Genes are transcribed from transcription start sites (TSSs), and their position in a genome is strictly controlled to avoid mis-expression of undesired regions. In this study, we designed and developed a methodology for the evaluation of promoter context, which detects proximal promoter regions from − 200 to − 60 bp relative to a TSS, in Arabidopsis and rice genomes. The method positively evaluates spacer sequences and Regulatory Element Groups, but not core promoter elements like TATA boxes, and is able to predict the position of a TSS within a width of 200 bp. An important feature of the evaluation/prediction method is its independence of the core promoter elements, which was demonstrated by successful prediction of all the TATA, GA, and coreless types of promoters without notable differences in the accuracy of prediction. The positive relationship identified between the evaluation scores and gene expression levels suggests that this method is useful for the evaluation of promoter maturity. Promoters determine not only the frequency and timing of transcription, but the position and direction of transcription start sites (TSSs). Decoding this information from the nucleotide sequence is one of the most important goals of functional genomics.2, revealing that TSS of a gene is made of a cluster with a width of tens of bp and that multiple clusters are associated with a gene. Accordingly, the most major TSS, or the peak TSS, of the top cluster is considered as the representative transcription start site of a gene3. This data is indispensable for extraction of functional elements and likewise recognition of promoter structure of each gene4.TSS of a gene used to be determined as the most upstream end of several full-length cDNA clones covering the downstream gene body, which was reflected to gene models. Development of TSS-seq supported by the emerged NGS technology enabled TSS mapping with higher scales5, therefore, they can be recognized using these orders. In mammalian genomes, the orders range from a gene-wide length of about 10 kbp; to a range of clusters of TSSs spanning ~ 100 bp; and the finest range which determines distribution of TSSs in a cluster, of one bp5. In addition, to these three orders, the distribution of TSS is regulated by chromatin structure, often accompanied by epigenetic modulation in chromosomal to local ranges6. The emergence of a TSS is thus a result of multi-level regulation.During the analysis, the distribution of TSS was found to be of hierarchical orders7. This motif is found in a limited number of genic promoters, and is therefore not applicable to the majority of promoters. Genome-wide TSS analysis has revealed some rules which appear to be followed in mammals8 and higher plants9. The latter, called the YR Rule, is a relaxed form of the Inr motif, and covers the majority of Arabidopsis promoters. The major factor influencing the position and direction of TSSs had been thought to be the presence of the TATA box, a core promoter element found in yeast, Drosophila, higher plants, mammals, and many other eukaryotes7. However, large-scale promoter analyses have revealed that 32% of promoters in humans1 and 25% in Arabidopsis9 contain TATA boxes, demonstrating that TATA-positive promoters are in the minority in both animals and plants.The finest order of regulation, which we call local-range regulation, is known to be determined by a well-known consensus sequence motif called Initiator (Inr)Drosophila7, and GA and CA elements in higher plants9. Mammalian TATA-less promoters have been found to be associated with CpG islands1. This group of sequences is related to several elements, including Sp18, but because of its sequence diversity, the CpG islands themselves are not thought to be cis-element for a specific DNA-binding protein. Therefore, they could be a core promoter element modifying the DNA structure to make it suitable for transcriptional initiation.The finding of TATA-less promoters led to the identification of other core elements among these promoters, including DPE in Arabidopsis promoters9, are poorly understood. Therefore, it is not clear whether there is a general determinant for the middle-range restriction of TSSs which is applicable to both coreless and core-containing promoters.The core elements are believed to be factors in the middle-range (~ 100 bp) TSS determination. It is not known whether the core elements alone are enough to restrict TSSs within the middle range, or whether additional determinants are required. Middle-range determinants in coreless promoters, which account for 28% of We are interested in the evaluation of promoter context with a span of ~ 1 kb region. We hypothesize that in addition to the core promoter elements it is also related to the middle-range TSS distribution. This topic is not well understood, but we assume it is a middle-range constituent of promoters if it does exist. If it does, the detection and assessment of the promoter context can assist in the prediction of promoter positions for coreless type promoters. Their methodology has the potential to measure promoter maturity, which distinguishes newly emerged promoters from long-existing ones without taking sequence conservation into consideration. Our work on the evaluation of sequences in the proximal and distal promoter regions resulted in the establishment of a successful measure of the promoter context in a core-type independent manner.10 and maize11. Therefore, it is not practical to expect it from minor plant and crop species and also ecotypes and cultivars even in model plant species, such as Arabidopsis and rice. This situation can be relieved by development of sequence-based TSS prediction methods which does not require any experimental costs.TSS-seq is an established, but laborious and cost-consuming methodology to cover the majority of genes in a genome. Although TSS info is indispensable for recognition of promoter structure, which is highly related to its expression profile, its data in higher plants is currently available only for ArabidopsisArabidopsis genome. These include Genic Top, Genic Companion, Intragenic, Antisense, and Orphan9. In this work, we focused on Genic Top promoters which are the primary determinant of expression for protein-coding genes3. In our previous studies, analysis of the localization profile of each octamer sequence along the promoter region of the Genic Top type revealed several distinct groups of promoter constituents, including core promoter elements, Regulatory Element Groups (REGs), Inr, and some other sequences involved in translational initiation12. We identified possible spacer sequences which appear at the highest frequencies among all the octamer sequences in the promoter region, and have no known functions. Figure Arabidopsis genome. The core elements, TATA, Y Patch, and GA, are localized around the TSS, and the REG upstream of the core elements with a peak at around -100 bp, as reported previously12. A spacer AAAAAAAA in the figure is the most frequently observed octamer in the promoter region, and shows no match with any functional promoter elements, such as the core elements and REG. This spacer has a peak upstream of TATA, at around − 70 bp, and its occurrence gradually decreases in the upstream direction. Its frequency drops after + 51 bp, suggesting that the octamer does not occur preferentially in the coding region. Overall, the octamer preferentially localizes at the proximal promoter region. Another spacer, TTTTTTTT, shows a similar occurrence to AAAAAAAA in the distal promoter region, but has a very different distribution at the proximal region. Because these two octamers are complementary, the preferential occurrence of AAAAAAAA over TTTTTTTT produces strand bias at the proximal promoter region. These profiles may suggest that there is some promoter context elevating in the proximal promoter region over the distal region in a strand-specific manner.Clusters of TSSs, which correspond with promoters, are found in various positions in relation to the gene structure in the In order to produce a measure of promoter context, we developed several score tables for all possible octamers, which reflects the occurrence of the octamers. One type is the Intergenic Index (IGI). IGI200_60 is a score table reflecting the occurrence of elements in a range from − 200 to − 60 bp, and the score is normalized to make the score zero for octamers with neutral occurrence. A positive score indicates more frequent occurrence than that of the neutral octamers in the region. The flow of the calculation is illustrated in Supplemental Figure We prepared another type of score, the Promoter Index (PRI), by subtracting the IGI of the distal promoter region from that of the proximal region. A high PRI is an indication of a proximal promoter region. The examination of several regions for the distal promoter within − 800 to − 200 bp revealed that a region from − 750 to − 450 bp gave the best results in TSS prediction  of the two factors examined indicated that 0.0 gave the best prediction score  and the downstream region (+ 1 to + 200), a finding which is consistent with the results shown in Panel C. The peak position of the rice PRI was around − 20, which shifted toward the downstream side compared with the peak position in Arabidopsis  and rice (48.18%)  was considerably lower than that of the Arabidopsis promoters (77.78%), reflecting the reduced specificity of PRI in rice from that in Arabidopsis  in order to improve the specific detection of rice promoter regions. The FUI was calculated as for PRI by subtracting IGI750_450, with an exchange of the frequency of the proximal promoter region to that of the 5' UTR. The high specificity of FUI for the 5' UTR over other genic regions is shown in Supplemental Figure The rice PRI produced a positive score in the 5' UTR in addition to the proximal promoter region (− 200 to − 60)  were subjected to PRI and TSSPlant for prediction of the position of the TSS. Because TSSPlant does not have any schemes to select the best TSS, we ran two strategies: acceptance of all the predictions, and selection of one TSS with the highest score within the 2 kb region. Both results are included in the table.We compared our PRI-based TSS prediction with that produced by TSSPlantAs shown in Table Lastly, we examined which promoter-constituting sequences contributed to the high PRI score. The scatter plots in the four panels of Fig. Arabidopsis or rice.Each panel highlights different octamer groups. Octamers of the TATA box are shown in Panel A, and this group does not contribute to high PRI in either 12. This group is a mixture of varied scores, both positive and negative, and does not show a tendency toward high or low PRI scores. We concluded that these two groups do not produce high PRI scores as a whole. The results shown in Panels A and B are consistent with core-type independent prediction by PRI  and rice 152), with considerable conservation (90)2, with cArabidopsis promoter region, which are the most frequently detected 50 octamers in the promoter region, excluding core and REG (sum of 200_60 & 750_450). This group has PRI scores varying from high to low in Arabidopsis, revealing that not all the highly detected sequences in the promoter region had a preference toward the proximal promoter region. Comparison with the rice scores revealed that the high and low scores of octamers in this group were well conserved between the two species. These results suggest that sequences paving the promoter context are conserved to some extent, despite the difference of GC content between the two .Panel D emphasizes the spacer sequences paving the In summary, our analyses revealed that REG and a part of the spacer sequences contribute to high PRI scores, and core elements, especially the TATA box, do not. The PRI method was developed to detect the middle-range promoter context by evaluation of differential appearance within a region from − 750 to − 60 relative to TSS. Therefore, these results, positive effects of REG and spacers and negligible effects of core elements, are reasonable. These observations provide the basis for core-type-independent promoter detection using PRI.15. Later genome-wide promoter analyses revealed that a considerable number of promoters do not have either a TATA box or CpG islands2, which means that these coreless promoters cannot be detected using the core element-based promoter search. In addition, the existence of coreless promoters implies that the known core elements are not indispensable for transcriptional initiation. Higher plants do not have the CpG type4 and many promoters do not have any detectable core promoter elements9, so core-based promoter prediction could be less useful in plants.Decades ago, prediction of the promoter regions in genome sequences was attempted by finding the TATA box, the first core promoter element identified in a wide range of eukaryotes, and the CpG islands, which are known to be accompanied by mammalian promoters. This core element-based approach alone turned out to be insufficient for prediction16. These features are applicable to mammals and fish but not to yeast, insects, or higher plants16. Therefore, the features established in mammals are not a general rule among eukaryotes.Another approach to promoter detection utilizes the structural features of the DNA, accompanied by DNA sequences13, but improvement of the methodology is still required for better prediction. One big problem with the machine learning strategy is that it does not necessarily advance our knowledge, even if the prediction system works well.Recently, machine learning has been introduced into promoter prediction. Methodologically, this is a powerful general-purpose strategy which is applicable to a wide range of problems, including image recognition and speech interpretation. It requires positive and negative sequences for learning, and the quality of the output depends on the number, diversity, and range of the sequences utilized. This approach has had some success17. Combinational approaches are expected to produce better prediction accuracy than stand-alone methods, but if essential knowledge is lacking, combination does not cover this lack.The methodologies mentioned above can be combined, and an integrated strategy has recently been reported12 and TSSPlant13.Our initial plan for quantification of the promoter context in a manner independent of the core promoter types was to focus on the spacer sequences in the promoter region. After development, one thing we did not expect was the positive contribution of REG to our evaluation method. Even so, evaluation of the promoter context without taking account of the core elements has been successfully established in this study. This is the first report of middle-range (~ 1 kb) promoter evaluation method solely based on the nucleotide sequence. Pinpoint prediction of TSS, which is local-range prediction, should be achieved using other methodologies, such as YR RuleThe requirements for the spacer sequences in the promoter region are not well understood. We assume that they include the absence of undesirable functions and the tuning of nucleosome positioning. Strand-specific differences in the PRI scores Figs. , 6D and Arabidopsis genome is between around 1800 bp (head-to-head junction of the TATA type) and around 500 bp (tail-to-head junction of the Coreless type)18. The actual length of Arabidopsis promoters should be less than this.A longstanding question is the length of the actual promoter of the Genic Top type. The least strict determination of the promoter end is the closest edge of the adjacent gene. The distance to the neighboring gene from a TSS on average in the packed e.g., Fig. Arabidopsis with respect to the promoter context. Our previous studies of Arabidopsis 80 accessions detected pressure for sequence conservation starting from − 500 or − 400 toward the TSS . Assuming that the promoter region is more conserved than the intergenic region, this observation suggests that the promoter region starts from − 500 or − 400 toward the downstream region.The PRI starts rising from around − 500 bp toward the downstream region . For Arabidopsis analysis, 324,461 TSS clusters, including 21,673 Genic Top clusters, were utilized. For rice, 250,548 TSS clusters, including 22,405 Genic Top clusters, were used. TAIR1020 and RGAP721 were used as genome annotation information and the genome sequence for Arabidopsis and rice, respectively. Promoter sequences were extracted from the genome sequences based on the position of the peak TSS of TSS clusters. Other Arabidopsis and rice sequences were obtained from TAIR10 and RGAP7, respectively. Octamer sequences for promoter elements  of Arabidopsis and rice were determined in our previous reports22.TSS-seq data from several TSS libraries of https://github.com/yyyamamoto/TssPrediction). The preparation of the PRI tables for Arabidopsis and rice are described in Supplemental Fig. 1. The scoring of genomic sequences with PRI/IGI/FUI tables were done using Chrom_scan.py, and peak picking of the scanned data after smoothing with a bin of 151 bp using peak_find_SG.py. TSSPlant for Linux13 (https://www.cbrc.kaust.edu.sa/download/) was locally run with default settings.Sequence analysis was achieved using home-made Python, Perl and shell scripts and summarized using Excel . Our PRI tables of Arabidopsis and rice prepared with all the chromosomes for training, and scripts for preparation of PRI tables and for sequence evaluation with the tables are available at GitHub (Arabidopsis spacer sequences in the promoter region, used in Fig. Arabidopsis Genic Top promoters.Finalized flow of the methods are illustrated in Supplemental Figure Supplementary Information.


Building ribosomes for cellular protein translation is a massive, energy-consuming undertaking. The process is executed by all cells to replenish the relevant pools of proteins required for cellular functions. Cancer cells are strikingly dependent on this activity, as they need continuous protein synthesis for sustained proliferation and growth. Ribosome biogenesis requires the activities of three RNA polymerases, which transcribe essential RNAs that make up the backbone of the ribosome, and hundreds of proteins, which provide structural and functional support. Of the three RNA polymerases, RNA polymerase I executes a critical and rate-limiting step by transcribing three key ribosomal RNAs. Pol I transcription is pervasively deregulated in cancers, enabling unlimited protein synthesis. Here, we review this enzyme and provide examples of current efforts to target Pol I transcription therapeutically.RNA polymerase I is a highly processive enzyme with fast initiation and elongation rates. The structure of Pol I, with its in-built RNA cleavage ability and incorporation of subunits homologous to transcription factors, enables it to quickly and efficiently synthesize the enormous amount of rRNA required for ribosome biogenesis. Each step of Pol I transcription is carefully controlled. However, cancers have highjacked these control points to switch the enzyme, and its transcription, on permanently. While this provides an exceptional benefit to cancer cells, it also creates a potential cancer therapeutic vulnerability. We review the current research on the regulation of Pol I transcription, and we discuss chemical biology efforts to develop new targeted agents against this process. Lastly, we highlight challenges that have arisen from the introduction of agents with promiscuous mechanisms of action and provide examples of agents with specificity and selectivity against Pol I. Ribosome biogenesis is a complex and metabolically costly process involving the activities of three cellular RNA polymerases, their RNA products, and hundreds of proteins ,2,3,4,5.The ribosome is a ribonucleoprotein complex responsible for translating mRNA into proteins ,5. The eIn 1969, Roeder and Rutter made the seminal discovery that eukaryotes possess three different DNA-dependent RNA polymerases (Pols), in contrast to the single RNA polymerase found in prokaryotes . Over thThe nucleolus forms around the active sites of rRNA gene transcription, which are defined by the multicopy rRNA gene clusters termed as nucleolar organizing regions (NORs) . Human NXenopus, where they were first discovered and are best studied, the enhancers influence the number of activated promoters, but are not absolutely required for basal transcription or polymerase loading [cis and inhibit unlinked promoters in trans, but related regulatory factors remain to be identified. We do not know the relevance of these elements and whether they regulate transcription in humans. The spacer promoter is separated from the functional promoter by transcription termination recognition sequences essentially blocking read-through transcription [The ribosomal DNA (rDNA) gene repeats are arranged head-to-tail ,18,23 FA. Each r loading ,26,27,28cription . In micecription ,30.The first, rate-limiting step of ribosome biogenesis is the transcription of rDNA by Pol I into a 47S rRNA precursor ,31,32. TWhile Pol I machinery is predominantly localized in the fibrillar center of the nucleolus, Pol I transcription occurs on the border of the fibrillar center and dense fibrillar component . The PolSaccharomyces cerevisiae. The nomenclature for yeast and human subunits is different and has evolved over time. We refer the reader to a recent review for the naming convention [Structural studies of Pol I have detailed the enzyme and the preinitiation complex in the various steps in the transcription cycle, namely, preinitiation, initiation, and elongation  and with Pol III AC40, AC19), which provide mostly structural support for the core assembly [reviewed in ,39. The , AC19, wPol I contains four peripheral subunits unique to this enzyme: A43 (human RPA43), A14, A49, and A34.5. The A43-A14 heterodimer forms the stalk, a structure that protrudes from the core. Preinitiation factor Rrn3 (human RRN3) binds to the A43-A14 stalk and recruits the Rrn3-Pol I complex to the rDNA promoter ,45,46,47Within the past year, two groups have elucidated the structure of human Pol I for the first time ,51 Figu. OverallPol I is a highly efficient RNA polymerase that has evolved for the transcription of its long 13 kb transcript. The structure of Pol I, with its in-built RNA cleavage ability and incorporation of subunits homologous to transcription factors, enables it to quickly and efficiently synthesize the enormous amount of rRNA required for ribosome biogenesis ,53. ThisInitiation. The 140-160-base pair rRNA gene promoter contains two key elements, a core element and the UCE [I110, TAFI48, TAFI63, TAFI12, and TAFI41 [I63 and TAFI110 interact with RRN3 on the RRN3-Pol I complex and recruit Pol I to the promoter. Together, these proteins form the PIC. This process is relatively conserved in yeast, as yeast has Rrn3, TBP, and a core complex homologous to SL-1 [ the UCE ,31. Bind the UCE ,56. Whild TAFI41 ,31. RRN3d TAFI41 . Similard TAFI41 ,46,47,51 to SL-1 ,45,46,47 to SL-1 .The successful assembly of the PIC bends the promoter to an angle, remarkably different from that of the Pol II promoter, favorable for transcription initiation. Pol I stutters on the first few nucleotides, during which the DNA duplex melts to favor the formation of the transcription bubble and promoter escape. This process is further assisted by A49 and A12.2, which support the binding of Pol I to the promoter and the formation of the open elongation complex, respectively ,43. Pol Elongation. In the active site, two magnesium cations in the catalytic aspartate triad coordinate an NTP condensation reaction. During this reaction, one nucleoside monophosphate (NMP) is added to the nascent RNA strand as pyrophosphate is released. Pol I then translocates down the DNA template by one nucleotide [cleotide . This trcleotide . As eachcleotide . Pol I ncleotide . The meccleotide ,60,61,62Pausing and Backtracking. Given the ratchet motion during elongation, the enzyme is prone to backtracking. Furthermore, if the polymerase encounters an obstacle, such as DNA damage or an incorrect nucleotide, it will pause. The polymerase will then backtrack. Since the “gating tyrosine” in the active site remains “open”, the polymerase can backtrack as much as it needs to. The C-terminus of A12.2 inserts into the active site and cleaves the RNA [ the RNA ,64. This the RNA . Ineffic the RNA , and the the RNA .Termination. Transcription termination elements are positioned on two separate sites on the rDNA gene repeat: at the 3′ end of the transcribed region and upstream of the transcription start site. Transcription termination factor I (TTF-I) binds to the termination element at the 3′ end of the transcribed region, bends the DNA, and triggers Pol I to pause [to pause . Howeverto pause . Given tto pause ,68.Pol I Complex Stability. Pol I processivity is facilitated by enzyme stability. However, the mechanistic understanding of which factors govern mammalian Pol I assembly, stability, and localization is incomplete. In yeast, the interaction between A190 and A135 is stable [s stable , and in s stable .In yeast, A49 stabilizes the expression of A34.5 and is mediated by a protease-sensitive linker domain. Conversely, depletion of A34.5 also destabilizes A49, suggesting that this complex is inherently unstable if either subunit is missing . In contExternal factors, such as zinc availability and temperature, also mediate Pol I stability. Zinc depletion has been shown to induce vacuolar proteolysis of Pol I in yeast . Cold te1 phase, and resumes full capacity during S phase and G2 phase [Pol I transcription is regulated by metabolic states and environmental factors, such as cell growth, nutrient availability, stress, and the cell cycle [reviewed in ,7,8,9. CG2 phase . There aG2 phase ,83.PIC factors are targets of post-translational modifications. These regulatory events affect UBF, SL-1, and RRN3 ,84, and I110 during mitosis prevents SL-1 from interacting with UBF and prevents transcription initiation [1 phase. Both SL-1 and UBF are fully active during S phase and G2 phase [Cell cycle-dependent transcription of Pol I is also achieved by post-translational modifications of the transcription factors. The phosphorylation of SL-1 subunit TAFitiation . SL-1 isG2 phase ,93.Strikingly, Pol I transcription activity and ribosome biogenesis are also under the control of the circadian clock ,95. TranChanging the number of active (versus silent) rRNA genes at an rDNA repeat is regulated by epigenetic mechanisms. The rDNA of actively transcribed genes exists in a nucleosome-deplete, “open” euchromatin configuration that is characterized by DNA hypomethylation, H4ac, and H3K4me2 . In Approximately half of the rRNA genes are maintained in an active state. However, the number of active rRNA genes differs based on cell type, suggesting that the number of active genes is passed down through cell lineages during development and differentiation . This inOf all genes, the rRNA genes are the most heavily transcribed. Given the high transcriptional activity and the speed of the polymerase on the long 13 kb transcript, this polymerase is particularly sensitive to transcriptional stresses . A surroRNA polymerases encounter obstacles generated by altered chromatin conformation or DNA adducts, such as those caused by DNA damage and UV irradiation, that stall or arrest transcription. Each polymerase has its own error rate, with Pol II having the highest fidelity, closely matched by Pol I, while Pol III error rates are the highest . To resoThe largest subunit of yeast Pol III, C160, is also ubiquitinated and degraded by the proteasome upon transcription stalling. To induce cell stress, Lesniewska et al.  treated Pol I transcription is a critical step in ribosome biogenesis and protein translation. As such, it is essential, and proportional, to cancer cell growth and a rate-limiting factor for cancer cell proliferation ,12. OverStaining of the NOR using silver, which recognizes both nucleolar proteins and RNA, is termed as argyrophilic nucleolar organizing region (AgNOR) staining, and it has been used extensively to assess tumor specimens ,131. TheMore recently, we introduced specific detection of the 47S rRNA precursor using chromogenic in situ hybridization for visualization and quantification of Pol I transcription activity in human tissue samples . Using tSeveral studies have used surrogate markers for Pol I activity, such as the expression of rRNA methyltransferase fibrillarin (FBL) ,137 and Cancer cells employ several different mechanisms to increase Pol I transcription and ribosome biogenesis ,142,143.mTOR drives multiple steps in ribosome biogenesis and regulates both transcription of rRNA and mRNA synthesis of ribosomal proteins  and cyclins are also deregulated in many cancers due to their mutations, amplifications, and uncontrolled activation. Their deregulation leads also to interference of Pol I transcription by phosphorylation of SL-1 and UBF to maintain constitutively high Pol I transcription rates ,143,165 Additionally, epigenetic modification of the rDNA promoter may contribute to the high Pol I transcription activity in cancer cells. For example, hepatocellular carcinomas are characterized by hypomethylation of the rDNA promoter, leading to a persistently “open” euchromatin state and upregulation of Pol I transcription . rDNA hyI110 to prevent their interaction and productive initiation [Schizosaccharomyces pombe, Dicer and other RNA interference mutants are inviable in a manner dependent on Pol I transcription [Several tumor suppressors, which are mutated and inactivated in cancers, control and attenuate Pol I transcription activity ,9. The Ritiation . PTEN diitiation . BRCA1, itiation . It has itiation . Nucleolitiation . Furtheritiation . These aitiation . Cellulaitiation ,92. MYBBitiation . RUNX2 titiation ,176. DICcription . Deletiocription . The ovecription .Given the essential role of ribosome biogenesis in cancer cell growth and the activated state of Pol I in many cancers, Pol I is a rational target for cancer therapeutics. The high DNA metabolic activity due to the activated transcriptional rates creates unique vulnerabilities at this genetic locus, especially to events that cause transcriptional impediments. Enzyme stability is required for effective transcription elongation. This is especially critical for Pol I, given the high initiation rates and fast processivity over the long precursor transcript. Furthermore, the polymerase density, analyzed in detail in yeast, is very high and renders this enzyme highly vulnerable to perturbations caused by lesions or conformational impediments. In fact, several classes of chemotherapeutic drugs—including alkylating agents, anti-metabolites, antibiotics, and topoisomerase inhibitors—disrupt Pol I transcription . Hence, Alkylating agents  attach alkyl groups to DNA to form DNA adducts. These adducts trigger a DNA damage response and induce cell cycle arrest and cell death . CisplatAnti-metabolites  mimic cellular metabolites, interfering with enzymatic processes and incorporating into DNA and RNA and interfere with rRNA processing . MethotrChemotherapeutic agents in the class of antibiotics, such as Actinomycin D, intercalate with DNA and induce DNA damage ,185,186.Topoisomerases (TOP) are enzymes that are required to resolve DNA supercoiling and facilitate processes such as transcription, replication, and recombination ,188. TOPG quadruplexes are unusual four-stranded secondary DNA structures that are formed by G-G base pairs via Hoogsteen hydrogen bonding . These sWe have summarized these drugs in It is evident that many challenges remain in the quest to develop effective Pol I inhibitors. Most of the current drugs induce nonspecific, widespread DNA damage. It would be optimal to test drugs that target Pol I transcription directly. Yet, the mechanisms that govern the stability and regulation of the Pol I enzyme itself remain unclear, making it an elusive enzyme to target. While rRNA synthesis is upregulated in many types of cancer, it is also essential for normal cells. An effective cancer therapeutic must therefore selectively target Pol I transcription to exploit cancer cell vulnerabilities without affecting normal cells. Currently there are only few pharmacological tools that qualify as specific and selective Pol I inhibitors for this purpose.We recently discovered a first-in-class small molecule, BMH-21, that specifically and selectively blocks Pol I transcription ,210. BMHBMH-21 blocks three critical steps in the transcription cycle, namely initiation, promoter escape, and elongation ,218 Fig. BMH-21 RPA1 degradation is prominently observed in cancer cells and is associated with BMH-21-induced cancer cell death . The degFBXL14 as an E3 ligase involved in the BMH-21-induced degradation of RPA1 [By conducting an unbiased RNAi screen against ubiquitome proteins, we recently identified SCF of RPA1 . We show of RPA1 . However of RPA1 . We infeThe discovery of BMH-21 is exciting for both fundamental and translational reasons. The compound induces the proteasome-mediated degradation of the Pol I catalytic subunit, analogous to prior studies of the proteasome-mediated degradation of the large subunits of Pols II and III. Prior studies focused on the regulation of Pol I activity through the modification of its transcription factors and the rDNA, but these results show that the Pol I enzyme itself can also be regulated through the degradation of its catalytic subunit. This finding thus provides essential knowledge about the stability and regulation of the Pol I complex relevant for the mechanistic understanding of the enzyme function. BMH-21 is the first compound to specifically and selectively inhibit Pol I without having off-target effects, such as those by other chemotherapeutic drugs. This class of small molecules thus has very promising potential in the clinic, and preclinical studies are currently underway on BMH-21 analogs.Pol I is responsible for the first and rate-limiting step of ribosome biogenesis—the transcription of rDNA into a 47S rRNA precursor. To match their proliferative and biosynthetic activities, cancer cells possess abnormally high rates of ribosome biogenesis. Since major cancer drivers constitutively activate Pol I transcription, Pol I is a rational target for cancer therapeutics. Current studies focus on the regulation of Pol I activity through the modification of its transcription factors and the rDNA, but very little is known about the stability and regulation of the enzyme itself. The finding that the Pol I complex can be regulated through the degradation of its catalytic subunit provides fundamental knowledge about the stability and regulation of the enzyme relevant for the mechanistic understanding of the enzyme function and the development of Pol I—targeting agents. Preclinical studies have detailed the precise mechanisms of how the BMH-21 class of small molecules inhibits Pol I transcription. Development of these molecules for clinical testing is ongoing. These findings open up a new path for the discovery of other molecules that take advantage of this new regulatory mechanisms.


Fungal species have the capability of producing an overwhelming diversity of bioactive substances that can have beneficial but also detrimental effects on human health. These so-called secondary metabolites naturally serve as antimicrobial “weapon systems”, signaling molecules or developmental effectors for fungi and hence are produced only under very specific environmental conditions or stages in their life cycle. However, as these complex conditions are difficult or even impossible to mimic in laboratory settings, only a small fraction of the true chemical diversity of fungi is known so far. This also implies that a large space for potentially new pharmaceuticals remains unexplored. We here present an overview on current developments in advanced methods that can be used to explore this chemical space. We focus on genetic and genomic methods, how to detect genes that harbor the blueprints for the production of these compounds , and ways to activate these silent chromosomal regions. We provide an in-depth view of the chromatin-level regulation of BGCs and of the potential to use the CRISPR/Cas technology as an activation tool. Penicillium rubens, discovered by Alexander Fleming in 1929 [Tolypocladium inflatum which is used as an immunosuppressant [Aspergillus terreus [Aspergillus oryzae or citric acid by Aspergillus niger [Bacteria, plants, and filamentous fungi are capable of producing many chemically diverse bioactive substances, referred to as natural products or secondary metabolites (SMs) . Probabl in 1929  which in in 1929 . Many fupressant ,6, or lo terreus . Other fus niger ), the agus niger ,11, growus niger ) and manus niger ,14,15,16us niger .SMs are per definition not essential for growth but may provide selective advantages for the producing organism upon specific environmental challenges: e.g., pH stress , temperThe blueprints for such bioactive substances are stored in biosynthetic genes that are, in most cases, physically linked in fungal genomes and together with genes for regulators and transporters sometimes constitute very large BGCs ,29. ThesDepending on the so-called backbone or key enzyme(s) involved in the biosynthesis, SMs are categorized according to the chemical families. They belong to e.g., polyketides, non-ribosomal peptides, terpenes and alkaloids or prenylated tryptophan derivates. Accordingly, they are synthesized by polyketide synthases  and non-reducing (NR-PKS)), non-ribosomal peptide synthetases (NRPSs), terpene cyclases (TCs) and dimethylallyltryptophan synthases (DMATSs) or hybrids of them ,29. Next to the backbone enzyme-encoding gene(s) BGCs often harbor genes involved in self-resistance against a potentially toxic SM produced by the BGC, transport of precursors, intermediates, or the resulting compound ,32, tranFusarium graminearum, polyketide synthase PKS8 was shown to be a stand-alone gene that is responsible for the synthesis of gibepyrone A [Aspergillus oryzae does not have a backbone enzyme-encoding gene at all [A few exceptions exist that deviate from this standard configuration. For example, in pyrone A , while te at all . In othee at all . The oppe at all .Aspergillus fumigatus [Aspergillus niger [A. oryzae and its close relative Aspergillus flavus [Streptomyces [Umbilicaria pustulata [Fungi exhibit a very diversified and specialized chemical repertoire. The diversification of BGCs increases with the phylogenetic distance ,38 but iumigatus ,40, Aspeus niger  as well s flavus . Constans flavus . A compaptomyces  and Umbiustulata .Sclerotinia sclerotium [Magnaporthe oryzae [A. fumigatus [Zymoseptoria tritici [BGCs are differently affected by evolution compared to the rest of the genome. They are located outside of so-called syntenic blocks, i.e., their position within the genome, and the BGC itself is less conserved than the rest of the genome ,47. In slerotium , Magnapoe oryzae ,51, A. fumigatus , and Zym tritici .de novo assembly of a BGC but also reductive genomic evolution which led to the “Black Queen Hypothesis” (BQH) [From an evolutionary perspective, the ability to quickly adapt to new environmental challenges is fundamental for the survival of an organism. In the case of fungi and other microbes, this means that they can adapt and change their metabolomic arsenal fast enough to properly compete against other microbes or environmental changes. This implies that the relevant genomic regions and hence the genes situated in these regions  experience regular mutations (single nucleotide polymorphisms (SNPs) such as missense, nonsense, frameshift, or gain/loss of function) and genomic rearrangements as for instance gene duplications, gene or BGC loss, BGC rearrangements, pseudogenization events and also the acquisition of genetic material via horizontal gene transfer . Organiss” (BQH) . The BQHFusarium fujikuroi [For the artificial activation of silent BGCs in a laboratory context, this means that some of the BGCs will carry deleterious mutations or even miss whole genes that would be necessary for the biosynthesis of the BGC product. In these cases, solely transcriptional activation will not suffice. Close examination of the BGC of interest can already unveil if genes carry a premature stop codon or if homologous BGCs indicate missing genes or frameshift mutations. A possible workaround in these scenarios is the exchange of single genes by their homologs or the genetic repair of a nonsense mutation as performed by Burkhardt et al. with the STC5 gene in ujikuroi .Verticillium dahliae it was found that BGC and pathogenicity-related genes are often located close to transposable elements [Aspergillus fumigatus isolates, horizontally transferred BGCs, BGC idiomorphs , and BGCs that are present in different genomic locations within the same or closely related species) are often flanked by TEs [A. oryzae and A flavus where two strain isolates had different BGCs in the same genomic locus [Botrytis species where the BOT BGC, involved in botrydial biosynthesis, was present at four different genomic locations across seven examined species [Sclerotinia, they found that the overall co-occurrence of BGC genes and TEs is not significantly enhanced. Upon closer examination, however, it became evident that a subset of BGC genes, which is enriched in key-enzyme encoding genes, is co-occurrent with TEs and that genes in this subset often derive from recent gene duplication events [Multiple genomic, inter-species, and environmental factors contribute to this elevated diversification and evolution of BGCs. The occurrence of mutations and genomic rearrangements depend on many exogenous  and endogenous factors . As stated above, BGCs and pathogenicity-related genes are often in polymorphic regions that are prone to such events . Transposable elements (TEs) play an important role during evolution and also in the de novo assembly of BGCs. In elements . In a cod by TEs . Similaric locus  or in th species ,58. Whenn events . BGC genA. nidulans to Podospora [Fusarium to Botrytis [Aspergillus fumigatus [F. graminearum which consists of a 12 gene BGC and a separated 2 gene BGC plus one single gene at three different genomic loci [De novo assembly is hypothesized to be a two-step process. The first step starts with the framework establishment of the new metabolic pathway . Often, odospora , or the Botrytis  and manyBotrytis ,64,65,66Botrytis ). In a sBotrytis  or that umigatus ) are formic loci .A. fumigatus [A. flavus and A. oryzae [S. sclerotiorum [V. dahlia [All in all, the genomic comparative studies from umigatus , A. flav. oryzae , S. sclerotiorum , V. dahl. dahlia , and als. dahlia  and Roka. dahlia  give verThe fact that this evolutionarily driven arms-race is not only apparent between closely related species but also between different ecotypes of the same species illustrates that BGCs are evolving at a fast pace. This highlights that the research pool of fungal genera and species must be expanded to increase the chance of finding novel natural products in the future. However, most of the current research is focused on mining BGCs in only a few but very well-described genera, the so-called model organisms.In this review, we highlight the concepts and technical possibilities on how to decrypt the secondary metabolome of a given (filamentous) fungus by efficiently deploying targeted and untargeted BGC-activation methods in synergy with genome mining. Special attention will be paid to more recent strategies involving the chromatin regulation of BGCs and the new possibilities currently emerging by the combination of CRISPR/Cas technology and transcriptional activators, global regulators, or chromatin-modifying enzymes.In silico-prediction of BGCs within the genome of the target fungus gives important information about the  chemical potential of a fungus. This is not only important for deciding if a species is a promising candidate for novel bioactive compounds but is also a prerequisite for linking those compounds to a specific cluster and also for targeted BGC activation. Bioinformatic analyses of high-quality genome sequences and transcriptome datasets are becoming cornerstones to explore the theoretical chemical diversity of SMs in a given species. Those resources are routinely used today for gene annotation [notation , BGC prenotation , clusternotation ,71,72, pnotation , drug tanotation ,75 and anotation . As outlThe majority of BGC prediction tools can be classified into either high-confidence/low-novelty (rule-based) or low-confidence/high-novelty (rule-independent) ,77. High-confidence/low novelty methods reliably detect BGCs that are closely related to already verified cluster types  by scanning the genome for their specific signatures . These signatures are retrieved from experimentally verified data that links the compound to the respective BGC, which are then implemented into the algorithm. The prediction tool antiSMASH [backbone enzyme-encoding genes which serve as anchor-point for further analysis of the region. In a second step, the cluster borders are determined by scanning the area around this anchor point for the presence of other BGC-related genes [ntiSMASH  is a vered genes ,79. Thislow-confidence/high-novelty (rule-independent methods) pursue the aim of detecting BGCs of a novel yet unknown type that does not follow currently known patterns . There are multiple strategies for finding new BGC types that use various experimental and -omics data for this purpose. In contrast to this, MIPS-CG, for example, utilizes an algorithm that does not rely on the use of backbone genes as BGC-anchor points as some BGCs were shown to lack these . Instead, to identify these non-canonical BGCs, MIPS-CG performs pairwise genome comparisons between different fungal species and removes syntenic blocks, because BGCs are often not located in such regions. Following the assumption that BGCs follow a basic common structure (similar gene functions) MIPS-CG scans for clustered genes that follow this pattern [ pattern . EvoMining algorithm uses a phylogenomic approach to detect BGCs. It is based on three evolutionary concepts. First, those new enzymatic functions evolve by retaining the reaction mechanism of the enzyme but changing substrate specificity. Second, the evolution of metabolic pathways can lead to the deployment of existing enzyme families that perform new functions  and third, that BGCs have their origin in central metabolism [The tabolism ,80.Clusterfinder algorithm which converts a genome into a string of Pfam domains . Subsequently, BGCs are annotated where stretches with a significant amount of BGC-related Pfam domains occur [AntiSMASH version 4 introduced the ns occur ,82. ARTS algorithm (Antibiotic Resistant Target Seeker), although currently supporting only bacterial genomes, is a tool for specifically finding BGCs that encode for an antibiotic. When bacteria produce an antibiotic substance, they can either detoxify and shuttle the compound out of the cell or express a resistant homolog of the gene that is targeted by the antibiotic. The resistance pathway is exploited by ARTS. The algorithm compares the genome to a reference genome and looks for duplicate housekeeping genes in the genome. These resistant homologs often are inside the same BGC. Furthermore, the cluster is often acquired by horizontal gene transfer (HGT). With the combination of BGC prediction via antiSMASH, gene duplicate screening and the comparison of the phylogeny of core gene trees of the organism and the cluster genes, ARTS can predict clusters that are highly likely to be responsible for the biosynthesis of an antibiotic [FRIGG pipeline pursues a similar approach but can be used for fungal genomes [The tibiotic ,84. The  genomes . Middas-M follows the hypothesis that BGCs can be found where an array of genes is coregulated. They combine transcriptomic data of several culture conditions with genomic data to predict BGCs [ict BGCs . This meAlgorithms use various curated but also non-curated data sources for their calculation of BGC genes. These data repositories can basically hold any kind of information about BGCs . Curated data sources contain fewer data entries, but the reliability and quality of these entries are often pristine, non-redundant, and experimentally backed which leads to more reliable predictions. Non-curated data sources basically hold all the information that is available . This means that the algorithm has to process and filter a lot of data of various quality and actuality . Depending on the popularity of the examined genus this also can lead to many redundancies that might contain flawed information. All in all, non-curated sources contain more, but less reliable data which can reduce the quality and reliability of the prediction.It should be mentioned that, as the experimental information about a novel BGC type increases, it will subsequently pass over from the rule-independent (high novelty/low confidence) to the rule-based (low novelty/ high confidence) prediction methods. This developmental process of prediction tools will undoubtedly lead to the discovery of yet unknown BGCs in already known and well-described species; however, it is strongly dependent on high-quality and accurate experimental data, provided by laboratories. The elucidation of novel BGC types and their genomic signatures, plus their proper deposit in data repositories  will significantly improve BGC predictions in the future. For more detailed information about genome mining and predictive tools, please consult the review of Blin and coworkers from 2019 .In the past decades, many strategies have been developed to shed light on this “dark matter” in fungal genomes and thereby unlock the chemical wealth residing within the fungal kingdom. In the pre-genomics era approaches predominantly sought to induce SM biosynthesis by mimicking environmental triggers. Genome sequencing and bioinformatic analyses for BGC predictions were developed later on and did not only reveal that filamentous fungi possess far more BGCs than anticipated, but also opened opportunities for a more targeted activation of single BGCs. We are now at a point where the combination of technological possibilities, abundance of available methods, and the already substantial amount of collected data makes it possible to expand the research to novel yet not well described fungal species. There is no “one for all”-approach that is superior to other strategies, but available methods should rather be used in a complementary and context-dependent manner.Fungal SMs serve different purposes during the life cycle of a fungal colony and accordingly, their production profiles somehow mirror these environmental or developmental conditions. Therefore, one of the approaches to trigger the production of new SMs is to impose challenging, sometimes stressful growth conditions on the fungal cells. Indeed, testing different cultivation conditions and imposing environmental stress has proven to be a very effective way of triggering the production of otherwise absent secondary metabolites. This approach was termed “One Strain-Many Compounds” (OSMAC) ,116 and A. terreus produces the pathogenesis-related SM terrain when fungal culture conditions mimic the environment of the plant or rhizosphere, which is associated with nitrogen starvation, iron shortage, and the presence of methionine [In some instances, it was shown that the fungus reacted as expected to the applied conditions. For example, UV light exposure can trigger the production of UV protectants , while othionine . global regulators. The purpose of global regulators is to coordinate the expression of an array of genes that ensure a resource-efficient response that is suited to the environmental circumstances [Environmental stimuli are generally processed via mstances ,121. Themstances ,123 whicmstances . The most thoroughly researched environmental signals that are connected to the production of fungal metabolites are nutrient availability and light regulation. nitrogen source also greatly impacts secondary metabolism, as shown for some well-established model organisms from the genus Fusarium [Aspergillus [F. fujikuroi, deletion of AREA and AREB led to differential regulation of many known but also yet cryptic BGCs [F. graminearum, AreA is required for the production of deoxynivalenol (DON), zearalenone, and fusarielin H [Acremonium chrysogenum where the deletion of areA led to the reduction of cephalosporin [Fusarium oxysporum where AreA is necessary for the synthesis of beauvericin and ferricrocin [The type and concentration of the available Fusarium ,126,127 ergillus . The majrielin H . Similarlosporin  and in Fricrocin .Light is also an important natural regulator of growth, development/conidiation and biosynthesis of natural products in fungi [laeA in A. nidulans, resulted in the abolishment of the production of sterigmatocystin, penicillin, and lovastatin while overexpression of laeA led to increased lovastatin and penicillin production [Valsa mali [Aspergillus ochraceus [Penicillium expansum [Chaetomium globosum [Fusarium verticillioides [and F. fujikuroi [in fungi ,135,136.in fungi ,140,141.oduction . Similarlsa mali , Aspergiexpansum , Chaetomglobosum , Fusariullioides  and F. fujikuroi . TherefopH value of the growth medium [temperature stress [osmotic stress, and salinity [metals and trace elements [carbon source can also be a critical parameter [oxidative stress [A. nidulans and other fungi [Other variables influencing SM levels are the h medium ,152,153,h medium ,155,156,e stress ,157,158,salinity ,161,162,elements ,165,166.arameter ,167,168 arameter . For oxie stress ,170,171 e stress  and Apyae stress ,174. Thee stress  or Nsd1 and there are targeted methods, that aim to activate only a specific BGC by manipulating regulatory elements of the BGC ). The advantage of targeted methods is that changes in the metabolome can be much more easily linked to the BGC under study. Applying molecular biology tools for genetic engineering enables the alteration of regulatory mechanisms at the genomic or epigenetic layer. This way, cryptic BGCs not transcribed under any tested laboratory condition can be activated in the native host by the manipulation of global regulators, pathway-specific regulators, chromatin modifiers, or by disruption of a repressive signaling pathway. Furthermore, if the fungus is not amenable to any approach that requires genetic transformation, the whole BGC may be transferred to and expressed in another organism . There are A. flavus [A. nidulans [F. fujikuroi [By overexpression of a pathway-specific TF, the whole cluster may be upregulated. This strategy was shown to be successful in increasing the production of aflatoxin in . flavus  and also. flavus , and aspnidulans  or trichujikuroi . FurtherAspergillus 50% to up to 70% of the BGCs contain a pathway-specific TF [Aspergillus niger, however, provided evidence that eight of 45 BGCs that contain a TF, show no co-expression between the BGC-synthetic genes and the TF, which indicates that they are not affiliated with the BGC and hence, overexpression would not lead to its activation [A. nidulans [A. nidulans, which is inactivated by the presence of glucose [A. nidulans. The modular composition of many TFs  made it possible to fuse the DNA-binding domain of the asperlin BGC-specific TF (AlnR) with the trans-activator domain of another TF (afoA). This way, the overexpression of this hybrid TF led to the discovery of the antibiotic (+)-asperlin [Bioinformatic analyses revealed that in the case of the genus cific TF ,241. Co-tivation . This hynidulans . This ap glucose  and acti glucose . Another glucose . A possiasperlin .serial promoter replacements of all BGC-specific genes can be conducted. This approach has been successful in the activation of several uncharacterized BGCs in A. nidulans, finally shown to be responsible for the expression of the Ivo gene cluster producing a new pigment [In the case of clusters that do not have a TF,  pigment , or for  pigment , and chi pigment . The ideEscherichia coli are often sufficient [Saccharomyces cerevisiae, Hansenula polymorpha or Pichia pastoris exist [In the case that none of the aforementioned methods worked out or the studied species is not amenable to transformation or does not yield stable transformants, heterologous expression in a model host can be a powerful tool for the activation of unknown BGCs. For this method, single protein domains or genes or a whole BGC are introduced into a well-known production host. For the expression of single domains or genes, bacterial hosts such as fficient ,273. Foris exist ,275.A. oryzae [A. nidulans [A. niger [F. grameniarum [Penicillium strains [If the expression scaffold of the donor organism  is however not suited for the host there are two other possibilities. The regulatory elements of a BGC can be exchanged by host-specific ones, or the BGC can be heterologously expressed in a host that is closely related to the donor organism . There a. oryzae , A. nidunidulans  A. nigerA. niger , but alsmeniarum ,280 and  strains ,282 are  strains ,284, HeX strains  or CoIN  strains  have beeA nidulans). This already led to the identification of 15 new metabolites from a library of 56 FACs each containing one unknown BGC from A. aculeatus, A. terreus or A. wentii in the heterologous expression host A. nidulans. It also resulted in the elucidation of the biosynthetic pathway of acu-dioxomorpholine from A. aculeatus [During the FAC-MS approach, the donors’ DNA is sheared and random chromosomal parts (up to 300 kb) which eventually contain a whole BGC are cloned into fungal artificial chromosomes (FACs). These FACs are then transformed into the host organism  of the sterigmatocystin cluster in combination with the niiA/niAD promoter. In this system, the TF-encoding genes aflR and its cofactor aflS are put under the control of the bi-directional promoter of the niiA/niaD genes coding for nitrate- and nitrite reductase, respectively, in A. nidulans. The genes of the BGC of interest are put under the control of the eight sterigmatocystin promoters that are regulated by AflR/AflS. This way, the orchestrated expression of up to eight genes of an unknown BGC without reusing a single promoter sequence can be accomplished by the growth of nitrate as the sole N-source leading to a high induction of the TFs.This approach uses the Hoefgen and coworkers utilized the 2A peptide of the picornavirus to enable the transcription and translation of a whole BGC with only one promoter and one terminator. The 2A peptide auto-cleaves itself after translation without leading to the disassembly of ribosomes. This way, several genes can be co-expressed with the use of only a single promoter. The cloning of the construct however can be difficult and laborious and the transcript levels of the genes will stay equal and cannot be individually regulated.Saccharomyces cerevisiae. New promoter sequences that are coregulated with pADH2  have been utilized to enable cloning via a high throughput DNA assembly strategy by homologous recombination into 2 µ vectors. Genome mining assisted the selection of novel BCGs and subsequent cloning into yeast plasmids with an upper limit of seven genes per plasmid (maximum of two plasmids per clone). Expression is followed by untargeted metabolomics and LC-MS and NMR for structural elucidation of putatively novel compounds. For proof of concept, 41 investigated BGCs (from ascomycete and basidiomycete species) resulted in the detection of 22 new compounds.With the Hex approach, it is possible to express whole fungal BGCs in an engineered strain of activating BGCs by locus-specific modification of histones. These new approaches would not only make it possible to activate BGCs where other methods failed but have the potential of giving many new insights into the histone code of gene regulation. The next sections concentrate on the regulation of BGC expression via chromatin and histone modifications and describe also the current state of locus-specific chromatin modifications for the activation of secondary metabolites. After that, we will review the role of a CRISPR/Cas as a carrier for targeted BGC activation via locus-specific chromatin modification.While previously mentioned methods have already led to the discovery of many bioactive substances of fungal origin, many BGCs may still resist discovery with these approaches. Therefore, another strategy would be the manipulation of epigenetic and chromatin-based regulation of BGCs. Until recently, this could only be accomplished by the manipulation of global chromatin remodelers, however, as the general knowledge of this level of regulation increases, engineering of programmable chromatin regulators becomes feasible. The emergence of CRISPR/Cas-based methods, moreover, opens up new opportunities for In eukaryotes, genomic DNA wraps around histone protein octamers (~146 bp DNA/nucleosome) to form nucleosome chains  ,299. EacThe DNA within heterochromatic regions is not freely accessible for transcriptional activation. Pioneering factors however are capable of binding to condensed chromatin and subsequently recruit TFs or chromatin remodelers. This way, heterochromatin can be reversed to a more open and accessible state which promotes the binding and interaction of TFs or other reader/writer/eraser proteins and subsequently can result in gene activation ,303. In H3K9me3 is established by the histone methyl-transferase KMT1  [A. nidulans homolog HepA) which is a reader protein for this mark [Neurospora crassa) is subsequently recruited for further silencing of the region [A. nidulans can activate its sterigmatocystin cluster that contains hallmarks of constitutive heterochromatin . Our lab showed that under inducing conditions in the wild type (nutrient starvation), H3K9me3 peaks are depleted from the ST BGC, and dissociation of HepA and increase of acetylation levels in the BGC occur, and these events are correlated with transcriptional activation of the cluster [Epichloe festucae where BGCs that are silent in axenic culture, had H3K9me3 marks, but during plant infection, the H3K9me3 marks were reduced and the BGCs were activated [F. fujikuroi does not have any detectable H3K9me3-enriched areas inside BGCs. In F. fujikuroi, these marks are generally in pericentric and centromeric regions and sometimes in transposon-rich regions with few or no annotated genes [Fusarium mangiferae, deletion of the clrD homolog FmKMT1 led to increased production of beauvericin biosynthesis while fusapyrone biosynthesis was nearly abolished [Methylation of H3K9 is a hallmark of constitutive heterochromatin. homolog)  and the his mark . In somee region . In the  cluster . A similctivated . In conted genes . In Fusabolished . These ebolished ,310,311.H3K27me3 [Aspergillus and Penicillium [Ustilago [F. graminearum [F. fujikuroi [KMT6 of the PRC2 led to de-repression of several BGCs. More interestingly, formerly H3K27me3 regions are acetylated in KMT6 knock-down strains as shown for the beauvericin BGC in F. fujikuroi [Verticillium dahliae where lack of Set7, the PRC2 methyl transferase, led to the induction of 839 genes of which 75% are within H3K27me3 domains in the wild type. Furthermore, many genes that are upregulated in planta are also located within these domains [N. crassa, H3K27me3 marks are distributed throughout the genome but especially in the sub-telomeric regions where it was shown that a short DNA telomere repeat 17) can trigger the establishment of large domains of H3K27me2/3 [N. crassa facultative heterochromatin covers around 7% of the genome containing 1000 silent genes [Magnaporthe oryzae, 50% of TEs and many plant infection-related genes, which are suppressed in axenic culture, are covered by H3K27me3 [The second pathway for heterochromatin formation is mediated by the polycomb repressive complex II and marked by the histone modification H3K27me3 ,312,313.H3K27me3 . Some geicillium , UstilagUstilago , and somUstilago  however ujikuroi  many BGCujikuroi . Similar domains . In the K27me2/3 . In N. cH3K27me3 .These examples show the versatile nature of gene regulation by H3K27me3 and H3K9me3 in different fungal genera which still needs more research that elucidates the mechanism and chronological order of the (de)-repression process.N. crassa [Accumulating evidence in mammals  and also. crassa ) suggest. crassa . If thisA. flavus [A. nidulans [Candida albicans in subtelomeric regions [A. nidulans [While heterochromatic regions suppress the transcription of underlying genes, euchromatin promotes gene expression. It is characterized by highly accessible DNA  and is often marked by histone acetylation and H3K4 trimethylation. Histone acetylation is regarded as an active mark and is established by histone acetyl transferases (HATs) . Usually. flavus , HosB annidulans ) while o regions , HdaA renidulans ). These nidulans . For refA. nidulans [F. graminearum [A. nidulans [F. fujikuroi [F. graminearum [cclA, sppA, setA). This was observed in many species such as A. nidulans  [A. fumigatus (gliotoxin) [F. fujikuroi  [F. graminearum  [A. nidulans  [F. fujikuroi (gibberellic acid) [F. graminearum  [kdmB) in A. nidulans by our laboratory. It led to a 20% increase of global H3K4me3 but 90% of all annotated genes that are connected to secondary metabolism were downregulated. Sterigmatocystin and orsellinic acid biosynthesis were reduced while products of the monodictyphenone pathway were increased  [kdmB deletion or overexpression. For example, one could assume that, due to the downregulation of the majority of secondary metabolism genes, the precursor pool may have been increased which may have led to a better turnover by the same amounts of enzymes from the mdp pathway, resulting in higher quantities of mpd-related metabolites [F. fujukuroi [F. graminearum [F. graminearum, we found that many SMs are regulated by Kdm5 in a demethylase-independent role  [H3K4me1/2/3 is probably one of the most discussed and controversial histone modifications in terms of gene transcription and activation. It is established by the COMPASS complex with Set1 as the catalytic subunit . H3K4me3nidulans ,355 or Kminearum . This wonidulans , F. fujiujikuroi  and F. gminearum  or the p F9775B) ,358, A. iotoxin) , F. fujiIK, FUS) , F. gramusarins) . But alsic acid)  and F. gvalenol)  was obse emodin) . Followiabolites . Similarujukuroi  and F. gTaken together, results that try to link H3K4me3 and active transcription often result in complex and sometimes contradictory results. The role of H3K4me3 as protection against silencing would explain why this mark often but not always is correlated with transcriptional activation. Further insight into the local role of H3K4 trimethylation would be important to evaluate its role in the induction and transcription of silent BGCs.A. nidulans, the H4K12 acetyltransferase EsaA is essential for viability and also involved in the up-regulation of three of four examined BGCs. EsaA overexpression led to depletion of the H4 nucleosome at investigated loci and increased expression levels of BGCs. In the case of the cryptic ORS cluster, increased acetylation and nucleosome depletion occurred, but the BGC was not activated. It was suggested by the authors that EsaA and H4K12 acetylation could be responsible for histone depletion at promoter regions so that other effectors such as TFs can access the locus and recruit the transcriptional machinery [In achinery .A. parasiticus where they detected an increase of overall H4 acetylation in the aflatoxin BGC promoters followed by aflR binding and transcription [Similar findings were published by Roze et al. in cription .F. fujikuroi it was seen that the overall correlation between genome-wide H3K9ac and transcription is weak but that in the case of BGCs the correlation is very strong, suggesting that H3K9ac has important roles in the production of SMs [F. fujikuroi also results in increased levels of H3K9ac in gene promoters and increased transcriptional activity. This even resulted in the activation of the bikaverin cluster under repressive conditions [H3K9 acetylation, which is the mark counteracting silencing by H3K9me3, is enriched in transcriptionally active promoters, sometimes enriched especially in BGCs. In n of SMs . In the n of SMs . Anothernditions .A. nidulans, and additionally H3K18 and H3K27 in F. graminearum [F. fujikuroi [A. nidulans  GcnE is necessary for activation. While H3K14 acetylation was not enriched within clusters, H3K9 acetylation was only applied in BGCs (only sterigmatocystin and ORS clusters were examined for H3K9ac). While genes outside the cluster showed no signs of differential expression, all BGCs that were expressed in the wild type showed abolished transcription in the gcnE deletion mutant [The most intensively studied HAT GcnE, which is part of the SAGA/Ada complex, was shown to be responsible for the acetylation of H3K9 and H3K14 in minearum  and H3K4ujikuroi . In the n mutant ,368. Then mutant .A. flavus, Beauveria bassiana and F. graminearum [A. flavus led to the removal of both H3K9 and H3K56 acetylation which resulted in impaired growth and virulence, vulnerability to DNA damage stress and also to the abolished expression of genes of the aflatoxin cluster, further promoting H3K9 acetylation as an important mark for gene transcription [Recently the fungal-specific HAT Rtt109, which is responsible for H3K9 and/ or H3K56 acetylation (DNA damage repair), was described in minearum . Deletiocription .Neurospora crassa, it was found that H3K27 acetylation is one of the most predictive histone marks of open chromatin [F. fujikuroi [M. oryzae [H3K27 acetylation is the counteracting mark of the silencing H3K27me3 modification. During chromatin accessibility studies in hromatin . As alreujikuroi  and M. o. oryzae  that H3KA. nidulans. H3K9/K14 acetylation is enriched in the promoter with the highest level at the first nucleosome after the translation start site. H3K4me3 is enriched at the first three nucleosomes downstream of the ATG and H3K36me3 spreads across the active gene body. While H3K4me3 and H3K9/K14Ac decreased towards the 3′ of the gene, H3K36me3 increased [V. dahliae [Candida albicans [Aspergillus parasiticus [Actively transcribed genes have a distinct chromatin signature around the promoter region, gene body, and terminator. We assessed the histone mark occupation around the start codon in all active genes of Chromosome IV of ncreased . Similar dahliae  and Candalbicans . Furtherasiticus . Noteworasiticus .The production of SMs is a metabolically costly process requiring high energy input to produce the necessary reduction equivalents (NADPH) and ATP. Therefore, their biosynthesis is strictly economized. To ensure that energy is not wasted, fungi by default silence their BGCs at the level of heterochromatin formation, making these genomic regions inaccessible to the transcriptional machinery ,315,348.A. niger [Aspergillus sp. [One particular successful and easy-to-apply strategy for artificial lifting heterochromatin based silencing was the application of chemical inhibitors for HDACs that are known to be essential for most heterochromatin formation complexes. HDAC inhibitors (HDACi) lead to higher acetylation of histones, a driver for gene expression. The most rewarding results following this strategy used SAHA, butyric acid, valproic acid, nicotinamide, and trichostatin as additives to the growth medium ,342. A sA. niger , or the llus sp.  or in thllus sp. . Table 6There are however downsides to strategies that interfere with globally active regulators. While approaches that mimic environmental conditions result in a native regulatory response of BGCs, the disruption of global regulatory mechanisms can lead to the synthesis of cryptic compounds that emerge due to uncoordinated regulation of genes or by bio-transformation of the inhibitors ,344,374.In recent years, however, CRISPR/Cas technology advanced to a point where new options for targeted local chromatin modifications are available and some have already been established in fungal species.CRISPR/Cas is a fast-advancing technology in molecular biology that is nowadays deployed in many prokaryotes and eukaryotes, illustrated by around 25,000 publications connected to “CRISPR” over the last 5 years. Its fast development in terms of genome editing but also in epigenome editing and as a tool for transcriptional activation makes it a very promising option for future application. Although CRISPR/Cas technology is widely used for gene manipulation, approaches for gene and BGC activation are just recently gaining attention in filamentous fungi. In the next section, we shortly introduce the principle of CRISPR/CAS technology and different classes and types that are available before moving to approaches that are applied in filamentous fungi and future perspectives of gene activation  applications.Streptococcus pyrogenes, SpCas9. CRISPR/Cas is the major component of the acquired bacterial or archaeal immune system [The best-known variant of CRIPSR/Cas systems is the RNA-guided nuclease Cas9 from e system . It is aThe native lifecycle of the CRISPR/Cas adaptive immunity consists of three stages. Adaption, expression, and interference . Upon inAfter the discovery of CRISPR/Cas, its potential instantly attracted the interest of the scientific community. Many research groups refined this strategy over the past years to one of the most versatile tools used in modern molecular biology that has now been established in many eukaryotic organisms, including filamentous fungi ,382. NewSpCas9 from Streptococcus pyrogenes or Cas12a  from Francisella novicida, Acidaminococcus sp. or Lachnospiraceae bacterium  are being deployed for molecular biology in fungi. They have important differences that make both of them viable options, depending on the application [Following Cas9, different variants of CRISPR-Cas systems have been found in nature as reviewed in detail by . They arlication .different gRNA processing. Cas9 needs the matured form of the tracrRNA and the crRNA which, in nature, anneal to produce a functional guide RNA that can then build a complex with the Cas9 protein. Genetic engineering-led, however, to the development of both crRNA and tracrRNA in one single guide RNA (sgRNA) which increased the handling comfort and efficiency [Easier handling and cloning with Cas12a due to ficiency . Neverthficiency  or tRNAsficiency  that flaficiency . Nødvig ficiency   and a 23–25 nt-long protospacer sequence (PS)  b. This gThe DNA cleavage pattern is different between Cas9 and Cas12a. While SpCas9 produces a blunt end cut 3 bps upstream of the NGG PAM [ NGG PAM , Cas12a  NGG PAM . In the  NGG PAM , while C NGG PAM .The PAM sequence of Cas9 is the short 3 nucleotide long G-rich motif NGG while Cas12a has a T-rich PAM  and nicking CRISPR/Cas tools. Cas9 proteins that can only nick the DNA  [Genetic engineering led to the development of , nCas9)  resulted, nCas9) . There a, nCas9) ,401. In The development of catalytically inactive Cas9 and later Cas12a variants  made CRISPR/Cas to a very powerful tool in molecular biology ,402. dCaAlthough SpCas9 is currently the prevalent choice for gene editing and other applications, the Cas12a system has many benefits for working with filamentous fungi. The biggest advantage with regard to BGC activation is the easy deployment of multiple gRNAs as compared to SpCas9. While Cas12a can process the raw pre-crRNA transcript directly, Cas9 needs more complex cloning strategies involving features that allow for a proper release of blunt end sgRNAs . Cas12a is, therefore, much easier to handle which not only makes experiments more time efficient but also more robust as the system requires fewer components.temperature maximum. Most filamentous fungi grow well around room temperature. SpCas9 has its catalytic maximum at 32 °C which can be challenging for some fungi. Cas12a, on the other hand, can be deployed at lower temperatures  which increases the efficiency in most fungal strains [The second advantage for work with filamentous fungi specifically is the  strains .One of the drawbacks of the CRISPR/Cas system is the requirement of the PAM motif at the target locus. The difference in PAM sequences in different variants increases the versatility and flexibility in this matter which can be very important for experiments that require specific loci, with limited PAM options, to be targeted.Various approaches that involve CRISPR/Cas technology have been already applied to different fungal species . EspeciaTo increase the editing efficiency by utilizing homologous DNA repair pathways, linear or circular double-stranded DNA with homologous regions or single-stranded DNA oligos with small homologous regions can be transformed together with the Cas construct. These then can get inserted at the Cas9 restriction site after cleavage which not only can increase the mutation rate but makes it also possible not only to mutate, but exchange the DNA sequence via homology-directed repair mechanisms c 389,40.A. nidulans [The transformation of the CRISPR/Cas machinery and the guide RNA(s) can be performed on a single  or multinidulans ,389, by nidulans  or withinidulans . We recenidulans ,409. Othnidulans .If the fungus is not amenable to stable or transient genomic transformations, mutation by CRISPR/Cas systems can also be achieved by transformation of the in vitro pre-assembled  ribonucleotide complex (RNP) ,411,412.Catalytically inactive Cas variants  have great potential to be used for the activation of silent BGCs. When fused to a trans-activator domain it can be deployed as a programmable TF for the activation of one or multiple genes . This CRISPRa method was established simultaneously in the filamentous fungi or dCas9  and dCasor dCas9  and shor. rubens . In ever. rubens  was chos. rubens . The hyb. rubens . Simultapromoter . This fapromoter . Furtherpromoter .Targeted locus-specific deposition of histone marks via fusion proteins of dCas and chromatin active domains is an emerging field in molecular biology. In human cancer cells, targeted modification of H3K9me3 and H3K27ac can be accomplished by deploying a fusion protein composed of dCas9 and the H3K9 methyl-transferase KRAB  or the histone acetyl transferase p300, respectively. In both cases, the targeting of the fusion proteins to DNA accessible sites  led to the respective modification at the locus . In the case of H3K9me3, it was even shown that the DNA is inaccessible after the histone mark H3K9me3 is deployed ,418.A. niger, although the actual effect on chromatin status  has not been assessed [FUM1 and managed to activate the fumonisin cluster in A. niger. Furthermore, they fused endogenous proteins such as GcnE, the acetyltransferase of the SAGA complex, histone deacetylases HosA and RpdA, and the H3K9 demethylase Lde to dCas9 separately and tested its effect on the SM gene breF. While the fusion of the catalytic core of human p300 fused to dCas9 led to an activation of the target gene as expected, fusion proteins of dCas9 and GcnE, RpdA and HosA resulted in repression of the gene while no difference was seen with the dCas9-Lde fusion protein. While most of the results are as expected, the repression effect by dCas9-GcnE is interesting. Although the authors state that the repression of breF by dCas9-GcnE is expected as GcnE was shown to be a negative regulator of 12 PKSs in A. niger, the result is surprising to us. Upregulation of BGCs due to the deletion of a broad domain regulator-encoding gene such as gcnE could be due to many indirect effects, for instance if GcnE was the activator of a repressor of these BGCs. Targeting the acetyltransferase to a specific genomic location, however, should lead to higher levels of acetylation only at the specific location and, therefore, to upregulation of only the targeted gene.In fungi, gene activation and repression by targeting chromatin active domains via CRISPR/Cas to target loci were accomplished in assessed . Li et afwnA was observed. Again, this is theoretically consistent with literature where fwnA expression decreased in hosA deletion strains. Such as with GcnE however, comparing a local effect  with a genome-wide effect  does not take indirect regulatory effects into account. Unfortunately, histone modifications of the targeted loci were not analyzed, so it is not clear if really a change in histone modifications is responsible for the observations. Furthermore, there could also be the possibility of host-mediated recruitment of the endogenous fusion protein  which could interfere with the experimental setup. Using only the catalytic domain (of homologs) would be a way of circumventing this.In the case of the dCas9-HosA, activation of the pigmentation gene Histone phosphorylation is another mechanism for gene induction that is prevalent in stress response gene promoters. A fusion of dCas9 and a hyperactive variant of the human histone kinase MSK1  could be targeted to promoters for gene activation by phosphorylation of H3S28 and H3S10 . Here, sIn summary, the targeted deployment of histone modifications as a regulator of transcription is an emerging field in fungal research but experimental data is currently scarce. More research is needed to fully assess this strategy for the activation of silent BGCs. If successful, CRISPR/Cas-based targeted deployment of chromatin active domains will not only result in the discovery of many natural products but will also provide a lot of information about transcription and the local chromatin context.Next, we want to summarize insights regarding the deployment of CRISPR/Cas methods. This is aimed at helping with the experimental planning. It will focus on the two main CAS systems that have been used for fungal research, Cas9, and Cas12a.Cas and dCas approaches have different prerequisites in regard to the target site, residence time and off-targets. When using CRISPR/Cas for gene-editing purposes, the successful outcome depends on a one-time event (the cleavage of DNA). In the case of CRISRRa or CRISPRi however the effect is determined by a continuous interaction of the fusion complex with the proteome or DNA at the target locus [et locus ,421. ConOff-target annealing also has different consequences depending on the application. Cas proteins can anneal to off-target sites but as long as the sgRNA does not match appropriately, no cut will occur. In the case of dCas approaches, however, this could theoretically lead to off-target effects mediated by the active domain that is fused to the dCas protein.tools that design gRNAs for different (d)Cas systems based on one or several of the following features: sequence composition, chromatin accessibility, gene expression, nucleotide position, RNA secondary structure, melting temperature, free energy, off-target possibility, and more [There are several and more . Some ofand more . Most ofand more  feature and more . Guide RCRISPRa approaches, the location of deployment within the promoter (in plants) was shown to have a distinctly different effect on the activation of the target gene even if the sgRNAs were only as little as 50 base-pairs apart from each other [In the case of ch other . For morch other ,427.Cas efficiency depends on multiple factors including Cas-sgRNA complex formation and concentration, target site accessibility, residence time, and codon optimization. By codon optimization alone, Cas efficiency could be increased from 35 to 70% [5 to 70% .Cas stabilizes the sgRNA, but the complex formation can be hindered by other RNAs and some divalent ions. To be functional, the Cas protein and the sgRNA/crRNA have to form a complex. Unbound sgRNAs get degraded very quickly. Upon complex formation, the Cas9 protein stabilizes the sgRNA, undergoes conformational changes, and is released from the inactive apo-state ,430. Ranapo-state Cas9 can bind DNA in a non-specific manner while the protein remains catalytically inactive, so no unguided “rogue”-activity is happening under normal conditions [2+ or Co2+Mn ions can lead to unspecific DNA cleavage even without bound crRNA (Cas12a) or sgRNA (Cas9), respectively, which makes media composition potentially also an important brick in the wall of CRISPR/Cas applications [2+-dependent but it was shown that in the case of LbCas12a and FnCas12a, affinity to the crRNA is dependent on 2+Mg ions which were found to be coordinated in the RNP complex [divalent ions can have a significant impact on Cas activity and specificity which should be kept in mind when deciding on culture conditions.It also is important to note that in the nditions . It was,ications . Process complex ,436. It residence time of Cas at its target locus are the proper pairing with the PAM, the subsequent annealing to the seed region, the local proteome and its fluctuations , and the concentration of Cas-sgRNA complex [The determinants of the  complex . The imp complex ,437. The complex .The proteome of the target site can prevent binding of Cas-sgRNA complex or even dislodge bound Cas. In vitro experiments confirmed that cleavage by Cas9 is nearly abolished when targeted to DNA occupied by nucleosomes. At the edges of nucleosomes or within linker regions, however, cleavage was largely unaffected. Interestingly, the position of the PAM was the essential determinant of cleavage efficiency when sequences close to the border of a nucleosome were targeted. This was verified in vitro by designing two nearly perfectly overlapping sgRNAs (shifted by four nts) but with opposite orientations. The sgRNA that had the PAM located proximal to the nucleosome showed drastically reduced cleavage efficiency compared to the sgRNA that had the PAM located distal [d distal . This obd distal ,439,440.d distal .Streptococcus pyogenes), which is known to remain bound to both DNA ends after cleavage [Staphylococcus aureus) [Acidaminococcus sp.) [The obstruction of CRISPR/Cas by proteins is not limited to nucleosomes. In the case of SpCas9   and AsCacus sp.)  it was spost-PAM interactions were found to be important for stable interactions between the Cas protein and the DNA. SpCas9 was not able to remain in a place of the target site when the DNA sequence 14 base pairs downstream was occupied by another protein. It was observed that this post-PAM interaction is weak in force but very crucial for Cas9 binding and cleavage [Apart from the sgRNA annealing site itself, cleavage . Displaccleavage . SaCas9,cleavage . Zhang acleavage .Methylated DNA could be cleaved without problems by Cas9 [ by Cas9  and also by Cas9 .The examples from above show that the proteome of the target site can have a profound impact on the binding and residence time and therefore cleavage efficiency of CRISPR/Cas. Structures that statically occupy and block the DNA such as nucleosomes should be avoided when choosing a target site for CRISPR/Cas applications.Off-target annealing has different consequences, depending on the application . Cleavage at off-target locations depends on PAM sequence and guide-RNA homology. Two major concerns about the deployment of CRISPR/Cas systems are the possibility of off-target effects  and the restriction that CRISPR/Cas systems need a specific PAM sequence for annealing. An interesting finding in case of off-target activity of Cas9 was, that the RNP complex could bind to many off-targets, even with a seed sequence complementarity of only five nts  cleavage pattern of a specific Cas-sgRNA complex in vivo, the GUIDE-SEQ approach can be applied which performs an unbiased detection of CRISPR/Cas-mediated double-strand breaks (DSBs) by in vivo integration of an oligo at sites that have DSBs  and subsequent amplification and next-generation sequencing [The  PAMless  or PAM-f PAMless ,453,454  PAMless  variantsquencing .The information above should illustrate the many application forms and variants of CRISPR/Cas systems. There is not a one for all experimental strategy because the prerequisites of the experimental question determine not only the variant of CRISPR/Cas to be deployed but also the target genetic features  and their connected properties  that have to be considered during gRNA design. In fungal organisms, mutational CRISPR approaches are already widely implemented. In the case of CRISPRa or targeted chromatin remodeling, however, this technology is still in its infancy but harbors great potential of the activation of BGCs and the discovery of new bioactive metabolites in the future.Genome mining is a core component in the revelation of unknown BGCs in fungal genomes. The data sources that are used for predictions are very diverse across the platforms and include not only DNA or protein sequences but also transcript data, phylogenetic data, and more. Deploying more and more predictive parameters that are connected to BGCs and their regulation will surely promote the discovery of new BGCs in the future. Increasing insights into novel BGC types  will also lead to a transition from “high novelty/low reliability” to “low novelty/high reliability” BGC prediction algorithms which, in turn, again increases their discovery rate. Approaches for the detection of novel BGC types are very diverse and will surely enable us to discover new and currently unknown BGC types in heavily researched model organisms.The development of these tools, however, is similar to a feedback loop between prediction and experimental verification. Predictions of known BGCs largely depend on the detection of patterns from already verified BGC types and so, the provision of high-quality experimental verification data of BGCs is a crucial component of reliable predictions. Curated databases fulfill these requirements but need the regular attention of professionals in the field. The guided deposition of such data by the research group itself into curated databases will hopefully become a standard procedure within the publication process in the future. This would increase the reliability of predictions and also accelerate the discovery process of BGCs in fungal genomes and, hence, the development of novel pharmaceutics.CRISPR/Cas technology is emerging as a new tool and already has proven to deliver new molecules by the activation of silent BGCs in a number of organisms. Its functionality as a transcriptional activator was already experimentally shown in fungi by fusing the trans-activator VPR to dCas9 and dCas12a. Heterochromatic regions, however, could get problematic because of target site accessibility and the sole deployment of trans-activator domains.N. crassa), also deployed by GcnE, within the promoter region correlate best with gene activation across several fungal species. As there are often nucleosome-free regions in promoters, even within heterochromatin, nucleosome positioning maps assist with the choice of a proper entry point of dCas-fusion proteins. Depending on the target locus and the prevalent histone marks, additional activators  could be necessary to induce target genes. H3S28ph also seems a promising way of activating single genes but more research, especially in the fungal context is needed in this regard. Furthermore, if DNA motifs are also proven to be responsible for occurring histone marks in fungi, this would be an additional opportunity to relieve whole BGCs from heterochromatin. This way, the programmable histone modifier can be used in combination with these mutants to activate silent BGCs and reveal their biosynthetic product.The targeted local histone modifications could represent the next step in the toolbox for the activation of silent BGCs. If it is possible to relieve heterochromatic regions of silent marks , the targeted and locus-specific transition to transcriptionally active euchromatin could be within reach. The choice of the right histone-modification domain, however, is still a topic that needs thorough research. Many observations that connect transcriptional activation and histone modification indicate that H3K9 acetylation , deployed by Rtt109 and GcnE, and H3K27 acetylation (hallmark for open chromatin and de-repression in