The Applications of Promoter-gene-Engineered Biosensors

Genome-wide identification of MBD gene family members in Eleutherococcus senticosus with their expression motifs under drought stress and DNA demethylation

BACKGROUND

Methyl-binding domain (MBD) is a class of methyl-CpG-binding domain proteins that affects the regulation of gene expression through epigenetic modifications. MBD genes are not only inseparable from DNA methylation but have also been identified and validated in various plants. Although MBD is involved in a group of physiological processes and stress regulation in these plants, MBD genes in Eleutherococcus senticosus remain largely unknown.

RESULTS

Twenty EsMBD genes were identified in E. senticosus. Among the 24 chromosomes of E. senticosus, EsMBD genes were unevenly distributed on 12 chromosomes, and only one tandem repeat gene existed. Collinearity analysis showed that the fragment duplication was the main motif for EsMBD gene expansion. As the species of Araliaceae evolved, MBD genes also evolved and gradually exhibited different functional differentiation. Furthermore, cis-acting element analysis showed that there were numerous cis-acting elements in the EsMBD promoter region, among which light response elements and anaerobic induction elements were dominant. The expression motif analysis revealed that 60% of the EsMBDs were up-regulated in the 30% water content group.

CONCLUSIONS

By comparing the transcriptome data of different saponin contents of E. senticosus and integrating them with the outcomes of molecular docking analysis, we hypothesized that EsMBD2 and EsMBD5 jointly affect the secondary metabolic processes of E. senticosus saponins by binding to methylated CpG under conditions of drought stress. The results of this study laid the foundation for subsequent research on the E. senticosus and MBD genes.

Development of a synthetic transcription factor-based S-adenosylmethionine biosensor in Saccharomyces cerevisiae

S-Adenosylmethionine (SAM) is a crucial small-molecule metabolite widely used in food and medicine. The development of high-throughput biosensors for SAM biosynthesis can significantly improve the titer of SAM. This paper constructed a synthetic transcription factor (TF)-based biosensor for SAM detecting in Saccharomyces cerevisiae. The synthetic TF, named MetJ-hER-VP16, consists of an Escherichia coli-derived DNA-binding domain MetJ, GS linker, the human estrogen receptor binding domain hER, and the viral activation domain VP16. The synthetic biosensor is capable of sensing SAM in a dose-dependent manner with fluorescence as the output. Additionally, it is tightly regulated by the inducer SAM and β-estradiol, which means that the fluorescence output is only available when both are present together. The synthetic SAM biosensor could potentially be applied for high-throughput metabolic engineering and is expected to improve SAM production.

Evolved Biosensor with High Sensitivity and Specificity for Measuring Cadmium in Actual Environmental Samples

Bacterial biosensors have great potential in contaminant detection for sensitivity, specificity, cost-effectiveness, and easy operation. However, the existing cadmium-responsive bacterial biosensors cannot meet the real-world detection requirements due to lack of sensitivity, specificity, and anti-interference capability. This study aimed to develop a bacterial biosensor for detecting the total and extractable cadmium in actual environmental samples. We constructed the cadmium-responsive biosensor with the regulatory element (cadmium resistance transcriptional regulatory, CadR) and the reporting element (GFP) and improved its performance by directed evolution. The mutant libraries of biosensors were generated by error-prone PCR and screened by continuous five-round fluorescence-activated cell sorting (FACS), and a bacteria variant epCadR5 with higher performance was finally isolated. Biosensor fluorescence intensity was measured by a microplate reader, and results showed that the evolved cadmium-responsive bacterial biosensor was of high sensitivity and specificity in detecting trace cadmium, with a detection limit of 0.45 μg/L, which is 6.8 times more specific to cadmium than that of the wild-type. Furthermore, microscopic qualitative analysis results showed that the bacteria could produce fluorescence response in a cadmium-contaminated soil matrix, and quantitative analysis results showed that the values of cadmium from epCadR5 bacteria were close to that from inductively coupled plasma-mass spectrometry. These results suggest that the biosensor may have a broad application prospect in the detection of cadmium-contaminated soil and water.

A Novel Coupled Reaction-Diffusion System for Explainable Gene Expression Profiling

Machine learning (ML)-based algorithms are playing an important role in cancer diagnosis and are increasingly being used to aid clinical decision-making. However, these commonly operate as 'black boxes' and it is unclear how decisions are derived. Recently, techniques have been applied to help us understand how specific ML models work and explain the rational for outputs. This study aims to determine why a given type of cancer has a certain phenotypic characteristic. Cancer results in cellular dysregulation and a thorough consideration of cancer regulators is required. This would increase our understanding of the nature of the disease and help discover more effective diagnostic, prognostic, and treatment methods for a variety of cancer types and stages. Our study proposes a novel explainable analysis of potential biomarkers denoting tumorigenesis in non-small cell lung cancer. A number of these biomarkers are known to appear following various treatment pathways. An enhanced analysis is enabled through a novel mathematical formulation for the regulators of mRNA, the regulators of ncRNA, and the coupled mRNA-ncRNA regulators. Temporal gene expression profiles are approximated in a two-dimensional spatial domain for the transition states before converging to the stationary state, using a system comprised of coupled-reaction partial differential equations. Simulation experiments demonstrate that the proposed mathematical gene-expression profile represents a best fit for the population abundance of these oncogenes. In future, our proposed solution can lead to the development of alternative interpretable approaches, through the application of ML models to discover unknown dynamics in gene regulatory systems.

Future perspective: high-throughput construction of new ultrasensitive cytokine and virion liquid chips for high-throughput screening (HTS) of anti-inflammatory drugs or clinical diagnosis and treatment of inflammatory diseases

Pathogen-host cell interactions play an important role in many human infectious and inflammatory diseases. Several pathogens, including Escherichia coli (E. coli), Mycobacterium tuberculosis (M. tb), and even the recent 2019 novel coronavirus (2019-nCoV), can cause serious breathing and brain disorders, tissue injury and inflammation, leading to high rates of mortality and resulting in great loss to human physical and mental health as well as the global economy. These infectious diseases exploit the microbial and host factors to induce serious inflammatory and immunological symptoms. Thus the development of anti-inflammatory drugs targeting bacterial/viral infection is an urgent need. In previous studies, YojI-IFNAR2, YojI-IL10RA, YojI-NRP1,YojI-SIGLEC7, and YojI-MC4R membrane-protein interactions were found to mediate E. coli invasion of the blood-brain barrier (BBB), which activated the downstream anti-inflammatory proteins NACHT, LRR and PYD domains-containing protein 2(NLRP2), using a proteomic chip conjugated with cell immunofluorescence labeling. However, the studies of pathogen (bacteria/virus)-host cell interactions mediated by membrane protein interactions did not extend their principles to broad biomedical applications such as 2019-nCoV infectious disease therapy. The first part of this feature article presents in-depth analysis of the cross-talk of cellular anti-inflammatory transduction signaling among interferon membrane protein receptor II (IFNAR2), interleukin-10 receptor subunit alpha (IL-10RA), NLRP2 and [Ca²⁺]-dependent phospholipase A2 (PLA2G5), based on experimental results and important published studies, which lays a theoretical foundation for the high-throughput construction of the cytokine and virion solution chip. The paper then moves on to the construction of the novel GPCR recombinant herpes virion chip and virion nano-oscillators for profiling membrane protein functions, which drove the idea of constructing the new recombinant virion and cytokine liquid chips for HTS of leading drugs. Due to the different structural properties of GPCR, IFNAR2, ACE2 and Spike of 2019-nCoV, their ligands will either bind the extracellular domain of IFNAR2/ACE2/Spike or the specific loops of the GPCR on the envelope of the recombinant herpes virions to induce dynamic charge distribution changes that lead to the variable electron transition for detection. Taken together, the combined overview of two of the most innovative and exciting developments in the immunoinflammatory field provides new insight into high-throughput construction of ultrasensitive cytokine and virion liquid chips for HTS of anti-inflammatory drugs or clinical diagnosis and treatment of inflammatory diseases including infectious diseases, acute or chronic inflammation (acute gouty arthritis or rheumatoid arthritis), cardiovascular disease, atheromatosis, diabetes, obesity, tissue injury and tumors. It has significant value in the prevention and treatment of these serious and painful diseases. Graphical abstract.

Transporter Engineering for Microbial Manufacturing

Microbes play an important role in biotransformation and biosynthesis of biofuels, natural products, and polymers. Therefore, microbial manufacturing has been widely used in medicine, industry, and agriculture. However, common strategies including enzyme engineering, pathway optimization, and host engineering are generally inadequate to obtain an efficient microbial production system. Transporter engineering provides an alternative strategy to promote the transmembrane transfer of substrates, intermediates, and final products in microbial cells and thus enhances production by alleviating feedback inhibition and cytotoxicity caused by final products. According to the current studies in transport engineering, native transporters usually have low expression and poor transportation ability, resulting in inefficient transport processes and microbial production. In this review, current approaches for transporter mining, characterization, and verification are comprehensively summarized. Practical approaches to enhance the transport system in engineered cells, such as balancing transporter overexpression and cell growth, and evolution of native transporters are discussed. Furthermore, the applications of transporter engineering in microbial manufacturing, including enhancement of substrate utilization, concentration of metabolic flux to the target pathway, and acceleration of efflux and recovery of products, demonstrate its outstanding advantages and promising prospects.

Tuning the Binding Affinity of Heme-Responsive Biosensor for Precise and Dynamic Pathway Regulation

Current challenge for dynamic pathway control in metabolic engineering is enabling the components of the artificial regulatory system to be tunable. Here, we designed and built a heme-responsive regulatory system containing a heme biosensor HrtR and CRISPRi to regulate chemicals production while maintaining the intracellular heme homeostasis. A series of engineered biosensors with varied sensitivity and threshold were obtained by semi-rational design with site saturated mutation of HrtR. The modified metabolite-binding affinity of HrtR was confirmed by heme titration and molecular dynamic simulation. Dynamic regulation pattern of the system was validated by the fluctuation of gene expression and intracellular heme concentration. The efficiency of this regulatory system was proved by improving the 5-aminolevulinic acid (ALA) production to 5.35g/L, the highest yield in batch fermentation of Escherichia coli. This system was also successfully used in improving porphobilinogen (PBG) and porphyrins biosynthesis and can be applied in many other biological processes.

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Designed and built a heme-responsive regulatory system employing HrtR and CRISPRi

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Turning the binding affinity of HrtR by site saturation mutations

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Optimizing the system to achieve dynamic regulation of target genes

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The system was applied to the ALA, PBG, and porphyrins production