Estuary sediments are one of the important components of coastal ecosystems and have been regarded as a sink for various types of organic pollutants. Organic pollutants such as endocrine disrupting compounds (EDCs) which have been associated with various environmental and human health effects were detected in the estuary sediment at trace level. Considering various interferences that may exist in the estuarine sediment, a sensitive and selective method, capable of detecting multiclass EDC pollutants at the trace levels, needs to be developed and optimized to be applied for environmental analysis. A combination of Soxhlet extraction followed by offline solid phase extraction (SPE) cleaned up with detection based on LC triple quadrupole MS was optimized and validated in this study. The targeted compounds consisted of ten multiclass EDCs, namely, diclofenac, primidone, bisphenol A, estrone (E1), 17β-estradiol (E2), 17α-ethynylestradiol (EE2), 4-octylphenol (4-OP), 4-nonylphenol (4-NP), progesterone, and testosterone. The method showed high extraction efficiency with percentage of recovery from 78% to 108% and excellent sensitivity with detection limit between 0.02ngg-1 and 0.81ngg-1. Excellent linearity from 0.991 to 0.999 was achieved for the developed compounds and the relative standard deviation was less than 18%, an indication of good precision analysis. Evaluation of the matrix effects showed ionization suppression for all the developed compounds. Verification of the method was carried out by analyzing the estuarine sediment collected from Langat River. The analyzed estuarine sediments showed a trace concentration of diclofenac, bisphenol A, progesterone, testosterone, primidone, and E1. However, E2, EE2, 4-OP, and 4-NP were below the method's detection limit. Diclofenac exhibited the highest concentration at 2.67ngg-1 followed by bisphenol A (1.78ngg-1) while E1 showed the lowest concentration at 0.07ngg-1.
The low conductivity of separation electrolytes employed in nonaqueous capillary electrophoresis (NACE) limits the use of on-line sample concentration or stacking by field enhancement. Herein, micelle-to-solvent stacking (MSS) was performed by the simple injection of a micellar solution plug prior to electrokinetic injection of sample prepared under field-enhanced stacking conditions (known as field-enhanced sample injection, FESI). The proposed approach allowed a 214-625-fold improvement in peak signals for targeted anticancer drugs (e.g., tamoxifen) and its major metabolites in NACE using 100% methanol-based separation electrolyte that comprised of 7.5mM deoxycholic acid sodium salt, 15mM acetic acid and 1mM 18-crown-6. These improvements yielded tamoxifen and its metabolites with 2-5 times better stacking efficiency as compared to those obtained without micellar solution injection or FESI only. This is comparable to the results typically achieved when FESI is combined with isotachophoresis (electrokinetic supercharging). The FESI-MSS-NACE was tested for the measuring levels of target drugs in plasma. The analytical figures of merit are also reported.
A new sample preparation method, ion-pair vortex assisted liquid-liquid microextraction (VALLME-BE), for the determination of a highly polar anti-diabetic drug (metformin) in plasma sample was developed. The VALLME-BE was performed by diluting the plasma in borate buffer and extracted to 150µL 1-octanol containing 0.2M di-(2-ethylhexyl)phosphoric acid as intermediate phase. The drug was next back-extracted into 20µL of 0.075M HCl solution. The effects of pH, ion-pair concentration, type of organic solvent, volume of extraction phases, ionic strength, vortexing and centrifugation times on the extraction efficiency were investigated. The optimum conditions were at pH 9.3, 60s vortexing and 2min centrifugation. The microextract, contained metformin and buformin (internal standard), was directly injected into a HPLC unit using C1 column (250mm×4.6mm×10µm) and detected at 235nm. The method was validated and calibration curve was linear with r2>0.99 over the range of 20-2000µgL-1. The limits of detection and quantitation were 1.4 and 4.1µgL-1, respectively. The accuracy was within 94.8-108% of the nominal concentration. The relative standard deviation for inter- and intra-day precision was less than 10.8%. The method was conveniently applied for the determination of metformin in plasma samples.
Different extraction procedures were evaluated to assess their potential for measuring volatile organic compounds (VOCs) from raw rubber materials. Four headspace sampling techniques (SHS, DHS, HS-SPME and µ-CTE) were studied. Each method was firstly optimised to ensure their reliability in performance. Passive sampling was also compared as a rapid identification of background VOCs. 352 VOCs were identified, 71 from passive sampling and 281 from active headspace sampling, with 62 not previously reported (hexanenitrile, octanone, decanal, indole, aniline, anisole, alpha-pinene as well as pentanol and butanol). The volatiles belonged to a broad range of chemical classes (ketones, aldehydes, aromatics, acids, alkanes, alcohol and cyclic) with their thermal effects (lower boiling points) greatly affecting their abundance at a higher temperature. Micro-chamber (µ-CTE) was found to be the most suitability for routine assessments due to its operational efficiency (rapidity, simplicity and repeatability), identifying 115 compounds from both temperatures (30 °C and 60 °C). Whereas, HS-SPME a widely applied headspace technique, only identified 75 compounds and DHS identified 74 VOCs and SHS only 17 VOCs. Regardless of the extraction technique, the highest extraction efficiency corresponded to aromatics and acids, and the lowest compound extraction were aldehyde and hydrocarbon. The interaction between techniques and temperature for all chemical groups were evaluated using two-way ANOVA (p-value is 0.000197) explaining the highly significant interactions between factors.
The development of free and total cholesterol nanobiosensors based on a single step electrochemical integration of gold nanoparticles (AuNPs), cholesterol oxidase (COx), cholesterol esterase (CE) and a mediator with polypyrrole (PPy) films is described. The incorporation of the various components in the PPy films was confirmed by chronopotentiometry, cyclic voltammetry (CV), scanning electron microscopy, energy dispersive X-ray analysis (SEM-EDX), and Fourier transformed infrared (FTIR) spectroscopy. The free cholesterol, PPy-NO3--Fe(CN)64--AuNPs-COx, nanobiosensor achieved a minimum detectable concentration of 5 μM, a linear concentration range of 5-25 μM and a sensitivity of 1.6 µA cm-2 µM-1 in 0.05 M phosphate buffer (pH 7.00). For the total cholesterol, PPy-NO3--Fe(CN)64--AuNPs-COx-CE, nanobiosensor which also involved the co-incorporation of cholesterol esterase (CE) with the other components, the achieved performances include a minimum detectable total cholesterol concentration of 25 μM, a broader linear concentration range of 25-170 μM and a lower sensitivity of 0.1 µA µM-1 cm-2. Owing to its high selectivity, the presence of common interferants did not affect the total cholesterol measurement with the PPy-NO3--Fe(CN)64--AuNPs-COx-CE nanobiosensor. Both nanobiosensors were successfully used for direct and indirect determination of total cholesterol in human blood serum samples.
The developments in mass spectrometry (MS) in the past few decades reveal the power and versatility of this technology. MS methods are utilized in routine analyses as well as research activities involving a broad range of analytes (elements and molecules) and countless matrices. However, manual MS analysis is gradually becoming a thing of the past. In this article, the available MS automation strategies are critically evaluated. Automation of analytical workflows culminating with MS detection encompasses involvement of automated operations in any of the steps related to sample handling/treatment before MS detection, sample introduction, MS data acquisition, and MS data processing. Automated MS workflows help to overcome the intrinsic limitations of MS methodology regarding reproducibility, throughput, and the expertise required to operate MS instruments. Such workflows often comprise automated off-line and on-line steps such as sampling, extraction, derivatization, and separation. The most common instrumental tools include autosamplers, multi-axis robots, flow injection systems, and lab-on-a-chip. Prototyping customized automated MS systems is a way to introduce non-standard automated features to MS workflows. The review highlights the enabling role of automated MS procedures in various sectors of academic research and industry. Examples include applications of automated MS workflows in bioscience, environmental studies, and exploration of the outer space.
The organophosphorous nerve agent VX is classified by the Chemical Warfare Convention (CWC) as a Schedule 1 chemical; namely a substance that is highly toxic with no use that is of benefit to society. Even with this classification, the nefarious use of the Schedule 1 chemical VX has been observed, as demonstrated in 2017 in Malaysia. Therefore, undertaking chemical analysis on samples of VX to identify chemical attribution signatures (CAS) for chemical forensics is required. To further understand the chemical profile of VX, and to aid in the identification of potential CAS, three in house synthesised stocks of VX were investigated. The three VX stocks analysed were synthesised in 2014, 2017 and 2018 using the same method, allowing for a comparison of data between each of the stocks at different stages of storage. As opposed to a majority of literature reports, these agent stocks were not stabilised, nor were they subjected to forced degradation. Using NMR, high resolution (HR) LC-HRMS, GC-(EI)MS and GC-(CI)MS to gain a full insight into the CAS profile, a total of 44 compounds were identified. Of these compounds, 30 were readily identified through accurate mass measurement and NIST library matches. A further seven were identified through extensive LC-HRMS/MS studies, with seven remaining unresolved. Several compounds, identified in minor amounts, were able to be traced back to impurities in the precursor compounds used in the synthesis of VX, and hence may be useful as CAS for source attribution.
An optical genosensor based on Schiff base complex (Zn2+ salphen) DNA label and acrylic microspheres (AMs) as polymer support of the capturing DNA probe (cpDNA) was developed for dengue virus serotype 2 (DEN-2) detection via reflectance spectrophotometric method. The solid-state optical DNA biosensor showed high selectivity and specificity up to one-base mismatch in the target DNA sequence owing to the salphen chemical structure that is rich in localized electrons, and allowed π-π stacking interaction between stacked base pairs of double-stranded DNA (dsDNA). The reflectometric DNA microsensor demonstrated a broad linear detection range towards DEN-2 DNA from 1 × 10-15 M to 1 × 10-3 M with a low limit of detection (LOD) obtained at 1.21 × 10-16 M. The DNA biosensor gave reproducible optical response with a satisfactory relative standard deviation (RSD) at 3.1%, (n = 3), and the reflectance response was stable even after four regeneration cycles of the DNA biosensor. The optical genosensor was proven comparable with standard reverse transcription polymerase chain reaction (RT-PCR) in detecting DEN-2 genome acquired from clinical samples of serum, urine and saliva of dengue virus infected patients under informed consent. The developed reflectometric DNA biosensor is advantageous in offering an early DEN-2 diagnosis, when fever symptom started to manifest in patient.
The technique of Fourier transform infrared spectroscopy is widely used to generate spectral data for use in the detection of food contaminants. Monochloropropanediol (MCPD) is a refining process-induced contaminant that is found in palm-based fats and oils. In this study, a chemometric approach was used to evaluate the relationship between the FTIR spectra and the total MCPD content of a palm-based cooking oil. A total of 156 samples were used to develop partial least squares regression (PLSR), artificial neural network (nnet), average artificial neural network (avNNET), random forest (RF) and cubist models. In addition, a consensus approach was used to generate fusion result consisted from all the model mentioned above. All the models were evaluated based on validation performed using training and testing datasets. In addition, the box plot of coefficient of determination (R2), root mean square error (RMSE), slopes and intercepts by 100 times randomization was also compared. Evaluation of performance based on the testing R2 and RMSE suggested that the cubist model predicted total MCPD content with the highest accuracy, followed by the RF, avNNET, nnet and PLSR models. The overfitting tendency was assessed based on differences in R2 and RMSE in the training and testing calibrations. The observations showed that the cubist and avNNET models possessed a certain degree of overfitting. However, the accuracy of these models in predicting the total MCPD content was high. Results of the consensus model showed that it slightly improved the accuracy of prediction as well as significantly reduced its uncertainty. The important variables derived from the cubist and RF models suggested that the wavenumbers corresponding to the MCPDs originated from the -CH=CH2 or CH=CH (990-900 cm-1) and C-Cl stretch (800-700 cm-1) regions of the FTIR spectrum data. In short, chemometrics in combination with FTIR analysis especially for the consensus model represent a potential and flexible technique for estimating the total MCPD content of refined vegetable oils.
A dynamic pH junction was used in capillary electrophoresis (CE-DAD) to on-line preconcentrate, separate, and determine trace amounts of sulfonamide antibiotics (SAs) in milk and yoghurt samples in this study. A sample matrix with 0.15% acetic acid and 10% methanol (MeOH) at a pH of 4.0, and a background electrolyte (BGE) that contained 35 mM sodium citrate with 10% MeOH at a pH of 8.5, and an acidic barrage of 0.4% acetic acid with 10% MeOH at a pH of 2.5 were utilised to achieve a stacking effect for SAs through a dynamic pH junction. Under optimised conditions, the proposed preconcentration method showed good linearity (30-500 ng/mL, r2 ≥ 0.9940), low limits of detection (LODs) of 4.1-6.3 ng/mL, and acceptable analytes recovery (81.2-106.9%) with relative standard deviations (RSDs) within 5.3-13.7 (n = 9). The limits of quantification (LOQs) were below the maximum residue limit approved by the European Union (EU) in this type of matrices. Sensitivity enhancement factors of up to 129 were reached with the optimised dynamic pH junction using CE with a diode array detector (DAD). The method was used to determine SAs in fresh milk, low-fat milk, full-cream milk, and yoghurt samples.
Paper-based analytical devices (PADs) with four new designs could be fabricated using commercially available home-based scan-and-cut printer. They serve for miniaturised platforms for chemical analysis. Replication analysis of a sample together with the calibration (using the analyte standards at different concentrations) can be completed in a single run, by utilising smartphone as the detector. Some new approaches for choosing detection zones were suggested. The four proposed PAD designs here were used as models in microliter scale operation to demonstrate the well-known chemistries of colorimetric determinations of iron, phosphate, and hardness using 1,10-phenanthroline and simple aqueous guava leaf extract; molybdate, and EBT-EDTA complexometric titration, respectively, through calibrations: where Blue (B) value = 88.2log [Fe3+] - 80.8, R2 = 0.989; B value = 1.75 [Fe3+] + 0.198, R2 = 0.999; Grey scale (I) value = 1.77 [Fe3+] - 1.22, R2 = 0.997; Red (R) value = 16.1log [PO43-] + 8.95, R2 = 0.999; Hue (H) value = 43.3log [Ca2+] + 233, R2 = 0.994, respectively. For the hardness, using one of the PAD designs, true titration was also possible. Applications of the proposed devices and procedures were demonstrated for real world samples with validation. Additionally, kinetic study of the molybdenum blue for phosphate was demonstrated using one of the PADs.
Oil and grease content in wastewater is used as an environmental monitoring parameter in the oil and gas industry to prevent serious pollution. Conventional oil and grease laboratory testing is time-consuming and necessitates the use of a hazardous chemical solvent, resulting in non-real-time test data and unnecessary chemical waste. On-site or real-time analysis can enable monitoring of oil and grease in wastewater before discharge to the environment from an operating plant, allowing immediate action to be taken to mitigate environmental impact before contamination spirals out of control. Bioluminescent whole-cell biosensors have been reported to have high sensitivity and selectivity in environmental samples, but only for a few traces of organic compounds such as polycyclic aromatics and naphthalene, allowing for faster analysis times. However, no evaluation of biosensor application for oil and grease (a mixture of hydrocarbons) detection in wastewater, which is critical in the oil and gas industry, has been published to date. Herein, the advantages, disadvantages, challenges, and limitations of using a whole-cell bioluminescent biosensor technology to measure oil and grease content in wastewater are carefully reviewed. This review attempts to bridge the knowledge gap between conventional laboratory methods and biosensor technology in terms of analytical challenges, identifying areas for improvement as well as real-world applications for oil and grease content detection in wastewater.
With each passing year, the agriculture and wood processing industries generate increasingly high tonnages of biomass waste, which instead of being burned or left to accumulate should be utilized more sustainably. In parallel, advances in green technology have encouraged large companies and nations to begin using eco-friendly materials, including eco-friendly emulsifiers, which are used in various industries and in bio-based materials. The emulsion-conducive properties of lignocellulosic materials such as cellulose, hemicellulose, and lignin, the building blocks of plant and wood structures, have demonstrated a particular ability to alter the landscape of emulsion technology. Beyond that, the further modification of their structure may improve emulsion stability, which often determines the performance of emulsions. Considering those trends, this review examines the performance of lignocellulosic materials after modification according to their stability, droplet size, and distribution by size, all of which suggest their outstanding potential as materials for emulsifying agents.
Electro-mediated microextraction (EMM) combined with micro-high performance liquid chromatography-ultraviolet detection was successfully developed for the determination of selected phenols, namely 4-chlorophenol (4CP), 2-nitrophenol (2NP) and 2,4-dichlorophenols (2,4 DCP) in water. A solvent-impregnated agarose gel disc was utilized as a solvent holder in this study. Under optimum extraction conditions, the method showed good linearity in the range of 0.1-250µgL-1, 0.3-250µgL-1and 0.2-500µgL-1for 4CP, 2NP and 2,4 DCP, respectively with correlation coefficients of ≥ 0.9975, ultra-trace LODs (0.03-0.1µgL-1) and satisfactory relative recovery average (85.0-114.1%) for the analysis of selected phenols. The proposed method was rapid and eco-friendly as the solvent holder was constructed using minute amounts of extraction solvent immobilized within the biodegradable agarose gel disc. A comparative microextraction technique termed solvent-impregnated agarose gel liquid phase microextraction (AG-LPME) was re-optimized and validated for the extraction of phenols in water. The method offered good linearity, ultra-trace LODs ranging 0.1-0.5µgL-1and satisfactory average of relative recovery (86.1-114.1%). The EMM was superior in terms of sensitivity and time-effectiveness compared to AG-LPME. Both techniques combine extraction and pre-concentration in mini-scaled approaches using an eco-friendly solvent holder that fulfil the green chemistry concept.
In this present study, magnetic nanoparticles (MNPs) nanocomposites modified with polyaniline (PANI) coated newly synthesised dicationic ionic liquid (DICAT) forming MNP-PANI-DICAT were successfully synthesised as new generation material for magnetic solid phase extraction (MSPE). MNP-PANI-DICAT was characterised by FT-IR NMR, CHN, BET, SEM, TEM, and VSM techniques and the results were compared with MNP-PANI and native MNP. This new material was applied as a magnetic adsorbent for the pre-concentration and separation of polycyclic aromatic hydrocarbons (PAHs) due to the π-π interaction between polyaniline shell and dicationic ionic liquid (DICAT) with PAHs compounds. Under the optimal conditions, the proposed method was evaluated and applied for the analysis of PAHs in environmental samples using gas chromatography-mass spectrometry (GC-MS). The validation method showed good linearity (0.005-500µgL-1) with the coefficient of determination (R2) > 0.999. The limits of detection (LOD) and quantification (LOQ) of the developed method (MNP-PANI-DICAT-MSPE) were in the range of 0.0008-0.2086µgL-1and 0.0024-0.6320µgL-1, respectively. The enrichment factor (EF) of PAHs on MNP-PANI-DICAT-MSPE were in the range of 7.546-29.632. The extraction recoveries of natural water, sludge, and soil samples were ranged from 80.2% to 111.9% with relative standard deviation (RSD) less than 5.6%. The newly synthesised MNP-PANI-DICAT possess good sensitivity, reusability, and fast extraction of PAHs under the MSPE procedure in various environmental samples.
In this study, a simple sample preparation method was developed for the determination of tri-and hexavalent chromium in water samples. It utilizes a pre-heated customized glass tube (CGT), to supply the heat energy required for the reaction of Cr(III) with ammonium pyrrolidinedithiocarbamate (APDC). The products of the Cr complexes, tris(1-pyrrolidinecarbodithioato)chromium(III) and bis(1-pyrrolidinecarbodithioato)[1-pyrrolidinecarbodithio(thioperoxoato)]chromium(III) were chromatographed with Shimadzu LC-20AT and Zobax Eclipse C18 (150mm × 4.6mm, 5µm) column using ACN: Water, (7:3, v/v) as the mobile phase. The concentration of Cr(III) ranged from 0.06mgL-1to 0.09mgL-1and that of Cr(VI) was between 0.02mgL-1to 0.04mgL-1in the samples. Percentage recoveries from spiked real samples were between 87% (tap water) to 110% (wastewater) for Cr(III) and 92% (pond water) to 117% (tap water) for Cr(VI). The limits of detection (LODs) were 0.0029mgL-1and 0.0014mg/L-1for Cr(III) Cr(VI) respectively. While the limits of quantitation (LOQs), were 0.0098mgL-1and 0.0047mgL-1for Cr(III) and Cr(VI) respectively. Method precision (RSD (%)) was 3.3% and 3.5% for Cr(III) and Cr(VI) respectively. The developed method was applied for the speciation analysis of chromium in drinking water, tap water, wastewater, river water, and pond water samples. Our findings proved the method is simple and inexpensive. The method was validated by the analysis of a certified reference material (CRM) SLRS-4. The percentage recovery and RSD(%) from the spiked CRM were 91% and 115% and 0.32% and 1.4% for Cr(III) and Cr(VI) respectively.
Molecularly imprinted polymer (MIP) was employed as sorbent in ultrasound assisted emulsification molecularly imprinted polymer micro-solid phase extraction (USAE-MIP-µ-SPE) of bisphenol A (BPA) in water, beverages and the aqueous liquid in canned foods prior to high performance liquid chromatography-diode array detector (HPLC-DAD) analysis. Several effective variables, such as types of emulsification solvent and its volume, types of desorption solvent and its volume, salting out effect, pH of sample solution, mass of sorbent, extraction and desorption time, and sample volume, were optimized comprehensively. Under the optimized USAE-MIP-µ-SPE and HPLC-DAD conditions, the method demonstrated good linearity over the range of 0.5-700μgL-1with a coefficient determination of R2=0.9973, low limit of detection (0.07μgL-1), good analyte recoveries (82.2-118.9%) and acceptable RSDs (0.7-14.2%, n=3) with enrichment factor of 49. The method was applied to thirty samples of drinking water, mineral water, river water, lake water, as well as beverages and canned foods, the presence of BPA was identified in four samples. The proposed method showed good selectivity and reusability for extraction of BPA, and hence the USAE-MIP-µ-SPE is rapid, simple, cost effective and environmentally friendly.
A paper-based polymeric ionic liquid (p-Poly-(MMA-IL)) was successfully developed by grafting the polymeric ionic liquid on the surface of commercial filter paper (FP) by using the dipping method, presenting a new cost-effective film. The newly developed p-Poly-(MMA-IL) FP was then applied as a paper-based thin-film microextraction (p-TFME) analytical device to extract 14 compounds as representative of five groups of antibiotic drugs, which were sulfonamides, tetracyclines, fluoroquinolones, penicillin and macrolides in environmental water samples. Besides, p-Poly-(MMA-IL) FP, p-Poly-(MMA) FP, and unmodified filter paper were successfully characterised by FTIR, NMR, FESEM, TGA, and XRD techniques. They underwent significant parameters optimisation, which affected the extraction efficiency. Under optimal conditions, the proposed (p-Poly-(MMA-IL) FP-TFME) device method was evaluated and applied to analyse multi-class antibiotic drugs in environmental water samples by using a liquid chromatography-mass spectrometry (LC-MS). The validation method showed that a good linearity (0.1 μg L-1 - 500 μg L-1) was noted (R2 > 0.993, n = 3). Detection and quantification limits were within 0.05 μg L-1 - 4.52 μg L-1 and 0.15 μg L-1 - 13.6 μg L-1, respectively. The relative standard deviation (RSD) values ranged at 1.4%-12.2% (intra-day, n = 15) and 4.4%-11.0% (inter-day, n = 10). The extraction recoveries of environmental water samples ranged from 79.1% to 126.8%, with an RSD of less than 15.4% (n = 3). The newly developed paper-based polymeric ionic liquid (p-Poly-(MMA-IL) FP) for analysis of multi-class antibiotic drugs under the p-TFME analytical device procedure was successfully achieved with limited sample volume and organic solvent, fast extraction, and feasible in daily analysis. The detection concentration and relative RSD of multi-class antibiotics determined in various environmental water samples by the proposed method (n = 5) were within 0.44 μg L-1 - 54.41 μg L-1 and 0.69%-15.56%, respectively. These results signified the potential of the p-Poly-(MMA-IL) FP-TFME device as an efficient, sensitive and environmentally friendly approach for analysing antibiotics.
In this work, we proposed a biosensor for trypsin proteolytic activity assay using immobilization of model peptides on screen-printed electrodes (SPE) modified with gold nanoparticles (AuNPs) prepared by electrosynthetic method. Sensing of proteolytic activity was based on electrochemical oxidation of tyrosine residues of peptides. We designed peptides containing N-terminal cysteine residue for immobilization on an SPE, modified with gold nanoparticles, trypsin-specific cleavage site and tyrosine residue as a redox label. The peptides were immobilized on SPE by formation of chemical bonds between mercapto groups of the N-terminal cysteine residues and AuNPs. After the incubation with trypsin, time-dependent cleavage of the immobilized peptides was observed by decline in tyrosine electrochemical oxidation signal. The kinetic parameters of trypsin, such as the catalytic constant (kcat), the Michaelis constant (KM) and the catalytic efficiency (kcat/KM), toward the CGGGRYR peptide were determined as 0.33 ± 0.01 min-1, 198 ± 24 nM and 0.0016 min-1 nM-1, respectively. Using the developed biosensor, we demonstrated the possibility of analysis of trypsin specificity toward the peptides with amino acid residues disrupting proteolysis. Further, we designed the peptides with proline or glutamic acid residues after the cleavage site (CGGRPYR and CGGREYR), and trypsin had reduced activity toward both of them according to the existing knowledge of the enzyme specificity. The developed biosensor system allows one to perform a comparative analysis of the protease steady-state kinetic parameters and specificity toward model peptides with different amino acid sequences.
COVID-19 pandemic is a serious global health issue today due to the rapid human to human transmission of SARS-CoV-2, a new type of coronavirus that causes fatal pneumonia. SARS -CoV-2 has a faster rate of transmission than other coronaviruses such as SARS and MERS and until now there are no approved specific drugs or vaccines for treatment. Thus, early diagnosis is crucial to prevent the extensive spread of the disease. The reverse transcription-polymerase chain reaction (RT-PCR) is the most routinely used method until now to detect SARS-CoV-2 infections. However, several other faster and accurate assays are being developed for the diagnosis of COVID-19 aiming to control the spread of infection through the identification of patients and immediate isolation. In this review, we will discuss the various detection methods of the SARS-CoV-2 virus including the recent developments in immunological assays, amplification techniques as well as biosensors.