Maramycin, a Cytotoxic Isoquinolinequinone Terpenoid Produced through Heterologous Expression of a Bifunctional Indole Prenyltransferase/Tryptophan Indole-Lyase in S. albidoflavus

Isoquinolinequinones represent an important family of natural alkaloids with profound biological activities. Heterologous expression of a rare bifunctional indole prenyltransferase/tryptophan indole-lyase enzyme from Streptomyces mirabilis P8-A2 in S. albidoflavus J1074 led to the activation of a putative isoquinolinequinone biosynthetic gene cluster and production of a novel isoquinolinequinone alkaloid, named maramycin (1). The structure of maramycin was determined by analysis of spectroscopic (1D/2D NMR) and MS spectrometric data. The prevalence of this bifunctional biosynthetic enzyme was explored and found to be a recent evolutionary event with only a few representatives in nature. Maramycin exhibited moderate cytotoxicity against human prostate cancer cell lines, LNCaP and C4-2B. The discovery of maramycin (1) enriched the chemical diversity of natural isoquinolinequinones and also provided new insights into crosstalk between the host biosynthetic genes and the heterologous biosynthetic genes in generating new chemical scaffolds.

Complete, circular genome sequence of a Bosea sp. isolate from soil

Here, we report the complete, circular genome sequence of a potential novel species from the underexplored Alphaproteobacterial genus Bosea. Bosea sp. NBC_00550 was isolated from a soil sample collected in Lyngby, Denmark. We explore the biosynthetic potential of Bosea sp. NBC_00550 and compare it with that of other Bosea species.

Complete Genome Sequences of the Two Strains Methylorubrum extorquens NBC_00036 and NBC_00404

Here, we report the complete genome sequences of Methylorubrum extorquens NBC_00036 and Methylorubrum extorquens NBC_00404. The genomes were sequenced using the Oxford Nanopore Technologies MinION and Illumina NovaSeq systems. Both genomes are circular, with sizes of 5,661,342 bp and 5,869,086 bp, respectively.

Identification of the Biosynthetic Gene Cluster for Pyracrimycin A, an Antibiotic Produced by Streptomyces sp

Actinomycetes make a wealth of complex, structurally diverse natural products, and a key challenge is to link them to their biosynthetic gene clusters and delineate the reactions catalyzed by each of the enzymes. Here, we report the biosynthetic gene cluster for pyracrimycin A, a set of nine genes that includes a core nonribosomal peptide synthase (pymB) that utilizes serine and proline as precursors and a monooxygenase (pymC) that catalyzes Baeyer-Villiger oxidation. The cluster is similar to the one for brabantamide A; however, pyracrimycin A biosynthesis differs in that feeding experiments with isotope-labeled serine and proline suggest that a ring opening reaction takes place and a carbon is lost from serine downstream of the oxidation reaction. Based on these data, we propose a full biosynthesis pathway for pyracrimycin A.

Discovery and Characterization of Epemicins A and B, New 30-Membered Macrolides from Kutzneria sp. CA-103260

Actinobacteria have been a rich source of novel, structurally complex natural products for many decades. Although the largest genus is Streptomyces, from which the majority of antibiotics in current and past clinical use were originally isolated, other less common genera also have the potential to produce a wealth of novel secondary metabolites. One example is the Kutzneria genus, which currently contains only five reported species. One of these species is Kutzneria albida DSM 43870T, which has 46 predicted biosynthetic gene clusters and is known to produce the macrolide antibiotic aculeximycin. Here, we report the isolation and structural characterization of two novel 30-membered glycosylated macrolides, epemicins A and B, that are structurally related to aculeximycin, from a rare Kutzneria sp. The absolute configuration for all chiral centers in the two compounds is proposed based on extensive 1D and 2D NMR studies and bioinformatics analysis of the gene cluster. Through heterologous expression and genetic inactivation, we have confirmed the link between the biosynthetic gene cluster and the new molecules. These findings show the potential of rare Actinobacteria to produce new, structurally diverse metabolites. Furthermore, the gene inactivation represents the first published report to genetically manipulate a representative of the Kutzneria genus.

Complete Genome Sequence of the Rare Actinobacterium Kutzneria sp. Strain CA-103260

Here, we report the sequencing, assembly, and annotation of the genome of the rare actinobacterium Kutzneria sp. strain CA-103260. The genome of CA-103260 was sequenced using PacBio and Illumina technologies and it consists of a circular 11,609,901-bp chromosome.

Programmable polyketide biosynthesis platform for production of aromatic compounds in yeast

To accelerate the shift to bio-based production and overcome complicated functional implementation of natural and artificial biosynthetic pathways to industry relevant organisms, development of new, versatile, bio-based production platforms is required. Here we present a novel yeast-based platform for biosynthesis of bacterial aromatic polyketides. The platform is based on a synthetic polyketide synthase system enabling a first demonstration of bacterial aromatic polyketide biosynthesis in a eukaryotic host.

Dissemination of antibiotic resistance genes from antibiotic producers to pathogens

It has been hypothesized that some antibiotic resistance genes (ARGs) found in pathogenic bacteria derive from antibiotic-producing actinobacteria. Here we provide bioinformatic and experimental evidence supporting this hypothesis. We identify genes in proteobacteria, including some pathogens, that appear to be closely related to actinobacterial ARGs known to confer resistance against clinically important antibiotics. Furthermore, we identify two potential examples of recent horizontal transfer of actinobacterial ARGs to proteobacterial pathogens. Based on this bioinformatic evidence, we propose and experimentally test a 'carry-back' mechanism for the transfer, involving conjugative transfer of a carrier sequence from proteobacteria to actinobacteria, recombination of the carrier sequence with the actinobacterial ARG, followed by natural transformation of proteobacteria with the carrier-sandwiched ARG. Our results support the existence of ancient and, possibly, recent transfers of ARGs from antibiotic-producing actinobacteria to proteobacteria, and provide evidence for a defined mechanism.

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Metabolic engineering with systems biology tools to optimize production of prokaryotic secondary metabolites

This Highlight examines current status of metabolic engineering and systems biology tools deployed for the optimal production of prokaryotic secondary metabolites.

Model-driven discovery of synergistic inhibitors against E. coli and S. enterica serovar Typhimurium targeting a novel synthetic lethal pair, aldA and prpC

Mathematical models of biochemical networks form a cornerstone of bacterial systems biology. Inconsistencies between simulation output and experimental data point to gaps in knowledge about the fundamental biology of the organism. One such inconsistency centers on the gene aldA in Escherichia coli: it is essential in a computational model of E. coli metabolism, but experimentally it is not. Here, we reconcile this disparity by providing evidence that aldA and prpC form a synthetic lethal pair, as the double knockout could only be created through complementation with a plasmid-borne copy of aldA. Moreover, virtual and biological screening against the two proteins led to a set of compounds that inhibited the growth of E. coli and Salmonella enterica serovar Typhimurium synergistically at 100-200 μM individual concentrations. These results highlight the power of metabolic models to drive basic biological discovery and their potential use to discover new combination antibiotics.

CRISPR-Cas9 Based Engineering of Actinomycetal Genomes

Bacteria of the order Actinomycetales are one of the most important sources of pharmacologically active and industrially relevant secondary metabolites. Unfortunately, many of them are still recalcitrant to genetic manipulation, which is a bottleneck for systematic metabolic engineering. To facilitate the genetic manipulation of actinomycetes, we developed a highly efficient CRISPR-Cas9 system to delete gene(s) or gene cluster(s), implement precise gene replacements, and reversibly control gene expression in actinomycetes. We demonstrate our system by targeting two genes, actIORF1 (SCO5087) and actVB (SCO5092), from the actinorhodin biosynthetic gene cluster in Streptomyces coelicolor A3(2). Our CRISPR-Cas9 system successfully inactivated the targeted genes. When no templates for homology-directed repair (HDR) were present, the site-specific DNA double-strand breaks (DSBs) introduced by Cas9 were repaired through the error-prone nonhomologous end joining (NHEJ) pathway, resulting in a library of deletions with variable sizes around the targeted sequence. If templates for HDR were provided at the same time, precise deletions of the targeted gene were observed with near 100% frequency. Moreover, we developed a system to efficiently and reversibly control expression of target genes, deemed CRISPRi, based on a catalytically dead variant of Cas9 (dCas9). The CRISPR-Cas9 based system described here comprises a powerful and broadly applicable set of tools to manipulate actinomycetal genomes.

Metabolic engineering of antibiotic factories: new tools for antibiotic production in actinomycetes

Actinomycetes are excellent sources for novel bioactive compounds, which serve as potential drug candidates for antibiotics development. While industrial efforts to find and develop novel antimicrobials have been severely reduced during the past two decades, the increasing threat of multidrug-resistant pathogens and the development of new technologies to find and produce such compounds have again attracted interest in this field. Based on improvements in whole-genome sequencing, novel methods have been developed to identify the secondary metabolite biosynthetic gene clusters by genome mining, to clone them, and to express them in heterologous hosts in much higher throughput than before. These technologies now enable metabolic engineering approaches to optimize production yields and to directly manipulate the pathways to generate modified products.

Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters

Background

A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system’s dynamics.

Results

We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics.

Conclusions

A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.

Capsule deletion via a λ-Red knockout system perturbs biofilm formation and fimbriae expression in Klebsiella pneumoniae MGH 78578

Background

Klebsiella pneumoniae is a leading cause of hospital-acquired urinary tract infections and pneumonia worldwide, and is responsible for many cases of pyogenic liver abscess among diabetic patients in Asia. A defining characteristic of this pathogen is the presence of a thick, exterior capsule that has been reported to play a role in biofilm formation and to protect the organism from threats such antibiotics and host immune challenge.

Findings

We constructed two knockout mutants of K. pneumoniae to investigate how perturbations to capsule biosynthesis alter the cellular phenotype. In the first mutant, we deleted the entire gene cluster responsible for biosynthesis of the extracellular polysaccharide capsule. In the second mutant, we deleted the capsule export subsystem within this cluster. We find that both knockout mutants have lower amounts of capsule but produce greater amounts of biofilm. Moreover, one of the two mutants abolishes fimbriae expression as well.

Conclusions

These results are expected to provide insight into the interaction between capsule biosynthesis, biofilm formation, and fimbriae expression in this organism.

Systems biology and biotechnology of Streptomyces species for the production of secondary metabolites

Streptomyces species continue to attract attention as a source of novel medicinal compounds. Despite a long history of studies on these microorganisms, they still have many biochemical mysteries to be elucidated. Investigations of novel secondary metabolites and their biosynthetic gene clusters have been more systematized with high-throughput techniques through inspections of correlations among components of the primary and secondary metabolisms at the genome scale. Moreover, up-to-date information on the genome of Streptomyces species with emphasis on their secondary metabolism has been collected in the form of databases and knowledgebases, providing predictive information and enabling one to explore experimentally unrecognized biological spaces of secondary metabolism. Herein, we review recent trends in the systems biology and biotechnology of Streptomyces species.

Studying Salmonellae and Yersiniae host-pathogen interactions using integrated 'omics and modeling

Salmonella and Yersinia are two distantly related genera containing species with wide host-range specificity and pathogenic capacity. The metabolic complexity of these organisms facilitates robust lifestyles both outside of and within animal hosts. Using a pathogen-centric systems biology approach, we are combining a multi-omics (transcriptomics, proteomics, metabolomics) strategy to define properties of these pathogens under a variety of conditions including those that mimic the environments encountered during pathogenesis. These high-dimensional omics datasets are being integrated in selected ways to improve genome annotations, discover novel virulence-related factors, and model growth under infectious states. We will review the evolving technological approaches toward understanding complex microbial life through multi-omic measurements and integration, while highlighting some of our most recent successes in this area.

Reconciling a Salmonella enterica metabolic model with experimental data confirms that overexpression of the glyoxylate shunt can rescue a lethal ppc deletion mutant

The in silico reconstruction of metabolic networks has become an effective and useful systems biology approach to predict and explain many different cellular phenotypes. When simulation outputs do not match experimental data, the source of the inconsistency can often be traced to incomplete biological information that is consequently not captured in the model. To address this problem, general approaches continue to be needed that can suggest experimentally testable hypotheses to reconcile inconsistencies between simulation and experimental data. Here, we present such an approach that focuses specifically on correcting cases in which experimental data show a particular gene to be essential but model simulations do not. We use metabolic models to predict efficient compensatory pathways, after which cloning and overexpression of these pathways are performed to investigate whether they restore growth and to help determine why these compensatory pathways are not active in mutant cells. We demonstrate this technique for a ppc knockout of Salmonella enterica serovar Typhimurium; the inability of cells to route flux through the glyoxylate shunt when ppc is removed was correctly identified by our approach as the cause of the discrepancy. These results demonstrate the feasibility of our approach to drive biological discovery while simultaneously refining metabolic network reconstructions.

Multiple-omic data analysis of Klebsiella pneumoniae MGH 78578 reveals its transcriptional architecture and regulatory features

Background

The increasing number of infections caused by strains of Klebsiella pneumoniae that are resistant to multiple antibiotics has developed into a major medical problem worldwide. The development of next-generation sequencing technologies now permits rapid sequencing of many K. pneumoniae isolates, but sequence information alone does not provide important structural and operational information for its genome.

Results

Here we take a systems biology approach to annotate the K. pneumoniae MGH 78578 genome at the structural and operational levels. Through the acquisition and simultaneous analysis of multiple sample-matched –omics data sets from two growth conditions, we detected 2677, 1227, and 1066 binding sites for RNA polymerase, RpoD, and RpoS, respectively, 3660 RNA polymerase-guided transcript segments, and 3585 transcription start sites throughout the genome. Moreover, analysis of the transcription start site data identified 83 probable leaderless mRNAs, while analysis of unannotated transcripts suggested the presence of 119 putative open reading frames, 15 small RNAs, and 185 antisense transcripts that are not currently annotated.

Conclusions

These findings highlight the strengths of systems biology approaches to the refinement of sequence-based annotations, and to provide new insight into fundamental genome-level biology for this important human pathogen.

An experimentally-supported genome-scale metabolic network reconstruction for Yersinia pestis CO92

Background

Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas.

Results

Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain.

Conclusions

Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, provides an in silico platform with which to investigate the metabolism of this important human pathogen.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

Background

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem.

Results

Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches.

Conclusion

Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.

Genetic basis of growth adaptation of Escherichia coli after deletion of pgi, a major metabolic gene

Bacterial survival requires adaptation to different environmental perturbations such as exposure to antibiotics, changes in temperature or oxygen levels, DNA damage, and alternative nutrient sources. During adaptation, bacteria often develop beneficial mutations that confer increased fitness in the new environment. Adaptation to the loss of a major non-essential gene product that cripples growth, however, has not been studied at the whole-genome level. We investigated the ability of Escherichia coli K-12 MG1655 to overcome the loss of phosphoglucose isomerase (pgi) by adaptively evolving ten replicates of E. coli lacking pgi for 50 days in glucose M9 minimal medium and by characterizing endpoint clones through whole-genome re-sequencing and phenotype profiling. We found that 1) the growth rates for all ten endpoint clones increased approximately 3-fold over the 50-day period; 2) two to five mutations arose during adaptation, most frequently in the NADH/NADPH transhydrogenases udhA and pntAB and in the stress-associated sigma factor rpoS; and 3) despite similar growth rates, at least three distinct endpoint phenotypes developed as defined by different rates of acetate and formate secretion. These results demonstrate that E. coli can adapt to the loss of a major metabolic gene product with only a handful of mutations and that adaptation can result in multiple, alternative phenotypes.

Microbial regulatory and metabolic networks

Reconstruction of transcriptional regulatory and metabolic networks is the foundation of large-scale microbial systems and synthetic biology. An enormous amount of information including the annotated genomic sequences and the genomic locations of DNA-binding regulatory proteins can be used to define metabolic and regulatory networks in cells. In particular, advances in experimental methods to map regulatory networks in microbial cells have allowed reliable data-driven reconstruction of these networks. Recent work on metabolic engineering and experimental evolution of microbes highlights the key role of global regulatory networks in controlling specific metabolic processes and the need to consider the integrated function of multiple types of networks for both scientific and engineering purposes.