Recent Advances in Aptasensing Strategies for Monitoring Phycotoxins: Promising for Food Safety
Abstract
:1. Introduction
2. Overview of Developed Aptasensors for Phycotoxins
3. Monitoring of Phycotoxin Pollutants in Environmental and Drinking Water
3.1. Microcystin-Leucine-Arginine (MC-LR)
A Retrospect of Past Studies on Microcystins-LR (MCs) Aptasensor Platforms
3.2. Saxitoxins (STXs)
A Brief Lookat Aptasensing Stages on Saxitoxins (STXs)
Target | Aptamer Modification | Aptamer Sequences 5′-3′ | Length (nt) | Kd (nM) | Ref |
---|---|---|---|---|---|
MC-LR | 5′-SH | TTT TTG GGT CCC GGG GTA GGG ATG GGA GGT ATG GAG GGG TCC TTG TTT CCC TCT TG- | 55 | 50 | [31] |
5′-HS-(CH2)6 | GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC | 60 | 28 ± 8 nM | [30] | |
- | GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC | 60 | 28 ± 8 nM | [16] | |
5′-NH2-(CH2) 6 | TTT TTG GGT CCC GGG GTA GGG ATG GGA GGT ATG GAG GGG TCC TTG TTT CCC TCT TG | 56 | 50 | [29] | |
5′-NH2-(CH2) 6 | GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC | 60 | 28 ± 8 nM | ||
5′-NH2-(CH2) 6 | CAC GCA ACA ACA CAA CAT GCC CAG CGC CTG GAA CAT ATC CTA TGA GTT AGT CCG CCC ACA | 60 | 92 | ||
5′-NH2-(CH2) 6 | CAC GCA CAG AAG ACA CCT ACA GGG CCA GAT CAC AAT CGG TTA GTG AAC TCG TAC GGC GCG | 60 | 103 | ||
5′-(SH)-(CH2)6- | GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC | 60 | 28 ± 8 nM | [33] | |
5′-(SH)-(CH2)6 | GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC | 60 | 28 ± 8 nM | [32] | |
AAAAAAAAAAAAA | GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC | 60 | 28 ± 8 nM | [20] | |
FAM | GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC | 60 | 28 ± 8 nM | [35] | |
QD525 | GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC | 60 | 28 ± 8 nM | [36] | |
- | GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC | 60 | 28 ± 8 nM | [37] | |
5′-SH-TTTTTT | GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC | 60 | 28 ± 8 nM | [38] | |
STX | 5′-SH-CTTCTTCTTCTT &TTCTTCTTC-3′ | TTG AGG GTC GCA TCC CGT GGA AAC AGG TTC ATT G | 34 | 133 nM | [43] |
FAM | GGC GGG TTT TGA GGG TCG CAT CCC GTG GAA ACA GGT TCA TTG TTC CCG CC | 50 | 32.8nM | [44] | |
5′-Thiol | GGT ATT GAG GGT CGC ATC CCG TGG AAA CAT GTT CAT TGG GCG CAC TCC GCT TTC TGT AGA TGG CTC TAA CTC TCC TCT | 78 | -(long) | [45] | |
HB-M-30f (HEX 5′-fluorophore (HEX, hexachlorofluorescein) & quencher (BHQ1, black-hole quencher 1)-3′ | TTG AGG GTC GCA TCC CGT GGA AAC AGG TTC ATT G | 34 | 133 nM | [46] |
4. Monitoring of Phycotoxin Pollutants in Fish
4.1. Tetrodotoxins (TTXs)
Some Aptasensing Platforms on Tetrodotoxins (TTXs)
5. Monitoring of Phycotoxin Pollutants in Fish and Shellfishes
5.1. Okadaic Acid (OA)
Recent Development in Aptasensing Platforms on Okadaic Acid (OA)
5.2. Brevetoxins (BTXs)
Aptasensing Platforms on Brevetoxins (BTXs)
5.3. Aptasensing Platforms for the Other Phycotoxins in Fish and Shellfish
5.3.1. Designed Aptasensing Platforms on Gonyautoxin (GTX)
5.3.2. A Developed Aptasensor for the Identity of Palytoxin (PTX)
5.3.3. A platform of Anatoxin-a (ATXs) Aptasensing
Target | Aptamer Modification | Aptamer Sequences 5′-3′ | Length (nt) | Kd (nM) | Ref |
---|---|---|---|---|---|
ATXa | 5′-HO–(CH2)6–S–S–(CH2)6 | TGG CGA CAA GAA GAC GTA CAA ACA CGC ACC AGG CCG GAG TGG AGT ATT CTG AGG TCG G | 58 | 81.3 ± 8 nM | [27] |
OA | - | GGT CAC CAA CAA CAG GGA GCG CTA CGC GAA GGG TCA ATG TGA CGT CAT GCG GAT GTG TGG | 60 | 23 ± 1.52 nM | [47] |
3′-Biotin 3′-FAM | ATT TGA CCA TGT CGA GGG AGA CGC GCA GTC GCT ACC ACC T | 40 | - | [48] | |
5′-Thiol- | GGT CAC CAA CAA CAG GGA GCG CTA CGC GAA GGG TCA ATG TGA CGT CAT GCG GAT GTG TGG | 60 | 23 ± 1.52 nM | [70] | |
- | GGT CAC CAA CAA CAG GGA GCG CTA CGC GAA GGG TCA ATG TGA CGT CAT GCG GAT GTG TGG | 60 | 23 ± 1.52 nM | [49] | |
5′-(SH)-(CH2)6- | GGT CAC CAA CAA CAG GGA GCG CTA CGC GAA GGG TCA ATG TGA CGT CAT GCG GAT GTG TGG | 60 | 23 ± 1.52 nM | [7] | |
5′-(SH)-(CH2)6 3′-Biotin | GGT CAC CAA CAA CAG GGA GCG CTA CGC GAA GGG TCA ATG TGA CGT CAT GCG GAT GTG TGG | 60 | 23 ± 1.52 nM | ||
5′-(SH)-(CH2)6- | GGC CGC GAG AGA GAC AAC AAG GAT ATA TAT TAT ATG TCG GTT GTA GTG TTG GGT TGC G | 58 | 92 nM | ||
5′-SH-(CH2)6- | GGT CAC CAA CAA CAG GGA GCG CTA CGC GAA GGG TCA ATG TGA CGT CAT GCG GAT GTG TGG | 60 | 23 ± 1.52 nM | [50] | |
GTX | - | AAC CTT TGG TCG GGC AAG GTA GGT T | 25 | 17.7nM | [25] |
BTX | 5′-SH-(CH2)6 | GGC CAC CAA ACC ACA CCG TCG CAA CCG CGA GAA CCG AAG TAG TGA TCA TGT CCC TGC G | 58 | 92 nM | [51] |
5′-ThioMC6-D | AT ACC AGC TTA TTC AAT TGG CCA CCA AAC CAC ACC GTC GCA ACC GCG AGA ACC GAA GTA GTG ATC ATG TCC CTG CGT GAG ATA GTA AGT GCA ATC T | 96 | - | [9] | |
5′-SH–(CH2)6 | GTG CGT CCC TGT ACT AGT GAT GAA GCC AAG AGC GCC AAC GCT GCC ACA CCA AAC CAC CGG | 60 | 42 nM | [52] | |
5′-NH2-(CH2)6 | GTT GCC GTC TCC TTA TCC CAC CAC TGC CGA CAC CAC CCC CCC GCG AGA GCG AGA GAG CAC T | 61 | 96 nM |
6. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Target | Method | LOD | Linear Range | Analytical Signal vs. Concentration Slope | Real Sample | Characteristics | Ref |
---|---|---|---|---|---|---|---|
MC-LR | AAIA | 0.3 μg/L | 0.5–4.0 μg/L | Y = 9.2288x + 8.1072 R2 = 0.968 | Drinking water | A portable analyzer, assay time: 35 min | [29] |
Infinity-shaped DNA structure and TdT enzyme | 20 pM in tap water, 35 pM in serum | 70 pM–900 nM for tap water and 100 pM–750 nM in serum | Y = 1.181x − 2.0437 R2 = 0.99924 | Tap water & serum | Assay time: 90 min plus 12 h preparation phase, using DPV analysis | [20] | |
Electrospinning & seeded growth on MOF of the solid-phase microextraction (SPME) fiber | 0.003 ng/mL | 0.008–1.000 ng/mL | Y = 12.135665x − 33.418 R2 = 0.9996 | Drinking water | Assay time of 20 min plus 72 h preparation phase | [16] | |
Dual signal amplification system: HRP enzyme & electroactive nanomaterials | 0.002 nM | 0.005–30 nM | Y = 6.28logx + 16.39 R2 = 0.994 | Water from taps, reservoirs & rivers | About 40 h for the synthesis of an AuNP@ MoS2-TiONB nanocomposite and 2 h for the construction | [30] | |
Electrochemical impedance spectroscopy (EIS) | 1.8 × 10−11 mol/L | 1.0 × 10−7–5 × 10−11 mol/L | Y = 9.9724logx + 111.24 R2 = 0.997 | Water | About 6 h for assay time and preparation phase | [31] | |
Signal amplification strategy with DNase I | 0.22 nM | 0.25–20 nM | Y = 0.55x − 3.630 R2 = 0.9996 | Drinking water | Directly analysis | [32] | |
Cantilever array | 1 μg/L | 1–50 μg/L | Y = 2.11x + 9.01 R2 = 0.97 | Buffer | Label-free analysis, About 85 min for assay time and preparation phase | [33] | |
Gold nanoparticles (AuNPs) and plasma resonance | 0.37 nM | 0.5 nM–7.5 μM | Y = 0.1662logx + 0.2533 R2 = 0.997 | Water | Label-free analyzer, quick detecting: 30 min | [34] | |
Graphene-modified screen-printed carbon electrodes (SPEs) | 1.9 pM in buffer 1.67 pM inthe spiked sample | 0.1 pM–1.0 nM | Y = 12.20logx + 28.35 R2 = 0.988 | Buffer | Label-free, a stable assay | [14] | |
Single-walled carbon nanotubes (SWNTs) & dapoxyl dye | 138 pM (0.137 µg/L) | 0.4–1200 nM. | Y = 0.0089x − 2.76 R2 = 0.9929 | Tap water & serum | Label-free analyzer only 75 min for assay time | [35] | |
Fluorescence resonance energy transfer (FRET)-based quantum dot (QD) | 10−4 μg/L | 10−4–102 ng/mL | Y = 0.15logx + 0.93 R2 = 0.94 | Eutrophic water | Short lifetime unsuitable for on-site analysis of the target | [36] | |
Oriented formation of gold nanoparticle (AuNP) dimers | 0.05 nM | 0.1–250 nM | R2 = 0.990119 | Water | Achieving results within 5 min | [37] | |
Solid-state nanopores | 1 μg/L | 0.1 nM–20 μM | denotes | Water | - | [38] | |
TTX | SERS | 0.006 ng/mL | 0.01–300 ng/mL | Y = 1470.04x + 3386.77 R2 = 0.9958 | Pufferfish and clam meat | Without cumbersome procedures, exhibited signal responses within 1 month, immobilization-free, dual-mode detection | [39] |
Fluorescence reporter | 0.074 nM | 0.1–500 nM | Y = 0.002x + 2.4713 R2 = 0.9958 | denotes | Label-free direct analysis, environmental and eco-friendly | [40] | |
Docking and molecular dynamics (MD) simulations and microscale thermophoresis (MST) | denotes | denotes | denotes | Pufferfish | Effective repurposing approach, susceptible | [41] | |
Triple cycle amplification-based MNPs-apt | 0.265 pg/mL | 0.05–500 ng/mL | Y = 4936.74 + 1327logx R2 = 0.9932 | Clams and shellfish | Isothermal amplification, reliable sensitivity, and stability, practical for the analysis of food | [42] | |
STX | Electrochemical aptasensor | 0.92 nM | 1–400 nM | Y = 26.7x + 5.48 R2 = 0.9932 | Seawater | Label-free direct analysis, empathetic detection, good practical adaptability and robustness, good recovery, assay time within 30 min | [43] |
Colorimetric aptasensor | 0.1423 nM | 0.1457–37.30 nM | Y = 42.09logx + 38.70 R2 = 0.9863 | Seawater and Scallop | Label-free direct analysis, a terminal-fixed anti-STX aptamer, assay time of 75 min, high selectivity, and good recoveries | [44] | |
Square Wave Voltammetry (SWV), Electrochemical Impedance Spectroscopy (EIS) | 4.669 pg/mL | 10 pg/mL–1 μg/mL | Y = 0.05282x + 0.03536 R2 = 0.9713 | Freshwater | High sensitivity, wide detection range, reduce the error rate | [45] | |
Fluorescent aptasensor | 1.8 ng/mL | 0–24 ng/mL | Y = 5.25x + 587.2 R2 = 0.998 | Shellfish | Assay time of 30 min, simple | [46] | |
ATX | Impedimetric | 0.5 nM | 1–100 nM | denotes | Drinking water | Label-free direct analysis, assay time 60 min | [27] |
OA | LC-based aptasensor | 0.42 pM | 0.1–100 pM | Y = 22.5x + 68.6 R2 = 0.988 | Clam | Label-free direct analysis, low-cost detection, rapid | [47] |
Fluorescent aptasensor | 1.1 ng/L | 1.0 ng/L–50.0 μg/L | Y = 438.3logx + 3344 R2 = 0.9909 | Shellfish | Ultrahigh-sensitivity, a duplexed aptamer-isothermal amplification, used for on-site food safety screening | [48] | |
Aptamer-based microcantilever-array | 1 pg/ml | 1–5000 pg/ml | Y = 29.2496 × 0.4014/(1 + 0.0892 × 0.4014) R2 = 0.9887 | Clam | Label-free direct analysis, excellent dynamic range, economical | [7] | |
Microfluidic based aptasensor | 8 pM | 10–250 nM | Y = −0.0142x + 6.1139 R2 = 0.9887 | Mussel | Assay time of 30 min, stable, easy to use | [9] | |
Piezoelectric aptasensor | 0.32 nM | 0.5–200 nM | Y = 139.0x + 489.3 R2= 0.9826 | Mussel | Label-free direct analysis, ultrasensitive, low-cost | [49] | |
Paper SERS aptasensor | 0.31 ng/mL | 1.0–2500 ng/mL | Y = 475.55logx + 356.20 R2 = 0.9865 | Shellfish | Rapid on-site analysis, low-cost | [50] | |
GTX | Optical BLI aptasensor | 50 pg/mL | 0.2–90 ng/mL | Y = 0.0049x + 0.0146 R2 = 0.998 | Shellfish | Label-free direct analysis, stable, good reproducibility, high affinity to GTX1/4, simple detection | [25] |
PTX | Competitive BLI aptasensor | 0.04 pg/mL | 200–700 pg/mL | Y = (25.05427 − 0.10812)/[1 + (x/0.00180)−1.50701] + 0.10812 R2=0.999 | Shellfish and seawater | Assay time of 30 min, ultra-sensitive, real-time | [24] |
BTX | EIS | 106 pg/mL | 0.01–2000 ng/mL | Y = 12.2 + (102.35 − 12.2)/(1 + (x/6.66)0.59) R2 = 0.997 | Shellfish | Competitive assay | [51] |
QCR | 220 nM/mL | 1–1000 nM | Y = 0.0752x + 12.34 R2 = 0.997 | Shellfish | Label-free direct analysis, assay time of 60 min plus preparation phase | [9] | |
SE | 720 pg/mL in buffer, LOQ~900 pg/mL in real seafood samples | 0.5–2000 nM | Y = 3.023logx + 2.059 R2 = 0.95 | Fish and shrimp | Label-free direct analysis, assay time of 90 min plus preparation phase | [52] | |
TIRE | 1.32 ng/mL in buffer, LOQ~1.8 ng/mL in real seafood samples |
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Zahraee, H.; Mehrzad, A.; Abnous, K.; Chen, C.-H.; Khoshbin, Z.; Verdian, A. Recent Advances in Aptasensing Strategies for Monitoring Phycotoxins: Promising for Food Safety. Biosensors 2023, 13, 56. https://doi.org/10.3390/bios13010056
Zahraee H, Mehrzad A, Abnous K, Chen C-H, Khoshbin Z, Verdian A. Recent Advances in Aptasensing Strategies for Monitoring Phycotoxins: Promising for Food Safety. Biosensors. 2023; 13(1):56. https://doi.org/10.3390/bios13010056
Chicago/Turabian StyleZahraee, Hamed, Atiyeh Mehrzad, Khalil Abnous, Chih-Hsin Chen, Zahra Khoshbin, and Asma Verdian. 2023. "Recent Advances in Aptasensing Strategies for Monitoring Phycotoxins: Promising for Food Safety" Biosensors 13, no. 1: 56. https://doi.org/10.3390/bios13010056
APA StyleZahraee, H., Mehrzad, A., Abnous, K., Chen, C. -H., Khoshbin, Z., & Verdian, A. (2023). Recent Advances in Aptasensing Strategies for Monitoring Phycotoxins: Promising for Food Safety. Biosensors, 13(1), 56. https://doi.org/10.3390/bios13010056