Advances in bacterial whole-cell biosensors for the detection of bioavailable mercury: A review

Challenges and opportunities in commercializing whole-cell bioreporters in environmental application

Since the initial introduction of whole-cell bioreporters (WCBs) nearly 30 years ago, their high sensitivity, selectivity, and suitability for on-site detection have rendered them highly promising for environmental monitoring, medical diagnosis, food safety, biomanufacturing, and other fields. Especially in the environmental field, the technology provides a fast and efficient way to assess the bioavailability of pollutants in the environment. Despite these advantages, the technology has not been commercialized. This lack of commercialization is confusing, given the broad application prospects of WCBs. Over the years, numerous research papers have focused primarily on enhancing the sensitivity and selectivity of WCBs, with little attention paid to their wider commercial applications. So far, there is no a critical review has been published yet on this topic. Therefore, in this article we critically reviewed the research progress of WCBs over the past three decades, assessing the performance and limitations of current systems to understand the barriers to commercial deployment. By identifying these obstacles, this article provided researchers and industry stakeholders with deeper insights into the challenges hindering market entry and inspire further research toward overcoming these barriers, thereby facilitating the commercialization of WCBs as a promising technology for environmental monitoring.

Design, modeling and in silico simulation of bacterial biosensors for detecting heavy metals in irrigation water for precision agriculture

Sensors used in precision agriculture for the detection of heavy metals in irrigation water are generally expensive and sometimes their deployment and maintenance represent a permanent investment to keep them in operation, leaving a lasting polluting footprint in the environment at the end of their lifespan. This represents an area of opportunity to design new biological devices that can replace part, or all of the sensors currently used. In this article, a novel workflow is proposed to fully carry out the complete process of design, modeling, and simulation of reprogrammable microorganisms in silico. As a proof-of-concept, the workflow has been used to design three whole-cell biosensors for the detection of heavy metals in irrigation water, namely arsenic, mercury and lead. These biosensors are in compliance with the concentration limits established by the World Health Organization (WHO). The proposed workflow allows the design of a wide variety of completely in silico biodevices, which aids in solving problems that cannot be easily addressed with classical computing. The workflow is based on two technologies typical of synthetic biology: the design of synthetic genetic circuits, and in silico synthetic engineering, which allows us to address the design of reprogrammable microorganisms using software and hardware to develop theoretical models. These models enable the behavior prediction of complex biological systems. The output of the workflow is then exported in the form of complete genomes in SBOL, GenBank and FASTA formats, enabling their subsequent in vivo implementation in a laboratory. The present proposal enables professionals in the area of computer science to collaborate in biotechnological processes from a theoretical perspective previously or complementary to a design process carried out directly in the laboratory by molecular biologists. Therefore, key results pertaining to this work include the fully in silico workflow that leads to designs that can be tested in the lab in vitro or in vivo, and a proof-of-concept of how the workflow generates synthetic circuits in the form of three whole-cell heavy metal biosensors that were designed, modeled and simulated using the workflow. The simulations carried out show realistic spatial distributions of biosensors reacting to different concentrations (zero, low and threshold level) of heavy metal presence and at different growth phases (stationary and exponential) that are backed up by the whole design and modeling phases of the workflow.

Ultrasensitive detection of trace Hg(Ⅱ) in acidic conditions using DMABR loaded on sepiolite: Function, application and mechanism studies

Fast and real-time detection of trace Hg(Ⅱ) by fluorescent probes under acidic conditions is urgently required due to the high toxicity and accessibility to creatures and human being. However, fluorescent probes for Hg(Ⅱ) detection in environmental samples are rarely reported due to the protonation potential of acidic mercury sources. In this study, the SD probe was developed by 5-(p-dimethylaminobenzylidene) rhodanine (DMABR) loaded on sepiolite by hydrothermal treatment, and showed excellent Hg(Ⅱ) detection performances for mercury sources at pH 4-10 due to buffering ability of the hyperconjugated lactam rings. Sepiolite functioned as the support skeleton to decrease intermolecular transition, and thus increased the sensitivity. At pH 4, the SD probe showed high selectivity and sensitivity for Hg(Ⅱ) among various species, with low LOD and binding constant of 4.78 × 10-9 M and 1.34 × 106 M-1, respectively. Through DFT calculations, MAS 1H NMR and 2D-COS analysis, the detection mechanism was demonstrated as SN1 substitution of the spontaneous leaving H on amino groups in the transient state during tautomeric equilibrium, rather than the expected high-affinity sulphydryl. Additionally, the SD probe exhibited promising potential in quantifying water-soluble and bioavailable Hg(Ⅱ) in acidic polluted soil and water samples. Moreover, real-time detection was realized by paper-based strips.

Multiplex Detection of Foodborne Pathogens using 3D Nanostructure Swab and Deep Learning-Based Classification of Raman Spectra

Proactive management of foodborne illness requires routine surveillance of foodborne pathogens, which requires developing simple, rapid, and sensitive detection methods. Here, a strategy is presented that enables the detection of multiple foodborne bacteria using a 3D nanostructure swab and deep learning-based Raman signal classification. The nanostructure swab efficiently captures foodborne pathogens, and the portable Raman instrument directly collects the Raman signals of captured bacteria. a deep learning algorithm has been demonstrated, 1D convolutional neural network with binary labeling, achieves superior performance in classifying individual bacterial species. This methodology has been extended to mixed bacterial populations, maintaining accuracy close to 100%. In addition, the gradient-weighted class activation mapping method is used to provide an investigation of the Raman bands for foodborne pathogens. For practical application, blind tests are conducted on contaminated kitchen utensils and foods. The proposed technique is validated by the successful detection of bacterial species from the contaminated surfaces. The use of a 3D nanostructure swab, portable Raman device, and deep learning-based classification provides a powerful tool for rapid identification (≈5 min) of foodborne bacterial species. The detection strategy shows significant potential for reliable food safety monitoring, making a meaningful contribution to public health and the food industry.

Determinants of mer Promoter Activity from Pseudomonas aeruginosa

Since the MerR family is known for its special regulatory mechanism, we aimed to explore which factors determine the expression activity of the mer promoter. The Tn501/Tn21 mer promoter contains an abnormally long spacer (19 bp) between the -35 and -10 elements, which is essential for the unique DNA distortion mechanism. To further understand the role of base sequences in the mer promoter spacer, this study systematically engineered a series of mutant derivatives and used luminescent and fluorescent reporter genes to investigate the expression activity of these derivatives. The results reveal that the expression activity of the mer promoter is synergistically modulated by the spacer length (17 bp is optimal) and the region upstream of -10 (especially -13G). The spacing is regulated by MerR transcription factors through symmetrical sequences, and -13G presumably functions through interaction with the RNA polymerase sigma-70 subunit.

Replacing manual operation with bio-automation: A high-throughput evolution strategy to construct an integrated whole-cell biosensor for the simultaneous detection of methylmercury and mercury ions without manual sample digestion

Methylmercury is primarily responsible for most food mercury pollution cases. However, most biosensors developed for mercury pollution analysis can only detect mercury ions. Although oxidative strong-acid digestion or microwave-assisted digestion can convert methylmercury into mercury ions, it is unsuitable for on-site detection. This study designed a bio-digestion gene circuit and integrated it into a mercury ion whole-cell biosensor，creating a novel on-site methylmercury detection method. Five alkyl mercury lyases from different bacterial genomes were screened via bioinformatics analysis, of which goMerB from Gordonia otitis showed the highest catalytic biological digestion efficiency. The goMerB site-specific saturation and random mutation libraries were constructed. After two rounds of high-throughput visualization screening, the catalytic activity of the mutant increased 2.5-fold. The distance between the three crucial amino acid sites and methylmercury changed in the mutant, which likely contributed to the enhanced catalytic efficiency. The optimized whole-cell biosensor showed a linear dynamic concentration range of 100 nM to 100 μM (R2 =0.991), satisfactory specificity, and interference resistance. The detection limit of the goMerBt6-MerR-RFP biosensor was 0.015 μM, while the limit of quantitation was 0.049 μM. This study demonstrated the application of synthetic biology for food safety detection and highlighted the future potential of "Lab in a Cell" for hazard analysis.

Tailored bacteria tackling with environmental mercury: Inspired by natural mercuric detoxification operons

Mercury (Hg) and its inorganic and organic compounds significantly threaten the ecosystem and human health. However, the natural and anthropogenic Hg environmental inputs exceed 5000 metric tons annually. Hg is usually discharged in elemental or ionic forms, accumulating in surface water and sediments where Hg-methylating microbes-mediated biotransformation occurs. Microbial genetic factors such as the mer operon play a significant role in the complex Hg biogeochemical cycle. Previous reviews summarize the fate of environmental Hg, its biogeochemistry, and the mechanism of bacterial Hg resistance. This review mainly focuses on the mer operon and its components in detecting, absorbing, bioaccumulating, and detoxifying environmental Hg. Four components of the mer operon, including the MerR regulator, divergent mer promoter, and detoxification factors MerA and MerB, are rare bio-parts for assembling synthetic bacteria, which tackle pollutant Hg. Bacteria are designed to integrate synthetic biology, protein engineering, and metabolic engineering. In summary, this review highlights that designed bacteria based on the mer operon can potentially sense and bioremediate pollutant Hg in a green and low-cost manner.

Engineering the Ultrasensitive Visual Whole-Cell Biosensors by Evolved MerR and 5' UTR for Detection of Ultratrace Mercury

The existing mercury whole-cell biosensors (WCBs, parts per billion range) are not able to meet the real-world requirements due to their lack of sensitivity for the detection of ultratrace mercury in the environment. Ultratrace mercury is a potential threat to human health via the food chain. Here, we developed an ultrasensitive mercury WCB by directed evolution of the mercury-responsive transcriptional activator (MerR) sensing module to detect ultratrace mercury. Subsequently, the mutant WCB (m4-1) responding to mercury in the parts per trillion range after 1 h of induction was obtained. Its detection limit (LOD) was 0.313 ng/L, comparable to those of some analytical instruments. Surprisingly, the m4-1 WCB also responded to methylmercury (LOD = 98 ng/L), which is far more toxic than inorganic mercury. For more convenient detection, we have increased another green fluorescent protein reporter module with an optimized 5' untranslated region (5' UTR) sequence. This yields two visual WCBs with an enhanced fluorescence output. At a concentration of 2.5 ng/L, the fluorescence signals can be directly observed by the naked eye. With the combination of mobile phone imaging and image processing software, the 2GC WCB provided simple, rapid, and reliable quantitative and qualitative analysis of real samples (LOD = 0.307 ng/L). Taken together, these results indicate that the ultrasensitive visual whole-cell biosensors for ultratrace mercury detection are successfully designed using a combination of directed evolution and synthetic biotechnology.

Direct Uptake and Intracellular Dissolution of HgS Nanoparticles: Evidence from a Bacterial Biosensor Approach

Mercury sulfide nanoparticles (HgSNPs), which occur widely in oxic and anoxic environments, can be microbially converted to highly toxic methylmercury or volatile elemental mercury, but it remains challenging to assess their bioavailability. In this study, an Escherichia coli-based whole-cell fluorescent biosensor was developed to explore the bioavailability and microbial activation process of HgSNPs. Results show that HgSNPs (3.17 ± 0.96 nm) trigger a sharp increase in fluorescence intensity of the biosensor, with signal responses almost equal to that of ionic Hg (Hg(II)) within 10 h, indicating high bioavailability of HgSNP. The intracellular total Hg (THg) of cells exposed to HgSNPs (200 μg L-1) was 3.52-8.59-folds higher than that of cells exposed to Hg(II) (200 μg L-1), suggesting that intracellular HgSNPs were only partially dissolved. Speciation analysis using size-exclusion chromatography (SEC)-inductively coupled plasma mass spectrometry (ICP-MS) revealed that the bacterial filtrate was not responsible for HgSNP dissolution, suggesting that HgSNPs entered cells in nanoparticle form. Combined with fluorescence intensity and intracellular THg analysis, the intracellular HgSNP dissolution ratio was estimated at 22-29%. Overall, our findings highlight the rapid internalization and high intracellular dissolution ratio of HgSNPs by E. coli, and intracellular THg combined with biosensors could provide innovative tools to explore the microbial uptake and dissolution of HgSNPs.

Combining Copper and Zinc into a Biosensor for Anti-Chemoresistance and Achieving Osteosarcoma Therapeutic Efficacy

Due to its built-up chemoresistance after prolonged usage, the demand for replacing platinum in metal-based drugs (MBD) is rising. The first MBD approved by the FDA for cancer therapy was cisplatin in 1978. Even after nearly four and a half decades of trials, there has been no significant improvement in osteosarcoma (OS) therapy. In fact, many MBD have been developed, but the chemoresistance problem raised by platinum remains unresolved. This motivates us to elucidate the possibilities of the copper and zinc (CuZn) combination to replace platinum in MBD. Thus, the anti-chemoresistance properties of CuZn and their physiological functions for OS therapy are highlighted. Herein, we summarise their chelators, main organic solvents, and ligand functions in their structures that are involved in anti-chemoresistance properties. Through this review, it is rational to discuss their ligands' roles as biosensors in drug delivery systems. Hereafter, an in-depth understanding of their redox and photoactive function relationships is provided. The disadvantage is that the other functions of biosensors cannot be elaborated on here. As a result, this review is being developed, which is expected to intensify OS drugs with higher cure rates. Nonetheless, this advancement intends to solve the major chemoresistance obstacle towards clinical efficacy.