Lecture Notes Review: Biosensors and Protein Structure

Recap from Last Lecture

• Bacteria-based Biosensors:

  • Utilize engineered bacteria with a stress-inducible promoter linked to a reporter gene.

  • When the stress response is activated (e.g., due to water quality issues), bacteria emit a signal ("flash" a warning).

  • Applications include water quality monitoring.

  • Can be specific (e.g., UO$_{2}^{2+}$) or semi-specific.

  • Comparison of Stress-inducible vs. Constituent Sensors:

    • Constituent: Always "on" when the water supply is OK, or partially "off" if the supply is not OK.

    • Stress-inducible: "off" when water is OK, "on" or partially "off" when water is not OK.

    • The negative control M2G's behavior depends on the context.

  • Commercial products are widely used, and this sensor type is highlighted as an excellent publication.

  • Self-testing function is a key feature.

• Urban/Industrial Monitoring:

  • Biosensors enable continuous, unattended, real-time monitoring.

  • Concept: Microbial biosensors for detecting endocrine disruptors in urban waterways (e.g., Biosensors & Bioelectronics, 2021).

  • Fabrication: Immobilization of engineered bacteria on an electrode, where cells produce an electric current upon detection.

  • Example: 4-Hydroxytamoxifen (4-HT) as a model endocrine disruptor.

  • Detection can occur in minutes (Nature, 2022).

• Mammalian Cell-based Biosensors:

  • Involve G-protein coupled receptors, where conformational changes offer unique possibilities.

  • Like bacteria-based sensors, these can be specific (ligand-specific) or semi-specific.

  • Cool Applications: Allergy profilers (activation of HRH2-histamine receptor leads to reporter protein signaling) and neurons for sensing warfare agents.

Enzyme-based Biosensors: Fundamentals

• Introduction:

  • Enzyme sensors are a key topic for today's lecture and will be included in quizzes and exams.

  • Students are expected to be familiar with basic undergraduate material related to enzymes and proteins.

• Principles of Enzyme Biosensors:

  • Bioreceptor: An enzyme (e.g., Glucose Oxidase - GOx in a glucose sensor) is attached to a transducer surface.

  • Function: Enzymes are highly selective biocatalysts that accelerate chemical reactions, enabling relatively fast detection.

  • Analyte Role: In enzyme-based sensors, the analyte can be either:

    • (i) Enzyme substrate (S): The enzyme converts the substrate into a product (P).

    • (ii) Enzyme inhibitor (I): The enzyme's activity is reduced by the inhibitor.

  • Signal Generation: In both cases, the reaction product or the change in reaction rate is used to generate a signal, although the sensor's response to analyte concentration will differ.

Protein Structure: A Quick Reminder

• Proteins as Copolymers: Linear co-polymers of just twenty amino acids, exhibiting amazing structural variety.

• Amino Acid Diversity: Students should know the different categories of amino acids (small, aliphatic, alcohols, sulfur-containing, aromatic, acidic, basic, amides) and their general properties (hydrophobic/hydrophilic, charged at neutral pH).

• Amino Acid Functionality: Each amino acid has common $NH_{2}$ (alpha-amino) and $COOH$ (alpha-carboxyl) groups attached to a central alpha-carbon, but different side chains (R-groups).

  • The $NH_{2}$ and $COOH$ groups are very reactive and can be used for biomolecule immobilization on surfaces.

  • Side chains also contain reactive functional groups crucial for immobilization.

• Peptide Bonds & Polypeptides:

  • Dipeptides and polypeptides form through peptide bonds, where most alpha-amino and alpha-carboxyl groups are consumed.

  • The N-terminus (amino end) and C-terminus (carboxyl end) remain reactive at the ends of the polypeptide chain.

• Levels of Protein Structure:

  • Primary Structure: The linear sequence of amino acids in a polypeptide chain. This is crucial because even proteins with low sequence homology (e.g., Chymotrypsin and Thrombin with $30\%$ homology) can have almost identical folds, highlighting the importance of sequence-to-structure relationships.

  • Secondary Structure: Defines the local folding/conformation of protein segments, primarily stabilized by patterns of hydrogen bonding between backbone atoms.

    • Alpha-helix: A common motif where the $CO$ group of residue 'n' forms a hydrogen bond with the $NH$ group of residue '$n+4$'. Often depicted as ribbons or rods, with side chains pointing outwards. $H$ bonds are approximately $2.86\ Å$ long.

    • Beta-strands & Beta-sheets: Beta-strands are polypeptide chains in beta-sheets where the backbone is almost fully extended (distance between adjacent AAs is $3.5\ Å$ vs $1.5\ Å$ in alpha-helix). Peptide carbonyls point in alternating directions. Depicted by broad arrows pointing towards the carboxyl-terminus.

      • Directionality: Beta-strands can be arranged in antiparallel (N-terminus of one strand adjacent to C-terminus of another) or parallel (directionally aligned) arrangements.

      • Hydrogen Bonding in Beta-sheets:

        • Antiparallel: $NH$- and $CO$-groups of each amino acid are hydrogen bonded to the $CO$- and $NH$-group respectively of a partner on the adjacent beta-strand.

        • Parallel: For each amino acid, the $NH$-group is $H$-bonded to the $CO$-group of one amino acid on the adjacent strand, while the $CO$-group is $H$-bonded to the $NH$-group on the amino acid two residues further along the chain.

      • Beta-sheets are critical structural elements, often comprising $4$ to $10+$ strands. Most proteins contain both alpha-helices and beta-sheets for stability.

  • Tertiary Structure: Describes the global three-dimensional folding of the polypeptide chain, assembling different elements of secondary structure into a particular arrangement. Amino acid residues in the active site are brought together. Many proteins have distinct structural domains (e.g., Pyruvate kinase is a 3-domain protein), which are fundamental units of tertiary structure and useful for protein engineering.

  • Quaternary Structure: Describes the assembly of multiple polypeptide chains (subunits) in proteins when more than one is present (e.g., Glucose isomerase, Phosphorylase).

    • Active sites are often formed by a pair of subunits.

    • Interwoven arrangements (like in Glucose Isomerase) can lead to high stability, resisting dissociation.

• Maintaining Protein Structure and Activity:

  • Proteins are only active if their unique tertiary/quaternary structure is maintained.

  • Stabilized by a variety of covalent (e.g., disulfide bonds, $S-S$) and non-covalent interactions (e.g., hydrogen bonds, hydrophobic interactions).

  • In water-soluble proteins, hydrophilic amino acids are on the surface, while hydrophobic groups are shielded in the interior, with hydrophobic interactions being critical for fold integrity.

  • Importance of Protein Structure Knowledge:

    • Understanding stability (single vs. multi-subunit, overall fold).

    • Identifying amino acid residues at/near the binding/catalytic site for immobilization chemistry.

    • Determining availability/relative position of C- and N-terminus for immobilization methods.

    • Enabling optimization and performance improvements through protein engineering.

Why Enzymes are Useful in Biosensors

• Key Advantages:

  • Sensitivity: Can detect very low concentrations of analytes.

  • Selectivity: Highly specific for their substrates, minimizing interference.

  • Stability/Reproducibility: Desirable for practical applications.

  • Ease of Integration: Can be readily integrated with various types of transducers.

  • Signal Amplification: Enzymes can catalyze multiple reactions, leading to amplified signals.

• Historical and Commercial Success: Enzymes dominated the biosensors field in the 1990s, with enzyme-based glucose biosensors for diabetics remaining the biggest commercial success story.

Examples of Enzyme-based Biosensors

Luciferase Biosensors for ATP Detection

• Principle: Luciferases are enzymes that convert energy into light (bioluminescence).

  • Bacterial luciferase reaction: $FMNH<em>{2} + RCHO + O</em>{2} \rightarrow FMN + RCOOH + H_{2}O + light$ ($490nm$).

  • Firefly luciferase reaction: $Luciferin + ATP \rightarrow Luciferyl\ adenylate + PPi$, followed by $Luciferyl\ adenylate + O_{2} \rightarrow Oxyluciferin + AMP + light$ ($560nm$).

• ATP as an Analyte:

  • Early-stage cell breaking: Monitoring quality of erythrocytes in blood banks (though better assays are now available).

  • Hygiene Monitoring: Detecting bacteria on surfaces.

• Hygiene Monitoring with Luciferase:

  • Traditional Method: Cotton swab followed by petri dish culture takes about a day for results.

  • Luciferase Assay: Takes minutes.

  • Commercial Products: e.g., Lumitester, using bacterial luciferase to measure bioluminescence from ATP decomposition.

  • AMP-ATP Circulation Technology (Patented): Allows measurement of both ATP and AMP as part of the ATP cycle, offering better sensitivity and more stable light signals.

    • In heat-treated foods, ATP breaks down to AMP, so detecting both provides a more reliable assessment of hygiene.

  • Measurement Procedure: Moistening a swab, wiping the surface, inserting it into a sensor, and obtaining results in $\sim 10$ seconds.

  • Performance: Comparative analysis in hospital kitchens (280 spots) showed discrepancies with traditional microbiology, with the biosensor being more sensitive.

  • Beyond Kitchens: Used for hygiene monitoring in various environments.

• Airborne ATP Detection:

  • System Components:

    1. Condensation system to concentrate aerosols (suspension of particles/droplets in a gas).

    2. ATP extraction from captured bacteria (lysis of microorganisms).

    3. Bioluminescence detection of ATP.

  • Flow Rate: e.g., $2\ L/min$ (older), $100\ L/min$ (newer, battery-operated/hand-held devices).

  • Performance: Dynamic range from $10^{-12}\ M$ to $10^{-3}\ M$ ATP. practically real-time detection ($10^{7}\ E.coli/mL$ produces detectable ATP).

  • Applications: Air monitoring for military, health, and general air quality control in public places (e.g., transportation systems).

  • Recent Relevance: Used for COVID and airborne allergens.

SARS-CoV-2 Detection: Advanced Biosensors

• Electrode-based Virus Detection (Nature Com, 2023):

  • Virus captured by antibodies (ABs) immobilized on an electrode.

  • Detection based on oxidation of Tyrosine present on viral proteins.

  • Efficient, fast (5 mins detection), and portable aerosol sampler integrated with AB-based biosensor.

  • Critically, addresses the current lack of automated real-time airborne SARS-CoV-2 detection devices.

  • Offline air sampling (collection, then lab analysis) is commonly used, making real-time portable devices an advancement.

• Antibody-based Detection (Nature Biomed Eng, 2021):

  • Utilizes a Luciferase design to detect serological antibodies, monitoring vaccination response.

  • Patient antibodies are incubated with SARS-CoV proteins (fused to $LgBiT/SmBiT$ split luciferase fragments).

  • Active luciferase is only reconstructed when antibody arms bind to both $LgBiT$ and $SmBiT$ sensors (i.e., $\sim 50\%$ of antibodies are detected).

  • Provides dose-dependent luminescence signal, allowing for quantitative measurement of antibody response, unlike many qualitative lateral flow tests.

Glucose Sensor: Glucose Oxidase (GOx)

• Challenge: Chemically detecting glucose in a blood sample without separation is difficult due to other active compounds.

• Solution: Enzyme electrodes modify the electrode tip to specifically measure enzymatic reactions.

• Principle: Glucose Oxidase catalyzes the reaction: $Glucose + O<em>{2} + H</em>{2}O \rightarrow Gluconic\ acid + H<em>{2}O</em>{2}$

  • At neutral pH, gluconic acid (product) dissociates to give $COO^{-}$ and $H^{+}$.

  • The reaction can be followed by monitoring pH.

• Fabrication (pH Electrode based):

  1. Start with a conventional pH electrode.

  2. Add a membrane that is permeable to $S$ (glucose) and $P$ (gluconic acid) but not to the enzyme ($E$).

  3. Immobilize GOx (or other enzyme) between two membranes.

  4. This creates an enzyme electrode, functioning as a biosensor.

• Clark-type Oxygen Electrode: Early biosensors like the Clark electrode measured oxygen consumption (rather than pH change) as glucose is oxidized, consuming $O_{2}$.

Polyphenol Oxidase (PPO) "Bananatrode"

• Concept: A plant-based biosensor made from banana, which contains plenty of PPO.

• Reaction: PPO catalyzes the oxidation of dopamine to dopamine quinone (consuming $O_{2}$).

• Application: Dopamine detection.

Organophosphate Hydrolases (OPAA) for Neurotoxins

• Analytes: Practically important neurotoxins like Sarin (chemical warfare agent), Dichlorvos (insecticide), Paraoxon (organophosphorus pesticide).

• Enzyme: Organophosphate hydrolases (e.g., Aryldialkylphosphatase, EC 3.1.8.1) catalyze the hydrolysis of P-O bonds.

• Mechanism: Hydrolysis products are strong acids.

• Detection: Can be done with a pH-sensitive device due to the change in acidity.

• Relevance: Many organophosphates are banned in various countries.

Acetylcholinesterase (AChE)-based Biosensors (Inhibitor Detection)

• Commonality of Analytes: Sarin, paraoxon, dichlorvos, and many other warfare agents/pesticides are powerful inhibitors of Acetylcholinesterase (AChE).

• AChE General Function: Hydrolyzes Acetylcholine into choline and acetic acid ($CH_3COOH$).

  • AChE is a serine esterase with a catalytic triad (Ser, His, Glu) and is a very fast enzyme.

  • Involved in neurotransmission (parasympathetic neuron).

• Biosensor Principle: Detection is based on the inhibition of the enzyme's activity by the agent being detected.

  • Clinical Relevance: For clinical diagnostics, red blood cell cholinesterase (RBC) and plasma pseudocholinesterase levels are determined (different context).

• Detection Schemes:

  • pH-based assay: Monitoring pH changes due to acetic acid production.

  • Amperometric/Optical Detection: Using acetylthiocholine as a substrate, which produces thiocholine. Thiocholine can be further modified or detected electrochemically.

  • Multi-enzyme System (Biosensors and Bioelectronics, 2020):

    1. AChE converts acetylthiocholine to thiocholine and $CH_3COOH$.

    2. Choline Oxidase (ChOx) converts thiocholine to $H<em>2O</em>2$.

    3. Horseradish Peroxidase (HRP) oxidizes $H<em>2O</em>2$ and luminol, causing luminol to emit light (chemiluminescence).

  • Application: Foldable paper-based biosensors for pesticide detection (e.g., chlorpyrifos, recently banned in EU).

  • Compatibility with Smartphones: Integrated light detectors (cameras) in smartphones provide sufficient sensitivity for colorimetric or chemiluminescence analysis (though sometimes less sensitive).

Neuraminidase for Influenza Detection

• Analyte: Influenza virus (RNA viruses, A and B subtypes).

• Enzyme: Viral neuraminidase.

• Function: Neuraminidase cleaves sialic acids from cell surface glycoproteins of host cells, essential for virus replication (exiting the cell).

• Biosensor Principle (e.g., Zstat-Flu):

  1. Swab taken from patient's throat, specimen extracted/diluted.

  2. Add a chromogenic or luminescence-based substrate.

  3. Incubate for $\sim 20$ minutes.

  4. Result: Blue color or light emission indicates infection.

• Detection: Reliably detects both influenza A and B but cannot differentiate between clades/subtypes as all possess neuraminidase.

Enzyme Properties and Engineering

• Desired Enzyme Properties for Biosensors: Sensitivity, selectivity, stability/reproducibility, ease of integration, signal amplification.

• If Suitable Enzyme is Not Available: Properties can be engineered through:

  • Rational Protein Engineering: Knowledge-based structural alterations, such as amino acid substitutions or combining/moving protein domains. Requires high-resolution protein structure and detailed knowledge.

  • Directed Evolution: Introduction of a very large number of gene mutations followed by high-throughput screening (HTS) to select proteins with desired characteristics.

    • Challenge: Screening all combinations is impractical (e.g., $20^{50}$ combinations for 50 positions is $1.23 \times 10^{65}$).

    • Solution: Construct libraries smartly to increase hit rate, have great HTS capabilities ($10^6$ samples/day routine, $10^8$ doable), and good screening methods (looking only for desired traits).

    • Process (e.g., for thermostability):

      1. Generate a library of mutants (e.g., via error-prone PCR).

      2. Mutant enzymes expressed in a suitable host.

      3. Assay at a temperature above normal inactivation temperature (e.g., $40^{\circ}C$).

      4. Most denature, but a few survive.

      5. Pick surviving colony, use as starting point for a new library for assay at an even higher temperature (e.g., $45^{\circ}C, 50^{\circ}C, 55^{\circ}C, 60^{\circ}C$).

      6. This iterative process mimics natural evolution ("adapt or die").

    • Example: Lactate Oxidase (LOX): Directed evolution increased LOX half-life at $70^{\circ}C$ by $\sim 36$ times, significantly prolonging LOX-based biosensor lifetime.

      • Application: Lactate levels in serum indicate oxygenation state of tissues (ischemic conditions). Used in life-threatening surgery, intensive therapy, and sports monitoring (lactate build-up).

      • Recent Implementation (Nano Letters, 2025): Real-time lactic acid monitoring in sweat using highly sensitive, selective, and reproducible LOX-based sensors with a wide detection range.

Advanced Biosensor Designs and Rational Protein Engineering

• When Directed Evolution is Insufficient: Directed evolution is fast and less expensive if HTS is available but cannot be used for everything (e.g., re-designing luciferase's binding domain for every analyte).

• Modular Luciferase-based Biosensor Platform (Nature, 2021):

  • Concept: Design luciferase with a closed (dark) state and open (luminescent) state, where analyte binding drives the switch from closed to open.

  • Goal: A modular platform easily repurposed for different targets, where conformational change is independent of analyte's molecular details.

  • Two Protein Components:

    1. "lucCage": Comprises a cage domain, a latch domain with a target-binding motif, and a split luciferase fragment ($SmBiT$).

    2. "lucKey": Contains a key peptide that binds to the open state of lucCage and another split luciferase fragment ($LgBiT$), complementary to $SmBiT$.

  • Mechanism:

    • Closed State: lucCage cannot bind lucKey, preventing SmBiT/LgBiT interaction (no luminescence).

    • Open State: Analyte binding to the target-binding motif causes a conformational change, allowing lucKey to bind to lucCage, bringing SmBiT and LgBiT together to form active luciferase (luminescence).

  • COVID Biosensor Application: Engineered "lucCageRBD" with a protein binder (pM affinity to SARS-CoV-2 spike protein RBD) detected monomeric RBD (15 pM LOD) and full trimeric spike protein (47 pM LOD) with light signal changes. Works in body fluids (e.g., $20\%$ diluted serum).

• Split RNA Polymerase Cell-Free Biosensor (Sci Adv, 2025):

  • Concept: A cell-free biosensor based on a split T7 RNA polymerase fused to affinity domains (e.g., nanobodies, Nb) against a protein target/analyte.

  • Mechanism: Target analyte drives polymerase reassembly, inducing reporter expression (e.g., LacZ) that produces a colorimetric readout (e.g., yellow pigment CPRG to purple CPR).

  • Application: COVID detection, working in serum and saliva.

• Enzyme-Switch "BLA-BLIP" Biosensor for Therapeutic Drug Monitoring (Biosensors & Bioelectronics, 2023):

  • Problem: Therapeutic monoclonal antibodies (TmAb) for cancer/autoimmune diseases have large interpatient variability in pharmacokinetics, requiring dosage optimization.

  • Sensor: In its closed state, \beta-lactamase (BLA) is inhibited by \beta-lactamase inhibitor protein (BLIP). The sensor also has two small binding proteins (Affimers) specific to variable regions of the target antibody.

  • Mechanism: Binding of the therapeutic mAb causes a conformational change, removing BLIP and activating BLA. BLA-catalyzed reaction generates a red product (colorimetric detection).

  • Performance: Detects sub-nM therapeutic antibodies (e.g., Humira) in serum.

• Enzyme-amplified DNA Detection (Inhibitor-DNA-Enzyme, IDE, Complex):

  • Principle: Enzyme is conjugated with a single-stranded DNA (ssDNA) tagged with an enzyme inhibitor.

  • Initial State: Enzyme is inactive because the flexible ssDNA allows the inhibitor to get into the active site ("intramolecular" inhibition).

  • Detection: Binding of target DNA (complementary to ssDNA) leads to the formation of a rigid double-stranded DNA (dsDNA) duplex, pulling the inhibitor out of the active site.

  • Signal: The activated enzyme cleaves its substrate, generating an optical signal (light).

Enzyme Kinetics: Essential for Biosensor Operation

• Importance: Understanding enzyme kinetics (the relationship between reaction rate and substrate concentration, and factors affecting it) is critical for achieving good performance.

• Michaelis-Menten Equation: Provides the relationship between initial reaction rate ($v$), maximum reaction rate ($V<em>{max}$), substrate concentration ($[S]$), and Michaelis constant ($K</em>m$):

  • $v = \frac{V<em>{max}[S]}{K</em>m + [S]}$ This describes how the initial rate declines at low substrate concentrations, approaching a constant rate at high substrate concentrations.

• Implications for Different Substrate Concentrations:

  • If [S] >> Km: The equation simplifies to $v \approx V</em>{max}$.

    • This effectively represents a zero-order reaction, where the rate is largely independent of substrate concentration.

  • If [S] << Km: The equation simplifies to $v \approx \frac{V</em>{max}[S]}{K<em>m} = K</em>{app}[S]$ (where $K_{app}$ is a constant).

    • This effectively represents a first-order reaction, where the rate is proportional to the reactant's concentration.

• Operational Considerations for Substrate-based Biosensors:

  • Biosensor 1 (measuring reaction rate): If the biosensor measures analyte concentration via the reaction rate (signal proportional to rate), it must operate where the rate increases approximately linearly with analyte concentration. Therefore, the enzyme needs a $K<em>m$ above the detection range ([S] << Km operation) to ensure sensitivity to changes in analyte concentration. If operating near $V<em>{max}$ (point 1 on MM plot), the rate is insensitive to $[S]$. For a linear response, operate below $K</em>m$ (e.g., points 3 or 4).

  • Biosensor 2 (measuring total product): If the biosensor determines total analyte concentration by converting all analyte-substrate into product, it needs the enzyme to work fast.

    • Therefore, it should operate above $K<em>m$ (i.e., using an enzyme with low $K</em>m$ and high $V_{max}$) to ensure rapid conversion, unlike Biosensor 1. The total product will be proportional to the initial analyte concentration.

• Operational Considerations for Inhibitor-based Biosensors:

  • Analyte as Inhibitor (Example: Biosensor 3 (Substrate) vs. Biosensor 4 (Inhibitor)):

    • "On" sensor (Analyte = Substrate): Signal goes up with increasing analyte concentration.

    • "Off" sensor (Analyte = Inhibitor): Signal goes down with increasing analyte concentration (the more 'A' is present, the slower the enzyme works, less product accumulated).

  • Types of Inhibition:

    • Competitive Inhibition: Inhibitor binds to the active site, competing with the substrate. Can be outcompeted by high substrate concentration.

      • Effect: Apparent $K<em>m$ increases, but $V</em>{max}$ is unaffected.

      • Optimal $[S]$ for competitive inhibitor detection: Low $[S]$ (but not too low) is generally better. At very high $[S]$, the inhibitor is outcompeted, leading to very low sensitivity (small signal change). Optimal sensitivity is often achieved in the middle range.

    • Non-competitive Inhibition: Inhibitor binds to a site distinct from the active site, affecting the enzyme's catalytic efficiency without affecting substrate binding. Cannot be outcompeted by high substrate concentration.

      • Possible Mechanism: Remote inhibitor binding affects catalytic group positioning.

      • Effect: $V<em>{max}$ decreases, but $K</em>m$ is unchanged.

      • Optimal $[S]$ for non-competitive inhibitor detection: Higher $[S]$ is generally better to maximize signal change difference between inhibited and uninhibited states.

Summary of Enzyme Biosensors

• Enzymes are widely used as sensing biomolecules in biosensors.

• If a suitable enzyme is available, it is often the bioreceptor of choice, especially when extremely high sensitivity is not required.

• Desired properties (selectivity, sensitivity, stability) can be significantly improved through protein engineering or directed evolution.

• In enzyme sensors, the analyte can act as either a substrate or an inhibitor of the enzyme.

• A thorough understanding of protein structures and enzyme kinetics is essential for selecting (or engineering/evolving) the appropriate enzyme and determining optimal operating conditions.

• Enzymes are also routinely employed for signal amplification. This will be discussed further in the next lecture.