Development of a serum miRNA panel for detection of early stage non-small cell lung cancer.

Minimally invasive testing for early detection of lung cancer to improve patient survival is a major unmet clinical need. This study aimed to develop and validate a serum multi-microRNA (multimiR) panel as a minimally invasive test for early detection of nonsmall cell lung cancer (NSCLC) regardless of smoking status, gender, and ethnicity. Our study included 744 NSCLC cases and 944 matched controls, including smokers and nonsmokers, male and female, with Asian and Caucasian subjects. Using RT-qPCR and a tightly controlled workflow, we quantified the absolute expression of 520 circulating microRNAs (miRNAs) in a Chinese cohort of 180 early stage NSCLC cases and 216 healthy controls (male smokers). Candidate biomarkers were verified in two case-control cohorts of 432 Chinese and 218 Caucasians, respectively (including females and nonsmokers). A multimiR panel for NSCLC detection was developed using a twofold cross-validation and validated in three additional Asian cohorts comprising 642 subjects. We discovered 35 candidate miRNA biomarkers, verified 22 of them, and developed a five-miR panel that detected NSCLC with area under curve (AUC) of 0.936-0.984 in the discovery and verification cohorts. The panel was validated in three independent cohorts with AUCs of 0.973, 0.916, and 0.917. The sensitivity of five-miR test was 81.3% for all stages, 82.9% for stages I and II, and 83.0% for stage I NSCLC, when the specificity is at 90.7%. We developed a minimally invasive five-miR serum test for detecting early stage NSCLC and validated its performance in multiple patient cohorts independent of smoking status, gender, and ethnicity.

Development and validation of a circulating microRNA panel for the early detection of breast cancer.

BACKGROUND: Mammography is widely used for breast cancer screening but suffers from a high false-positive rate. Here, we perform the largest comprehensive, multi-center study to date involving diverse ethnic groups, for the identification of circulating miRNAs for breast cancer screening. METHODS: This study had a discovery phase (n = 289) and two validation phases (n = 374 and n = 379). Quantitative PCR profiling of 324 miRNAs was performed on serum samples from breast cancer (all stages) and healthy subjects to identify miRNA biomarkers. Two-fold cross-validation was used for building and optimising breast cancer-associated miRNA panels. An optimal panel was validated in cohorts with Caucasian and Asian samples. Diagnostic ability was evaluated using area under the curve (AUC) analysis. RESULTS: The study identified and validated 30 miRNAs dysregulated in breast cancer. An optimised eight-miRNA panel showed consistent performance in all cohorts and was successfully validated with AUC, accuracy, sensitivity, and specificity of 0.915, 82.3%, 72.2% and 91.5%, respectively. The prediction model detected breast cancer in both Caucasian and Asian populations with AUCs ranging from 0.880 to 0.973, including pre-malignant lesions (stage 0; AUC of 0.831) and early-stage (stages I-II) cancers (AUC of 0.916). CONCLUSIONS: Our panel can potentially be used for breast cancer screening, in conjunction with mammography.

Development and validation of a serum microRNA biomarker panel for detecting gastric cancer in a high-risk population.

OBJECTIVE: An unmet need exists for a non-invasive biomarker assay to aid gastric cancer diagnosis. We aimed to develop a serum microRNA (miRNA) panel for identifying patients with all stages of gastric cancer from a high-risk population. DESIGN: We conducted a three-phase, multicentre study comprising 5248 subjects from Singapore and Korea. Biomarker discovery and verification phases were done through comprehensive serum miRNA profiling and multivariant analysis of 578 miRNA candidates in retrospective cohorts of 682 subjects. A clinical assay was developed and validated in a prospective cohort of 4566 symptomatic subjects who underwent endoscopy. Assay performance was confirmed with histological diagnosis and compared with Helicobacter pylori (HP) serology, serum pepsinogens (PGs), 'ABC' method, carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA19-9). Cost-effectiveness was analysed using a Markov decision model. RESULTS: We developed a clinical assay for detection of gastric cancer based on a 12-miRNA biomarker panel. The 12-miRNA panel had area under the curve (AUC)=0.93 (95% CI 0.90 to 0.95) and AUC=0.92 (95% CI 0.88 to 0.96) in the discovery and verification cohorts, respectively. In the prospective study, overall sensitivity was 87.0% (95% CI 79.4% to 92.5%) at specificity of 68.4% (95% CI 67.0% to 69.8%). AUC was 0.848 (95% CI 0.81 to 0.88), higher than HP serology (0.635), PG 1/2 ratio (0.641), PG index (0.576), ABC method (0.647), CEA (0.576) and CA19-9 (0.595). The number needed to screen is 489 annually. It is cost-effective for mass screening relative to current practice (incremental cost-effectiveness ratio=US$44 531/quality-of-life year). CONCLUSION: We developed and validated a serum 12-miRNA biomarker assay, which may be a cost-effective risk assessment for gastric cancer. TRIAL REGISTRATION NUMBER: This study is registered with ClinicalTrials.gov (Registration number: NCT04329299).

Molecular exploration of paediatric intracranial germinomas from multi-ethnic Singapore.

BACKGROUND: Germinomas (IG) account for up to 50% of all intracranial germ cell tumours. These tumours are reputed to be more prevalent in Oriental populations in comparison to Western cohorts. Biological characteristics of IG in other ethnic groups are unknown. Singapore is a multi-ethnic country with diverse cultures. Owing to inter-racial heterogeneity, the authors hypothesize there are molecular differences between paediatric IG patients in our local population. The aims of this study are exploratory: firstly, to identify molecular characteristics in this tumour type and circulating CSF unique to different racial cohorts; and next, to corroborate our findings with published literature. METHODS: This is a single-institution, retrospective study of prospectively collected data. Inclusion criteria encompass all paediatric patients with histologically confirmed IG. Excess CSF and brain tumour tissues are collected for molecular analysis. Tumour tissues are subjected to a next generation sequencing (NGS) targeted panel for KIT and PDGRA. All CSF samples are profiled via a high-throughput miRNA multiplexed workflow. Results are then corroborated with existing literature and public databases. RESULTS: In our cohort of 14 patients, there are KIT exon variants in the tumour tissues and CSF miRNAs corroborative with published studies. Separately, there are also KIT exon variants and miRNAs not previously highlighted in IG. A subgroup analysis demonstrates differential CSF miRNAs between Chinese and Malay IG patients. CONCLUSION: This is the first in-depth molecular study of a mixed ethnic population of paediatric IGs from a Southeast Asian cohort. Validation studies are required to assess the relevance of novel findings in our study.

Experimental design-aided systematic pathway optimization of glucose uptake and deoxyxylulose phosphate pathway for improved amorphadiene production.

Artemisinin is a potent antimalarial drug; however, it suffers from unstable and insufficient supply from plant source. Here, we established a novel multivariate-modular approach based on experimental design for systematic pathway optimization that succeeded in improving the production of amorphadiene (AD), the precursor of artemisinin, in Escherichia coli. It was initially found that the AD production was limited by the imbalance of glyceraldehyde 3-phosphate (GAP) and pyruvate (PYR), the two precursors of the 1-deoxy-D-xylulose-5-phosphate (DXP) pathway. Furthermore, it was identified that GAP and PYR could be balanced by replacing the phosphoenolpyruvate (PEP)-dependent phosphotransferase system (PTS) with the ATP-dependent galactose permease and glucose kinase system (GGS) and this resulted in fivefold increase in AD titer (11 to 60 mg/L). Subsequently, the experimental design-aided systematic pathway optimization (EDASPO) method was applied to systematically optimize the transcriptional expressions of eight critical genes in the glucose uptake and the DXP and AD synthesis pathways. These genes were classified into four modules and simultaneously controlled by T7 promoter or its variants. A regression model was generated using the four-module experimental data and predicted the optimal expression ratios among these modules, resulting in another threefold increase in AD titer (60 to 201 mg/L). This EDASPO method may be useful for the optimization of other pathways and products beyond the scope of this study.

Optimization of amorphadiene synthesis in bacillus subtilis via transcriptional, translational, and media modulation.

Genetically engineered microbes have been intensively investigated as a means for the cost-effective production of isoprenoids. Bacillus subtilis is a promising microbial host for this purpose because of its fast growth rate and GRAS (generally regarded as safe) status. To date, development of this host has been impaired by the lack of genetic tools for modulating the expression of multiple genes. In this study, we present a novel two-promoter system which can be used to independently control the expression levels of two gene cassettes over a large dynamic range. Coupled with protein translation engineering and systematic media optimization, ~20 mg/L amorphadiene was produced in shake flask scale, a 40-fold improvement over the highest reported isoprenoid product yield in B. subtilis. As the tools and strategies developed here can be extended to the overproduction of other valuable metabolites, this proof-of-concept study lays the foundation for high level heterologous production of isoprenoids in Bacillus.

A Spatial-Temporal Transformer Architecture Using Multi-Channel Signals for Sleep Stage Classification.

Sleep stage classification is a fundamental task in diagnosing and monitoring sleep diseases. There are 2 challenges that remain open: (1) Since most methods only rely on input from a single channel, the spatial-temporal relationship of sleep signals has not been fully explored. (2) Lack of sleep data makes models hard to train from scratch. Here, we propose a vision Transformer-based architecture to process multi-channel polysomnogram signals. The method is an end-to-end framework that consists of a spatial encoder, a temporal encoder, and an MLP head classifier. The spatial encoder using a pre-trained Vision Transformer captures spatial information from multiple PSG channels. The temporal encoder utilizing the self-attention mechanism understands transitions between nearby epochs. In addition, we introduce a tailored image generation method to extract features within multi-channel and reshape them for transfer learning. We validate our method on 3 datasets and outperform the state-of-the-art algorithms. Our method fully explores the spatial-temporal relationship among different brain regions and addresses the problem of data insufficiency in clinical environments. Benefiting from reformulating the problem as image classification, the method could be applied to other 1D-signal problems in the future.

Preanalytic Methodological Considerations and Sample Quality Control of Circulating miRNAs.

As miRNAs emerge as potential circulating biomarkers for the diagnosis or prognosis of a wide variety of diseases, the quantification of miRNA necessitates careful preanalytic considerations and sample quality control becomes crucial. This study comprehensively analyzed the profiles of 356 miRNAs by quantitative RT-PCR in various blood sample types, with various processing protocols. The comprehensive analysis investigated the correlations of individual miRNAs with certain confounding factors. On the basis of these profiles, a panel of 7 miRNAs was established for the quality control of samples corresponding to hemolysis and platelet contamination. The panel was used to investigate the confounding impacts based on the size of the blood collection tube, the centrifugation protocol, post-freeze-thaw spinning, and whole blood storage. A standard dual-spin workflow for the processing of blood had been established for optimal sample quality. The real-time stability of 356 miRNAs was also investigated with demonstration of the temperature and time-induced miRNA degradation profile. Stability-related miRNAs were identified from real-time stability study and further incorporated into the quality control panel. This quality control panel enables the assessment of sample quality for more robust and reliable detection of circulating miRNAs.

Enhancing solubility of deoxyxylulose phosphate pathway enzymes for microbial isoprenoid production.

BACKGROUND: Recombinant proteins are routinely overexpressed in metabolic engineering. It is well known that some over-expressed heterologous recombinant enzymes are insoluble with little or no enzymatic activity. This study examined the solubility of over-expressed homologous enzymes of the deoxyxylulose phosphate pathway (DXP) and the impact of inclusion body formation on metabolic engineering of microbes. RESULTS: Four enzymes of this pathway (DXS, ISPG, ISPH and ISPA), but not all, were highly insoluble, regardless of the expression systems used. Insoluble dxs (the committed enzyme of DXP pathway) was found to be inactive. Expressions of fusion tags did not significantly improve the solubility of dxs. However, hypertonic media containing sorbitol, an osmolyte, successfully doubled the solubility of dxs, with the concomitant improvement in microbial production of the metabolite, DXP. Similarly, sorbitol significantly improved the production of soluble and functional ERG12, the committed enzyme in the mevalonate pathway. CONCLUSION: This study demonstrated the unanticipated findings that some over-expressed homologous enzymes of the DXP pathway were highly insoluble, forming inclusion bodies, which affected metabolite formation. Sorbitol was found to increase both the solubility and function of some of these over-expressed enzymes, a strategy to increase the production of secondary metabolites.

Novel reference genes for quantifying transcriptional responses of Escherichia coli to protein overexpression by quantitative PCR.

BACKGROUND: Accurate interpretation of quantitative PCR (qPCR) data requires normalization using constitutively expressed reference genes. Ribosomal RNA is often used as a reference gene for transcriptional studies in E. coli. However, the choice of reliable reference genes has not been systematically validated. The objective of this study is to identify a set of reliable reference genes for transcription analysis in recombinant protein over-expression studies in E. coli. RESULTS: In this study, the meta-analysis of 240 sets of single-channel Affymetrix microarray data representing over-expressions of 63 distinct recombinant proteins in various E. coli strains identified twenty candidate reference genes that were stably expressed across all conditions. The expression of these twenty genes and two commonly used reference genes, rrsA encoding ribosomal RNA 16S and ihfB, was quantified by qPCR in E. coli cells over-expressing four genes of the 1-Deoxy-D-Xylulose 5-Phosphate pathway. From these results, two independent statistical algorithms identified three novel reference genes cysG, hcaT, and idnT but not rrsA and ihfB as highly invariant in two E. coli strains, across different growth temperatures and induction conditions. Transcriptomic data normalized by the geometric average of these three genes demonstrated that genes of the lycopene synthetic pathway maintained steady expression upon enzyme overexpression. In contrast, the use of rrsA or ihfB as reference genes led to the mis-interpretation that lycopene pathway genes were regulated during enzyme over-expression. CONCLUSION: This study identified cysG/hcaT/idnT to be reliable novel reference genes for transcription analysis in recombinant protein producing E. coli.

Systematic evaluation of multiple qPCR platforms, NanoString and miRNA-Seq for microRNA biomarker discovery in human biofluids.

Aberrant miRNA expression has been associated with many diseases, and extracellular miRNAs that circulate in the bloodstream are remarkably stable. Recently, there has been growing interest in identifying cell-free circulating miRNAs that can serve as non-invasive biomarkers for early detection of disease or selection of treatment options. However, quantifying miRNA levels in biofluids is technically challenging due to their low abundance. Using reference samples, we performed a cross-platform evaluation in which miRNA profiling was performed on four different qPCR platforms (MiRXES, Qiagen, Applied Biosystems, Exiqon), nCounter technology (NanoString), and miRNA-Seq. Overall, our results suggest that using miRNA-Seq for discovery and targeted qPCR for validation is a rational strategy for miRNA biomarker development in clinical samples that involve limited amounts of biofluids.

Development of a microRNA Panel for Classification of Abnormal Mammograms for Breast Cancer.

Mammography is extensively used for breast cancer screening but has high false-positive rates. Here, prospectively collected blood samples were used to identify circulating microRNA (miRNA) biomarkers to discriminate between malignant and benign breast lesions among women with abnormal mammograms. The Discovery cohort comprised 72 patients with breast cancer and 197 patients with benign breast lesions, while the Validation cohort had 73 and 196 cancer and benign cases, respectively. Absolute expression levels of 324 miRNAs were determined using RT-qPCR. miRNA biomarker panels were identified by: (1) determining differential expression between malignant and benign breast lesions, (2) focusing on top differentially expressed miRNAs, and (3) building panels from an unbiased search among all expressed miRNAs. Two-fold cross-validation incorporating a feature selection algorithm and logistic regression was performed. A six-miRNA biomarker panel identified by the third strategy, had an area under the curve (AUC) of 0.785 and 0.774 in the Discovery and Validation cohorts, respectively, and an AUC of 0.881 when differentiating between cases versus those with benign lesions or healthy individuals with normal mammograms. Biomarker panel scores increased with tumor size, stage and number of lymph nodes involved. Our work demonstrates that circulating miRNA signatures can potentially be used with mammography to differentiate between patients with malignant and benign breast lesions.

Combining Circulating MicroRNA and NT-proBNP to Detect and Categorize Heart Failure Subtypes.

BACKGROUND: Clinicians need improved tools to better identify nonacute heart failure with preserved ejection fraction (HFpEF). OBJECTIVES: The purpose of this study was to derive and validate circulating microRNA signatures for nonacute heart failure (HF). METHODS: Discovery and validation cohorts (N = 1,710), comprised 903 HF and 807 non-HF patients from Singapore and New Zealand (NZ). MicroRNA biomarker panel discovery in a Singapore cohort (n = 546) was independently validated in a second Singapore cohort (Validation 1; n = 448) and a NZ cohort (Validation 2; n = 716). RESULTS: In discovery, an 8-microRNA panel identified HF with an area under the curve (AUC) 0.96, specificity 0.88, and accuracy 0.89. Corresponding metrics were 0.88, 0.66, and 0.77 in Validation 1, and 0.87, 0.58, and 0.74 in Validation 2. Combining microRNA panels with N-terminal pro-B-type natriuretic peptide (NT-proBNP) clearly improved specificity and accuracy from AUC 0.96, specificity 0.91, and accuracy 0.90 for NT-proBNP alone to corresponding metrics of 0.99, 0.99, and 0.93 in the discovery and 0.97, 0.96, and 0.93 in Validation 1. The 8-microRNA discovery panel distinguished HFpEF from HF with reduced ejection fraction with AUC 0.81, specificity 0.66, and accuracy 0.72. Corresponding metrics were 0.65, 0.41, and 0.56 in Validation 1 and 0.65, 0.41, and 0.62 in Validation 2. For phenotype categorization, combined markers achieved AUC 0.87, specificity 0.75, and accuracy 0.77 in the discovery with corresponding metrics of 0.74, 0.59, and 0.67 in Validation 1 and 0.72, 0.52, and 0.68 in Validation 2, as compared with NT-proBNP alone of AUC 0.71, specificity 0.46, and accuracy 0.62 in the discovery; with corresponding metrics of 0.72, 0.44, and 0.57 in Validation 1 and 0.69, 0.48, and 0.66 in Validation 2. Accordingly, false negative (FN) (81% Singapore and all NZ FN cases were HFpEF) as classified by a guideline-endorsed NT-proBNP ruleout threshold, were correctly reclassified by the 8-microRNA panel in the majority (72% and 88% of FN in Singapore and NZ, respectively) of cases. CONCLUSIONS: Multi-microRNA panels in combination with NT-proBNP are highly discriminatory and improved specificity and accuracy in identifying nonacute HF. These findings suggest potential utility in the identification of nonacute HF, where clinical assessment, imaging, and NT-proBNP may not be definitive, especially in HFpEF.

In Vitro Metabolic Engineering of Amorpha-4,11-diene Biosynthesis at Enhanced Rate and Specific Yield of Production.

In vitro metabolic engineering is an alternative approach to cell-based biosynthesis. It offers unprecedented flexibility for the study of biochemical pathways, thus providing useful information for the rational design and assembly of reaction modules. Herein, we took the advantage of in vitro metabolic engineering to initially gain insight into the regulatory network of a reconstituted amorpha-4,11-diene (AD) synthetic pathway. Guided by lin-log approximation, we rapidly identified the hitherto unrecognized inhibition of adenosine triphosphate (ATP) on both farnesyl pyrophosphate synthase (FPPS) and amorpha-4,11-diene synthase (ADS). Furthermore, the byproduct, pyrophosphate (PPi), potently inhibits ADS, but not FPPS. To lower the inhibition, an ATP recycling system and pyrophosphatase were used and resulted in a significant (∼3-fold) enhancement in the rate of AD production (∼5.7 µmol L-1 min-1). A coimmobilized multienzyme reaction system was then developed to recycle the enzymes. When inhibitory metabolites concentrations were reduced, the specific enzymatic yield of AD was further enhanced (>6-fold). This study demonstrated that mitigating the accumulation of inhibitory metabolites can result in higher yields of AD production by in vitro multienzymatic reactions.

Establishing multiple omics baselines for three Southeast Asian populations in the Singapore Integrative Omics Study.

The Singapore Integrative Omics Study provides valuable insights on establishing population reference measurement in 364 Chinese, Malay, and Indian individuals. These measurements include > 2.5 millions genetic variants, 21,649 transcripts expression, 282 lipid species quantification, and 284 clinical, lifestyle, and dietary variables. This concept paper introduces the depth of the data resource, and investigates the extent of ethnic variation at these omics and non-omics biomarkers. It is evident that there are specific biomarkers in each of these platforms to differentiate between the ethnicities, and intra-population analyses suggest that Chinese and Indians are the most biologically homogeneous and heterogeneous, respectively, of the three groups. Consistent patterns of correlations between lipid species also suggest the possibility of lipid tagging to simplify future lipidomics assays. The Singapore Integrative Omics Study is expected to allow the characterization of intra-omic and inter-omic correlations within and across all three ethnic groups through a systems biology approach.The Singapore Genome Variation projects characterized the genetics of Singapore's Chinese, Malay, and Indian populations. The Singapore Integrative Omics Study introduced here goes further in providing multi-omic measurements in individuals from these populations, including genetic, transcriptome, lipidome, and lifestyle data, and will facilitate the study of common diseases in Asian communities.

Combinatorial engineering of 1-deoxy-D-xylulose 5-phosphate pathway using cross-lapping in vitro assembly (CLIVA) method.

The ability to assemble multiple fragments of DNA into a plasmid in a single step is invaluable to studies in metabolic engineering and synthetic biology. Using phosphorothioate chemistry for high efficiency and site specific cleavage of sequences, a novel ligase independent cloning method (cross-lapping in vitro assembly, CLIVA) was systematically and rationally optimized in E. coli. A series of 16 constructs combinatorially expressing genes encoding enzymes in the 1-deoxy-D-xylulose 5-phosphate (DXP) pathway were assembled using multiple DNA modules. A plasmid (21.6 kb) containing 16 pathway genes, was successfully assembled from 7 modules with high efficiency (2.0 x 10(3) cfu/ µg input DNA) within 2 days. Overexpressions of these constructs revealed the unanticipated inhibitory effects of certain combinations of genes on the production of amorphadiene. Interestingly, the inhibitory effects were correlated to the increase in the accumulation of intracellular methylerythritol cyclodiphosphate (MEC), an intermediate metabolite in the DXP pathway. The overexpression of the iron sulfur cluster operon was found to modestly increase the production of amorphadiene. This study demonstrated the utility of CLIVA in the assembly of multiple fragments of DNA into a plasmid which enabled the rapid exploration of biological pathways.

Combining genotype improvement and statistical media optimization for isoprenoid production in E. coli.

Isoprenoids are a large and diverse class of compounds that includes many high value natural products and are thus in great demand. To meet the increasing demand for isoprenoid compounds, metabolic engineering of microbes has been used to produce isoprenoids in an economical and sustainable manner. To achieve high isoprenoid yields using this technology, the availability of metabolic precursors feeding the deoxyxylulose phosphate (DXP) pathway, responsible for isoprenoid biosynthesis, has to be optimized. In this study, phosphoenolpyruvate, a vital DXP pathway precursor, was enriched by deleting the genes encoding the carbohydrate phosphotransferase system (PTS) in E. coli. Production of lycopene (a C40 isoprenoid) was maximized by optimizing growth medium and culture conditions. In optimized conditions, the lycopene yield from PTS mutant was seven fold higher than that obtained from the wild type strain. This resulted in the highest reported specific yield of lycopene produced from the DXP pathway in E. coli to date (20,000 µg/g dry cell weight). Both the copy number of the plasmid encoding the lycopene biosynthetic genes and the expression were found to be increased in the optimized media. Deletion of PTS together with a similar optimization strategy was also successful in enhancing the production of amorpha-1,4-diene, a distinct C15 isoprenoid, suggesting that the approaches developed herein can be generally applied to optimize production of other isoprenoids.

Statistical experimental design guided optimization of a one-pot biphasic multienzyme total synthesis of amorpha-4,11-diene.

In vitro synthesis of chemicals and pharmaceuticals using enzymes is of considerable interest as these biocatalysts facilitate a wide variety of reactions under mild conditions with excellent regio-, chemo- and stereoselectivities. A significant challenge in a multi-enzymatic reaction is the need to optimize the various steps involved simultaneously so as to obtain high-yield of a product. In this study, statistical experimental design was used to guide the optimization of a total synthesis of amorpha-4,11-diene (AD) using multienzymes in the mevalonate pathway. A combinatorial approach guided by Taguchi orthogonal array design identified the local optimum enzymatic activity ratio for Erg12:Erg8:Erg19:Idi:IspA to be 100∶100∶1∶25∶5, with a constant concentration of amorpha-4,11-diene synthase (Ads, 100 mg/L). The model also identified an unexpected inhibitory effect of farnesyl pyrophosphate synthase (IspA), where the activity was negatively correlated with AD yield. This was due to the precipitation of farnesyl pyrophosphate (FPP), the product of IspA. Response surface methodology was then used to optimize IspA and Ads activities simultaneously so as to minimize the accumulation of FPP and the result showed that Ads to be a critical factor. By increasing the concentration of Ads, a complete conversion (∼100%) of mevalonic acid (MVA) to AD was achieved. Monovalent ions and pH were effective means of enhancing the specific Ads activity and specific AD yield significantly. The results from this study represent the first in vitro reconstitution of the mevalonate pathway for the production of an isoprenoid and the approaches developed herein may be used to produce other isopentenyl pyrophosphate (IPP)/dimethylallyl pyrophosphate (DMAPP) based products.

Metabolite profiling identified methylerythritol cyclodiphosphate efflux as a limiting step in microbial isoprenoid production.

Isoprenoids are natural products that are all derived from isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP). These precursors are synthesized either by the mevalonate (MVA) pathway or the 1-Deoxy-D-Xylulose 5-Phosphate (DXP) pathway. Metabolic engineering of microbes has enabled overproduction of various isoprenoid products from the DXP pathway including lycopene, artemisinic acid, taxadiene and levopimaradiene. To date, there is no method to accurately measure all the DXP metabolic intermediates simultaneously so as to enable the identification of potential flux limiting steps. In this study, a solid phase extraction coupled with ultra performance liquid chromatography mass spectrometry (SPE UPLC-MS) method was developed. This method was used to measure the DXP intermediates in genetically engineered E. coli. Unexpectedly, methylerythritol cyclodiphosphate (MEC) was found to efflux when certain enzymes of the pathway were over-expressed, demonstrating the existence of a novel competing pathway branch in the DXP metabolism. Guided by these findings, ispG was overexpressed and was found to effectively reduce the efflux of MEC inside the cells, resulting in a significant increase in downstream isoprenoid production. This study demonstrated the necessity to quantify metabolites enabling the identification of a hitherto unrecognized pathway and provided useful insights into rational design in metabolic engineering.

An environment-sensitive synthetic microbial ecosystem.

Microbial ecosystems have been widely used in industrial production, but the inter-relationships of organisms within them haven't been completely clarified due to complex composition and structure of natural microbial ecosystems. So it is challenging for ecologists to get deep insights on how ecosystems function and interplay with surrounding environments. But the recent progresses in synthetic biology show that construction of artificial ecosystems where relationships of species are comparatively clear could help us further uncover the meadow of those tiny societies. By using two quorum-sensing signal transduction circuits, this research designed, simulated and constructed a synthetic ecosystem where various population dynamics formed by changing environmental factors. Coherent experimental data and mathematical simulation in our study show that different antibiotics levels and initial cell densities can result in correlated population dynamics such as extinction, obligatory mutualism, facultative mutualism and commensalism. This synthetic ecosystem provides valuable information for addressing questions in ecology and may act as a chassis for construction of more complex microbial ecosystems.