Blueprints for Biosensors: Design, Limitations, and Applications

Computation-guided transcription factor biosensor specificity engineering for adipic acid detection

Transcription factor (TF)-based biosensors that connect small-molecule sensing with readouts such as fluorescence have proven to be useful synthetic biology tools for applications in biotechnology. However, the development of specific TF-based biosensors is hindered by the limited repertoire of TFs specific for molecules of interest since current construction methods rely on a limited set of characterized TFs. In this study, we present an approach for engineering the specificity of TFs through a computation-based workflow using molecular docking that enables targeted alteration of TF ligand specificity. Using this method, we engineer the LysR family BenM TF to alter its specificity from its cognate ligand cis,cis-muconic acid to adipic acid through a single amino acid substitution identified by our computational workflow. When implemented in a cell-free system, the engineered biosensor shows higher ligand sensitivity, expanding the potential applications of this circuit. We further investigate ligand binding through molecular dynamics to analyze the substitution, elucidating the impact of modulating a single amino acid position on the mechanism of BenM ligand binding. This study represents the first application of biomolecular modeling methods for altering BenM specificity and for gaining insights into how mutations influence the structural dynamics of BenM. Such methods can potentially be applied to other TFs to alter specificity and analyze the dynamics responsible for these changes, highlighting the applicability of computational tools for informing experiments. In addition, our developed adipic acid biosensor can be applied for the identification and engineering of enzymes to produce adipic acid.

Design and Characterization of a Generalist Biosensor for Indole Derivatives

Transcription factor (TF)-based biosensors are useful synthetic biology tools for applications in a variety of areas of biotechnology. A major challenge of biosensor circuits is the limited repertoire of identified and well-characterized TFs for applications of interest, in addition to the challenge of optimizing selected biosensors. In this work, we implement the IclR family repressor TF TtgV from Pseudomonas putida DOT-T1E as an indole-derivative biosensor in Escherichia coli. We optimize the genetic circuit utilizing different components, providing insights into biosensor design and expanding on previous studies investigating this TF. We discover novel physiologically relevant ligands of TtgV, such as skatole. The broad specificity of TtgV makes it a useful target for directed evolution and protein engineering toward desired specificity. TtgV, as an indole-derivative biosensor, is a promising genetic component for the detection of compounds with biological activities relevant to health and the gut microbiome.

Wastewater-borne viruses and bacteria, surveillance and biosensors at the interface of academia and field deployment

Wastewater is a complex, but an ideal, matrix for disease monitoring and surveillance as it represents the entire load of enteric pathogens from a local catchment area. It captures both clinical and community disease burdens. Global interest in wastewater surveillance has been growing rapidly for infectious diseases monitoring and for providing an early warning of potential outbreaks. Although molecular detection methods show high sensitivity and specificity in pathogen monitoring from wastewater, they are strongly limited by challenges, including expensive laboratory settings and prolonged sample processing and analysis. Alternatively, biosensors exhibit a wide range of practical utility in real-time monitoring of biological and chemical markers. However, field deployment of biosensors is primarily challenged by prolonged sample processing and pathogen concentration steps due to complex wastewater matrices. This review summarizes the role of wastewater surveillance and provides an overview of infectious viral and bacterial pathogens with cutting-edge technologies for their detection. It emphasizes the practical utility of biosensors in pathogen monitoring and the major bottlenecks for wastewater surveillance of pathogens, and overcoming approaches to field deployment of biosensors for real-time pathogen detection. Furthermore, the promising potential of novel machine learning algorithms to resolve uncertainties in wastewater data is discussed.

Graphene-based biosensors in milk analysis: A review of recent developments

Cow's milk, an excellent source of fat, protein, amino acids, vitamins and minerals, is currently one of the most consumed products worldwide. Contaminations originating from diverse sources, such as biological, chemical, and physical, cause dairy product quality problems and thus dairy-related disorders, raising public health issues. For this reason, legal authorities have deemed it necessary to classify certain contaminations in commercial milk and keep them within particular limitations; therefore, it is urgent to develop next-generation detection systems that can accurately identify just the contaminants of concern to human health. This review presents a detailed investigation of biosensors based on graphene and its derivatives, which offer superior sensitivity and selectivity, by classifying the contaminants under the headings biological, chemical, and physical, in cow's milk according to their sources. We reviewed the current status of graphene-based biosensor (GBs) technology for milk or dairy analysis, highlighting its strengths and weaknesses with the help of comparative studies, tables, and charts, and we put forward a novel perspective to handle future challenges.

Diagnostics of Tuberculosis with Single-Walled Carbon Nanotube-Based Field-Effect Transistors

Tuberculosis (TB) is still threatening millions of people's lives, especially in developing countries. One of the major factors contributing to the ongoing epidemic of TB is the lack of a fast, efficient, and inexpensive diagnostic strategy. In this work, we developed a semiconducting single-walled carbon nanotube (SWCNT)-based field-effect transistor (FET) device functionalized with anti-Mycobacterium tuberculosis antigen 85B antibody (Ab85B) to detect the major M. tuberculosis-secreted antigen 85B (Ag85B). Through optimizing the device fabrication process by evaluating the mass of the antibody and the concentration of the gating electrolyte, our Ab85B-SWCNT FET devices achieved the detection of the Ag85B spiked in phosphate-buffered saline (calibration samples) with a limit of detection (LOD) of 0.05 fg/mL. This SWCNT FET biosensor also showed good sensing performance in biological matrices including artificial sputum and can identify Ag85B in serum after introducing bovine serum albumin (BSA) into the blocking layer. Furthermore, our BSA-blocked Ab85B-SWCNT FET devices can distinguish between TB-positive and -negative clinical samples, promising the application of SWCNT FET devices in point-of-care TB diagnostics. Moreover, the robustness of this SWCNT-based biosensor to the TB diagnosis in blood serum was enhanced by blocking SWCNT devices directly with a glutaraldehyde cross-linked BSA layer, enabling future applications of these SWCNT-based biosensors in clinical testing.

Peptide-Based Flavivirus Biosensors: From Cell Structure to Virological and Serological Detection Methods

In tropical and developing countries, mosquito-borne diseases by flaviviruses pose a serious threat to public health. Early detection is critical for preventing their spread, but conventional methods are time-consuming and require skilled technicians. Biosensors have been developed to address this issue, but cross-reactivity with other flaviviruses remains a challenge. Peptides are essentially biomaterials used in diagnostics that allow virological and serological techniques to identify flavivirus selectively. This biomaterial originated as a small protein consisting of two to 50 amino acid chains. They offer flexibility in chemical modification and can be easily synthesized and applied to living cells in the engineering process. Peptides could potentially be developed as robust, low-cost, sensitive, and selective receptors for detecting flaviviruses. However, modification and selection of the receptor agents are crucial to determine the effectiveness of binding between the targets and the receptors. This paper addresses two potential peptide nucleic acids (PNAs) and affinity peptides that can detect flavivirus from another target-based biosensor as well as the potential peptide behaviors of flaviviruses. The PNAs detect flaviviruses based on the nucleotide base sequence of the target's virological profile via Watson-Crick base pairing, while the affinity peptides sense the epitope or immunological profile of the targets. Recent developments in the functionalization of peptides for flavivirus biosensors are explored in this Review by division into electrochemical, optical, and other detection methods.

Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments

Adaptive Laboratory Evolution (ALE) is a powerful tool for engineering and understanding microbial physiology. ALE relies on the selection and enrichment of mutations that enable survival or faster growth under a selective condition imposed by the experimental setup. Phenotypic fitness landscapes are often underpinned by complex genotypes involving multiple genes, with combinatorial positive and negative effects on fitness. Such genotype relationships result in mutational fitness landscapes with multiple local fitness maxima and valleys. Traversing local maxima to find a global maximum often requires an individual or sub-population of cells to traverse fitness valleys. Traversing involves gaining mutations that are not adaptive for a given local maximum but are necessary to 'peak shift' to another local maximum, or eventually a global maximum. Despite these relatively well understood evolutionary principles, and the combinatorial genotypes that underlie most metabolic phenotypes, the majority of applied ALE experiments are conducted using constant selection pressures. The use of constant pressure can result in populations becoming trapped within local maxima, and often precludes the attainment of optimum phenotypes associated with global maxima. Here, we argue that oscillating selection pressures is an easily accessible mechanism for traversing fitness landscapes in ALE experiments, and provide theoretical and practical frameworks for implementation.

Biosensor-guided discovery and engineering of metabolic enzymes

A variety of chemicals have been produced through metabolic engineering approaches, and enhancing biosynthesis performance can be achieved by using enzymes with high catalytic efficiency. Accordingly, a number of efforts have been made to discover enzymes in nature for various applications. In addition, enzyme engineering approaches have been attempted to suit specific industrial purposes. However, a significant challenge in enzyme discovery and engineering is the efficient screening of enzymes with the desired phenotype from extensive enzyme libraries. To overcome this bottleneck, genetically encoded biosensors have been developed to specifically detect target molecules produced by enzyme activity at the intracellular level. Especially, the biosensors facilitate high-throughput screening (HTS) of targeted enzymes, expanding enzyme discovery and engineering strategies with advances in systems and synthetic biology. This review examines biosensor-guided HTS systems and highlights studies that have utilized these tools to discover enzymes in diverse areas and engineer enzymes to enhance their properties, such as catalytic efficiency, specificity, and stability.

Design and development of opto-electrochemical biosensing devices for diagnosing chronic kidney disease

Chronic kidney disease (CKD) is emerging as one of the major causes of the increase in mortality rate and is expected to become 5th major cause by 2050. Many studies have shown that it is majorly related to various risk factors, and thus becoming one of the major health issues around the globe. Early detection of renal disease lowers the overall burden of disease by preventing individuals from developing kidney impairment. Therefore, diagnosis and prevention of CKD are becoming the major challenges, and in this situation, biosensors have emerged as one of the best possible solutions. Biosensors are becoming one of the preferred choices for various diseases diagnosis as they provide simpler, cost-effective and precise methods for onsite detection. In this review, we have tried to discuss the globally developed biosensors for the detection of CKD, focusing on their design, pattern, and applicability in real samples. Two major classifications of biosensors based on transduction systems, that is, optical and electrochemical, for kidney disease have been discussed in detail. Also, the major focus is given to clinical biomarkers such as albumin, creatinine, and others related to kidney dysfunction. Furthermore, the globally developed sensors for the detection of CKD are discussed in tabulated form comparing their analytical performance, response time, specificity as well as performance in biological fluids.

Identification and detection of microRNA kidney disease biomarkers in liquid biopsies

PURPOSE OF REVIEW

MicroRNAs (miRNAs) are emerging rapidly as a novel class of biomarkers of major organ disorders, including kidney diseases. However, current PCR-based detection methods are not amenable to development for high-throughput, cost-effective miRNA biomarker quantification.

RECENT FINDINGS

MiRNA biomarkers show significant promise for diagnosis and prognosis of kidney diseases, including diabetic kidney disease, acute kidney injury, IgA nephropathy and delayed graft function following kidney transplantation. A variety of novel methods to detect miRNAs in liquid biopsies including urine, plasma and serum are being developed. As miRNAs are functional transcripts that regulate the expression of many protein coding genes, differences in miRNA profiles in disease also offer clues to underlying disease mechanisms.

SUMMARY

Recent findings highlight the potential of miRNAs as biomarkers to detect and predict progression of kidney diseases. Developing in parallel, novel methods for miRNA detection will facilitate the integration of these biomarkers into rapid routine clinical testing and existing care pathways. Validated kidney disease biomarkers also hold promise to identify novel therapeutic tools and targets.

VIDEO ABSTRACT

http://links.lww.com/CONH/A43.

Multicomponent synthesis of pyrido[2,3-b]pyrazine derivatives: electrochemical DNA sensing, nonlinear optical properties and biological activity

We synthesized novel pyrido[2,3-b]pyrazin based heterocyclic compounds (4-7) and their chemical structures were ascertained by spectral techniques (NMR, FT-IR). Besides experimental investigation, density functional theory (DFT) computations with B3LYP/6-31G(d,p) level of theory were executed to obtain spectroscopic and electronic properties. Nonlinear optical (NLO) properties, frontier molecular orbitals (FMOs), UV-visible, vibrational analysis, natural bond orbitals (NBOs), transition density matrix (TDM) and density of states (DOS) analyses of molecules (4-7) were accomplished at B3LYP/6-31G (d,p) level. Global reactivity parameters (GRPs) were correlated with the band gap (Egap) values; compound 7 with lower Egap (3.444 eV), exhibited smaller value of hardness (1.722 eV) with greater softness value (0.290 eV-1). The dipole moment (μ), average polarizability 〈α〉, first (βtot) and second 〈γ〉 hyper-polarizabilities were calculated for compounds (4-7). Compound 7 showed less Egap, highest absorption wavelength and remarkable NLO response. The highest 〈α〉, βtot and 〈γ〉 values for compound 7 were observed as 3.90 × 10-23, 15.6 × 10-30 and 6.63 × 10-35 esu, respectively. High NLO response revealed that pyrido[2,3-b]pyrazin based heterocyclic compounds had very remarkable contributions towards NLO technological applications. Further compounds (4-7) are utilized for the first time in electrochemical sensing of DNA, in vitro antioxidant and antiurease activity.

Strategies for improving the production of bio-based vanillin

Vanillin (4-hydroxy-3-methoxybenzaldehyde) is one of the most popular flavors with wide applications in food, fragrance, and pharmaceutical industries. However, the high cost and limited yield of plant extraction failed to meet the vast market demand of natural vanillin. Vanillin biotechnology has emerged as a sustainable and cost-effective alternative to supply vanillin. In this review, we explored recent advances in vanillin biosynthesis and highlighted the potential of vanillin biotechnology. In particular, we addressed key challenges in using microorganisms and provided promising approaches for improving vanillin production with a special focus on chassis development, pathway construction and process optimization. Future directions of vanillin biosynthesis using inexpensive precursors are also thoroughly discussed.

AraC-Based Biosensor for the Detection of Isoprene in E. coli

Isoprene is a valuable platform chemical, which is produced by engineered microorganisms, albeit in low quantities. The amount of isoprene produced is usually measured by gas chromatography, which can be time-consuming and expensive. Alternatively, biosensors have evolved as a powerful tool for real-time high-throughput screening and monitoring of product synthesis. The AraC-pBAD-inducible system has been widely studied, evolved, and engineered to develop biosensors for small molecules. In our preliminary studies, the AraC-pBAD system was mildly induced at higher isoprene concentrations when arabinose was also available. Hence, in the present study, we designed and constructed a synthetic biosensor based on the AraC-pBAD system, wherein the ligand-binding domain of AraC was replaced with IsoA. On introducing this chimeric AraC-IsoA (AcIa) transcription factor with the native PBAD promoter system regulating rfp gene expression, fluorescence output was observed only when wild-type Escherichia coli cells were induced with both isoprene and arabinose. The biosensor sensitivity and dynamic range were further enhanced by removing operator sequences and by substituting the native promoter (PAraC) with the strong tac promoter (Ptac). The chimeric sensor did not work in AraC knockout strains; however, functionality was restored by reintroducing AraC. Hence, AraC is essential for the functioning of our biosensor, while AcIa provides enhanced sensitivity and specificity for isoprene. However, insights into how AraC-AcIa interacts and the possible working mechanism remain to be explored. This study provides a prototype for developing chimeric AraC-based biosensors with proteins devoid of known dimerizing domains and opens a new avenue for further study and exploration.

Electrochemical biosensors in healthcare services: bibliometric analysis and recent developments

Biosensors are nowadays being used in various fields including disease diagnosis and clinical analysis. The ability to detect biomolecules associated with disease is vital not only for accurate diagnosis of disease but also for drug discovery and development. Among the different types of biosensors, electrochemical biosensor is most widely used in clinical and health care services especially in multiplex assays due to its high susceptibility, low cost and small in size. This article includes comprehensive review of biosensors in medical field with special emphasis on electrochemical biosensors for multiplex assays and in healthcare services. Also, the publications on electrochemical biosensors are increasing rapidly; therefore, it is crucial to be aware of any latest developments or trends in this field of research. We used bibliometric analyses to summarize the progress of this research area. The study includes global publication counts on electrochemical biosensors for healthcare along with various bibliometric data analyses by VOSviewer software. The study also recognizes the top authors and journals in the related area, and determines proposal for monitoring research.

Engineering Modular and Highly Sensitive Cell-Based Biosensors for Aromatic Contaminant Monitoring and High-Throughput Enzyme Screening

Although a variety of whole-cell-based biosensors have been developed for different applications in recent years, most cannot meet practical requirements due to insufficient sensing performance. Here, we constructed two sets of modular genetic circuits by serial and parallel modes capable of significantly amplifying the input/output signal in Escherichia coli. The biosensors are engineered using σ⁵⁴-dependent phenol-responsive regulator DmpR as a sensor and enhanced green fluorescent protein as a reporter. Cells harboring serial and parallel genetic circuits displayed nearly 9- and 16-fold higher sensitivity than the general circuit. The genetic circuits enabled rapid detection of six phenolic contaminants in 12 h and showed the low limit of detection of 2.5 and 2.2 ppb for benzopyrene (BaP) and tetracycline (Tet), with a broad detection range of 0.01-1 and 0.005-5 μM, respectively. Furthermore, the positive rate was as high as 73% when the biosensor was applied to screen intracellular enzymes with ester-hydrolysis activity from soil metagenomic libraries using phenyl acetate as a phenolic substrate. Several novel enzymes were isolated, identified, and biochemically characterized, including serine peptidases and alkaline phosphatase family protein/metalloenzyme. Consequently, this study provides a new signal amplification method for cell-based biosensors that can be widely applied to environmental contaminant assessment and screening of intracellular enzymes.

Transcription factor-based biosensors for screening and dynamic regulation

Advances in synthetic biology and genetic engineering are bringing into the spotlight a wide range of bio-based applications that demand better sensing and control of biological behaviours. Transcription factor (TF)-based biosensors are promising tools that can be used to detect several types of chemical compounds and elicit a response according to the desired application. However, the wider use of this type of device is still hindered by several challenges, which can be addressed by increasing the current metabolite-activated transcription factor knowledge base, developing better methods to identify new transcription factors, and improving the overall workflow for the design of novel biosensor circuits. These improvements are particularly important in the bioproduction field, where researchers need better biosensor-based approaches for screening production-strains and precise dynamic regulation strategies. In this work, we summarize what is currently known about transcription factor-based biosensors, discuss recent experimental and computational approaches targeted at their modification and improvement, and suggest possible future research directions based on two applications: bioproduction screening and dynamic regulation of genetic circuits.

Genetically Encoded Detection of Biosynthetic Protease Inhibitors

Proteases are an important class of drug targets that continue to drive inhibitor discovery. These enzymes are prone to resistance mutations, yet their promise for treating viral diseases and other disorders continues to grow. This study develops a general approach for detecting microbially synthesized protease inhibitors and uses it to screen terpenoid pathways for inhibitory compounds. The detection scheme relies on a bacterial two-hybrid (B2H) system that links protease inactivation to the transcription of a swappable reporter gene. This system, which can accomodate multiple biochemical outputs (i.e., luminescence and antibiotic resistance), permitted the facile incorporation of four disease-relevant proteases. A B2H designed to detect the inactivation of the main protease of severe acute respiratory syndrome coronavirus 2 enabled the identification of a terpenoid inhibitor of modest potency. An analysis of multiple pathways that make this terpenoid, however, suggested that its production was necessary but not sufficient to confer a survival advantage in growth-coupled assays. This finding highlights an important challenge associated with the use of genetic selection to search for inhibitors─notably, the influence of pathway toxicity─and underlines the value of including multiple pathways with overlapping product profiles in pathway screens. This study provides a detailed experimental framework for using microbes to screen libraries of biosynthetic pathways for targeted protease inhibitors.

Electrodetection of Small Molecules by Conformation-Mediated Signal Enhancement

Electrochemical biosensors allow the rapid, selective, and sensitive transduction of critical biological parameters into measurable signals. However, current electrochemical biosensors often fail to selectively and sensitively detect small molecules because of their small size and low molecular complexity. We have developed an electrochemical biosensing platform that harnesses the analyte-dependent conformational change of highly selective solute-binding proteins to amplify the redox signal generated by analyte binding. Using this platform, we constructed and characterized two biosensors that can sense leucine and glycine, respectively. We show that these biosensors can selectively and sensitively detect their targets over a wide range of concentrations-up to 7 orders of magnitude-and that the selectivity of these sensors can be readily altered by switching the bioreceptor's binding domain. Our work represents a new paradigm for the design of a family of modular electrochemical biosensors, where access to electrode surfaces can be controlled by protein conformational changes.

Screening microbially produced Δ9-tetrahydrocannabinol using a yeast biosensor workflow

Microbial production of cannabinoids promises to provide a consistent, cheaper, and more sustainable supply of these important therapeutic molecules. However, scaling production to compete with traditional plant-based sources is challenging. Our ability to make strain variants greatly exceeds our capacity to screen and identify high producers, creating a bottleneck in metabolic engineering efforts. Here, we present a yeast-based biosensor for detecting microbially produced Δ⁹-tetrahydrocannabinol (THC) to increase throughput and lower the cost of screening. We port five human cannabinoid G protein-coupled receptors (GPCRs) into yeast, showing the cannabinoid type 2 receptor, CB2R, can couple to the yeast pheromone response pathway and report on the concentration of a variety of cannabinoids over a wide dynamic and operational range. We demonstrate that our cannabinoid biosensor can detect THC from microbial cell culture and use this as a tool for measuring relative production yields from a library of Δ⁹-tetrahydrocannabinol acid synthase (THCAS) mutants.

Microbial production of cannabinoids promises a cheaper and more sustainable route to these important therapeutic molecules, but strain improvement and screening is challenging. Here, the authors develop a yeast-based Δ9-tetrahydrocannabinol (THC) biosensor for screening microbial mutant libraries.

State-of-the-Art Smart and Intelligent Nanobiosensors for SARS-CoV-2 Diagnosis

The novel coronavirus appeared to be a milder infection initially, but the unexpected outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), commonly called COVID-19, was transmitted all over the world in late 2019 and caused a pandemic. Human health has been disastrously affected by SARS-CoV-2, which is still evolving and causing more serious concerns, leading to the innumerable loss of lives. Thus, this review provides an outline of SARS-CoV-2, of the traditional tools to diagnose SARS-CoV-2, and of the role of emerging nanomaterials with unique properties for fabricating biosensor devices to diagnose SARS-CoV-2. Smart and intelligent nanomaterial-enabled biosensors (nanobiosensors) have already proven their utility for the diagnosis of several viral infections, as various detection strategies based on nanobiosensor devices are already present, and several other methods are also being investigated by researchers for the determination of SARS-CoV-2 disease; however, considerably more is undetermined and yet to be explored. Hence, this review highlights the utility of various nanobiosensor devices for SARS-CoV-2 determination. Further, it also emphasizes the future outlook of nanobiosensing technologies for SARS-CoV-2 diagnosis.

Advances in engineering and optimization of transcription factor-based biosensors for plug-and-play small molecule detection

Transcription factor (TF)-based biosensors have been applied in biotechnology for a variety of functions, including protein engineering, dynamic control, environmental detection, and point-of-care diagnostics. Such biosensors are promising analytical tools due to their wide range of detectable ligands and modular nature. However, designing biosensors tailored for applications of interest with the desired performance parameters, including ligand specificity, remains challenging. Biosensors often require significant engineering and tuning to meet desired specificity, sensitivity, dynamic range, and operating range parameters. Another limitation is the orthogonality of biosensors across hosts, given the role of the cellular context. Here, we describe recent advances and examples in the engineering and optimization of TF-based biosensors for plug-and-play small molecule detection. We highlight novel developments in TF discovery and biosensor design, TF specificity engineering, and biosensor tuning, with emphasis on emerging computational methods.

Therapeutic cell engineering: designing programmable synthetic genetic circuits in mammalian cells

Cell therapy approaches that employ engineered mammalian cells for on-demand production of therapeutic agents in the patient's body are moving beyond proof-of-concept in translational medicine. The therapeutic cells can be customized to sense user-defined signals, process them, and respond in a programmable and predictable way. In this paper, we introduce the available tools and strategies employed to design therapeutic cells. Then, various approaches to control cell behaviors, including open-loop and closed-loop systems, are discussed. We also highlight therapeutic applications of engineered cells for early diagnosis and treatment of various diseases in the clinic and in experimental disease models. Finally, we consider emerging technologies such as digital devices and their potential for incorporation into future cell-based therapies.

Integrating bio medical sensors in detecting hidden signatures of COVID-19 with Artificial intelligence

Today COVID-19 pandemic articulates high stress on clinical resources around the world. At present, physical and viral tests are slowly emerging, and there is a need for robust pandemic detection that biomedical sensors can aid. The utility of biomedical sensors is correlated with the medical instruments with physiological metrics. These Biomedical sensors are integrated with the systematic device to track the target analytes with a biomedical component. The COVID-19 patients' samples are collected, and biomarkers are detected using four sensors: blood pressure sensor, G-FET based biosensor, electrochemical sensor, and potentiometric sensor with different quantifiable measures. The imputed data is then profiled with chest X-ray images from the Covid-19 patients.Multi-Layer Perceptron (MLP), an AI model, is deployed to identify the hidden signatures with biomarkers. The performance of the biosensor is measured with three parameters such as sensitivity, specificity and detection limit by generating the calibration plots that accurately fits the model.

Intracellular biosensor-based dynamic regulation to manipulate gene expression at the spatiotemporal level

The use of intracellular, biosensor-based dynamic regulation strategies to regulate and improve the production of useful compounds have progressed significantly over previous decades. By employing such an approach, it is possible to simultaneously realize high productivity and optimum growth states. However, industrial fermentation conditions contain a mixture of high- and low-performance non-genetic variants, as well as young and aged cells at all growth phases. Such significant individual variations would hinder the precise controlling of metabolic flux at the single-cell level to achieve high productivity at the macroscopic population level. Intracellular biosensors, as the regulatory centers of metabolic networks, can real-time sense intra- and extracellular conditions and, thus, could be synthetically adapted to balance the biomass formation and overproduction of compounds by individual cells. Herein, we highlight advances in the designing and engineering approaches to intracellular biosensors. Then, the spatiotemporal properties of biosensors associated with the distribution of inducers are compared. Also discussed is the use of such biosensors to dynamically control the cellular metabolic flux. Such biosensors could achieve single-cell regulation or collective regulation goals, depending on whether or not the inducer distribution is only intracellular.

Synthetic biology for the engineering of complex wine yeast communities

Wine fermentation is a representation of complex higher-order microbial interactions. Despite the beneficial properties that these communities bring to wine, their complexity poses challenges in predicting the nature and outcome of fermentation. Technological developments in synthetic biology enable the potential to engineer synthetic microbial communities for new purposes. Here we present the challenges and applications of engineered yeast communities in the context of a wine fermentation vessel, how this represents a model system to enable novel solutions for winemaking and introduce the concept of a 'synthetic' terroir. Furthermore, we introduce our vision for the application of control engineering.

Nanoarchitectonics for Abused-Drug Biosensors

Rapid, accessible, and highly accurate biosensors for the detection of addictive and abused drugs are needed to reduce the adverse personal and societal impacts of addiction. Modern sensors that utilize next-generation technologies, e.g., nanobiotechnology and nanoarchitectonics, have triggered revolutionary progress in the field as they allow accurate detection and tracking of trace levels of major classes of drugs. This paper reviews advances in the field of biosensors for the detection of commonly abused drugs, both prescribed such as codeine and morphine, and illegal narcotics like cocaine.

Visualising the next frontiers in wine yeast research

A range of game-changing biodigital and biodesign technologies are coming of age all around us, transforming our world in complex ways that are hard to predict. Not a day goes by without news of how data-centric engineering, algorithm-driven modelling, and biocyber technologies—including the convergence of artificial intelligence, machine learning, automated robotics, quantum computing, and genome editing—will change our world. If we are to be better at expecting the unexpected in the world of wine, we need to gain deeper insights into the potential and limitations of these technological developments and advances along with their promise and perils. This article anticipates how these fast-expanding bioinformational and biodesign toolkits might lead to the creation of synthetic organisms and model systems, and ultimately new understandings of biological complexities could be achieved. A total of four future frontiers in wine yeast research are discussed in this article: the construction of fully synthetic yeast genomes, including minimal genomes; supernumerary pan-genome neochromosomes; synthetic metagenomes; and synthetic yeast communities. These four concepts are at varying stages of development with plenty of technological pitfalls to overcome before such model chromosomes, genomes, strains, and yeast communities could illuminate some of the ill-understood aspects of yeast resilience, fermentation performance, flavour biosynthesis, and ecological interactions in vineyard and winery settings. From a winemaker's perspective, some of these ideas might be considered as far-fetched and, as such, tempting to ignore. However, synthetic biologists know that by exploring these futuristic concepts in the laboratory could well forge new research frontiers to deepen our understanding of the complexities of consistently producing fine wines with different fermentation processes from distinctive viticultural terroirs. As the saying goes in the disruptive technology industry, it take years to create an overnight success. The purpose of this article is neither to glorify any of these concepts as a panacea to all ills nor to crucify them as a danger to winemaking traditions. Rather, this article suggests that these proposed research endeavours deserve due consideration because they are likely to cast new light on the genetic blind spots of wine yeasts, and how they interact as communities in vineyards and wineries. Future-focussed research is, of course, designed to be subject to revision as new data and technologies become available. Successful dislodging of old paradigms with transformative innovations will require open-mindedness and pragmatism, not dogmatism—and this can make for a catch-22 situation in an archetypal traditional industry, such as the wine industry, with its rich territorial and socio-cultural connotations.

Review of Microdevices for Hemozoin-Based Malaria Detection

Despite being preventable and treatable, malaria still puts almost half of the world's population at risk. Thus, prompt, accurate and sensitive malaria diagnosis is crucial for disease control and elimination. Optical microscopy and immuno-rapid tests are the standard malaria diagnostic methods in the field. However, these are time-consuming and fail to detect low-level parasitemia. Biosensors and lab-on-a-chip devices, as reported to different applications, usually offer high sensitivity, specificity, and ease of use at the point of care. Thus, these can be explored as an alternative for malaria diagnosis. Alongside malaria infection inside the human red blood cells, parasites consume host hemoglobin generating the hemozoin crystal as a by-product. Hemozoin is produced in all parasite species either in symptomatic and asymptomatic individuals. Furthermore, hemozoin crystals are produced as the parasites invade the red blood cells and their content relates to disease progression. Hemozoin is, therefore, a unique indicator of infection, being used as a malaria biomarker. Herein, the so-far developed biosensors and lab-on-a-chip devices aiming for malaria detection by targeting hemozoin as a biomarker are reviewed and discussed to fulfil all the medical demands for malaria management towards elimination.

A Methodical Review on the Applications and Potentialities of Using Nanobiosensors for Disease Diagnosis

Presently, with the introduction of nanotechnology, the evolutions and applications of biosensors and/or nanobiosensors are becoming prevalent in various scientific domains such as environmental and agricultural sciences as well as biomedical, clinical, and healthcare sciences. Trends in these aspects have led to the discovery of various biosensors/nanobiosensors with their tremendous benefits to mankind. The characteristics of the various biosensors/nanobiosensors are primarily based on the nature of nanomaterials/nanoparticles employed in the sensing mechanisms. In the last few years, the identification, as well as the detection of biological markers linked with any form of diseases (communicable or noncommunicable), has been accomplished by several sensing procedures using nanotechnology vis-à-vis biosensors/nanobiosensors. Hence, this study employs a systematic approach in reviewing some contemporary developed exceedingly sensitive nanobiosensors alongside their biomedical, clinical, or/and healthcare applications as well as their potentialities, specifically for the detection of some deadly diseases drawn from some of the recent publications. Ways forward in the form of future trends that will advance creative innovations of the potentialities of nanobiosensors for biomedical, clinical, or/and healthcare applications particularly for disease diagnosis are also highlighted.

Strategies for Improving Small-Molecule Biosensors in Bacteria

In recent years, small-molecule biosensors have become increasingly important in synthetic biology and biochemistry, with numerous new applications continuing to be developed throughout the field. For many biosensors, however, their utility is hindered by poor functionality. Here, we review the known types of mechanisms of biosensors within bacterial cells, and the types of approaches for optimizing different biosensor functional parameters. Discussed approaches for improving biosensor functionality include methods of directly engineering biosensor genes, considerations for choosing genetic reporters, approaches for tuning gene expression, and strategies for incorporating additional genetic modules.

Synthetic Biology Approaches to Hydrocarbon Biosensors: A Review

Monooxygenases are a class of enzymes that facilitate the bacterial degradation of alkanes and alkenes. The regulatory components associated with monooxygenases are nature's own hydrocarbon sensors, and once functionally characterised, these components can be used to create rapid, inexpensive and sensitive biosensors for use in applications such as bioremediation and metabolic engineering. Many bacterial monooxygenases have been identified, yet the regulation of only a few of these have been investigated in detail. A wealth of genetic and functional diversity of regulatory enzymes and promoter elements still remains unexplored and unexploited, both in published genome sequences and in yet-to-be-cultured bacteria. In this review we examine in detail the current state of research on monooxygenase gene regulation, and on the development of transcription-factor-based microbial biosensors for detection of alkanes and alkenes. A new framework for the systematic characterisation of the underlying genetic components and for further development of biosensors is presented, and we identify focus areas that should be targeted to enable progression of more biosensor candidates to commercialisation and deployment in industry and in the environment.

Real-Time Monitoring of the Yeast Intracellular State During Bioprocesses With a Toolbox of Biosensors

Industrial fermentation processes strive for high robustness to ensure optimal and consistent performance. Medium components, fermentation products, and physical perturbations may cause stress and lower performance. Cellular stress elicits a range of responses, whose extracellular manifestations have been extensively studied; whereas intracellular aspects remain poorly known due to lack of tools for real-time monitoring. Genetically encoded biosensors have emerged as promising tools and have been used to improve microbial productivity and tolerance toward industrially relevant stresses. Here, fluorescent biosensors able to sense the yeast intracellular environment (pH, ATP levels, oxidative stress, glycolytic flux, and ribosome production) were implemented into a versatile and easy-to-use toolbox. Marker-free and efficient genome integration at a conserved site on chromosome X of Saccharomyces cerevisiae strains and a commercial Saccharomyces boulardii strain was developed. Moreover, multiple biosensors were used to simultaneously monitor different intracellular parameters in a single cell. Even when combined together, the biosensors did not significantly affect key physiological parameters, such as specific growth rate and product yields. Activation and response of each biosensor and their interconnection were assessed using an advanced micro-cultivation system. Finally, the toolbox was used to screen cell behavior in a synthetic lignocellulosic hydrolysate that mimicked harsh industrial substrates, revealing differences in the oxidative stress response between laboratory (CEN.PK113-7D) and industrial (Ethanol Red) S. cerevisiae strains. In summary, the toolbox will allow both the exploration of yeast diversity and physiological responses in natural and complex industrial conditions, as well as the possibility to monitor production processes.

New analytical methods using carbon-based nanomaterials for detection of Salmonella species as a major food poisoning organism in water and soil resources

Salmonella is one of the most prevalent causing agents of food- and water-borne illnesses, posing an ongoing public health threat. These food-poisoning bacteria contaminate the resources at different stages such as production, aggregation, processing, distribution, as well as marketing. According to the high incidence of salmonellosis, effective strategies for early-stage detection are required at the highest priority. Since traditional culture-dependent methods and polymerase chain reaction are labor-intensive and time-taking, identification of early and accurate detection of Salmonella in food and water samples can prevent significant health economic burden and lessen the costs. The immense potentiality of biosensors in diagnosis, such as simplicity in operation, the ability of multiplex analysis, high sensitivity, and specificity, have driven research in the evolution of nanotechnology, innovating newer biosensors. Carbon nanomaterials enhance the detection sensitivity of biosensors while obtaining low levels of detection limits due to their possibility to immobilize huge amounts of bioreceptor units at insignificant volume. Moreover, conjugation and functionalization of carbon nanomaterials with metallic nanoparticles or organic molecules enables surface functional groups. According to these remarkable properties, carbon nanomaterials are widely exploited in the development of novel biosensors. To be specific, carbon nanomaterials such as carbon nanotubes, graphene and fullerenes function as transducers in the analyte recognition process or surface immobilizers for biomolecules. Herein the potential application of carbon nanomaterials in the development of novel Salmonella biosensors platforms is reviewed comprehensively. In addition, the current problems and critical analyses of the future perspectives of Salmonella biosensors are discussed.

Methodological Approaches for Monitoring Five Major Food Safety Hazards Affecting Food Production in the Galicia-Northern Portugal Euroregion

The agri-food industry has historically determined the socioeconomic characteristics of Galicia and Northern Portugal, and it was recently identified as an area for collaboration in the Euroregion. In particular, there is a need for action to help to ensure the provision of safe and healthy foods by taking advantage of key enabling technologies. The goals of the FOODSENS project are aligned with this major objective, specifically with the development of biosensors able to monitor hazards relevant to the safety of food produced in the Euroregion. The present review addresses the state of the art of analytical methodologies and techniques-whether commercially available or in various stages of development-for monitoring food hazards, such as harmful algal blooms, mycotoxins, Listeria monocytogenes, allergens, and polycyclic aromatic hydrocarbons. We discuss the pros and cons of these methodologies and techniques and address lines of research for point-of-care detection. Accordingly, the development of miniaturized automated monitoring strategies is considered a priority in terms of health and economic interest, with a significant impact in several areas, such as food safety, water quality, pollution control, and public health. Finally, we present potential market opportunities that could result from the availability of rapid and reliable commercial methodologies.

The Future in Sensing Technologies for Malaria Surveillance: A Review of Hemozoin-Based Diagnosis

Early and effective malaria diagnosis is vital to control the disease spread and to prevent the emergence of severe cases and death. Currently, malaria diagnosis relies on optical microscopy and immuno-rapid tests; however, these require a drop of blood, are time-consuming, or are not specific and sensitive enough for reliable detection of low-level parasitaemia. Thus, there is an urge for simpler, prompt, and accurate alternative diagnostic methods. Particularly, hemozoin has been increasingly recognized as an attractive biomarker for malaria detection. As the disease proliferates, parasites digest host hemoglobin, in the process releasing toxic haem that is detoxified into an insoluble crystal, the hemozoin, which accumulates along with infection progression. Given its magnetic, optical, and acoustic unique features, hemozoin has been explored for new label-free diagnostic methods. Thereby, herein, we review the hemozoin-based malaria detection methods and critically discuss their challenges and potential for the development of an ideal diagnostic device.

Transistor-Based Biomolecule Sensors: Recent Technological Advancements and Future Prospects

Transistor-based sensors have been widely recognized to be highly sensitive and reliable for point-of-care/bed-side diagnosis. In this line, a range of cutting-edge technologies has been generated to elevate the role of transistors for biomolecule detection. Detection of a wide range of clinical biomarkers has been reported using various configurations of transistors. The inordinate sensitivity of transistors to the field-effect imparts high sensitivity toward wide range of biomolecules. This overview has gleaned the present achievements with the technological advancements using high performance transistor-based sensors. This review encloses transistors incorporated with a variety of functional nanomaterials and organic elements for their excellence in selectivity and sensitivity. In addition, the technological advancements in fabrication of these microdevices or nanodevices and functionalization of the sensing elements have also been discussed. The technological gap in the realization of sensors in transistor platforms and the resulted scope for research has been discussed. Finally, foreseen technological advancements and future research perspectives are described.

Multi-level rebalancing of the naringenin pathway using riboswitch-guided high-throughput screening

Recombinant microbes have emerged as promising alternatives to natural sources of naringenin-a key molecular scaffold for flavonoids. In recombinant strains, expression levels of the pathway genes should be optimized at both transcription and the translation stages to precisely allocate cellular resources and maximize metabolite production. However, the optimization of the expression levels of naringenin generally relies on evaluating a small number of variants from libraries constructed by varying transcription efficiency only. In this study, we introduce a systematic strategy for the multi-level optimization of biosynthetic pathways. We constructed a multi-level combinatorial library covering both transcription and translation stages using synthetic T7 promoter variants and computationally designed 5'-untranslated regions. Furthermore, we identified improved strains through high-throughput screening based on a synthetic naringenin riboswitch. The most-optimized strain obtained using this approach exhibited a 3-fold increase in naringenin production, compared with the parental strain in which only the transcription efficiency was modulated. Furthermore, in a fed-batch bioreactor, the optimized strain produced 260.2 mg/L naringenin, which is the highest concentration reported to date using glycerol and p-coumaric acid as substrates. Collectively, this work provides an efficient strategy for the expression optimization of the biosynthetic pathways.

Multilayer Genetic Circuits for Dynamic Regulation of Metabolic Pathways

The dynamic regulation of metabolic pathways is based on changes in external signals and endogenous changes in gene expression levels and has extensive applications in the field of synthetic biology and metabolic engineering. However, achieving dynamic control is not trivial, and dynamic control is difficult to obtain using simple, single-level, control strategies because they are often affected by native regulatory networks. Therefore, synthetic biologists usually apply the concept of logic gates to build more complex and multilayer genetic circuits that can process various signals and direct the metabolic flux toward the synthesis of the molecules of interest. In this review, we first summarize the applications of dynamic regulatory systems and genetic circuits and then discuss how to design multilayer genetic circuits to achieve the optimal control of metabolic fluxes in living cells.

COVID-19 Biomarkers and Advanced Sensing Technologies for Point-of-Care (POC) Diagnosis

COVID-19, also known as SARS-CoV-2 is a novel, respiratory virus currently plaguing humanity. Genetically, at its core, it is a single-strand positive-sense RNA virus. It is a beta-type Coronavirus and is distinct in its structure and binding mechanism compared to other types of coronaviruses. Testing for the virus remains a challenge due to the small market available for at-home detection. Currently, there are three main types of tests for biomarker detection: viral, antigen and antibody. Reverse Transcription-Polymerase Chain Reaction (RT-PCR) remains the gold standard for viral testing. However, the lack of quantitative detection and turnaround time for results are drawbacks. This manuscript focuses on recent advances in COVID-19 detection that have lower limits of detection and faster response times than RT-PCR testing. The advancements in sensing platforms have amplified the detection levels and provided real-time results for SARS-CoV-2 spike protein detection with limits as low as 1 fg/mL in the Graphene Field Effect Transistor (FET) sensor. Additionally, using multiple biomarkers, detection levels can achieve a specificity and sensitivity level comparable to that of PCR testing. Proper biomarker selection coupled with nano sensing detection platforms are key in the widespread use of Point of Care (POC) diagnosis in COVID-19 detection.

Bioinformational trends in grape and wine biotechnology

The creative destruction caused by the coronavirus pandemic is yielding immense opportunity for collaborative innovation networks. The confluence of biosciences, information sciences, and the engineering of biology, is unveiling promising bioinformational futures for a vibrant and sustainable bioeconomy. Bioinformational engineering, underpinned by DNA reading, writing, and editing technologies, has become a beacon of opportunity in a world paralysed by uncertainty. This article draws on lessons from the current pandemic and previous agricultural blights, and explores bioinformational research directions aimed at future-proofing the grape and wine industry against biological shocks from global blights and climate change.

Engineering Bacteria to Monitor the Bleeding of Animals Using Far-Red Fluorescence

Microorganisms living in animals can function as drug delivery systems or as detectors for some diseases. Here, we developed a biosensor constructed by the deletion of hemF and harboring ho1, chuA, and bdfp1.6 in Escherichia coli. HemF is an enzyme involved in heme synthesis in E. coli. ChuA and HO1 can transfer extracellular heme into cells and generate biliverdin (BV). BDFP1.6 can bind BV autocatalytically, and it emits a far-red fluorescence signal at 667 nm. Therefore, we named this biosensor as the far-red light for bleeding detector (FRLBD). Our results indicated that the FRLBD was highly efficient and specific for detecting heme or blood in vitro. Moreover, the FRLBD could be used to detect bleeding in the zebrafish induced by aspirin, and a convolutional neural network was an appropriate model to identify the fluorescence features in the images.

Transcription-Factor-based Biosensor Engineering for Applications in Synthetic Biology

Transcription-factor-based biosensors (TFBs) are often used for metabolite detection, adaptive evolution, and metabolic flux control. However, designing TFBs with superior performance for applications in synthetic biology remains challenging. Specifically, natural TFBs often do not meet real-time detection requirements owing to their slow response times and inappropriate dynamic ranges, detection ranges, sensitivity, and selectivity. Furthermore, designing and optimizing complex dynamic regulation networks is time-consuming and labor-intensive. This Review highlights TFB-based applications and recent engineering strategies ranging from traditional trial-and-error approaches to novel computer-model-based rational design approaches. The limitations of the applications and these engineering strategies are additionally reviewed.

A comprehensive review on the applications of nano-biosensor-based approaches for non-communicable and communicable disease detection

The outstretched applications of biosensors in diverse domains has become the reason for their attraction for scientific communities. Because they are analytical devices, they can detect both quantitative and qualitative biological components through the generation of detectable signals. In the recent past, biosensors witnessed significant changes and developments in their design as well as features. Nanotechnology has revolutionized sensing phenomena by increasing biodiagnostic capacity in terms of specificity, size, and cost, resulting in exceptional sensitivity and flexibility. The steep increase of non-communicable diseases across the world has emerged as a matter of concern. In parallel, the abrupt outbreak of communicable diseases poses a serious threat to mankind. For decreasing the morbidity and mortality associated with various communicable and non-communicable diseases, early detection and subsequent treatment are indispensable. Detection of different biological markers generates quantifiable signals that can be electrochemical, mass-based, optical, thermal, or piezoelectric. Speculating on the incumbent applicability and versatility of nano-biosensors in large disciplines, this review highlights different types of biosensors along with their components and detection mechanisms. Moreover, it deals with the current advancements made in biosensors and the applications of nano-biosensors in detection of various non-communicable and communicable diseases, as well as future prospects of nano-biosensors for diagnostics.

Portable Sensing Devices for Detection of COVID-19: A Review

The coronavirus pandemic is the most challenging incident that people have faced in recent years. Despite the time-consuming and expensive conventional methods, point-of-care diagnostics have a crucial role in deterrence, timely detection, and intensive care of the disease's progress. Hence, this detrimental health emergency persuaded researchers to accelerate the development of highly-scalable diagnostic devices to control the propagation of the virus even in the least developed countries. The strategies exploited for detecting COVID-19 stem from the already designed systems for studying other maladies, particularly viral infections. The present report reviews not only the novel advances in portable diagnostic devices for recognizing COVID-19, but also the previously existing biosensors for detecting other viruses. It discusses their adaptability for identifying surface proteins, whole viruses, viral genomes, host antibodies, and other biomarkers in biological samples. The prominence of different types of biosensors such as electrochemical, optical, and electrical for detecting low viral loads have been underlined. Thus, it is anticipated that this review will assist scientists who have embarked on a competition to come up with more efficient and marketable in-situ test kits for identifying the infection even in its incubation time without sample pretreatment. Finally, a conclusion is provided to highlight the importance of such an approach for monitoring people to combat the spread of such contagious diseases.

Macrolide Biosensor Optimization through Cellular Substrate Sequestration

Developing and optimizing small-molecule biosensors is a central goal of synthetic biology. Here we incorporate additional cellular components to improve biosensor sensitivity by preventing target molecules from diffusing out of cells. We demonstrate that trapping erythromycin within Escherichia coli through phosphorylation increases the sensitivity of its biosensor (MphR) by approximately 10-fold. When combined with prior engineering efforts, our optimized biosensor can detect erythromycin concentrations as low as 13 nM. We show that this strategy works with a range of macrolide substrates, enabling the potential usage of our optimized system for drug development and metabolic engineering. This strategy can be extended in future studies to improve the sensitivity of other biosensors. Our findings further suggest that many naturally evolved genes involved in resistance to multiple classes of antibiotics may increase intracellular drug concentrations to modulate their own expression, acting as a form of regulatory feedback.

Transcription factor-based biosensors: a molecular-guided approach for natural product engineering

Natural products and their derivatives offer a rich source of chemical and biological diversity; however, traditional engineering of their biosynthetic pathways to improve yields and access to unnatural derivatives requires a precise understanding of their enzymatic processes. High-throughput screening platforms based on allosteric transcription-factor based biosensors can be leveraged to overcome the screening bottleneck to enable searching through large libraries of pathway/strain variants. Herein, the development and application of engineered allosteric transcription factor-based biosensors is described that enable optimization of precursor availability, product titers, and downstream product tailoring for advancing the natural product bioeconomy. We discuss recent successes for tailoring biosensor design, including computationally-based approaches, and present our future outlook with the integration of cell-free technologies and de novo protein design for rapidly generating biosensor tools.