BackgroundAccurate 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.ResultsIn 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.ConclusionThis study identified cysG/hcaT/idnT to be reliable novel reference genes for transcription analysis in recombinant protein producing E. coli.

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.

ObjectiveAn 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.DesignWe 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.ResultsWe 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).ConclusionWe developed and validated a serum 12-miRNA biomarker assay, which may be a cost-effective risk assessment for gastric cancer.Trial registration numberThis study is registered with ClinicalTrials.gov (Registration number: NCT04329299).

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