Metabolomic analysis of a synthetic metabolic switch in Streptomyces coelicolor A3(2)

Effect of pII key nitrogen regulatory gene on strain growth and butenyl-spinosyn biosynthesis in Saccharopolyspora pogona

PII signal transduction proteins are widely found in bacteria and plant chloroplast, and play a central role in nitrogen metabolism regulation, which interact with many key proteins in metabolic pathways to regulate carbon/nitrogen balance by sensing changes in concentrations of cell-mediated indicators such as α-ketoglutarate. In this study, the knockout strain Saccharopolyspora pogona-ΔpII and overexpression strain S. pogona-pII were constructed using CRISPR/Cas9 technology and the shuttle vector POJ260, respectively, to investigate the effects on the growth and secondary metabolite biosynthesis of S. pogona. Growth curve, electron microscopy, and spore germination experiments were performed, and it was found that the deletion of the pII gene inhibited the growth to a certain extent in the mutant. HPLC analysis showed that the yield of butenyl-spinosyn in the S. pogona-pII strain increased to 245% than that in the wild-type strain while that in S. pogona-ΔpII decreased by approximately 51%. This result showed that the pII gene can promote the growth and butenyl-spinosyn biosynthesis of S. pogona. This research first investigated PII nitrogen metabolism regulators in S. pogona, providing significant scientific evidence and a research basis for elucidating the mechanism by which these factors regulate the growth of S. pogona, optimizing the synthesis network of butenyl-spinosyn and constructing a strain with a high butenyl-spinosyn yield. KEY POINTS: • pII key nitrogen regulatory gene deletion can inhibit the growth and development of S. pogona. • Overexpressed pII gene can significantly promote the butenyl-spinosyn biosynthesis. • pII gene can affect the amino acid circulation and the accumulation of butenyl-spinosyn precursors in S. pogona.

Differences at Species Level and in Repertoires of Secondary Metabolite Biosynthetic Gene Clusters among Streptomyces coelicolor A3(2) and Type Strains of S. coelicolor and Its Taxonomic Neighbors

Streptomyces coelicolor A3(2) is used worldwide for genetic studies, and its complete genome sequence was published in 2002. However, as the whole genome of the type strain of S. coelicolor has not been analyzed, the relationship between S. coelicolor A3(2) and the type strain is not yet well known. To clarify differences in their biosynthetic potential, as well as their taxonomic positions, we sequenced whole genomes of S. coelicolor NBRC 12854T and type strains of its closely related species—such as Streptomyces daghestanicus, Streptomyces hydrogenans, and Streptomyces violascens—via PacBio. Biosynthetic gene clusters for polyketides and non-ribosomal peptides were surveyed by antiSMASH, followed by bioinformatic analyses. Type strains of Streptomyces albidoflavus, S. coelicolor, S. daghestanicus, S. hydrogenans, and S. violascens shared the same 16S rDNA sequence, but S. coelicolor A3(2) did not. S. coelicolor A3(2) and S. coelicolor NBRC 12854T can be classified as Streptomycesanthocyanicus and S. albidoflavus, respectively. In contrast, S. daghestanicus, S. hydrogenans, and S. violascens are independent species, despite their identical 16S rDNA sequences. S. coelicolor A3(2), S. coelicolor NBRC 12854T, S. daghestanicus NBRC 12762T, S. hydrogenans NBRC 13475T, and S. violascens NBRC 12920T each harbor specific polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS) gene clusters in their genomes, whereas PKS and NRPS gene clusters are well conserved between S. coelicolor A3(2) and S. anthocyanicus JCM 5058T, and between S. coelicolor NBRC 12854T and S. albidoflavus DSM 40455T, belonging to the same species. These results support our hypothesis that the repertoires of PKS and NRPS gene clusters are different between different species.

Metabolomics in the Context of Plant Natural Products Research: From Sample Preparation to Metabolite Analysis

Plant-derived natural products have long been considered a valuable source of lead compounds for drug development. Natural extracts are usually composed of hundreds to thousands of metabolites, whereby the bioactivity of natural extracts can be represented by synergism between several metabolites. However, isolating every single compound from a natural extract is not always possible due to the complex chemistry and presence of most secondary metabolites at very low levels. Metabolomics has emerged in recent years as an indispensable tool for the analysis of thousands of metabolites from crude natural extracts, leading to a paradigm shift in natural products drug research. Analytical methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) are used to comprehensively annotate the constituents of plant natural products for screening, drug discovery as well as for quality control purposes such as those required for phytomedicine. In this review, the current advancements in plant sample preparation, sample measurements, and data analysis are presented alongside a few case studies of the successful applications of these processes in plant natural product drug discovery.

Dynamical modelling of secondary metabolism and metabolic switches in Streptomyces xiamenensis 318

The production of secondary metabolites, while important for bioengineering purposes, presents a paradox in itself. Though widely existing in plants and bacteria, they have no definite physiological roles. Yet in both native habitats and laboratories, their production appears robust and follows apparent metabolic switches. We show in this work that the enzyme-catalysed process may improve the metabolic stability of the cells. The latter can be responsible for the overall metabolic behaviours such as dynamic metabolic landscape, metabolic switches and robustness, which can in turn affect the genetic formation of the organism in question. Mangrove-derived Streptomyces xiamenensis 318, with a relatively compact genome for secondary metabolism, is used as a model organism in our investigation. Integrated studies via kinetic metabolic modelling, transcriptase measurements and metabolic profiling were performed on this strain. Our results demonstrate that the secondary metabolites increase the metabolic fitness of the organism via stabilizing the underlying metabolic network. And the fluxes directing to NADH, NADPH, acetyl-CoA and glutamate provide the key switches for the overall and secondary metabolism. The information may be helpful for improving the xiamenmycin production on the strain.

Development and validation of an updated computational model of Streptomyces coelicolor primary and secondary metabolism

BACKGROUND

Streptomyces species produce a vast diversity of secondary metabolites of clinical and biotechnological importance, in particular antibiotics. Recent developments in metabolic engineering, synthetic and systems biology have opened new opportunities to exploit Streptomyces secondary metabolism, but achieving industry-level production without time-consuming optimization has remained challenging. Genome-scale metabolic modelling has been shown to be a powerful tool to guide metabolic engineering strategies for accelerated strain optimization, and several generations of models of Streptomyces metabolism have been developed for this purpose.

RESULTS

Here, we present the most recent update of a genome-scale stoichiometric constraint-based model of the metabolism of Streptomyces coelicolor, the major model organism for the production of antibiotics in the genus. We show that the updated model enables better metabolic flux and biomass predictions and facilitates the integrative analysis of multi-omics data such as transcriptomics, proteomics and metabolomics.

CONCLUSIONS

The updated model presented here provides an enhanced basis for the next generation of metabolic engineering attempts in Streptomyces.

Modelling microbial metabolic rewiring during growth in a complex medium

Background

In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now.

Results

We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs).

Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of choosing among alternative objective functions on the resulting predictions of fluxes distribution.

Conclusions

Here we provide a time-resolved, systems-level scheme of PhTAC125 metabolic re-wiring as a consequence of carbon source switching in a nutritionally complex medium. Our analyses suggest the presence of a potential efficient metabolic reprogramming machinery to continuously and promptly adapt to this nutritionally changing environment, consistent with adaptation to fast growth in a fairly, but probably inconstant and highly competitive, environment. Also, we show i) how functional partnership and co-regulation features can be predicted by integrating multi-step constraint-based metabolic modelling with fed-batch growth data and ii) that performing simulations under a sub-optimal objective function may lead to different flux distributions in respect to canonical FBA.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3311-0) contains supplementary material, which is available to authorized users.

Differential proteomic profiling reveals regulatory proteins and novel links between primary metabolism and spinosad production in Saccharopolyspora spinosa

Background

Saccharopolyspora spinosa is an important producer of antibiotic spinosad with clarified biosynthesis pathway but its complex regulation networks associated with primary metabolism and secondary metabolites production almost have never been concerned or studied before. The proteomic analysis of a novel Saccharopolyspora spinosa CCTCC M206084 was performed and aimed to provide a global profile of regulatory proteins.

Results

Two-dimensional-liquid chromatography-tandem mass spectrometry (LC-MS/MS) identified 1090, 1166, 701, and 509 proteins from four phases respectively, i.e., the logarithmic growth phase (T1), early stationary phase (T2), late stationary phase (T3), and decline phase (T4). Among the identified proteins, 1579 were unique to the S. spinosa proteome, including almost all the enzymes for spinosad biosynthesis. Trends in protein expression over the various time phases were deduced from using the modified protein abundance index (PAI), revealed the importance of stress pathway proteins and other global regulatory network proteins during spinosad biosynthesis. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis followed by one-dimensional LC-MS/MS identification revealed similar trend of protein expression from four phases with the results of semi-quantification by PAI. qRT-PCR analysis revealed that 6 different expressed genes showed a positive correlation between changes at translational and transcriptional expression level. Expression of three proteins that likely promote spinosad biosynthesis, namely, 5-methyltetrahydropteroyltriglutamate-homocysteine S-methyltransferase (MHSM), glutamine synthetase (GS) and cyclic nucleotide-binding domain-containing protein (CNDP) was validated by western blot, which confirmed the results of proteomic analysis.

Conclusions

This study is the first systematic analysis of the S. spinosa proteome during fermentation and its valuable proteomic data of regulatory proteins may be used to enhance the production yield of spinosad in future studies.

Metabolomics for secondary metabolite research

Metabolomics, the global characterization of metabolite profiles, is becoming an increasingly powerful tool for research on secondary metabolite discovery and production. In this review we discuss examples of recent technological advances and biological applications of metabolomics in the search for chemical novelty and the engineered production of bioactive secondary metabolites.

Direct proteomic quantification of the secretome of activated immune cells

Protein secretion allows communication of distant cells in an organism and controls a broad range of physiological functions. We describe a quantitative, high-resolution mass spectrometric workflow to detect and quantify proteins that are released from immune cells upon receptor ligation. We quantified the time-resolved release of 775 proteins, including 52 annotated cytokines from only 150,000 primary Toll-like receptor 4-activated macrophages per condition. Achieving low picogram sensitivity, we detected secreted proteins whose abundance increased by a factor of more than 10,000 upon stimulation. Secretome to transcriptome comparisons revealed the transcriptionally decoupled release of lysosomal proteins. From genetic models, we defined secretory profiles that depended on distinct intracellular signaling adaptors and showed that secretion of many proinflammatory proteins is safeguarded by redundant mechanisms, whereas signaling adaptor synergy promoted the release of anti-inflammatory proteins.

LC-MS metabolomics from study design to data-analysis - using a versatile pathogen as a test case

Thanks to significant improvements in LC-MS technology, metabolomics is increasingly used as a tool to discriminate the responses of organisms to various stimuli or drugs. In this minireview we discuss all aspects of the LC-MS metabolomics pipeline, using a complex and versatile model organism, Leishmania donovani, as an illustrative example. The benefits of a hyphenated mass spectrometry platform and a detailed overview of the entire experimental pipeline from sampling, sample storage and sample list set-up to LC-MS measurements and the generation of meaningful results with state-of-the-art data-analysis software will be thoroughly discussed. Finally, we also highlight important pitfalls in the processing of LC-MS data and comment on the benefits of implementing metabolomics in a systems biology approach.

Intracellular Metabolite Pool Changes in Response to Nutrient Depletion Induced Metabolic Switching in Streptomyces coelicolor

A metabolite profiling study of the antibiotic producing bacterium Streptomyces coelicolor A3(2) has been performed. The aim of this study was to monitor intracellular metabolite pool changes occurring as strains of S. coelicolor react to nutrient depletion with metabolic re-modeling, so-called metabolic switching, and transition from growth to secondary metabolite production phase. Two different culture media were applied, providing depletion of the key nutrients phosphate and L-glutamate, respectively, as the triggers for metabolic switching. Targeted GC-MS and LC-MS methods were employed to quantify important primary metabolite groups like amino acids, organic acids, sugar phosphates and other phosphorylated metabolites, and nucleotides in time-course samples withdrawn from fully-controlled batch fermentations. A general decline, starting already in the early growth phase, was observed for nucleotide pools and phosphorylated metabolite pools for both the phosphate and glutamate limited cultures. The change in amino acid and organic acid pools were more scattered, especially in the phosphate limited situation while a general decrease in amino acid and non-amino organic acid pools was observed in the L-glutamate limited situation. A phoP deletion mutant showed basically the same metabolite pool changes as the wild-type strain M145 when cultivated on phosphate limited medium. This implies that the inactivation of the phoP gene has only little effect on the detected metabolite levels in the cell. The energy charge was found to be relatively constant during growth, transition and secondary metabolite production phase. The results of this study and the employed targeted metabolite profiling methodology are directly relevant for the evaluation of precursor metabolite and energy supply for both natural and heterologous production of secondary metabolites in S. coelicolor.

Metabolomics methods for the synthetic biology of secondary metabolism

Many microbial secondary metabolites are of high biotechnological value for medicine, agriculture, and the food industry. Bacterial genome mining has revealed numerous novel secondary metabolite biosynthetic gene clusters, which encode the potential to synthesize a large diversity of compounds that have never been observed before. The stimulation or "awakening" of this cryptic microbial secondary metabolism has naturally attracted the attention of synthetic microbiologists, who exploit recent advances in DNA sequencing and synthesis to achieve unprecedented control over metabolic pathways. One of the indispensable tools in the synthetic biology toolbox is metabolomics, the global quantification of small biomolecules. This review illustrates the pivotal role of metabolomics for the synthetic microbiology of secondary metabolism, including its crucial role in novel compound discovery in microbes, the examination of side products of engineered metabolic pathways, as well as the identification of major bottlenecks for the overproduction of compounds of interest, especially in combination with metabolic modeling. We conclude by highlighting remaining challenges and recent technological advances that will drive metabolomics towards fulfilling its potential as a cornerstone technology of synthetic microbiology.