number of human deaths. Due to this devastation, the Ebola virus has attracted renewed interest as model for virus evolution. Recent literature on Ebola virus (EBOV) has contributed substantially to our understanding of the underlying genetics and its scope with reference to the 2014 outbreak. But no study yet, has focused on the conservation patterns of EBOV proteins. RESULTS: We analyzed the evolution of functional regions of EBOV and highlight the function of conserved residues in protein activities. We apply an array of computational tools to dissect the functions of EBOV proteins in detail: (i) protein sequence conservation, (ii) protein-protein interactome analysis, (iii) structural modeling and (iv) kinase prediction. Our results suggest the presence of novel post-translational modifications in EBOV proteins and their role in the modulation of protein functions and protein interactions. Moreover, on the basis of the presence of ATM recognition motifs in all EBOV proteins we postulate a role of DNA damage response pathways and ATM kinase in EVD. The ATM kinase is put forward, for further evaluation, as novel potential therapeutic target. AVAILABILITY AND IMPLEMENTATION: http://www.biw.kuleuven.be/CSB/EBOV-PTMs CONTACT: vera.vannoort@biw.kuleuven.beSupplementary information: Supplementary data are available at Bioinformatics online.

yMap: an automated method to map yeast variants to protein modifications and functional regions.

Summary: Recent advances in sequence technology result in large datasets of sequence variants. For the human genome, several tools are available to predict the impact of these variants on gene and protein functions. However, for model organisms such as yeast such tools are lacking, specifically to predict the effect of protein sequence altering variants on the protein level. We present a python framework that enables users to map in a fully automated fashion large set of variants to protein functional regions and post-translationally modified residues. Furthermore, we provide the user with the possibility to retrieve predicted functional information on modified residues from other resources for example that are predicted to play a role in protein-protein interactions. The results are complemented by statistical tests to highlight the significance of underlying functions and pathways affected by mutations. We show the application of this package on a yeast dataset derived from a recent evolutionary experiment on adaptation to ethanol. Availability and Implementation: The package is available from https://github.com/CSB-KUL/yMap and is implemented in Python. Contact: vera.vannoort@biw.kuleuven.be. Supplementary information: Supplementary data are available at Bioinformatics online.

Catabolism of the groundwater micropollutant 2,6-dichlorobenzamide beyond 2,6-dichlorobenzoate is plasmid encoded in Aminobacter sp. MSH1.

Aminobacter sp. MSH1 uses the groundwater micropollutant 2,6-dichlorobenzamide (BAM) as sole source of carbon and energy. In the first step, MSH1 converts BAM to 2,6-dichlorobenzoic acid (2,6-DCBA) by means of the BbdA amidase encoded on the IncP-1ß plasmid pBAM1. Information about the genes and degradation steps involved in 2,6-DCBA metabolism in MSH1 or any other organism is currently lacking. Here, we show that the genes for 2,6-DCBA degradation in strain MSH1 reside on a second catabolic plasmid in MSH1, designated as pBAM2. The complete sequence of pBAM2 was determined revealing that it is a 53.9 kb repABC family plasmid. The 2,6-DCBA catabolic genes on pBAM2 are organized in two main clusters bordered by IS elements and integrase genes and encode putative functions like Rieske mono-/dioxygenase, meta-cleavage dioxygenase, and reductive dehalogenases. The putative mono-oxygenase encoded by the bbdD gene was shown to convert 2,6-DCBA to 3-hydroxy-2,6-dichlorobenzoate (3-OH-2,6-DCBA). 3-OH-DCBA was degraded by wild-type MSH1 and not by a pBAM2-free MSH1 variant indicating that it is a likely intermediate in the pBAM2-encoded DCBA catabolic pathway. Based on the activity of BbdD and the putative functions of the other catabolic genes on pBAM2, a metabolic pathway for BAM/2,6-DCBA in strain MSH1 was suggested.

Integration of multi-omics data of a genome-reduced bacterium: Prevalence of post-transcriptional regulation and its correlation with protein abundances.

We developed a comprehensive resource for the genome-reduced bacterium Mycoplasma pneumoniae comprising 1748 consistently generated '-omics' data sets, and used it to quantify the power of antisense non-coding RNAs (ncRNAs), lysine acetylation, and protein phosphorylation in predicting protein abundance (11%, 24% and 8%, respectively). These factors taken together are four times more predictive of the proteome abundance than of mRNA abundance. In bacteria, post-translational modifications (PTMs) and ncRNA transcription were both found to increase with decreasing genomic GC-content and genome size. Thus, the evolutionary forces constraining genome size and GC-content modify the relative contributions of the different regulatory layers to proteome homeostasis, and impact more genomic and genetic features than previously appreciated. Indeed, these scaling principles will enable us to develop more informed approaches when engineering minimal synthetic genomes.

Adaptation to High Ethanol Reveals Complex Evolutionary Pathways.

Tolerance to high levels of ethanol is an ecologically and industrially relevant phenotype of microbes, but the molecular mechanisms underlying this complex trait remain largely unknown. Here, we use long-term experimental evolution of isogenic yeast populations of different initial ploidy to study adaptation to increasing levels of ethanol. Whole-genome sequencing of more than 30 evolved populations and over 100 adapted clones isolated throughout this two-year evolution experiment revealed how a complex interplay of de novo single nucleotide mutations, copy number variation, ploidy changes, mutator phenotypes, and clonal interference led to a significant increase in ethanol tolerance. Although the specific mutations differ between different evolved lineages, application of a novel computational pipeline, PheNetic, revealed that many mutations target functional modules involved in stress response, cell cycle regulation, DNA repair and respiration. Measuring the fitness effects of selected mutations introduced in non-evolved ethanol-sensitive cells revealed several adaptive mutations that had previously not been implicated in ethanol tolerance, including mutations in PRT1, VPS70 and MEX67. Interestingly, variation in VPS70 was recently identified as a QTL for ethanol tolerance in an industrial bio-ethanol strain. Taken together, our results show how, in contrast to adaptation to some other stresses, adaptation to a continuous complex and severe stress involves interplay of different evolutionary mechanisms. In addition, our study reveals functional modules involved in ethanol resistance and identifies several mutations that could help to improve the ethanol tolerance of industrial yeasts.

ARA-PEPs: a repository of putative sORF-encoded peptides in Arabidopsis thaliana.

BACKGROUND: Many eukaryotic RNAs have been considered non-coding as they only contain short open reading frames (sORFs). However, there is increasing evidence for the translation of these sORFs into bioactive peptides with potent signaling, antimicrobial, developmental, antioxidant roles etc. Yet only a few peptides encoded by sORFs are annotated in the model organism Arabidopsis thaliana. RESULTS: To aid the functional annotation of these peptides, we have developed ARA-PEPs (available at http://www.biw.kuleuven.be/CSB/ARA-PEPs ), a repository of putative peptides encoded by sORFs in the A. thaliana genome starting from in-house Tiling arrays, RNA-seq data and other publicly available datasets. ARA-PEPs currently lists 13,748 sORF-encoded peptides with transcriptional evidence. In addition to existing data, we have identified 100 novel transcriptionally active regions (TARs) that might encode 341 novel stress-induced peptides (SIPs). To aid in identification of bioactivity, we add functional annotation and sequence conservation to predicted peptides. CONCLUSION: To our knowledge, this is the largest repository of plant peptides encoded by sORFs with transcript evidence, publicly available and this resource will help scientists to effortlessly navigate the list of experimentally studied peptides, the experimental and computational evidence supporting the activity of these peptides and gain new perspectives for peptide discovery.

Correlated duplications and losses in the evolution of palmitoylation writer and eraser families.

BACKGROUND: Protein post-translational modifications (PTMs) change protein properties. Each PTM type is associated with domain families that apply the modification (writers), remove the modification (erasers) and bind to the modified sites (readers) together called toolkit domains. The evolutionary origin and diversification remains largely understudied, except for tyrosine phosphorylation. Protein palmitoylation entails the addition of a palmitoyl fatty acid to a cysteine residue. This PTM functions as a membrane anchor and is involved in a range of cellular processes. One writer family and two erasers families are known for protein palmitoylation. RESULTS: In this work we unravel the evolutionary history of these writer and eraser families. We constructed a high-quality profile hidden Markov model (HMM) of each family, searched for protein family members in fully sequenced genomes and subsequently constructed phylogenetic distributions of the families. We constructed Maximum Likelihood phylogenetic trees and using gene tree rearrangement and tree reconciliation inferred their evolutionary histories in terms of duplication and loss events. We identified lineages where the families expanded or contracted and found that the evolutionary histories of the families are correlated. The results show that the erasers were invented first, before the origin of the eukaryotes. The writers first arose in the eukaryotic ancestor. The writers and erasers show co-expansions in several eukaryotic ancestral lineages. These expansions often seem to be followed by contractions in some or all of the lineages further in evolution. CONCLUSIONS: A general pattern of correlated evolution appears between writer and eraser domains. These co-evolution patterns could be used in new methods for interaction prediction based on phylogenies.