A treasure trove of 1034 actinomycete genomes.

Filamentous Actinobacteria, recently renamed Actinomycetia, are the most prolific source of microbial bioactive natural products. Studies on biosynthetic gene clusters benefit from or require chromosome-level assemblies. Here, we provide DNA sequences from >1000 isolates: 881 complete genomes and 153 near-complete genomes, representing 28 genera and 389 species, including 244 likely novel species. All genomes are from filamentous isolates of the class Actinomycetia from the NBC culture collection. The largest genus is Streptomyces with 886 genomes including 742 complete assemblies. We use this data to show that analysis of complete genomes can bring biological understanding not previously derived from more fragmented sequences or less systematic datasets. We document the central and structured location of core genes and distal location of specialized metabolite biosynthetic gene clusters and duplicate core genes on the linear Streptomyces chromosome, and analyze the content and length of the terminal inverted repeats which are characteristic for Streptomyces. We then analyze the diversity of trans-AT polyketide synthase biosynthetic gene clusters, which encodes the machinery of a biotechnologically highly interesting compound class. These insights have both ecological and biotechnological implications in understanding the importance of high quality genomic resources and the complex role synteny plays in Actinomycetia biology.

Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data.

Finding the minimal set of gene functions needed to sustain life is of both fundamental and practical importance. Minimal gene lists have been proposed by using comparative genomics-based core proteome definitions. A definition of a core proteome that is supported by empirical data, is understood at the systems-level, and provides a basis for computing essential cell functions is lacking. Here, we use a systems biology-based genome-scale model of metabolism and expression to define a functional core proteome consisting of 356 gene products, accounting for 44% of the Escherichia coli proteome by mass based on proteomics data. This systems biology core proteome includes 212 genes not found in previous comparative genomics-based core proteome definitions, accounts for 65% of known essential genes in E. coli, and has 78% gene function overlap with minimal genomes (Buchnera aphidicola and Mycoplasma genitalium). Based on transcriptomics data across environmental and genetic backgrounds, the systems biology core proteome is significantly enriched in nondifferentially expressed genes and depleted in differentially expressed genes. Compared with the noncore, core gene expression levels are also similar across genetic backgrounds (two times higher Spearman rank correlation) and exhibit significantly more complex transcriptional and posttranscriptional regulatory features (40% more transcription start sites per gene, 22% longer 5'UTR). Thus, genome-scale systems biology approaches rigorously identify a functional core proteome needed to support growth. This framework, validated by using high-throughput datasets, facilitates a mechanistic understanding of systems-level core proteome function through in silico models; it de facto defines a paleome.

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

Covering: 2012 to 2016Metabolic engineering using systems biology tools is increasingly applied to overproduce secondary metabolites for their potential industrial production. In this Highlight, recent relevant metabolic engineering studies are analyzed with emphasis on host selection and engineering approaches for the optimal production of various prokaryotic secondary metabolites: native versus heterologous hosts (e.g., Escherichia coli) and rational versus random approaches. This comparative analysis is followed by discussions on systems biology tools deployed in optimizing the production of secondary metabolites. The potential contributions of additional systems biology tools are also discussed in the context of current challenges encountered during optimization of secondary metabolite production.

Genome-scale metabolic reconstructions of multiple Escherichia coli strains highlight strain-specific adaptations to nutritional environments.

Genome-scale models (GEMs) of metabolism were constructed for 55 fully sequenced Escherichia coli and Shigella strains. The GEMs enable a systems approach to characterizing the pan and core metabolic capabilities of the E. coli species. The majority of pan metabolic content was found to consist of alternate catabolic pathways for unique nutrient sources. The GEMs were then used to systematically analyze growth capabilities in more than 650 different growth-supporting environments. The results show that unique strain-specific metabolic capabilities correspond to pathotypes and environmental niches. Twelve of the GEMs were used to predict growth on six differentiating nutrients, and the predictions were found to agree with 80% of experimental outcomes. Additionally, GEMs were used to predict strain-specific auxotrophies. Twelve of the strains modeled were predicted to be auxotrophic for vitamins niacin (vitamin B3), thiamin (vitamin B1), or folate (vitamin B9). Six of the strains modeled have lost biosynthetic pathways for essential amino acids methionine, tryptophan, or leucine. Genome-scale analysis of multiple strains of a species can thus be used to define the metabolic essence of a microbial species and delineate growth differences that shed light on the adaptation process to a particular microenvironment.

MS/MS networking guided analysis of molecule and gene cluster families.

The ability to correlate the production of specialized metabolites to the genetic capacity of the organism that produces such molecules has become an invaluable tool in aiding the discovery of biotechnologically applicable molecules. Here, we accomplish this task by matching molecular families with gene cluster families, making these correlations to 60 microbes at one time instead of connecting one molecule to one organism at a time, such as how it is traditionally done. We can correlate these families through the use of nanospray desorption electrospray ionization MS/MS, an ambient pressure MS technique, in conjunction with MS/MS networking and peptidogenomics. We matched the molecular families of peptide natural products produced by 42 bacilli and 18 pseudomonads through the generation of amino acid sequence tags from MS/MS data of specific clusters found in the MS/MS network. These sequence tags were then linked to biosynthetic gene clusters in publicly accessible genomes, providing us with the ability to link particular molecules with the genes that produced them. As an example of its use, this approach was applied to two unsequenced Pseudoalteromonas species, leading to the discovery of the gene cluster for a molecular family, the bromoalterochromides, in the previously sequenced strain P. piscicida JCM 20779(T). The approach itself is not limited to 60 related strains, because spectral networking can be readily adopted to look at molecular family-gene cluster families of hundreds or more diverse organisms in one single MS/MS network.

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.

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.

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.

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.

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.

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.

An experimentally validated genome-scale metabolic reconstruction of Klebsiella pneumoniae MGH 78578, iYL1228.

Klebsiella pneumoniae is a Gram-negative bacterium of the family Enterobacteriaceae that possesses diverse metabolic capabilities: many strains are leading causes of hospital-acquired infections that are often refractory to multiple antibiotics, yet other strains are metabolically engineered and used for production of commercially valuable chemicals. To study its metabolism, we constructed a genome-scale metabolic model (iYL1228) for strain MGH 78578, experimentally determined its biomass composition, experimentally determined its ability to grow on a broad range of carbon, nitrogen, phosphorus and sulfur sources, and assessed the ability of the model to accurately simulate growth versus no growth on these substrates. The model contains 1,228 genes encoding 1,188 enzymes that catalyze 1,970 reactions and accurately simulates growth on 84% of the substrates tested. Furthermore, quantitative comparison of growth rates between the model and experimental data for nine of the substrates also showed good agreement. The genome-scale metabolic reconstruction for K. pneumoniae presented here thus provides an experimentally validated in silico platform for further studies of this important industrial and biomedical organism.

Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models.

After hundreds of generations of adaptive evolution at exponential growth, Escherichia coli grows as predicted using flux balance analysis (FBA) on genome-scale metabolic models (GEMs). However, it is not known whether the predicted pathway usage in FBA solutions is consistent with gene and protein expression in the wild-type and evolved strains. Here, we report that >98% of active reactions from FBA optimal growth solutions are supported by transcriptomic and proteomic data. Moreover, when E. coli adapts to growth rate selective pressure, the evolved strains upregulate genes within the optimal growth predictions, and downregulate genes outside of the optimal growth solutions. In addition, bottlenecks from dosage limitations of computationally predicted essential genes are overcome in the evolved strains. We also identify regulatory processes that may contribute to the development of the optimal growth phenotype in the evolved strains, such as the downregulation of known regulons and stringent response suppression. Thus, differential gene and protein expression from wild-type and adaptively evolved strains supports observed growth phenotype changes, and is consistent with GEM-computed optimal growth states.

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.

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.

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.

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.

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.

The aldehyde dehydrogenase, AldA, is essential for L-1,2-propanediol utilization in laboratory-evolved Escherichia coli.

Most Escherichia coli strains are naturally unable to grow on 1,2-propanediol (PDO) as a sole carbon source. Recently, however, a K-12 descendent E. coli strain was evolved to grow on 1,2-PDO, and it was hypothesized that this evolved ability was dependent on the aldehyde dehydrogenase, AldA, which is highly conserved among members of the family Enterobacteriacea. To test this hypothesis, we first performed computational model simulation, which confirmed the essentiality of the aldA gene for 1,2-PDO utilization by the evolved PDO-degrading E. coli. Next, we deleted the aldA gene from the evolved strain, and this deletion was sufficient to abolish the evolved phenotype. On re-introducing the gene on a plasmid, the evolved phenotype was restored. These findings provide experimental evidence for the computationally predicted role of AldA in 1,2-PDO utilization, and represent a good example of E. coli robustness, demonstrated by the bacterial deployment of a generalist enzyme (here AldA) in multiple pathways to survive carbon starvation and to grow on a non-native substrate when no native carbon source is available.