Cytidine deaminases are single stranded DNA mutators diversifying antibodies and restricting viral infection. Improper access to the genome leads to translocations and mutations in B cells and contributes to the mutation landscape in cancer, such as kataegis. It remains unclear how deaminases access double stranded genomes and whether off-target mutations favor certain loci, although transcription and opportunistic access during DNA repair are thought to play a role. In yeast, AID and the catalytic domain of APOBEC3G preferentially mutate transcriptionally active genes within narrow regions, 110 base pairs in width, fixed at RNA polymerase initiation sites. Unlike APOBEC3G, AID shows enhanced mutational preference for small RNA genes  suggesting a putative role for RNA in its recruitment. We uncover the high affinity of the deaminases for the single stranded DNA exposed by initiating RNA polymerases  without a requirement for specific cofactors.DOI:http://dx.doi.org/10.7554/eLife.03553.001 In cells, genetic information is stored within molecules of DNA, which contain sequences of four ‘bases’ arranged in different orders. Replacing one of these bases with a different base results in a mutation, which can have a positive or negative influence on the cell.Mammals use a group of enzymes called cytidine deaminases to help defend themselves against harmful invaders. These enzymes work by introducing mutations into the DNA of viruses, microbes and even the mammal itself. For example, an enzyme called APOBEC3G can mutate the DNA of viruses to prevent them spreading around the body. Another enzyme, called AID, can mutate the genes that make antibodies—proteins that attack the invading microbes—in order to make new varieties of antibodies. Unfortunately, the enzymes sometimes target other genes, which can lead to cancer and other diseases.Cytidine deaminases can only access and mutate single strands of DNA, so most of the DNA in a cell is protected because it is in a two-stranded double helix. However, there are times when the two strands are separated, such as when a section of DNA is being repaired, or when it is being transcribed to produce a molecule of RNA, which is subsequently used to make a protein. It is not clear when cytidine deaminases are able to target single stranded DNA, and whether they need help from any other components.Now, Taylor et al. have studied how these enzymes access single stranded DNA when artificially introduced into yeast. These experiments showed that AID and APOBEC3G can access single stranded DNA without the help of any extra components. The enzymes target genes that are being transcribed to make RNA, with the DNA at the start of the transcription site being the most prone to mutation.In mammal cells, most genes are normally protected from the mutations introduced by cytidine deaminases, but this protection does not appear to work in many cancer cells. The next challenge will be to develop a better understanding of how this protection works, and to work out why it sometimes goes wrong.DOI:http://dx.doi.org/10.7554/eLife.03553.002 Cytidine deaminases are a family of polynucleotide mutators that modify cytosines into uracil in viral nucleic acids as part of the innate immune defences . Their sAll members of the AID/APOBEC family are selective in the sequence context of the deaminated cytosine, with the two preceding nucleotides identifying the signature of individual deaminases . This muPhysiologically, the activity of such mutators is targeted to specific substrates and restricted from the rest of the genome to limit genomic instability. In the case of AID, expressed upon activation in only a fraction of B cells, by limiting access to the nuclear compartment and preferential recruitment to the immunoglobulin genes; in the case of APOBEC3G, expressed preferentially in lymphoid cells, by its localisation in the cytosol and binding to the viral genome and capsid. The mechanism that preferentially directs AID to the immunoglobulin genes is not fully understood, but active transcription has been repeatedly invoked as a requirement , but relatively few mutations, averaging 61 single nucleotide variations (SNVs) per genome  in haplr genome . Diploidr genome . Our expr genome . For comr genome .10.7554/C was found for AID* and YCC for sA3G* . We identify 1227 and 568 such mutation-enriched loci (MELs) in the AID* and sA3G* treated genomes, in contrast to just 1 obtained for EMS treatment (overlapping the body of the CAN1 gene and hence due to canavinine selection). On average 35 such MELs would be expected for simulated datasets of equivalent mutation loads . MELs spBoth AID and APOBEC3G target cytosines for deamination within a specific sequence context, leading to the mutation hotspots associated with antibody diversification and the recurrent mutations at CCC trinucleotides observed in HIV-1 genomes during the evolution of viral clades and which accumulate in viral genomes from infected individual . We therReinforcing the notion that MELs are highly favoured targets for mutations, we find these areas are frequency mutated on both alleles: 48% of AID* genomes and 56% of sA3G* genomes have mutations within MELs occurring on both chromosome alleles, compared to just 2–3% predicted for random fragments of equivalent size and mutation loads. MELs also contain most of the homozygous mutations detected (82% of AID* and 78% of sA3G*). Targeting of both alleles in MELs suggests they represent highly mutable regions within the genome, with the deaminases returning repeatedly to the same sites  to mutate.Re-analysis of deaminase mutations we previously reported in haploid yeast  identifiIn conclusion, deaminases preferentially target narrow focussed regions throughout the genome independent of the sequence density of deaminase targets.There is a well-recognised relationship between AID induced mutations and transcription both in B cells at immunoglobulin genes, and for off-target loci, with mutations preferentially accumulating towards the promoter proximal region of the transcription unit . The traInitiation of replication also transiently generates single stranded DNA at defined locations. However, there is no enrichment of mutated hotspots associated with replication origins (ARS) . AlthougMutation enrichment at promoters is not restricted to hotspots identified within MELs, which exclude 73% of the total mutations due to the threshold applied in defining enriched loci. Aligning all mutations to mRNA transcriptional starts (TSS) and termination sites (TTS) , revealeThe deaminase mutated hotspots thus identify the position where promoter melting occurs before the scanning polymerase encounters the TSS, suggesting a mechanistic basis for the hypothesis that the deaminases access the promoter coincidentally with the assembly of the pre-initiation complex. Consistent with the notion that initiating polymerases create transient access for the deaminases rather than specifically loading the proteins, we detect robust association of RNAP II with the promoter region of deaminase targeted promoters in yeast but negligible enhancement in the association of either AID or sA3G with mutated promoters compared to unmutated or intergenic regions . AdditioSupporting the idea that the deaminases preferentially mutate promoters due to their ability to recognize the melted DNA associated with the transcription pre-initiation complex, we observe that MELs occur in genes with above average transcriptional activity  but targIn summary, cytidine deaminases mutate at specific loci through the yeast genome, predominantly within active gene promoter regions.In B cells, AID is found in association with components of the transcription machinery such as SPT5 and SPT6, and RNAP II itself , therefoThe mutation frequency  in AID* genomes within tRNA genes is higher than at mRNA gene promoters  targeted by sA3G* than in those tRNA genes not targeted by sA3G*. We see no such difference with AID* target motifs which are present within tRNA, snRNA and snoRNA gene promoters at similar frequency as in other promoters . By including repeatedly mapped reads across the rDNA locus, we could detect several hundred mutations at low allele frequency all within the expected deaminase mutation context, giving confidence in their detection and location . MutatioAn alternative explanation for the enhanced targeting of small RNA promoters by AID* is that the RNAs themselves preferentially bind AID, thereby creating co-transcriptional enrichment of AID in the vicinity of their genes. Purified AID binds RNA, with its in vitro deamination activity enhanced by treatment with RNAse A , whereasIn order to test the RNA binding properties of AID in modulating its targeting preferences we introduced a chimeric snR6 RNA into the RNAP II driven YBR194W gene, which was identified in our dataset as a transcribed but poorly targeted promoter by both deaminases , while cWe conclude that the differential preference of AID* for tRNA, snRNAs and snoRNAs in yeast might reflect the ability of AID to preferentially associate with abundant small RNA species, in contrast to the catalytic domain of APOBEC3G (sA3G*) that possesses no RNA binding activity.Targeting mutations to initiating promoters is not likely a function of the size of the deaminase, as could be inferred from the results described for both AID and the single domain fragment of APOBEC3G used in our study. Similar promoter associated recurrent mutations can be elicited not only by APOBEC3A  but also by the double domain APOBEC3B . It is t3-fold lower frequency than at immunoglobulin genes  and the transcription start site (TSS), more precisely identify the pre-initiation complex (PIC) as the target for the deaminases.Enhanced targeting of RNAP III transcribed genes argues against active recruitment of the deaminases by conserved initiation factors, whereas the structural conservation of the DNA template conformation at the core pre-initiation complex of all polymerases  supportsBudding yeast RNAP II promoters show characteristic and highly regulated nucleosome exclusion. This is partly due to sequence composition, with regions enriched for poly dA•dT nucleotides that confer rigidity to the DNA and are therefore thermodynamically less favourable to wrap around nucleosomes , and parNeither the preferential targeting of promoters nor the narrow focus of the MELs is due to the preferential clustering of mutable motifs. Interestingly, the nature of the mutation hotspots within MELs (both at C and G), reveals that both strands of the melted DNA structure associated with active promoters are accessible. Furthermore, protection from mutation is evident at the TBP binding site while the peak of mutations ∼30 base pairs downstream identifies the site of RNAP loading and DNA melting mapped by permanganate footprinting  and highDifferences in the assembly of the PIC in TATA and TATA-like promoters, do not seem to affect mutation susceptibility, although predictably, TATA box promoters show a more defined distance between the TBP protected footprint and the accessible melted DNA  indicatiSaccharomyces cerevisiae. Mammalian promoters are frequently regulated by proximal pausing, with most promoters pausing within 200 base pairs of the TSS  and not ascribable to sequence context or targeting by specific cofactors. The precise and narrow location of the recurrent mutations pinpoints the site where the RNAP pre-initiation complex is loaded highlighting the conservation of the TBP (TATA binding protein) site and the formation of the pre-initiation complex, whereas exclusion of mutations from the TBP site confirms the poised nature of active yeast promoters., which has high affinity for deaminases and where both strands are accessible for mutation. They also strongly support the notion that AID might directly bind to single stranded DNA at the pre-initiating or stalling RNAP sites without a requirement for specific cofactors and that its targeting is modulated by its ability to interact with structured RNA species.These results suggest that initiating polymerases create a small but persistent accessible patch of single stranded DNA in vivoungΔ/ungΔ was generated by crossing BY4741 ungΔ  obtained from Euroscarf deletion collection  with the BY4742 ungΔ strain. BY4742 ungΔ was generated by removal of the UNG1 open reading frame by homologous recombination in the parental BY4742 strain, using a PCR generated URA3 cassette flanked by a 57-bp 5′ homology and 51-bp 3′ homology arms that include adaptamers for post integration removal of the URA3 selection cassette (ungΔ cells. Homology arms and the snR6 gene were amplified from genomic DNA using the primers (1) 5′-CCTGCCACTTTCAAAAGGCG-3′ and 5′-CGAAGGGTTACTTCGCGAACTCCTGTCCCTATTACATATTCAACC-3′, (2) 5′-GGTTGAATATGTAATAGGGACAGGAGTTCGCGAAGTAACCCTTCG-3′ and 5′-GCCAGGCATGCTAATGGCAAAACGAAATAAATCTCTTTGTAAAAC-3′, (3) 5′-GTTTTACAAAGAGATTTATTTCGTTTTGCCATTAGCATGCCTGGC-3′ and 5′-TGGTGGTCATATGCTCGGTG-3′. A PCR fusion of all three fragments with the first and last primer was used to retarget the URA3 containing locus. 5-Fluoroorotic acid counter-selection was used to isolate targeted colonies that were then mated with BY4742 ungΔ to generate the final BY4743 ungΔ/ungΔ YBR194W-snR6/YBR194W strain. Correct integration of all targeting constructs was confirmed by PCR.Yeast strain BY4743 cassette . The YBRYeast transformation and selection, genomic DNA extraction and mutation frequency calculation were performed as described previously . ControlungΔ/ungΔ yeast overnight in YEPD with 0.2% EMS, after which cells were washed in 5% sodium thiosulfate and plated for viability and canavanine resistance as above.Ethyl methanesulfonate (EMS) mutagenesis was performed by culturing BY4743 http://picard.sourceforge.net) and only uniquely mapped paired reads were retained. On average 43-fold sequence coverage was achieved for each yeast genome. Unprocessed sequence reads for this study have been deposited at the EMBL-EBI European Nucleotide Archive, study accession number PRJEB7456 (http://www.ebi.ac.uk/ena/data/view/PRJEB7456).DNA libraries were generated using the multiplexing Nextera DNA Sample Prep Kit  according to manufactures instructions. The libraries were sequenced by BGI . The de-multiplexed sequence reads were aligned to the reference yeast genome (SacCer_Apr2011/sacCer3) using BWA-MEM . OpticalAn in-house pipeline for mutation calling was used where GATK base quality score recalibration and indel realignment  was perfth percentile was used as a threshold to identify significantly mutated windows and adjacent windows merged. To refine the span of each individual mutation enriched loci (MEL), unmutated residues and residues falling in the following categories were removed and the window size adjusted: bases that had a count below the 25th percentile of all the counts in the window; bases which had a mutation count below four standard deviations from the average for the window and all bases with only a single detected mutation (where the median mutation count was above one). A final threshold was applied so that only regions with more than 5 mutations derived from at least four independent transformants were assigned as high confidence MELs. All MELs were manually assessed using a genome browser and are shown in Within each data set, mutations were pooled with the number of mutations within 150 base pair windows. Based on the assumption of a random distribution of mutation amongst the fragments, a binomial distribution was determined using the following parameters: size equal to the average number of mutations per clone and probability equal to the average number of mutations per clone over the total number of mutable motifs. Mutable motifs were the total number of WRC, YCC, or C bases for AID*, sA3G* and EMS respectively. The 99The averaged fraction of overlapping regions for simulated MEL dataset were determined by 1000 cycles of bootstrap analysis using randomised equivalent number of fragments of identical sizes for each dataset distributed across the genome.The normalised mutation density was calculated by dividing the mutation count for each residue by the total number of mutation for the dataset.ChIP enrichment was determined by taking the sum of the ChIP enrichment scores  for eachSaccharomyces Genome Database  were extracted and used for mutation calling by SomaticSniper. Mutations with a SomaticSniper score of above 50, a read depth of 10 in both the reference and the sample and no evidence of the mutated base in the reference genome were assigned.All analyses were performed using Bioconductor. Scripts are included as The tI(UAU)D RNA probes were generated by in vitro transcription  with or without biotin-UTP (Life Technologies), according to manufactures instructions. Free nucleotides were removed using Oligo Clean & Concentrator columns . The tI(UAU)D template was generated by annealing the following oligos 5′-AATTTAATACGACTCACTATAGGGCTCGTGTAGCTCAGTGGTTAGAGCTTCGTGCTTATAACG-3′ and 5′-TGCTCGAGGTGGGGTTTGAACCCACGACGGTCGCGTTATAAGCACGAAGCTCTAACC-3′. The pre-tI(UAU)D template was generated by PCR amplification from yeast genomic DNA using the following primers 5′- AATTTAATACGACTCACTATAGGGCTCGTGTAGCTCAGTGGTTAGAGC-3′ and 5′-TGCTCGAGGTGGGGTTTGAACCCACGACGG-3′. Biotinylation of total yeast RNA (Life Technologies), polyuridylic acid, polyadenylic acid-polyuridylic acid  and the tI(UAU)D probe were performed using the RNA 3′ End Biotinylation Kit (Pierce) according to manufacturers instructions.2 was then added to a final concentration of 20 mM and the RNA allowed to slowly cool to 10°C before being bound to magnetic beads  for 1 hr at 4°C. Unbound probe was removed by washing with RNA buffer  supplemented with 0.5% Triton X-100. The integrity of the RNA was monitored by denaturing gel electrophoresis and staining with toluidine blue.Biotinylated RNA probes (3.6 μg) were refolded by heating to 80°C for 5 min in folding buffer , MgClClarified whole cell extracts  from HEK 293 cells expressing Flag-AID, catalytically inactive AID (E58A mutation), APOBEC3G-Flag and the SV40-NLS tagged catalytic C-terminal domain of APOBEC3G (sA3G)-Flag, were incubated for 1 hr at 4°C in the presence of bead bound biotinylated RNA probes. Unbound proteins were removed by washing the beads four times in RNA buffer supplemented with 0.5% Triton X-100 at 4°C and the bound protein monitored by western using anti Flag antibodies .Overnight 60 ml yeast cultures fixed in 1% formaldehyde for 20 min and quenched in 0.125 M glycine  were washed twice in cold PBS, resuspended in RIPAlo  prior to lysis using a MPI TissueLyser , sonication using a Bioruptor  and centrifugation . Equal amounts of clarified chromatin were incubated overnight at 4°C with 3 μg anti-HA 16B12 , 2 μg anti-H3 ab1791 , 2 μg anti-RNAPII S5P ab5131 (Abcam). Purification followed on Protein-G dynabeads for 2 hr with extensive washes  and overnight elution in 25 mM Tris–HCl, 1 mM EDTA, pH to 9.8, 50 μg/ml proteinase K at 65°C. Input DNA was extracted using Gentra Puregene  with qPCR performed using QuantiFast SYBR kit (Qiagen) all as per manufactures instructions. Primers used are; YBR019C; 5′-ATCCAGCACCACCTGTAACC-3′ and 5′-AAACTTCTTTGCGTCCATCC-3′, YBR020W; 5′-ACCTGAGTTCAATTCTAGCGC-3′ and 5′-TCCGGTTTAGCATCATAAGCG-3′, YNL067W; 5′-AACCAAACTCTAGCCTCCAA-3′ and 5′-TGCTGACAGTAACACCTTCTGG-3′, YBL003C; 5′-TGTGCACTCTACCAACTGGG-3′ and 5′-ATGTCCGGTGGTAAAGGTGG-3′, YPL250C; 5′-AGAGAGTTGCTCCAGACCCT-3′ and 5′-GCATAAAGAAGCGGCTCTGC-3′, YEL009C; 5′-GGGGGAGAGTAACCTGTGTT-3′ and 5′-TTTCGGCTCGCTGTCTTACC-3′, YBR194W; 5′-TCTTCTTGCTCGGGGTTCTC-3′ and 5′-TGCTGAAGGCCTTTGCAAAG-3′, YPL189W; 5′-GCGAAGATTACGGCACTCGA-3′ and 5′-ACAGGTACGGGCTATCTGGA-3′, YLR183C; 5′-ACATCTGCCACGACACATCA-3′ and 5′-TGGTGGAGAGTACGGATCCA-3′, YJL105W; 5′-TTTCTTGCTCTTGGCGGCTA-3′ and 5′-AGTTAGGATCTGAGCCGGGT-3′, YPR007C; 5′-ACAGGTTCGAGCTTCATGGG-3′ and 5′-CGGGAATTTCATCCAGCGGA-3′, chrXV;367475-367594 5′-ACTTGGCACTTCTTCCTCAACA-3′ and 5′-TCGCAAAGTTGGCTAACCGT-3′, chrX;585916-586020 5′-ATGTCTCCCTGTTACCCGGT-3′ and 5′-ACAGGTGCTGTCACAAAACA-3′, chrIV;76,875-76,955 5'′-GGCAGCACCGAGAATGTTTT-3′ and 5′-GCTGTTAGCATATTGGGGGT-3′.RNA from 1 ml overnight cultures purified with RNAeasy plus (Qiagen) was used to generate cDNA using oligo-dTs and the GoScript Kit  followed by qPCR employing QuantiFast SYBR (Qiagen) all as per manufactures instructions. Primers used are TAF10; 5′-ATATTCCAGGATCAGGTCTTCCGTAGC-3′ and 5′-GTAGTCTTCTCATTCTGTTGATGTTGTTGTTG-3′, ACT1; 5′-CTTTCAACGTTCCAGCCTTC-3′ and 5′-CCAGCGTAAATTGGAACGAC-3′, YBR194W-snR6; 5′-CCTGCCACTTTCAAAAGGCG-3′ and 5′-CAGGGGAACTGCTGATCATCTCTG-3′, YBR194W; 5′-GGGTCGTGAAAAAGAGAACGG-3′ and 5′-ATGTGATGGTGCAGTGCCTC-3′.The YBR194W promoter region was amplified using the following primers; 5′-ATTGTGGCAGTTCGGCTTTG-3′ and 5′-AGGTTTCCCAGTCTGGCTTG-3′ and Sanger sequenced using the latter. review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent  and 2 reviewers, one of whom, Nick Proudfoot, is a member of our Board of Reviewing Editors.Thank you for sending your work entitled “Active RNAP pre-initiation sites are highly mutated by cytidine deaminases in yeast, with AID targeting small RNAs genes” for consideration at The Reviewing editor and another expert reviewer discussed their comments before we reached this decision, and the Reviewing editor has assembled the following comments to help you prepare a revised submission.E. coli and yeast has been undertaken by different labs and has contributed greatly to understand their mechanisms of action. Despite the limitations that yeast may have as a system to make conclusions about the in vivo action of these deaminases in human cells, it is clear that this type of approach reveals important features of the genome accessibility for these enzymes known to act specifically on ssDNA. In yeast, the pattern of mutations induced by these deaminases has been reported by different laboratories. This manuscript of Taylor and Rada, from the former laboratory of M. Neuberger, extends such studies further. A detailed analysis of clustering of mutations along the genome of diploid yeast reveals that such clusters are preferentially located at promoters of highly expressed RNAPII-driven genes. This is the case for both AID and APOBEC3G-induced mutations, and in the case of AID this is also observed for RNAPIII genes. Taylor and Rada conclude that this is due to the ability of the small RNAs to bring AID to its site of action. To probe this hypothesis they show that AID binds in vitro to yeast tRNA and poly U. This work is interesting and novel by providing new information about the yeast genome accessibility to human deaminases that should help clarify its mechanism of action. It is consistent with the ability of these enzymes to act on ssDNA formed at active pre-initiation complexes.Analysis of the in vivo effect of human deaminases, such as AID and APOBEC3G, in heterologous systems such as 1) We are not convinced that the authors provide significant evidence that this recruitment is RNA mediated. AID was discovered by the Honjo lab as an RNA modifying enzyme, and the ability of AID to interact in vitro with RNA is not that novel. More importantly, the data presented is insufficient to prove that RNA plays a direct role in recruiting AID to pre-initiation complexes in vivo. The difference between RNAPII and RNAPIII promoters (embedded in the body of the genes) could be due to a different structure of the pre-initiation complex, a difference in the opening and accessibility of the ssDNA formed at such promoters or to different factors that might influence the action of AID in vivo, not necessarily its recruitment. Despite this, it is clear that these proteins act at RNAPII promoters as deduced from the impressive enrichment of MELs at such promoters. Is the average length of the RNA generated in such promoters small? Do long RNA molecules bind AID in vitro?2) It is important to distinguish loading and recruitment of the deaminases from their sites of action . This study can only deduce sites of action not sites of loading and recruitment. This later point should be addressed by performing ChIP analysis to show that the deaminases are loaded at the promoter by the promoter initiation complex. Also reporter systems could be employed to probe these issues in vivo by turning on or off transcription (using inducible promoters e.g. GAL) This is relevant given the reported role of transcription factors in AID recruitment in human cells that in principle would not correlate with mutational hotspots.3) Are the authors sure that Canavinine is an Arginine permease transporter inhibitor or just an Arginine analogue that uses the same permease (encoded by the CAN1 gene). This later reason could explain why can1 mutations impede canavarine uptake leading to can resistance? Please comment.4) Can the authors further explain why mutations within the MELs are much more likely to occur on both alleles of the diploid strain compared to equivalent random fragments? As the information on whether such mutations are coincident between both alleles is not clear, I wonder whether the authors can exclude the possibility that such high levels could be due to gene conversion type of events whether or not mediated by double-strand breaks.5) It is important that 57% of AID and 46 % of sA3G mutations occur within the promoter region compared to only 21% of EMS mutations. However, considering that the authors found 1227 and 568 MELs in the AID and sA3G treated genomes, but only 1 for MMS, a simple analysis would reveal that the MMS mutations in the promoter region compared to the total frequency of MMS-induced MELs is extremely high. Could the authors clarify or discuss this point better, so that the reader does not get misled by a simple analysis, if that is the case? We have reinforced our conclusion that in yeast, the main determinant for targeting of the deaminases is the accessibility of the single stranded substrate at preinitiation complex sites. We now include ChIP data on the chromatin association of AID and APOBEC3G (sA3G) and new bioinformatic analyses. We have also reinforced the evidence in support for a role of RNA binding by AID in modulating the preferred sites of mutation by the addition of new genetic data, ChIP data and expression analysis. We have made changes in the text to improve the clarity and incorporate the new data, which has also resulted in the addition of a new author.1) We are not convinced that the authors provide significant evidence that this recruitment is RNA mediated. AID was discovered by the Honjo lab as an RNA modifying enzyme, and the ability of AID to interact in vitro with RNA is not that novel. More importantly, the data presented is insufficient to prove that RNA plays a direct role in recruiting AID to pre-initiation complexes in vivo. The difference between RNAPII and RNAPIII promoters (embedded in the body of the genes) could be due to a different structure of the pre-initiation complex, a difference in the opening and accessibility of the ssDNA formed at such promoters or to different factors that might influence the action of AID in vivo, not necessarily its recruitment. Despite this, it is clear that these proteins act at RNAPII promoters as deduced from the impressive enrichment of MELs at such promoters.Both sA3G and AID  can access and mutate DNA at promoters; however we noted that AID showed marked preference for promoters of small structured RNAs (such as tRNAs or snRNAs). The two proteins are a perfect genetic control for each other, since the most salient difference between the two deaminases is their ability to bind RNA: the catalytic domain of APOBEC3G (sA3G) does not bind RNA, while AID seems to have a very good ability to bind RNA and in particular small structured RNAs such as tRNAs or snRNAs. We speculated that this RNA binding difference must be the main determinant for the different targeting preferences of AID.in vivo is affected by it ability to interact with RNA.In order to confirm this finding, we have now transplanted a small structured RNA to a locus that although transcribed was not a preferred target for either AID or sA3G. The results are included in a revised 2) It is important to distinguish loading and recruitment of the deaminases from their sites of action . This study can only deduce sites of action not sites of loading and recruitment. This later point should be addressed by performing ChIP analysis to show that the deaminases are loaded at the promoter by the promoter initiation complex.We agree with the main concern of the reviewers in that we believe the activity of the deaminases does not necessarily correlate with their presence at chromatin, however we feel it is unlikely that ChIP experiments will provide a definitive answer to dissecting the mechanism that brings the deaminase to a genomic region (loading) versus the mechanism that promotes active mutation. The current literature in mammalian cells regarding association of AID with chromatin (as measured by ChIP) is complicated. The most solid data shows association of AID at the Sµ switch repeat region [a region that is highly enriched for AID targets] which is regulated by phosphorylation . ChIP data only occasionally and haphazardly correlates the presence of AID with mutation at off-target sites .We have argued in the past that mutation is a more reliable measure of the “past” association of the deaminases with their substrate. At this moment we do not have a reliable assay to measure unproductive association of the deaminases that would distinguish occupancy of a locus versus functional outcome. Single molecule analysis might be a possible way to compare recruitment and mutation, but we feel those experiments are beyond the scope of this manuscript.We are careful in our manuscript to avoid making the claim that the promoter initiation complex “actively loads” the deaminases, since we rather interpret our findings as indicating that the conformation of the DNA at the promoter site is permissive for the “access and activity” of the deaminases.Also reporter systems could be employed to probe these issues in vivo by turning on or off transcription (using inducible promoters e.g. GAL) This is relevant given the reported role of transcription factors in AID recruitment in human cells that in principle would not correlate with mutational hotspots.We have analysed transcription factor binding data and find enrichment of members of the basal transcription machinery and associated chromatin remodelling factors such as Spt16. No specific transcription factor is particularly associated with MEL containing promoter regions. The results are included as a new Is the average length of the RNA generated in such promoters small? Do long RNA molecules bind AID in vitro?As indicated in the modified We have repeated the immunoprecipitation experiments testing the RNA binding properties of the deaminases to make the result as robust and reproducible as possible and have modified Our data suggests that different deaminases vary in their preferences and capacity to bind single, double stranded or highly structured RNA. Our results agree with evidence from the literature that suggests APOBEC3G might multimerise on diverse messenger RNAs. Further studies will focus on the preferences of AID-RNA interactions in mammalian cells.As to whether there is a gene length preference for deaminases, for AID* and sA3G* datasets, we find no particular bias for mutations to occur at short or long RNAP II mRNA genes see  below.Au3) Are the authors sure that Canavinine is an Arginine permease transporter inhibitor or just an Arginine analogue that uses the same permease (encoded by the CAN1 gene). This later reason could explain why can1 mutations impede canavarine uptake leading to can resistance? Please comment.S. cerevisiae using the amino acid transporter encoded by the CAN1 gene. Mutations that impair the transport also render the cells resistant to the toxicity of the drug. We have now corrected the text.We apologise for the mistake in our description of mutation the CAN1 locus as a selection system and thank the reviewer for pointing it out. As the reviewers rightly suggest, we use resistance to L-canavanine  that is imported inside the cell by the yeast 4) Can the authors further explain why mutations within the MELs are much more likely to occur on both alleles of the diploid strain compared to equivalent random fragments? As the information on whether such mutations are coincident between both alleles is not clear, I wonder whether the authors can exclude the possibility that such high levels could be due to gene conversion type of events whether or not mediated by double-strand breaks.We observe that in many cases the same DNA fragment is associated with high density of mutations (MELs) in both alleles of the same gene . We argue the simplest explanation is repeated targeted of both alleles, either simultaneously or in successive rounds of mutation. Regions of equivalent size as MELs would only be expected to show biallelic mutations (homozygous or heterozygous) in 2-3% of the fragments (as predicted from a random distribution of the same number of mutations as in the observed datasets). We have modified the text in an attempt to make the point more clear but keeping the text concise.As the reviewers mention, an alternative that we do not favour is that gene-conversion between the two alleles accounts for the high frequency of homozygous mutations in MELs. We repeatedly discuss the absence of kataegic mutations as an indication that DNA breaks and repair are very rarely found in association with the mutation preferences in our datasets. Our published data  demonstrSince we favour repeated targeting by the deaminases as the explanation for the high frequency of bi-allelic mutation observed associated with MELs, we have not expanded on the gene-conversion argument in the text which we feel might misdirect the reader.5) It is important that 57% of AID and 46 % of sA3G mutations occur within the promoter region compared to only 21% of EMS mutations. However, considering that the authors found 1227 and 568 MELs in the AID and sA3G treated genomes, but only 1 for MMS, a simple analysis would reveal that the MMS mutations in the promoter region compared to the total frequency of MMS-induced MELs is extremely high. Could the authors clarify or discuss this point better, so that the reader does not get misled by a simple analysis, if that is the case?The compact nature of the yeast genome makes the proportion of sequences associated with “promoter” function much higher than in mammalian cells, thus up to 20% of the genome corresponds to promoters. Fully random mutation will therefore result in 20% of mutations occurring on promoters, which is the frequency seen in EMS treated samples. We have made a note in the text to clarify this.Our analysis reveals that the deaminase induced mutations are skewed towards promoter regions much more than expected (57% and 46% for AID and sA3G). Even within the small fraction of the genome corresponding to promoters, the regions with high density of mutations (that we define as MELs) are confined to even smaller regions, which when added up account for just 1.5% of the whole genome. This is a remarkable skewing that clearly deviates from random which our analyses attempt to convey.However, as the reviewers rightly question, the single MEL identified in the EMS induced mutation set is not associated with a promoter, but with the CAN1 gene body and is the result of the selection that requires at least two mutations to inactivate the both alleles at the CAN1 locus. We have adjusted the text to emphasise this point. Therefore, there are no EMS induced MELs which associate with promoter regions.


Anaplasmataceae family. Survival requires that the parasite fundamentally alter the native functions of the cell to allow its entry, intracellular replication, and transmission to a hematophagous arthropod. The small genomic repertoires encode several eukaryotic-like proteins, including ankyrin A (AnkA) of Anaplasma phagocytophilum and Ank200 and tandem-repeat containing proteins of Ehrlichia chaffeensis that localize to the host cell nucleus and directly bind DNA. As a model, A. phagocytophilum AnkA appears to directly alter host cell gene expression by recruiting chromatin modifying enzymes such as histone deacetylases and methyltransferases or by acting directly on transcription in cis. While cis binding could feasibly alter limited ranges of genes and cellular functions, the complex and dramatic alterations in transcription observed with infection are difficult to explain on the basis of individually targeted genes. We hypothesize that nucleomodulins can act broadly, even genome-wide, to affect entire chromosomal neighborhoods and topologically associating chromatin domains by recruiting chromatin remodeling complexes or by altering the folding patterns of chromatin that bring distant regulatory regions together to coordinate control of transcriptional reprogramming. This review focuses on the A. phagocytophilum nucleomodulin AnkA, how it impacts host cell transcriptional responses, and current investigations that seek to determine how these multifunctional eukaryotic-like proteins facilitate epigenetic alterations and cellular reprogramming at the chromosomal level.Obligate intracellular pathogenic bacteria evolved to manipulate their host cells with a limited range of proteins constrained by their compact genomes. The harsh environment of a phagocytic defense cell is one that challenges the majority of commensal and pathogenic bacteria; yet, these are the obligatory vertebrate homes for important pathogenic species in the  In order to infect mammalian hosts, bacterial pathogens evolved an array of mechanisms that serve to create an environment conducive for survival, replication, and spread. While many bacterial species survive in an extracellular environment, intracellular pathogens must be capable of both entering their host cells undetected and altering the cellular milieu in order to replicate. Traditionally, the ability of bacterial-derived proteins to induce disruptions of cell signaling or major cellular processes such as NF-κB, MAPK, and JAK/STAT pathways, are the predominant focus of host–pathogen interaction studies . RecentlEukaryotic DNA is highly organized and gene expression tightly regulated by an orchestrated network of proteins, RNAs, and other modulators. Histone octamers, or nucleosomes, organize DNA by acting as a bobbin on which the DNA winds. The charge of the histone proteins can be covalently modified in order to more tightly or loosely associate with DNA. Histone acetylation, which imparts a negative charge, is predominantly associated with an open configuration where promoters are easily accessed by RNA polymerases. Histone methylation or phosphorylation which impart a positive charge, cause DNA to more tightly associate with histone proteins, reducing promoter accessibility to transcription activating machinery. The process of modulating open and closed chromatin is further complicated by (i) the residue(s) of which histone protein(s) is/are modified, (ii) methylation of cytosine residues in DNA, and (iii) non-coding RNAs, and by the manner in which these mechanisms are intertwined. It therefore is no surprise that bacterial-derived proteins have evolved to interfere with host gene expression that improves bacterial fitness.Listeria monocytogenes, Chlamydia trachomatis, Shigella flexneri, and others, were found to target the host cell nucleus  that de-phosphorylates MAPKs in the nucleus resulting in a lack of histone H3 phosphorylation at serine 10 at a number of NF-κB-dependent genes , blocks binding of heterochromatin inducing protein BAHD1 at interferon-stimulated genes resulting in upregulated expression  protein effectors that when expressed, bind plant DNA and alter transcription and disease susceptibility (Anaplasmataceae family. Ankyrin A (AnkA) of Anaplasma phagocytophilum, as well as Ank200 and several tandem-repeat containing proteins (TRPs) from Ehrlichia chaffeensis, have been shown to enter the nucleus and bind DNA, and interact with host epigenetic machinery or alter nearby histone octamers  in 1990  that allows protein effectors to translocate into infected host cells where they likely act by mechanisms similar to those of other bacterial secreted effectors that target cytosolic pathways such as signal transduction, cytoskeletal rearrangements, intracellular trafficking, etc.  and AnkA, the latter of which was found by CYBB, encoding the gp91phox component of phagocyte oxidase  and special-AT rich binding protein-1  to investigate histone marks at defense gene promoters, acetylation of histone H3 was dramatically reduced, a finding often associated with silenced gene transcription .Of considerable interest is the interplay between chromatin structure and DNA methylation. Histone modifications, DNA methylation at CpG islands, and binding of methyl CpG DNA-binding proteins (MeCPs) via their methyl-DNA binding domains (MBDs) occur in concert during biological responses including neoplasia and cellular differentiation . Cytosin stimuli . MBDs ca stimuli . General stimuli . This coCYBB promoter during myeloid differentiation where it represses the transcription of CYBB, is involved in maintaining expression of BCL2 . In keeping with the original observations of Borjesson et al., most clusters were upregulated; however, the analysis also demonstrated a similar pattern of downregulated genes over long linear regions. Of interest was chromosome 17 with a 9.4 Mb cluster containing myeloid peroxidase (MPO), eosinophil peroxidase (EPX), and lactoperoxidase (LPO) which showed marked downregulation, and a 3.2 Mb cluster containing multiple upregulated chemokine genes . In addition to reduced transcript levels, MPO and EPX promoters were previously shown to be deacetylated upon A. phagocytophilum infection  was upregulated . The chromosomal landscape of the MHC locus is well documented with respect to chromatin looping via MARS and histone marks  complexes] or additional bacterial-derived nucleomodulins that further contribute to the dramatic changes observed. To examine this, we designed a genome-level bioinformatics approach to predict nucleomodulins based on the combination of secretory and NLSs and studied the genomes of 12 phylogenetically diverse intracellular prokaryotic pathogens, including for each . Among tfunction . ElucidaA. phagocytophilum and OspF of S. flexneri to alter inflammatory responses could provide opportunities for engineering of therapeutic agents which interfere with cellular responses in inflammatory diseases or other conditions where epigenetic factors control or contribute to disease.Understanding the role of prokaryotic control over complex eukaryotic transcription machinery in lieu of the bottleneck that would occur with single effector targets at signaling pathways will allow for better understanding of the essential components of whole cell transcriptional re-programming. However, this has implications not only for host–pathogen or host–symbiont interactions, but across biology. The ability of proteins like AnkA of The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.