Unlocking the spatial control of secondary metabolism uncovers

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Unlocking the spatial control of secondary metabolism uncovers hidden natural product diversity in Nostoc punctiforme Daniel Dehm, Julia Krumbholz, Martin Baunach, Vincent Wiebach, Katrin Hinrichs, Arthur Guljamow, Takeshi Tabuchi, Holger Jenke-Kodama, Roderich D. Süssmuth, and Elke Dittmann ACS Chem. Biol., Just Accepted Manuscript • DOI: 10.1021/acschembio.9b00240 • Publication Date (Web): 15 May 2019 Downloaded from http://pubs.acs.org on May 16, 2019

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ACS Chemical Biology

Unlocking the spatial control of secondary metabolism uncovers hidden natural product diversity in Nostoc punctiforme

Daniel Dehm1, Julia Krumbholz1, Martin Baunach1, Vincent Wiebach2, Katrin Hinrichs1, Arthur Guljamow1, Takeshi Tabuchi3, Holger Jenke-Kodama3, Roderich D. Süssmuth2, Elke Dittmann1*

1University

of Potsdam, Institute for Biochemistry and Biology, Karl-Liebknecht-Str. 24/25, 14476 Potsdam-Golm, Germany 2 Fakultät II - Institut für Chemie, Technische Universität Berlin, Straße des 17. Juni 124, 10623

Berlin, Germany. 3 Microbiology and Biochemistry of Secondary Metabolites Unit. Okinawa Institute of Science and Technology, Tancha 1919-1, Onna-son, 904-0495 Okinawa, Japan Keywords: cyanobacteria, natural products, single-cell analysis, genomic mining *corresponding author: Prof. Dr. Elke Dittmann University of Potsdam Institute of Biochemistry and Biology Department of Microbiology Karl-Liebknecht-Str. 24/25 14476 Potsdam-Golm Germany Email: [email protected] Tel.: 49-331-9775120

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Abstract

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biologically active natural products, yet the majority of biosynthetic gene clusters predicted for

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these multicellular collectives are currently orphan. Here, we present a systems analysis of

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secondary metabolite gene expression in the model strain Nostoc punctiforme PCC73102 using

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RNAseq and fluorescence reporter analysis. Our data demonstrate that the majority of the

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cryptic gene clusters are not silent but expressed with regular or sporadic pattern. Cultivation

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of N. punctiforme using high-density fermentation overrules the spatial control and leads to a

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pronounced upregulation of more than 50% of biosynthetic gene clusters. Our data suggest that

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a combination of autocrine factors, a high CO2 level and high light account for the upregulation

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of individual pathways. Our overarching study does not only shed light on the strategies of

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filamentous cyanobacteria to share the enormous metabolic burden connected with the

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production of specialized molecules but provides an avenue for the genome-based discovery of

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natural products in multicellular cyanobacteria as exemplified by the discovery of highly

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unusual variants of the tricyclic peptide microviridin.

Filamentous cyanobacteria belong to the most prolific producers of structurally unique and


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Filamentous cyanobacteria of the genus Nostoc are widespread in terrestrial ecosystems and

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play important roles in soil fertility and soil crust formation1. Their ability to fix atmospheric

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nitrogen makes them attractive for a variety of symbiotic partners including mosses, lichen, and

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cycads 2, 3. The complex lifestyle of the facultative symbionts involves the differentiation of at

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least four distinct cell and filament types: vegetative cells, nitrogen fixing heterocysts, motile

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hormogonia and spore-like akinets4, 5. The versatility of symbiotic Nostoc strains is reflected

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by their large genome sizes ranging from 7 to 10 Mbp 6,7 and the high density of natural product

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biosynthetic gene clusters (BGCs) of the nonribosomal peptide synthetase (NRPS), polyketide

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synthase (PKS) and ribosomal peptide (RiPP) types potentially encoding unique specialized

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molecules 8. While a number of structurally complex and biologically active natural products

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of terrestrial Nostoc strains have been uncovered in the past 9,10,11,12,13 the majority of BGCs is

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orphan, suggesting that the potential to produce specialized molecules is far greater than

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anticipated before the genome era.

30 31

The basis of any genome-based technology is the bioinformatic analysis utilizing computational

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platforms such as AntiSMASH 5.014, yet further exploitation of the predicted specialized

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molecules does not follow a standardized procedure 15, 16. The most challenging problem of the

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genome-based drug discovery is the poor expression of many of the natural product BGCs

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under standard laboratory conditions15. Although there is a common anticipation that the

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expression of natural product BGCs in microorganisms either directly or indirectly depends on

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environmental cues or physical interactions with organisms from the same habitat, approaches

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to wake up silent BGCs are manifold and show different success rates depending on the group

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of organisms investigated. Technologies include the variation of growth conditions, co-

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cultivation with other organisms, manipulation of either global or pathway-specific regulators

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and epigenetic perturbation 15. Most studies aiming to develop concepts for genomic mining of


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natural products were performed with heterotrophic bacteria and fungi, whereas systematic

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studies on cyanobacteria are currently missing 15, 16.

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N. punctiforme PCC73102 is a model strain capable of facultatively entering symbiosis with

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diverse plant and fungal hosts2, 3. The accessibility to genetic manipulation makes it a suitable

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organism for the design of advanced genome mining techniques. Moreover, the ecological

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context of the organism is already relatively well explored, thus providing a framework for the

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rational design of function-driven concepts for natural product discovery3, 4. A number of

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studies point towards a connection between specialized molecules and cellular differentiation

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of cyanobacteria. The nonribosomal peptide nostopeptolide was shown to act as a repressor or

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activator of hormogonia formation depending on its extracellular concentration in

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N. punctiforme17, while the regulation of heterocyst spacing within cyanobacterial filaments

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largely depends on the PatS morphogen, a small peptide undergoing a maturation process

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decisive for heterocyst development18. These studies collectively suggest that manifold

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autocrine signals control the outstanding life cycle of Nostoc. Furthermore, there is rising

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evidence for a cross-talk and interdependency of different signal classes 8, 19.

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In the present study we selected N. punctiforme PCC73102 with the aim to establish a model

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for the systems analysis of small-molecule natural products and their regulation in filamentous

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cyanobacteria. Both RNAseq analysis and transcriptional reporter strains were utilized to study

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gene expression of natural product BGCs. The latter analysis does not only provide insights

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into the quantity of BGC expression but also their spatial and life cycle specific expression. The

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study highlights the power of a reporter-guided approach to study natural product expression in

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bacteria featuring complex life cycles and provides guidelines for the genome mining of natural

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products in other filamentous cyanobacteria that are not accessible by genetic manipulation.

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Results and Discussion

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BGC expression throughout the life cycle of N. punctiforme

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Genome-based approaches for natural product discovery in cyanobacteria were so far mostly

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focussing on individual biosynthetic pathways

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classes were described by characterizing their biosynthetic pathways in vitro or by heterologous

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expression in E. coli rather than the analytics of the actual compounds in native cyanobacteria

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22,23.

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hampered by the limited accessibility of those strains harbouring large diversities of BGCs to

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genetic manipulation. We thus designed a study to gain insights into the global regulation of

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the secondary metabolism in the genetically accessible model cyanobacterium N. punctiforme.

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Whereas 16 natural product BGCs of the NRPS, PKS and RiPP types are predicted for strain

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N. punctiforme PCC73102 by the AntiSMASH 5.0 bioinformatic platform only two could be

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assigned to a product so far: nostopeptolide and anabaenopeptin, i.e. 14 of the predicted clusters

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are currently orphan

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specialized molecules and cellular differentiation of N. punctiforme, we designed a global

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transcriptomic analysis aimed to study the expression of BGCs in different stages of the life

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cycle. For that purpose, N. punctiforme was grown on filters to medium cell density and

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transferred onto fresh agar plates under diazotrophic conditions. The medium exchange

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typically triggers a new round of cellular differentiation starting with formation of motile

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filaments followed by re-differentiation of vegetative filaments with intercalary heterocysts8.

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Replicates of these filters were grown for one, three, five, seven and nine days where Nostoc

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finally reached high cell densities on the filters (Fig. S1). The nostopeptolide BGC was used as

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positive control to set a threshold above which expression of a BGC can be expected to yield a

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product (Fig. 1). The nostopeptolide BGC did not show major variations in the course of the

20,21.

In a number of cases, new compound

A systematic study on BGC expression and the underlying regulatory network is largely

19.

As several recent studies point to a connection between small


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experiments with values ranging from 15 to 25 transcripts per million (TPM). A virtually

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constitutive expression of nostopeptolide during the life cycle was already revealed in a recent

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study17. Accordingly, we set the base line for BGCs reliably expressed under laboratory

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conditions to 20 TPM. This empirical threshold is similar to the value recently determined for

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natural product BGCs of Salinispora strains based on inter-strain comparison of BGC gene

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expression24. From the fourteen BGCs further analyzed during this study only two, namely the

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pks3 gene cluster and a cryptic microviridin type RiPP gene cluster (mvd) exceeded expression

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levels of the nostopeptolide BGC. The lacking assignment of a product to these gene clusters

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is thus likely due to an analytical detection problem (Fig. 1 and 2). As we have recently designed

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a transcriptional reporter strain for the nostopeptolide BGC, the expression of the

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nostopeptolide BGC was also visualized using fluorescence microscopy. As described

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previously, the nostopeptolide BGC was consistently expressed in all vegetative cells in

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different stages of growth. As information on cell-type specific expression cannot be extracted

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from transcriptomic datasets, reporter strains were also constructed for 14 of the remaining

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BGCs including all NRPS and PKS gene clusters and five selected RiPP BGCs to complement

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the RNA sequencing study. Borders of the gene clusters and the putative 5`-UTRs of the

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transcripts were predicted based on bioinformatic analysis of BGCs and analysis of the

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transcriptional dataset (Dataset S1). For RiPP gene clusters, the 5`-UTR of the first precursor

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peptide gene was selected. The analysis of the pks3 reporter strain revealed a bright cyan

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fluorescent protein (CFP) signal suggesting a strong constitutive expression in all vegetative

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cells. The reporter strain thus confirmed the high expression levels already observed in the RNA

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sequencing study. Based on both types of analysis the nostopeptolide BGC and the pks3 BGC

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were both categorized as “Constitutively ON” (Fig. 1). On the opposite side, only two of the

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BGCs were considered as completely silent based on the analysis of BGC transcription and

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transcriptional reporter strains, namely the pks1 and pks2 gene clusters that showed

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transcriptional level around or below 1 TPM in the RNA sequencing study, and the absence of ACS Paragon Plus Environment

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specific CFP fluorescence under standard growth conditions. Notably, the pks1 gene clusters

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showed a strong increase in transcription at day nine of the time course experiment thus

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suggesting that expression of this cluster might be cell cycle or cell density-dependent (Fig.1).

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A majority of natural product BGCs is transcribed in a spatial pattern

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the reporter-based analysis while not exceeding the base line limit of transcription for most of

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the time points during the RNA sequencing study. This group of BGCs includes the

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anabaenopeptin BGC that was assigned to a product recently19, 25. Remarkably, for all these

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BGCs transcription was not evenly distributed among all cells but showed different types of a

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spatial pattern. While for the anabaenopeptin BGC and the pks4 gene cluster transcription was

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predominantly observed in single cells or two neighbouring cells (Fig. 2A and C), other BGCs

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were active in short stretches of cells such as the nrps2, ripp1a, ripp1b and ripp4 gene clusters.

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The pks5 and ripp3 gene clusters were actively transcribed in parts of the filaments, thereby

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almost reaching the constitutive expression level observed for the nostopeptolide and pks3

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BGCs. While the majority of the BGCs expressed with spatial restriction showed rather a

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sporadic pattern, the pks4 gene cluster showed a regularly spaced pattern within filaments (Fig.

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2C). For the majority of the BGC reporters, transcription was primarily observed in vegetative

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cells or in the pre-akinete stage, as recently described for anabaenopeptin, yet the pks5

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transcriptional reporter also showed a CFP signal in hormogonial cells and the nrps1 gene

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cluster was also observed in spore-like akinetes (Fig. S2). For none of the transcriptional

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reporters, CFP signals were observed in nitrogen-fixing heterocysts (Fig. S2). Transcript levels

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measured in the RNA sequencing study ranged from 1-2 TPM for nrps1 and ripp1b to 20 TPM,

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thereby confirming that this category of BGC is not silent but also does not reach overall

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transcriptional level of the constitutive BGC category. Notably, restricted expression in short

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stretches of cells was also revealed for the cryptic mvd gene cluster, despite of its rather high

Eight of the 16 natural product BGCs analyzed in more detail showed active transcription in


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expression level of around 60 TPM. The mvd gene cluster was thus assigned to the category of

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BGCs with spatial pattern that was designated as “ON with spatial restriction” (Fig. 2). The

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lack of assignment of a product to the majority of these BGCs is likely due to the rather low

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amount of product produced by only part of the cells. Our global transcriptomic study on N.

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punctiforme thus exemplifies that the majority of natural product BGCs in filamentous

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cyanobacteria is not silent but restricted to a marginal number of cells which express the

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individual BGCs at a rather high level. These expression patterns suggest that filamentous

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cyanobacteria either utilize their multicellularity for the division of labour or that the patterns

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reflect a metabolic incompatibility of individual molecules under conventional growth

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conditions. Although it is difficult to estimate the fitness costs connected with the production

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of complex secondary metabolites the observed specialization of cells for the production of

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different compounds ultimately leads to a reduction of the overall costs at the community level,

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whilst still maintaining a minimum level production of chemically diverse types of compounds

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under most circumstances. The low levels of compounds may enable a more rapid adaptation

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to changing biotic or abiotic conditions than switching metabolite production completely on

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and off, or at least ensure a minimum chance of survival for a part of the clonal community.

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One can therefore consider secondary metabolite production in filamentous Nostoc strains as a

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type of phenotypic plasticity.

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Multicellularity is a common feature among many prolific producers of specialized molecules

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including streptomycetes, myxobacteria, filamentous fungi and biofilm-forming bacilli. As for

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filamentous cyanobacteria, a large part of natural product BGCs is considered as silent under

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standard growth conditions in these microbial phyla and pathway-specific and global regulators

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tightly control production of the complex compounds

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transcription is analyzed by quantifying the amount of a given transcript in total mRNA were

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spatial patterns are neglected. Moreover, discrete levels of transcription for which the silence

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of BGCs is anticipated are arbitrary 24. One may therefore speculate that not all BGCs that are

26,27.


In most of the studies, however,

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currently considered as silent in these multicellular collectives are effectively silent. Moreover,

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there are already a few examples in the literature demonstrating a spatial regulation of

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individual compounds. In the fungus Aspergillus terreus, for instance, cell-type specific

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expression has been revealed for two NRPS-derived compounds, aspulvinones and melanin 28.

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Division of labour with regard to BGC gene expression has also been demonstrated for the

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NRPS product surfactin within multicellular biofilms of B. subtilis. Here, division of labour

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does not only facilitate a decrease in the overall metabolic burden of the community but also

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enables synergistic interactions of different cell types controlling flagellum-independent

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migration 29.

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Ultra-high-density induction of BGCs and role of autocrine signals, light and CO2

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We have recently demonstrated that cultivation of N. punctiforme with high concentrations of

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bicarbonate, enabled growth towards ultra-high densities19. We now utilized the BGC reporter

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library to systematically analyse the impact of HD cultivation on spatial BGC expression. Out

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of the 14 BGCs investigated eight showed a pronounced upregulation compared to conventional

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cultivation (Fig. 3). Most of the BGCs reached a maximum fluorescence after 20 days of HD

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cultivation. Upregulated BGCs included the two previously silent PKS gene clusters pks1 and

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pks2, the hybrid NRPS/PKS gene cluster pks4, four RiPP gene clusters including the cryptic

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mvd BGC and the anabaenopeptin NRPS. All other BGCs showed either a similar expression

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level or were slightly upregulated compared to the conventional cultivation. While the majority

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of upregulated BGCs were still only expressed in part of the cells or filaments the ripp1a gene

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cluster showed very bright fluorescence in all vegetative cells after HD cultivation. To assess

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the impact of autocrine signals accumulating in HD culture, aliquots of the conventional culture

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were treated with HD supernatant for seven days. In three of the cultures, addition of HD

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supernatant led to a significant upregulation, namely the pks1, pks2 and ripp1b gene clusters, ACS Paragon Plus Environment

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whereas other reporter strains showed a weak response (pks4) or no response at all. Since major

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differences in HD cultivation include the intrinsic high CO2 level and high light conditions

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aliquots of the HD responsive reporter cultures were also treated for up to seven days with

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dialysis bags containing mixtures of KHCO3 and K2CO3 as described previously30 or were

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exposed to high light conditions of 107 µmol photons m-2s-1. The ripp4 BGC showed a

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pronounced response to the higher CO2 levels after three days and the pks2, mvd and ripp1a

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gene clusters responded to 24 h high light treatment (Fig. 3). We postulate that high-density

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cultivation overrules the feedback control that is triggered by the individual compounds itself.

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The addition of HD supernatant or artificially high concentrations of CO2 or high light

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conditions can elicit a similar transcriptional response, albeit not to the same extent as in HD

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cultivation and not for all BGCs. One may therefore speculate that a combination of

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(hierarchical) signals, CO2 and high light accounts for the observed induction in HD cultivation.

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Discovery of novel microviridins

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Large-scale fermentation using the HDC1.1500 platform of the CellDeg company further

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enhanced metabolite production (Fig. 4A). Besides a strongly increased production of the

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known depsipeptides nostopeptolide 1052 (1) and nostopeptolide A (2) as well as the cyclic

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peptides nostamide A (3) and anabaenopeptin NZ857 (4) a multitude of uncharacterized peaks

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appeared in the HPLC chromatograms of the HD culture. In order to expand the knowledge of

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the bacteria’s secondary metabolome we decided to search for novel compounds. During the

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analysis of the culture supernatant by means of various mass spectrometric techniques we found

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a cluster of prominent molecular masses, that seemed to represent a novel compound family

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(Fig. 4B). Since the high mass range (1700-2287 Da) characterized the compounds as potential

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RiPPs, the mass differences of the individual mass peaks were analyzed with regard to potential,

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posttranslational peptide modifications and/or variations in the peptide chain length. Thereby,

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we realized that the mass difference between each peak and its respective neighbouring peak ACS Paragon Plus Environment

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commonly corresponded to one proteinogenic amino acid (Fig. 4B). To unravel the identity of

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the compound family, we compared the derived short amino acid sequences (ETGETA or

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ATEGTE) with the predicted core peptides of all RiPP precursors encoded in BGCs that

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showed a pronounced upregulation in response to HD cultivation. However, none of the

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putative core peptides matched with the sequences. Only upon including the leader peptides a

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hit was received. To our great surprise the sequence ATEGTE was part of the predicted leader

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sequence of the microviridin precursor peptide, right at the N-terminus of the predicted core

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sequence. Microviridins are a family of potent protease inhibitors that have been extensively

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investigated in our group 31. All natural microviridin congeners reported to date are 13- or 14-

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membered N-acetylated depsipeptides that feature a tricyclic structure composed of non-

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canonical macrolactone and macrolactam rings. Intriguingly, adding ATEGTE or its shortened

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sequence variants to the N-terminus of the core peptide would result in a group of highly

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unusual 15- to 20-membered microviridins. In accordance with this theory the individual

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molecular masses fit to the various elongated core peptides, if one considers the

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posttranslational formation of two intramolecular macrolactone rings and one macrolactam

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ring, which are a hallmark of microviridins. To gain further evidence we analyzed the

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compounds by means of tandem mass spectrometry, a method which has been frequently used

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for the characterization of microviridins and microviridin-like compounds 32. Finally, MALDI-

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TOF/TOF analysis together with chemical transformation unequivocally confirmed the

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compounds to be novel microviridins that share the typical tricyclic cage-like architecture but

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in the case of compounds 5-10 feature an unprecedented N-terminal extension instead of an

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acetylation (Fig. S4-S10). The missing acetylation is in accordance with the mvd gene cluster,

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which does not encode an acetyltransferase (Fig. 4). The new compounds have been named

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microviridin N3-N9 to emphasize the different number of N-terminal amino acids, which range

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from 3 to 9. Despite of its already high expression level only small amounts of the peptides are

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detectable under standard cultivation conditions (Fig. 4) that were neglected in our previous ACS Paragon Plus Environment

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analysis due to their unusual size. Hence, only the untargeted analysis of major peaks

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upregulated under HD cultivation ultimately allowed us to assign the product to the mvd

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pathway. Unlocking the spatial control of secondary metabolism as demonstrated in the high-

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density cultivation thus provides an avenue for structural elucidation and characterization of

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compounds in vivo and can make laborious heterologous expression approaches obsolete.

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N. punctiforme is a suitable model organism to further study the regulatory cascades in

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secondary metabolism of filamentous cyanobacteria. There are, however, immediate

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conclusions that can be drawn from the current study for further exploitation and suitable

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genomic mining strategies in cyanobacteria. It may not be sufficient to exchange a given BGC

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promoter with a strong inducible promoter without simultaneously altering the nutrient and

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light conditions. Similarly, variations in culture conditions may only lead to a significant

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upregulation of metabolites if the feedback control is being switched off. Our overarching study

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provides new perspectives on current bottlenecks in cyanobacterial natural product research

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and can inspire the discovery of a multitude of novel bioactive metabolites in other

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cyanobacteria.

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Methods Section

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Conventional cultivation of cyanobacteria

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N. punctiforme WT and reporter mutant strains were maintained as liquid cultures on a rotary

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shaker (50 rpm) under permanent white light illumination with an intensity of 30 µmol photons

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m-2s-1 at 23 °C in nitrogen-free BG110 or BG110 media supplemented with 2 µg/ml

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streptomycin (BG110-Strep2), respectively. For the transcriptome analysis N. punctiforme was

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maintained on solidified BG110 medium supplemented with 0.7% (w/v) Bacto agar (BD,

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Heidelberg, Germany) on HATF immobilon-NC membrane filters (Merck, Darmstadt,

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Germany). For cultivation under high partial pressure of carbon dioxide (highCO2), a method

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published by Pors, Y. et al. 30 was adapted. Therefore, low-density polyethylene (LDPE) bags ACS Paragon Plus Environment

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filled with 33 ml of a 4:1 mixture of 3M KHCO3 and 3M K2CO3 producing a CO2 partial

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pressure of 32 mbar over the solution were prepared. Precultures of N. punctiforme

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transcriptional reporters were set up in 250 ml cultivation flasks containing 100 ml BG110-

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Strep2 medium. For high light experiments, 100 ml cultures were illuminated with a dimmable

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full-spectrum LED-panel (HYG05-D100*3W-W, RoHS) at an intensity of 107 µmol photons

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m-2s-1 (50 rpm, 23 °C) whereas control cultures were incubated under standard low light

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conditions. Precultures for highCO2 and high light experiments, respectively, were incubated

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for two to three weeks and split into control and treatment aliquots for the duration of the

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experiments. To monitor differences in CFP transcription levels fluorescence micrographs were

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taken from both treatment and control cultures at different time points (0h, 24h, 72h, 168h for

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highCO2 and 24h for high light experiments, respectively).

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supernatant-addition experiment, conventionally grown N. punctiforme reporter mutant strains

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were pelleted and resuspended in 15 ml supernatant of the HD WT culture supplemented with

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2 µg/ml streptomycin in 35 ml culture flasks. In parallel, control cultures were cultivated in

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BG110-Strep2 medium. After 7 days all cultures were analyzed by confocal fluorescence

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microscopy.

For the high density (HD)

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High density cultivation of cyanobacteria

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For HD cultivation of N. punctiforme reporter mutant strains, 10 ml HD cultivators were used

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together with the HDC 9.10B platform [CellDEG GmbH, Germany]. For the cultivation of N.

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punctiforme WT, a 100 ml HD cultivator together with the HDC 1.100B platform was used.

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For both cultivation approaches 200 ml bicarbonate buffer was applied to the lower vessel of

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the cultivator. The buffer was obtained by mixing 3M solutions of KHCO3 and K2CO3 at ratios

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of 1:1, 4:1 and 9:1, providing CO2 partial pressures of 5, 32 and 90 mbar. Cells were shaken at

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150-250 rpm and illuminated with a dimmable full-spectrum LED-panel (HYG05-D100*3W-

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W, RoHS). Every 72 to 120 h the bicarbonate buffer was exchanged and the whole cell culture ACS Paragon Plus Environment

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was spun down (3000 rpm, 10 min) to determine the wet weight of the resulting cell pellets and

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to medium. The supernatant of WT cultivations was kept for further experiments. Reporter

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mutant strains were analyzed after 10, 20 and 30 d of HD cultivation by confocal fluorescence

307

microscopy. The N. punctiforme WT strain was grown for 30 to 40 d, after which cells were

308

harvested and further processed for HPLC analysis.

309

To obtain large amounts of biomass of N. punctiforme, WT HD cultivation was conducted by

310

the CellDEG GmbH on a larger scale. Therefore, N. punctiforme WT was cultured in a 1.5-

311

liter HD cultivator (HDC1.1500). Two 100 ml N. punctiforme WT precultures grown for 7 d

312

were used as a starter culture. The cultivation vessels were connected via a hydrophobic

313

membrane to a lower chamber containing air enriched with CO2 (8%-12%). Cells were shaken

314

at 100 rpm and illuminated by two LED light sources (AP673L, Valoya). The light intensity as

315

well as the CO2 concentration in the lower chamber was controlled by a growth control unit

316

[CellDEG GmbH, Germany]. The culture was grown for 28 d in BG110 media.

317 318

N. punctiforme WT transcriptome analysis

319

N. punctiforme was concentrated by centrifugation and plated onto HATF filters (Millipore,

320

Bedford, USA) on BG110 agarose plates. After growth to medium cell density under low light

321

conditions, the filters were transferred to plates containing 20 mL BG110.

322

Cells were harvested on days 0, 1, 3, 5, 7 and 9 by scraping them off the filter and were dissolved

323

in 1 mL Trizol (Life Technologies GmbH, Darmstadt, Germany). The samples were shaken

324

and incubated at 65 °C for 20 min. Afterwards the aqueous phase was recovered by two

325

extractions with chloroform. The resulting supernatant was cleaned up with the Qiagen

326

RNAeasy Kit including on-column DNAse digestion (Qiagen, Hilden, Germany). rRNA was

327

removed with the Ribo-Zero rRNA Removal Kit (Bacteria) (Illumina, San Diego, USA) and

328

sequencing libraries were prepared with the TruSeq Stranded mRNA Library Prep (Illumina).


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329

The sequencing was performed with a HiSeq 2500 sequencer (Illumina) on Rapid Run mode

330

for 250 bp paired-end reads.

331

A custom-made script and several third-party software tools were used for processing the

332

sequencing data and estimating the gene expression levels.

333

For the initial processing of the raw data, the first step of the a5miseq pipeline

334

combines the Trimmomatic software

335

perform quality trimming and correction of raw reads. Bowtie2 v2.2.3 36 was used to map the

336

paired-end reads to N. punctiforme ATCC29133 (PCC 73102) reference genome (assembly

337

accession number: GenBank GCA_000020025.1; RefSeq GCF_000020025.1). The alignments

338

files were fed into EDGE-pro v1.3.1

339

further processed and normalized with R package DESeq2 38, and TPM (transcripts per million)

340

for each gene was calculated accordingly 39, 40.

34

37

33

was run; it

and a SGA k-mer based correction algorithm

35

to

to obtain the raw read count per gene. The data was

341 342

Generation of transcriptional reporter mutants for N. punctiforme NRPS/PKS/RiPP BGCs

343

Nostopeptolide

344

were built as described earlier.

345

metabolite BGCs transcriptional reporter strains used in this study is described in the

346

supplementary methods section.

17

and anabaenopeptin 17, 19

19

transcriptional reporters (PnosA-CFP and PaptA-CFP)

Generation of the remaining N. punctiforme secondary

347 348

Confocal Fluorescence Microscopy

349

Confocal microscopy was performed on a Zeiss LSM 780 (Carl Zeiss Mikroskopie GmbH,

350

Jena, Germany), Axio Observer Z1 equipped with a diode laser (405 nm) as well as a HeNe-

351

Laser (633 nm) and an AxioCam digital microscope camera. For image acquisition a PlanApo

352

1.4/63× oil immersion objective and filter presets for eCFP and chlorophyll α detection

353

(excitation at 405/633 nm, detection at 450-550 nm and 650-725 nm, respectively) were used.

354

For device operation, image acquisition and processing the ZEN software was used. ACS Paragon Plus Environment

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Page 16 of 28

355 356

Sample preparation and HPLC analysis

357

For HPLC analysis, cell pellets (~ 0.7 g wet weight) were resuspended in 10 ml ddH2O and

358

lysed by sonification for 10 min (pulse on: 2 s, pulse off: 2 s; Bandelin Sonoplus HD3100).

359

Then the cells were centrifuged (13,000 rpm, 10 min). The supernatant was loaded onto a

360

SepPak Plus C18 column (Waters GmbH, Eschborn, Germany) and washed with 2 ml 5%

361

methanol, then the matrix-bound metabolites were eluted with 2 ml 100% methanol. Samples

362

were vacuum-dried and the resulting pellets were resuspended in 60% methanol. To remove

363

debris, samples were centrifuged and filtered (Acrodisc® 4 mm Syringe filters; Pall GmbH,

364

Dreieich, Germany). The filtered samples were analyzed by HPLC.

365

The HPLC analysis was carried out on a Shimadzu SCL-10AVP HPLC System. A sample

366

volume of 20 µl was injected and separated on a SymmetryShield RP18 column (3.5 μm, 4.6

367

mm x 100 mm) and a SymmetryShield Sentry Guard column (3.5 µm, 3.9 mm x 20 mm). As

368

mobile phases 0.05% TFA in water (solvent A) and 0.05% TFA in acetonitrile (solvent B) were

369

used. The following gradient conditions were used at a flow rate of 1 ml/min: equilibration with

370

20% solvent B for 1 min, followed by a linear gradient up to 60 % solvent B within 35 min,

371

followed by a linear gradient up to 100% solvent B within 1 min and finally solvent B was

372

reduced to 20% within 3 min. Absorption spectra were monitored at λ = 199 nm. The same

373

gradient conditions were used for peak sampling to fractionate the different compounds prior

374

to MALDI-TOF analysis. Peaks were sampled from 2.5 min to 18.5 min (Fig. S15-16). A

375

sample volume of 500 µl was used.

376 377

MALDI-TOF/TOF MS measurements

378

Dried samples were redissolved in aqueous acetonitrile (ACN; 20% v:v; Fluka) acidified with

379

trifluoroacetic acid (TFA, 0.1 % v:v; Sigma Aldrich) to a concentration of approximately 0.4

380

mg/ml. As a matrix solution 20 mg/ml dihydroxybenzoic acid (Sigma Aldrich) were dissolved ACS Paragon Plus Environment

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381

in 30% ACN acidified with 0.1% TFA. Equal amounts (2 µL) of the sample and matrix solution

382

were mixed in a reaction tube and 1 µL was spotted onto a stainless steel MALDI target plate

383

(Bruker Daltonic, Bremen, Germany) and dried. MALDI-TOF/TOF measurements were

384

performed on an UltrafleXtreme TOF/TOF MS (Bruker Daltonic) equipped with a 1 kHz 355

385

nm smartbeam-II laser and a 4 GHz Flash Detector. Microviridins were measured in positive

386

ionization mode in a mass range of m/z 1000-4000 using the reflector mode and deflection of

387

ions with m/z < 900 to filter out matrix ions. The laser power was set to 35% and the detector

388

to 10x. The instrument was calibrated for a mass to charge range from m/z 757 – 3150 before

389

measurements, using the Peptide Calibration Mix II (Bruker Daltonic). The sample rate was set

390

to 0.25 ns, lens voltage to 7.8 kV; Ion source voltage 1 at 20 kV and voltage 2 at 17.9 kV,

391

whereas the reflector voltage 1 was set to 21.1 kV and voltage 2 at 10.95 kV. Tandem MS

392

measurements were performed using the post-source decay (PSD) method and the integrated

393

LIFT module. For fragmentation, laser power was increased by 100% and the detector setting

394

by 150%. All measurements were analyzed using FlexAnalysis 3.4 (Bruker Daltonic).

395 396 397 398

Acknowledgements

399

technical assistance and performing the RNA sequencing. The study was supported by a grant

400

of the German Research Foundation (Di910/12-1) to E.D. and the DFG-funded Collaborative

401

Research Centre ChemBioSys (SFB 1127) to E.D. Further support to R.D.S. came from RTG

402

2473 and the cluster of Excellence under Germany´s Excellence Strategy – EXC 2008/1

403

(UniSysCat) – 390540038".

404 405 406

Additional Information

407

Information file. Furthermore, we provide the reader with two additional files containing all

408

TPM values gathered during RNA-seq (DatasetS1) as well as an overview of all theoretical and

409

observed ion masses of the microviridin MS/MS analysis (DatasetS2). All supporting

410

information is available online and can be downloaded from http://pubs.acs.org .

We thank H. Goto and the OIST DNA sequencing section (Okinawa, Japan) for providing

Additional information supporting the findings of this study is available within Supplementary

411 ACS Paragon Plus Environment

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412 413 414

Author contributions

415

analyzed transcriptional reporters, M.B., J.K. and V.W. performed chemical analytics, K.H.,

416

T.T., D.D. and H.J-K. performed RNA sequencing and bioinformatical analysis. R.D.S.

417

contributed to interpretation of data. E.D. wrote the manuscript with contributions of D.D. and

418

all other authors.

E.D. designed the study. D.D. constructed transcriptional reporters, D.D., J.K and A.G.

419


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symbiotic cyanobacterium Nostoc punctiforme. Proc Natl Acad Sci U S A 2015, 112, 18621867. 18. Yoon, H. S.; Golden, J. W., Heterocyst pattern formation controlled by a diffusible peptide. Science 1998, 282, 935-938. 19. Guljamow, A.; Kreische, M.; Ishida, K.; Liaimer, A.; Altermark, B.; Bahr, L.; Hertweck, C.; Ehwald, R.; Dittmann, E., High-density cultivation of terrestrial Nostoc strains leads to reprogramming of secondary metabolome. Appl Environ Microbiol 2017, 83, e01510e01517. 20. Dittmann, E.; Gugger, M.; Sivonen, K.; Fewer, D. P., Natural Product Biosynthetic Diversity and Comparative Genomics of the Cyanobacteria. Trends Microbiol 2015, 23, 642652. 21. Liaimer, A.; Jensen, J. B.; Dittmann, E., A Genetic and Chemical Perspective on Symbiotic Recruitment of Cyanobacteria of the Genus Nostoc into the Host Plant Blasia pusilla L. Front Microbiol 2016, 7, 1693. 22. Morinaka, B. I.; Lakis, E.; Verest, M.; Helf, M. J.; Scalvenzi, T.; Vagstad, A. L.; Sims, J.; Sunagawa, S.; Gugger, M.; Piel, J., Natural noncanonical protein splicing yields products with diverse beta-amino acid residues. Science 2018, 359, 779-782. 23. Zhang, Q.; Yang, X.; Wang, H.; van der Donk, W. A., High divergence of the precursor peptides in combinatorial lanthipeptide biosynthesis. ACS Chem Biol 2014, 9, 26862694. 24. Amos, G. C. A.; Awakawa, T.; Tuttle, R. N.; Letzel, A. C.; Kim, M. C.; Kudo, Y.; Fenical, W.; Moore, B. S.; Jensen, P. R., Comparative transcriptomics as a guide to natural product discovery and biosynthetic gene cluster functionality. Proc Natl Acad Sci U S A 2017, 114, E11121-E11130. 25. Rouhiainen, L.; Jokela, J.; Fewer, D. P.; Urmann, M.; Sivonen, K., Two Alternative Starter Modules for the Non-Ribosomal Biosynthesis of Specific Anabaenopeptin Variants in Anabaena (Cyanobacteria). Chem Biol 2010, 17, 265-273. 26. Niu, G.; Chater, K. F.; Tian, Y.; Zhang, J.; Tan, H., Specialised metabolites regulating antibiotic biosynthesis in Streptomyces spp. FEMS Microbiol Rev 2016, 40, 554573. 27. Hoskisson, P. A.; Fernandez-Martinez, L. T., Regulation of specialised metabolites in Actinobacteria - expanding the paradigms. Environ Microbiol Rep 2018, 10, 231-238. 28. Guo, C. J.; Sun, W. W.; Bruno, K. S.; Oakley, B. R.; Keller, N. P.; Wang, C. C. C., Spatial regulation of a common precursor from two distinct genes generates metabolite diversity. Chem Sci 2015, 6, 5913-5921. 29. van Gestel, J.; Vlamakis, H.; Kolter, R., From cell differentiation to cell collectives: Bacillus subtilis uses division of labor to migrate. PLoS Biol 2015, 13, e1002141. 30. Pors, Y.; Wustenberg, A.; Ehwald, R., A Batch Culture Method for Microalgae and Cyanobacteria with Co2 Supply through Polyethylene Membranes1. J Phycol 2010, 46, 825830. 31. Arnison, P. G.; Bibb, M. J.; Bierbaum, G.; Bowers, A. A.; Bugni, T. S.; Bulaj, G.; Camarero, J. A.; Campopiano, D. J.; Challis, G. L.; Clardy, J.; Cotter, P. D.; Craik, D. J.; Dawson, M.; Dittmann, E.; Donadio, S.; Dorrestein, P. C.; Entian, K. D.; Fischbach, M. A.; Garavelli, J. S.; Goransson, U.; Gruber, C. W.; Haft, D. H.; Hemscheidt, T. K.; Hertweck, C.; Hill, C.; Horswill, A. R.; Jaspars, M.; Kelly, W. L.; Klinman, J. P.; Kuipers, O. P.; Link, A. J.; Liu, W.; Marahiel, M. A.; Mitchell, D. A.; Moll, G. N.; Moore, B. S.; Muller, R.; Nair, S. K.; Nes, I. F.; Norris, G. E.; Olivera, B. M.; Onaka, H.; Patchett, M. L.; Piel, J.; Reaney, M. J.; Rebuffat, S.; Ross, R. P.; Sahl, H. G.; Schmidt, E. W.; Selsted, M. E.; Severinov, K.; Shen, B.; Sivonen, K.; Smith, L.; Stein, T.; Sussmuth, R. D.; Tagg, J. R.; Tang, G. L.; Truman, A. W.; Vederas, J. C.; Walsh, C. T.; Walton, J. D.; Wenzel, S. C.; Willey, J. M.; van der Donk, W. A., Ribosomally synthesized and post-translationally ACS Paragon Plus Environment

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modified peptide natural products: overview and recommendations for a universal nomenclature. Nat Prod Rep 2013, 30, 108-160. 32. Weiz, A. R.; Ishida, K.; Quitterer, F.; Meyer, S.; Kehr, J. C.; Muller, K. M.; Groll, M.; Hertweck, C.; Dittmann, E., Harnessing the evolvability of tricyclic microviridins to dissect protease-inhibitor interactions. Angew Chem Int Ed 2014, 53, 3735-3738. 33. Coil, D.; Jospin, G.; Darling, A. E., A5-miseq: an updated pipeline to assemble microbial genomes from Illumina MiSeq data. Bioinformatics 2015, 31, 587-589. 34. Lohse, M.; Bolger, A. M.; Nagel, A.; Fernie, A. R.; Lunn, J. E.; Stitt, M.; Usadel, B., RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics. Nucleic Acids Res 2012, 40, W622-627. 35. Simpson, J. T.; Durbin, R., Efficient de novo assembly of large genomes using compressed data structures. Genome Res 2012, 22, 549-556. 36. Langmead, B.; Salzberg, S. L., Fast gapped-read alignment with Bowtie 2. Nat Methods 2012, 9, 357-359. 37. Magoc, T.; Wood, D.; Salzberg, S. L., EDGE-pro: Estimated Degree of Gene Expression in Prokaryotic Genomes. Evol Bioinform Online 2013, 9, 127-136. 38. Love, M. I.; Huber, W.; Anders, S., Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014, 15, 550. 39. Li, B.; Ruotti, V.; Stewart, R. M.; Thomson, J. A.; Dewey, C. N., RNA-Seq gene expression estimation with read mapping uncertainty. Bioinformatics 2010, 26, 493-500. 40. Wagner, G. P.; Kin, K.; Lynch, V. J., Measurement of mRNA abundance using RNAseq data: RPKM measure is inconsistent among samples. Theory Biosci 2012, 131, 281-285.

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545

Figure legends

546

Figure 1

547

(lower part) under standard growth conditions. A) Schematic representation of gene clusters.

548

Blue ORFs indicate NRPS genes; purple ORFs PKS genes and yellow ORFs transporter genes.

549

B) Representative expression values of the first biosynthetic gene of each cluster in a 9 d time-

550

course experiment performed on filters grown on diazotrophic agar plates (Fig. S1). Dashed

551

line indicates base line level determined for constitutively expressed gene clusters. Values are

552

expressed as transcripts per million (TPM). C) Fluorescence micrographs of CFP

553

transcriptional reporter strains grown under diazotrophic growth conditions for respective genes

554

shown in the corresponding subfigures. CFP fluorescence is shown on the left and as overlay

555

with red autofluorescence of cyanobacteria to visualize cells not actively contributing to BGC

556

transcription.

BGCs of N. punctiforme that are constitutively expressed (upper part) or silent

557 558

Figure 2

559

Schematic representation of gene clusters. Blue ORFs indicate NRPS genes; purple ORFs PKS

560

genes, red ORFs RiPP precursor genes, brown ORFs RiPP maturases, green ORFs regulatory

561

genes and yellow ORFs transporter genes. B) Representative expression values of the first

562

biosynthetic gene or a representative RiPP precursor gene in a nine-day time-course experiment

563

performed on filters grown on diazotrophic agar plates (Fig. S1). Dashed line indicates base

564

line level determined for constitutively expressed gene clusters. Values are expressed as

565

transcripts per million (TPM). C) Fluorescence micrographs of CFP transcriptional reporter

566

strains grown under diazotrophic growth conditions for respective genes shown in the

567

corresponding B) subfigures. CFP fluorescence is shown on the left and as overlay with red

568

autofluorescence of cyanobacteria to visualize cells not actively contributing to BGC

569

transcription.

BGCs of N. punctiforme actively transcribed with spatial restriction. A)

570 571

Figure 3

572

cultivation (conv), 30 d high density cultivation (30 d HD), conventional cultivation

573

supplemented with supernatant of HD cultures for 7 d (conv+HDSup) conventional cultivation

574

with 32 mbar CO2 partial pressure over the solution (convhighCO2) for 3 d and conventional

575

cultivation under high light conditions applying an illumination light intensity of 107 µmol

576

photons m-²s-1 (convhigh light) for 24 h, respectively.

Fluorescence micrographs of selected BGC reporter mutants after conventional

577


22

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578

Figure 4

579

profiles of cell pellets and supernatants from N. punctiforme grown under conventional and

580

high-density conditions that indicate a strongly increased production of nostopeptolides

581

(nostopeptolide 1052 (1) and nostopeptolide A (2)), anabaenopeptins (nostamide A (3) and

582

anabaenopeptin NZ857 (4)) as well as many yet uncharacterized secondary metabolite

583

candidates with HD cultivation. Normalization of HPLC profiles is based on wet weight. B)

584

Novel family of microviridins (5-11) that could be detected in a fraction of the HD supernatant

585

by means of MALDI-TOF/TOF MS analysis. For more detailed information about the

586

annotation of compounds 1-4 see Fig. S3. For more detailed information of compound

587

fractionation see Fig. S15.

Comparative metabolomics and discovery of unusual microviridins. A) HPLC

588 589


23


Figure 1 BGCs of N. punctiforme that are constitutively expressed (upper part) or silent (lower part) under standard growth conditions. A) Schematic representation of gene clusters. Blue ORFs indicate NRPS genes; purple ORFs PKS genes and yellow ORFs transporter genes. B) Representative expression values of the first biosynthetic gene of each cluster in a 9 d time-course experiment performed on filters grown on diazotrophic agar plates (Fig. S1). Dashed line indicates base line level determined for constitutively expressed gene clusters. Values are expressed as transcripts per million (TPM). C) Fluorescence micrographs of CFP transcriptional reporter strains grown under diazotrophic growth conditions for respective genes shown in the corresponding subfigures. CFP fluorescence is shown on the left and as overlay with red autofluorescence of cyanobacteria to visualize cells not actively contributing to BGC transcription.


Page 24 of 28

Page 25 of 28 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 2 BGCs of N. punctiforme actively transcribed with spatial restriction. A) Schematic representation of gene clusters. Blue ORFs indicate NRPS genes; purple ORFs PKS genes, red ORFs RiPP precursor genes, brown ORFs RiPP maturases, green ORFs regulatory genes and yellow ORFs transporter genes. B) Representative expression values of the first biosynthetic gene or a representative RiPP precursor gene in a nine-day time-course experiment performed on filters grown on diazotrophic agar plates (Fig. S1). Dashed line indicates base line level determined for constitutively expressed gene clusters. Values are expressed as transcripts per million (TPM). C) Fluorescence micrographs of CFP transcriptional reporter strains grown under diazotrophic growth conditions for respective genes shown in the corresponding B) subfigures. CFP fluorescence is shown on the left and as overlay with red autofluorescence of cyanobacteria to visualize cells not actively contributing to BGC transcription.



Figure 3 Fluorescence micrographs of selected BGC reporter mutants after conventional cultivation (conv), 30 d high density cultivation (30 d HD), conventional cultivation supplemented with supernatant of HD cultures for 7 d (conv+HDSup) conventional cultivation with 32 mbar CO2 partial pressure over the solution (convhighCO2) for 3 d and conventional cultivation under high light conditions applying an illumination light intensity of 107 µmol photons m-²s-1 (convhigh light) for 24 h, respectively.


Page 26 of 28

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Figure 4 Comparative metabolomics and discovery of unusual microviridins. A) HPLC profiles of cell pellets and supernatants from N. punctiforme grown under conventional and high-density conditions that indicate a strongly increased production of nostopeptolides (nostopeptolide 1052 (1) and nostopeptolide A (2)), anabaenopeptins (nostamide A (3) and anabaenopeptin NZ857 (4)) as well as many yet uncharacterized secondary metabolite candidates with HD cultivation. Normalization of HPLC profiles is based on wet weight. B) Novel family of microviridins (5-11) that could be detected in a fraction of the HD supernatant by means of MALDI-TOF/TOF MS analysis. For more detailed information about the annotation of compounds 1-4 see Fig. S3. For more detailed information of compound fractionation see Fig. S15.



ToC graphics


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Unlocking the spatial control of secondary metabolism uncovers

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