Whitefly hijacks a plant detoxification gene that neutralizes plant toxins.

Plants protect themselves with a vast array of toxic secondary metabolites, yet most plants serve as food for insects. The evolutionary processes that allow herbivorous insects to resist plant defenses remain largely unknown. The whitefly Bemisia tabaci is a cosmopolitan, highly polyphagous agricultural pest that vectors several serious plant pathogenic viruses and is an excellent model to probe the molecular mechanisms involved in overcoming plant defenses. Here, we show that, through an exceptional horizontal gene transfer event, the whitefly has acquired the plant-derived phenolic glucoside malonyltransferase gene BtPMaT1. This gene enables whiteflies to neutralize phenolic glucosides. This was confirmed by genetically transforming tomato plants to produce small interfering RNAs that silence BtPMaT1, thus impairing the whiteflies' detoxification ability. These findings reveal an evolutionary scenario whereby herbivores harness the genetic toolkit of their host plants to develop resistance to plant defenses and how this can be exploited for crop protection.

Cytomegalovirus subverts macrophage identity.

Cytomegaloviruses (CMVs) have co-evolved with their mammalian hosts for millions of years, leading to remarkable host specificity and high infection prevalence. Macrophages, which already populate barrier tissues in the embryo, are the predominant immune cells at potential CMV entry sites. Here we show that, upon CMV infection, macrophages undergo a morphological, immunophenotypic, and metabolic transformation process with features of stemness, altered migration, enhanced invasiveness, and provision of the cell cycle machinery for viral proliferation. This complex process depends on Wnt signaling and the transcription factor ZEB1. In pulmonary infection, mouse CMV primarily targets and reprograms alveolar macrophages, which alters lung physiology and facilitates primary CMV and secondary bacterial infection by attenuating the inflammatory response. Thus, CMV profoundly perturbs macrophage identity beyond established limits of plasticity and rewires specific differentiation processes, allowing viral spread and impairing innate tissue immunity.

Covert RNA viruses in medflies differ in their mode of transmission and tissue tropism.

Numerous studies have demonstrated the presence of covert viral infections in insects. These infections can be transmitted in insect populations via two main routes: vertical from parents to offspring, or horizontal between nonrelated individuals. Thirteen covert RNA viruses have been described in the Mediterranean fruit fly (medfly). Some of these viruses are established in different laboratory-reared and wild medfly populations, although variations in the viral repertoire and viral levels have been observed at different time points. To better understand these viral dynamics, we characterized the prevalence and levels of covert RNA viruses in two medfly strains, assessed the route of transmission of these viruses, and explored their distribution in medfly adult tissues. Altogether, our results indicated that the different RNA viruses found in medflies vary in their preferred route of transmission. Two iflaviruses and a narnavirus are predominantly transmitted through vertical transmission via the female, while a nodavirus and a nora virus exhibited a preference for horizontal transmission. Overall, our results give valuable insights into the viral tropism and transmission of RNA viruses in the medfly, contributing to the understanding of viral dynamics in insect populations. IMPORTANCE: The presence of RNA viruses in insects has been extensively covered. However, the study of host-virus interaction has focused on viruses that cause detrimental effects to the host. In this manuscript, we uncovered which tissues are infected with covert RNA viruses in the agricultural pest Ceratitis capitata, and which is the preferred transmission route of these viruses. Our results showed that vertical and horizontal transmission can occur simultaneously, although each virus is transmitted more efficiently following one of these routes. Additionally, our results indicated an association between the tropism of the RNA virus and the preferred route of transmission. Overall, these results set the basis for understanding how viruses are established and maintained in medfly populations.

An evolution-based machine learning to identify cancer type-specific driver mutations.

Identifying cancer type-specific driver mutations is crucial for illuminating distinct pathologic mechanisms across various tumors and providing opportunities of patient-specific treatment. However, although many computational methods were developed to predict driver mutations in a type-specific manner, the methods still have room to improve. Here, we devise a novel feature based on sequence co-evolution analysis to identify cancer type-specific driver mutations and construct a machine learning (ML) model with state-of-the-art performance. Specifically, relying on 28 000 tumor samples across 66 cancer types, our ML framework outperformed current leading methods of detecting cancer driver mutations. Interestingly, the cancer mutations identified by sequence co-evolution feature are frequently observed in interfaces mediating tissue-specific protein-protein interactions that are known to associate with shaping tissue-specific oncogenesis. Moreover, we provide pre-calculated potential oncogenicity on available human proteins with prediction scores of all possible residue alterations through user-friendly website (http://sbi.postech.ac.kr/w/cancerCE). This work will facilitate the identification of cancer type-specific driver mutations in newly sequenced tumor samples.

Key gp120 Glycans Pose Roadblocks to the Rapid Development of VRC01-Class Antibodies in an HIV-1-Infected Chinese Donor.

VRC01-class antibodies neutralize diverse HIV-1 strains by targeting the conserved CD4-binding site. Despite extensive investigations, crucial events in the early stage of VRC01 development remain elusive. We demonstrated how VRC01-class antibodies emerged in a Chinese donor by antigen-specific single B cell sorting, structural and functional studies, and longitudinal antibody and virus repertoire analyses. A monoclonal antibody DRVIA7 with modest neutralizing breadth was isolated that displayed a subset of VRC01 signatures. X-ray and EM structures revealed a VRC01-like angle of approach, but less favorable interactions between the DRVIA7 light-chain CDR1 and the N terminus with N276 and V5 glycans of gp120. Although the DRVIA7 lineage was unable to acquire broad neutralization, longitudinal analysis revealed a repertoire-encoded VRC01 light-chain CDR3 signature and VRC01-like neutralizing heavy-chain precursors that rapidly matured within 2 years. Thus, light chain accommodation of the glycan shield should be taken into account in vaccine design targeting this conserved site of vulnerability.

Evolution and folding of repeat proteins.

Repeat proteins are made with tandem copies of similar amino acid stretches that fold into elongated architectures. These proteins constitute excellent model systems to investigate how evolution relates to structure, folding, and function. Here, we propose a scheme to map evolutionary information at the sequence level to a coarse-grained model for repeat-protein folding and use it to investigate the folding of thousands of repeat proteins. We model the energetics by a combination of an inverse Potts-model scheme with an explicit mechanistic model of duplications and deletions of repeats to calculate the evolutionary parameters of the system at the single-residue level. These parameters are used to inform an Ising-like model that allows for the generation of folding curves, apparent domain emergence, and occupation of intermediate states that are highly compatible with experimental data in specific case studies. We analyzed the folding of thousands of natural Ankyrin repeat proteins and found that a multiplicity of folding mechanisms are possible. Fully cooperative all-or-none transitions are obtained for arrays with enough sequence-similar elements and strong interactions between them, while noncooperative element-by-element intermittent folding arose if the elements are dissimilar and the interactions between them are energetically weak. Additionally, we characterized nucleation-propagation and multidomain folding mechanisms. We show that the global stability and cooperativity of the repeating arrays can be predicted from simple sequence scores.

Uncovering the Genomic Basis of Infection Through Co-genomic Sequencing of Hosts and Parasites.

Understanding the genomic basis of infectious disease is a fundamental objective in co-evolutionary theory with relevance to healthcare, agriculture, and epidemiology. Models of host-parasite co-evolution often assume that infection requires specific combinations of host and parasite genotypes. Co-evolving host and parasite loci are, therefore, expected to show associations that reflect an underlying infection/resistance allele matrix, yet little evidence for such genome-to-genome interactions has been observed among natural populations. We conducted a study to search for this genomic signature across 258 linked host (Daphnia magna) and parasite (Pasteuria ramosa) genomes. Our results show a clear signal of genomic association between multiple epistatically interacting loci in the host genome, and a family of genes encoding for collagen-like protein in the parasite genome. These findings are supported by laboratory-based infection trials, which show strong correspondence between phenotype and genotype at the identified loci. Our study provides clear genomic evidence of antagonistic co-evolution among wild populations.

Interactomics: Dozens of Viruses, Co-evolving With Humans, Including the Influenza A Virus, may Actively Distort Human Aging.

Some viruses (e.g., human immunodeficiency virus 1 and severe acute respiratory syndrome coronavirus 2) have been experimentally proposed to accelerate features of human aging and of cellular senescence. These observations, along with evolutionary considerations on viral fitness, raised the more general puzzling hypothesis that, beyond documented sources in human genetics, aging in our species may also depend on virally encoded interactions distorting our aging to the benefits of diverse viruses. Accordingly, we designed systematic network-based analyses of the human and viral protein interactomes, which unraveled dozens of viruses encoding proteins experimentally demonstrated to interact with proteins from pathways associated with human aging, including cellular senescence. We further corroborated our predictions that specific viruses interfere with human aging using published experimental evidence and transcriptomic data; identifying influenza A virus (subtype H1N1) as a major candidate age distorter, notably through manipulation of cellular senescence. By providing original evidence that viruses may convergently contribute to the evolution of numerous age-associated pathways through co-evolution, our network-based and bipartite network-based methodologies support an ecosystemic study of aging, also searching for genetic causes of aging outside a focal aging species. Our findings, predicting age distorters and targets for anti-aging therapies among human viruses, could have fundamental and practical implications for evolutionary biology, aging study, virology, medicine, and demography.

Large-Scale Identification of Known and Novel RRNPP Quorum-Sensing Systems by RRNPP_Detector Captures Novel Features of Bacterial, Plasmidic, and Viral Coevolution.

Gram-positive Firmicutes bacteria and their mobile genetic elements (plasmids and bacteriophages) encode peptide-based quorum-sensing systems (QSSs) that orchestrate behavioral transitions as a function of population densities. In their simplest form, termed "RRNPP", these QSSs are composed of two adjacent genes: a communication propeptide and its cognate intracellular receptor. RRNPP QSSs notably regulate social/competitive behaviors such as virulence or biofilm formation in bacteria, conjugation in plasmids, or lysogeny in temperate bacteriophages. However, the genetic diversity and the prevalence of these communication systems, together with the breadth of behaviors they control, remain largely underappreciated. To better assess the impact of density dependency on microbial community dynamics and evolution, we developed the RRNPP_detector software, which predicts known and novel RRNPP QSSs in chromosomes, plasmids, and bacteriophages of Firmicutes. Applying RRNPP_detector against available complete genomes of viruses and Firmicutes, we identified a rich repertoire of RRNPP QSSs from 11 already known subfamilies and 21 novel high-confidence candidate subfamilies distributed across a vast diversity of taxa. The analysis of high-confidence RRNPP subfamilies notably revealed 14 subfamilies shared between chromosomes/plasmids/phages, 181 plasmids and 82 phages encoding multiple communication systems, phage-encoded QSSs predicted to dynamically modulate bacterial behaviors, and 196 candidate biosynthetic gene clusters under density-dependent regulation. Overall, our work enhances the field of quorum-sensing research and reveals novel insights into the coevolution of gram-positive bacteria and their mobile genetic elements.

Co-evolution at protein-protein interfaces guides inference of stoichiometry of oligomeric protein complexes by de novo structure prediction.

The quaternary structure with specific stoichiometry is pivotal to the specific function of protein complexes. However, determining the structure of many protein complexes experimentally remains a major bottleneck. Structural bioinformatics approaches, such as the deep learning algorithm Alphafold2-multimer (AF2-multimer), leverage the co-evolution of amino acids and sequence-structure relationships for accurate de novo structure and contact prediction. Pseudo-likelihood maximization direct coupling analysis (plmDCA) has been used to detect co-evolving residue pairs by statistical modeling. Here, we provide evidence that combining both methods can be used for de novo prediction of the quaternary structure and stoichiometry of a protein complex. We achieve this by augmenting the existing AF2-multimer confidence metrics with an interpretable score to identify the complex with an optimal fraction of native contacts of co-evolving residue pairs at intermolecular interfaces. We use this strategy to predict the quaternary structure and non-trivial stoichiometries of Bacillus subtilis spore germination protein complexes with unknown structures. Co-evolution at intermolecular interfaces may therefore synergize with AI-based de novo quaternary structure prediction of structurally uncharacterized bacterial protein complexes.

Evolution of Transcript Abundance is Influenced by Indels in Protein Low Complexity Regions.

Protein Protein low complexity regions (LCRs) are compositionally biased amino acid sequences, many of which have significant evolutionary impacts on the proteins which contain them. They are mutationally unstable experiencing higher rates of indels and substitutions than higher complexity regions. LCRs also impact the expression of their proteins, likely through multiple effects along the path from gene transcription, through translation, and eventual protein degradation. It has been observed that proteins which contain LCRs are associated with elevated transcript abundance (TAb), despite having lower protein abundance. We have gathered and integrated human data to investigate the co-evolution of TAb and LCRs through ancestral reconstructions and model inference using an approximate Bayesian calculation based method. We observe that on short evolutionary timescales TAb evolution is significantly impacted by changes in LCR length, with insertions driving TAb down. But in contrast, the observed data is best explained by indel rates in LCRs which are unaffected by shifts in TAb. Our work demonstrates a coupling between LCR and TAb evolution, and the utility of incorporating multiple responses into evolutionary analyses.

Co-evolution of vaginal microbiome and cervical cancer.

BACKGROUND: Exploration of adaptive evolutionary changes at the genetic level in vaginal microbial communities during different stages of cervical cancer remains limited. This study aimed to elucidate the mutational profile of the vaginal microbiota throughout the progression of cervical disease and subsequently establish diagnostic models. METHODS: This study utilized a metagenomic dataset consisting of 151 subjects classified into four categories: invasive cervical cancer (CC) (n = 42), cervical intraepithelial neoplasia (CIN) (n = 43), HPV-infected (HPVi) patients without cervical lesions (n = 34), and healthy controls (n = 32). The analysis focused on changes in microbiome abundance and extracted information on genetic variation. Consequently, comprehensive multimodal microbial signatures associated with CC, encompassing taxonomic alterations, mutation signatures, and enriched metabolic functional pathways, were identified. Diagnostic models for predicting CC were established considering gene characteristics based on single nucleotide variants (SNVs). RESULTS: In this study, we screened and analyzed the abundances of 18 key microbial strains during CC progression. Additionally, 71,6358 non-redundant mutations were identified, predominantly consisting of SNVs that were further annotated into 25,773 genes. Altered abundances of SNVs and mutation types were observed across the four groups. Specifically, there were 9847 SNVs in the HPV-infected group and 14,892 in the CC group. Furthermore, two distinct mutation signatures corresponding to the benign and malignant groups were identified. The enriched metabolic pathways showed limited similarity with only two overlapping pathways among the four groups. HPVi patients exhibited active nucleotide biosynthesis, whereas patients with CC demonstrated a significantly higher abundance of signaling and cellular-associated protein families. In contrast, healthy controls showed a distinct enrichment in sugar metabolism. Moreover, biomarkers based on microbial SNV abundance displayed stronger diagnostic capability (cc.AUC = 0.87) than the species-level biomarkers (cc.AUC = 0.78). Ultimately, the integration of multimodal biomarkers demonstrated optimal performance for accurately identifying different cervical statuses (cc.AUC = 0.86), with an acceptable performance (AUC = 0.79) in the external testing set. CONCLUSIONS: The vaginal microbiome exhibits specific SNV evolution in conjunction with the progression of CC, and serves as a specific biomarker for distinguishing between different statuses of cervical disease.

Phylosymbiosis and metabolomics resolve phenotypically plastic and cryptic sponge species in the genus Agelas across the Caribbean basin.

Fundamental to holobiont biology is recognising how variation in microbial composition and function relates to host phenotypic variation. Sponges often exhibit considerable phenotypic plasticity and also harbour dense microbial communities that function to protect and nourish hosts. One of the most prominent sponge genera on Caribbean coral reefs is Agelas. Using a comprehensive set of morphological (growth form, spicule), chemical and molecular data on 13 recognised species of Agelas in the Caribbean basin, we were able to define only five species (=clades) and found that many morphospecies designations were incongruent with phylogenomic and population genetic analyses. Microbial communities were also strongly differentiated between phylogenetic species, showing little evidence of cryptic divergence and relatively low correlation with morphospecies assignment. Metagenomic analyses also showed strong correspondence to phylogenetic species, and to a lesser extent, geographical and morphological characters. Surprisingly, the variation in secondary metabolites produced by sponge holobionts was explained by geography and morphospecies assignment, in addition to phylogenetic species, and covaried significantly with a subset of microbial symbionts. Spicule characteristics were highly plastic, under greater impact from geographical location than phylogeny. Our results suggest that while phenotypic plasticity is rampant in Agelas, morphological differences within phylogenetic species affect functionally important ecological traits, including the composition of the symbiotic microbial communities and metabolomic profiles.

Co-phylogeny of a hyper-symbiotic system: Endosymbiotic bacteria (Gammaproteobacteria), chewing lice (Insecta: Phthiraptera) and birds (Passeriformes).

Chewing lice are hosts to endosymbiotic bacteria as well as themselves being permanent parasites. This offers a unique opportunity to examine the cophylogenetic relationships between three ecologically interconnected organismal groups: birds, chewing lice, and bacteria. Here, we examine the cophylogenetic relationships between lice in the genus Guimaraesiella Eichler, 1949, their endosymbiotic Sodalis-allied bacteria, and a range of bird species from across South China. Both event and distance-based cophylogenetic analyses were explored to compare phylogenies of the three organismal groups. Pair-wise comparisons between lice-endosymbionts and bird-endosymbionts indicated that their evolutionary histories are not independent. However, comparisons between lice and birds, showed mixed results; the distance-based method of ParaFit indicated that their evolutionary histories are not independent, while the event-based method of Jane indicated that their phylogenies were no more congruent than expected by chance. Notably, louse host-switching does not seem to have affected bacterial strains, as conspecific lice sampled from distantly related hosts share bacteria belonging to the same clade.

Interplay of Light and ABA signaling to modulate plant development.

The exogenous light cues and the phytohormone Abscisic acid (ABA) regulate several aspects of plant growth and development. In recent years, the role of the crosstalk between the light and ABA signaling pathways in regulating different physiological processes has become increasingly evident. This includes the regulation of germination and early seedling development, control of stomatal development and conductance, growth and development of roots, buds, branches, and regulation of flowering. Light and ABA signaling cascades have various convergence points at both DNA and protein levels. The molecular crosstalk involves several light signaling factors like HY5, COP1, PIFs and BBXs that integrate with ABA signaling components like the PYL receptors and ABI5. Especially, ABI5 and PIF4 promoters serve as key "hotspots" for the integration of these two pathways. Plants acquired both light and ABA signaling pathways before they colonized land almost 500 million years ago. In this review, we discuss the recent advances in the interplay of light and ABA signaling regulating plant development and provide an overview of the evolution of these two pathways.

Rhizobium hidalgonense and Rhizobium redzepovicii as faba bean (Vicia faba L.) microsymbionts in Mexican soils.

As a legume crop widely cultured in the world, faba bean (Vicia faba L.) forms root nodules with diverse Rhizobium species in different regions. However, the symbionts associated with this plant in Mexico have not been studied. To investigate the diversity and species/symbiovar affiliations of rhizobia associated with faba bean in Mexico, rhizobia were isolated from this plant grown in two Mexican sites in the present study. Based upon the analysis of recA gene phylogeny, two genotypes were distinguished among a total of 35 isolates, and they were identified as Rhizobium hidalgonense and Rhizobium redzepovicii, respectively, by the whole genomic sequence analysis. Both the species harbored identical nod gene cluster and the same phylogenetic positions of nodC and nifH. So, all of them were identified into the symbiovar viciae. As a minor group, R. hidalgonense was only isolated from slightly acid soil and R. redzepovicii was the dominant group in both the acid and neutral soils. In addition, several genes related to resistance to metals (zinc, copper etc.) and metalloids (arsenic) were detected in genomes of the reference isolates, which might offer them some adaptation benefits. As conclusion, the community composition of faba bean rhizobia in Mexico was different from those reported in other regions. Furthermore, our study identified sv. viciae as the second symbiovar in the species R. redzepovicii. These results added novel evidence about the co-evolution, diversification and biogeographic patterns of rhizobia in association with their host legumes in distinct geographic regions.

Mitochondrial genome sequence comparisons indicate that the elephant louse Haematomyzus elephantis (Piaget, 1869) contains cryptic species.

The parvorder Rhynchopthirina contains three currently recognised species of lice that parasitize elephants (both African savanna elephant Loxodonta africana and Asian elephant Elephas maximus), desert warthogs (Phacochoerus aethiopicus) and Red River hogs (Potamochoerus porcus), respectively. The Asian elephant lice and the African savanna elephant lice are currently treated as the same species, Haematomyzus elephantis (Piaget, 1869), based on morphology despite the fact that their hosts diverged 8.4 million years ago. In the current study, we sequenced 23 mitochondrial (mt) genes of African savanna elephant lice collected in South Africa and analysed the sequence divergence between African savanna elephant lice and previously sequenced Asian elephant lice. Sequence comparisons revealed >23% divergence for the 23 mt genes as a whole and ~17% divergence for cox1 gene between African savanna and Asian elephant lice, which were far higher than the divergence expected within a species. Furthermore, the mt gene sequence divergences between these lice are 3.76-4.6 times higher than that between their hosts, the African savanna and Asian elephants, which are expected for the co-divergence and co-evolution between lice and their elephant hosts. We conclude that (1) H. elephantis (Piaget, 1869) contains cryptic species and (2) African savanna and Asian elephant lice are different species genetically that may have co-diverged and co-evolved with their hosts.

Investigation of CaMV-host co-evolution through synonymous codon pattern.

Cauliflower mosaic virus (CaMV) has a double-stranded DNA genome and is globally distributed. The phylogeny tree of 121 CaMV isolates was categorized into two primary groups, with Iranian isolates showing the greatest genetic variations. Nucleotide A demonstrated the highest percentage (36.95%) in the CaMV genome and the dinucleotide odds ratio analysis revealed that TC dinucleotide (1.34 ≥ 1.23) and CG dinucleotide (0.63 ≤ 0.78) are overrepresented and underrepresented, respectively. Relative synonymous codon usage (RSCU) analysis confirmed codon usage bias in CaMV and its hosts. Brassica oleracea and Brassica rapa, among the susceptible hosts of CaMV, showed a codon adaptation index (CAI) value above 0.8. Additionally, relative codon deoptimization index (RCDI) results exhibited the highest degree of deoptimization in Raphanus sativus. These findings suggest that the genes of CaMV underwent codon adaptation with its hosts. Among the CaMV open reading frames (ORFs), genes that produce reverse transcriptase and virus coat proteins showed the highest CAI value of 0.83. These genes are crucial for the creation of new virion particles. The results confirm that CaMV co-evolved with its host to ensure the optimal expression of its genes in the hosts, allowing for easy infection and effective spread. To detect the force behind codon usage bias, an effective number of codons (ENC)-plot and neutrality plot were conducted. The results indicated that natural selection is the primary factor influencing CaMV codon usage bias.

Genomic coevolution of papillomavirus and immune system in placental mammals indicates the role of IFN-γ in the emergence of new variants.

Papillomaviruses (PVs) are causative agents for warts and cancers in different parts of the body in the mammalian lineage. Therefore, these viruses are proposed as model organisms to study host immune responses to pathogens causing chronic infections. The virus-associated cancer progression depends on two integral processes namely angiogenesis and immune response (AIR). The angiogenesis process aids in tumour progression through vessel formation and maturation but the host immune response, in contrast, makes every attempt to eliminate pathogens and thereby maintain healthy tissues. However, the evolutionary contribution of individual viral genes and host AIR genes in carcinogenesis is yet to be explored. Here, we applied the evolutionary genomics approach to find correlated evolution between six PV genes and 23 host AIR-related genes. We estimated that IFN-γ is the only host gene evolving in a correlated manner with all six PV genes under study. Furthermore, three papillomavirus genes, L2, E6, and E7, are found to interact with two third of host AIR-related genes. Moreover, a combined differential gene expression analysis and network analysis showed that inflammatory cytokine IFN-γ is the key regulator of hub genes in the PPI network of the differentially expressed genes. Functional enrichment of these hub genes is consistent with their established role in different cancers and viral infections. Overall, we conclude that IFN-γ maintains selective pressure on mammalian PV genes and seems to be a potential biomarker for PV-related cancers. This study demonstrates the evolutionary importance of IFN-γ in deciding the fate of carcinogenic PV variants.

Emergence of Novel RNA-Editing Sites by Changes in the Binding Affinity of a Conserved PPR Protein.

RNA editing converts cytidines to uridines in plant organellar transcripts. Editing typically restores codons for conserved amino acids. During evolution, specific C-to-U editing sites can be lost from some plant lineages by genomic C-to-T mutations. By contrast, the emergence of novel editing sites is less well documented. Editing sites are recognized by pentatricopeptide repeat (PPR) proteins with high specificity. RNA recognition by PPR proteins is partially predictable, but prediction is often inadequate for PPRs involved in RNA editing. Here we have characterized evolution and recognition of a recently gained editing site. We demonstrate that changes in the RNA recognition motifs that are not explainable with the current PPR code allow an ancient PPR protein, QED1, to uniquely target the ndhB-291 site in Brassicaceae. When expressed in tobacco, the Arabidopsis QED1 edits 33 high-confident off-target sites in chloroplasts and mitochondria causing a spectrum of mutant phenotypes. By manipulating the relative expression levels of QED1 and ndhB-291, we show that the target specificity of the PPR protein depends on the RNA:protein ratio. Finally, our data suggest that the low expression levels of PPR proteins are necessary to ensure the specificity of editing site selection and prevent deleterious off-target editing.