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MAE 6291 Biosensors and Bionanotechnology Format lecture, discussion, lots of questions

MAE 6291 Biosensors and Bionanotechnology Format lecture, discussion, lots of questions will aim to have students present segments of papers in each class (.25) homework ~ 1 every 2-3 classes to learn how to use what we cover (.25) and help analyze papers

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MAE 6291 Biosensors and Bionanotechnology Format lecture, discussion, lots of questions

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  1. MAE 6291 Biosensors and Bionanotechnology Format lecture, discussion, lots of questions will aim to have students present segments of papers in each class (.25) homework ~1 every 2-3 classes to learn how to use what we cover (.25) and help analyze papers occasional demonstrations – e.g. ELISA, fluorescence microscopy, pcr take-home midterm exam (.25) take-home final exam or student presentation (.25)

  2. Goals – 1. learn about nanotechnology-based biosensors molecules (analytes) detected molecules used to provide specificity transducing modalities (light, mass, electricity) assay formats (sandwich, labels, label-free) processes affecting time to get signal (diffusion, binding kinetics) and sensitivity multiplex methods (e.g. hybridization arrays) massively parallel DNA sequencing methods clinical significance of assays

  3. More Goals 2. Quantitative understanding of relevant nanoscale processes and phenomena, including Brownian motion, reaction kinetics, mechanical properties of biopolymers like DNA at the single-molecule level 3. Understand how some subcellular biological systems, like molecular motors, transduce chemical energy into motion 4. Appreciate overlap between engineering and biology 5. Gain experience reading research papers critically

  4. Contact info: jesilver@gwu.edu, tel 240 447 3268 set up time to meet for office hours Much better to meet often to go over questions early References for class 1 Philip Nelson Biological Physics Ch 1, 1.4-1.5 Dimensional analysis, molecules pp. 18-29 Ch 2, 2.2 Molecular Parts List, pp.45-62.

  5. Molecules (things) to be detected and how they interact ions small molecules (MW < 600g/mole=10-21g, or ~50 atoms – e.g. glucose) peptides – short string of amino acids proteins – string(s) of up to ~1000 amino acids viruses - ~1000+ proteins + NA genome (>104 bases) oligonucleotides – short string of nucleic acids = bases A, G, C, T (U) – joined via sugar-PO4 nucleic acid sequence

  6. Ions – e.g. Na+, K+, Mg++, Cl-, PO4— typical size? In solution: typical concentration, 1-100mM units: 1M = NA/liter = 6x1023/10-3m3 how many is that /cm3 or ml? how far apart are they? Why do they move? How will they be distributed near charged objects? Typical distances over which fixed charges are shielded Debye length =.3nm/I1/2 (I in M) What does this mean in terms of electrostatic interactions?

  7. Small molecules – e.g. sugars, < 100 atoms, size? (~1nm) What is significance of glucose in biology/medicine? Diabetes – does it go up or down? problems if it goes up problems if it goes down H, O, C = hydrogen, oxygen, carbon atoms, etc. Vertices = C atoms (understood) Lines = covalent bonds strength ~eV (1.6x10-19J)

  8. More on units Molecular weight = weight of NA(6x1023) molecules (=1 mole) in grams H has molecular weight =1g/mole C “weighs” 12 g/mole “Small” molecules defined as above have MWs ~or <500

  9. Aside on energy scales molecules always jiggling in water Average energy of molecule, each “mode” of interaction, e.g. translation, vibration between atoms = kBT(4x10-21J at room temp = 1/40thev) Do all molecules have average energy in solution? What is probability that a molecule has energy E? Boltzman distribution: p ~exp(-E/kBT)

  10. What is relative probability that a sugar molecule hit by a particularly energetic water molecule at room temperature will get enough energy to break a covalent bond? p ~ exp(-40kBT/kBT) = 10-18 So are covalent bonds usually stable at room temp.?

  11. Another class of small molecules All NH2-CHX-COOH side groups X differ some have + or – charge others partial charge others hydrophobic “greasy” -> weak interactions (~kBT) w/ other molecules

  12. Protein = linear polymer of amino acids (aa) chains from a few (“peptide”) to ~1000 aalong MWs ~100,000 g/mole (aka “kiloDalton”, kDa) Protein polymers “fold up” into fairly compact units ~10nm, based on weak interactions between amino acids

  13. Some proteins fairly rigid = “fixed” structure often known from crystallography Others don’t crystallize, probably “floppy” (or have parts that are floppy) in solution Some have a few, alternative “rigid” shapes (important!) Surface distribution of charged, polar (partially charged), hydrophobic, etc groups -> specific interactions with other molecules Note how different from usual physics– gazillions of identical electrons interacting uniformly

  14. Glucose oxidase~ 600 aaprotein enzyme that binds and oxidizes glucose. Ribbon model of its aa backbone, por- tions of which form helices. Note size, complexity relative to glucose, a simple sugar typical of small molecule targets ~ 3 nm

  15. Model of a particular protein showing charged surface regions (red -, blue +), and some drug molecules in binding pockets. Note complexity of surface allowing complex interaction with other molecules http://www.pnas.org/content/104/1/42/F6.expansion.html

  16. Proteins can interact forming larger polymers (of polymers) –> structural elements like fibers of collagen or microtubules (~25nm in diameter, microns long) Proteins also can act as enzymes, “catalyzing” chemical reactions that break and reform covalent bonds http://upload.wikimedia.org/wikipedia/commons/2/24/Induced_fit_diagram.svg

  17. Antibody – class of proteins with common structure: region that is invariant and region that varies a lot (in different ab’s), the latter having high, specific affinity for some other molecule (antigen, ligand) Nature’s “professional biosensor” molecule

  18. Ball and stick model of crystal structure of portion of • antibody (left) binding protein from HIV (green, right). • Variable region of • antibody (purple) • Antibodies are most • common molecules • used to make • bio-assays specific • Antibodies to particular antigens can be generated in • animals, then made in large quantities in vitro

  19. Base pairing – at edges – holds strands together; each bp = weak bond (~1 kBT) but runs of complementary sequence -> tight binding; can be used for specific recogni- tion of NA’s with compl. sequence Nucleic acids – polymers of “bases”

  20. Biological Macromolecules - DNA Base pairing – at edges – holds strands together Base stacking – above & below - compresses ds into helix Boiling separates strands RNA – like DNA, except OH at 2’ position, and Uridine for Thymine

  21. Single-stranded (ss) nucleic acids (NA’s) often used to detect complementary ssNA’s because of incredible specificity 1 base mismatch can be detected in a 20 base long dna How many different 20 base sequences are there? 420 = 1012

  22. ss NA’s can also fold into shapes that bind other molecules besides complementary NA’s Aptamer = single stranded nucleic acid that happens to have high affinity for another molecule Aptamers can be engineered and selected for ability to bind particular targets

  23. Molecules used to provide specificity in biosensors Enzymes – e.g. glucose oxidase for glucose Antibodies Genetically engineered antibody variants Nucleic acids – hybridization Aptamers – ss NAs that bind small molecules natural and engineered

  24. Fundamental relationship between NAs and proteins Some protein enzymes move along DNA molecules (molecular motors!), making RNA copy with equivalent base sequence (“transcription”) The RNA copy is then converted into a protein whose amino acid sequence is determined by the sequence of bases in the RNA (“translation”, “genetic code”) How do these motors work? How can they be studied? = topics of later classes!

  25. Immense medical significance Variants in DNA sequence -> proteins with variant amino acid sequence Amino acid sequence determines how protein folds, and hence its function Engineered changes in DNA sequence -> novel proteins, with possibly new functions So big interest in sensors that determine DNA sequence

  26. While we will focus on biosensors (and a few molecular motors), they are based on the same interactions that occur naturally in biological systems and hence provide insight into biological systems opportunity to develop innovative uses of biological materials opportunity to apply engineering tools to better understand how biological systems work

  27. Approach – qualitative understanding of biosensor phenomena, then quantitative analysis Proto-typical biosensor – ELISA Enzyme-linked immunosorbant assay

  28. 3. Add detection antibody that binds different site on target, wash 4. Detection antibody may be directly attached to an enzyme (e.g. HRP) that converts a substrate dye to a colored molecule, or the enzyme can be added on a 3rd molecule that binds the detection antibody 5. Wash away enzyme not specifically attached 6. Add substrate and measure color change “receptor” 1. Capture antibody(“receptor”) usually immobilized on surface, e.g. plastic 96 well (“mircrotiter “) plate Typical ELISA format 2. Test sample, that may contain target antigen (= analyte, ligand), is added to well; target molecule sticks to capture antibody; wash away whatever doesn’t stick

  29. Typical protocol Add sample in ~200ml, incubate ~1.5h (why so long?), wash Add 20 Ab coupled to enzyme (e.g HRP).incubate 1.5h, wash Add enz. substrate (e.g. tetramethylbenzene) Incubate 30min (in dark) Add stop solution (H2SO4) (why?), read OD (within 30min) Analyte with know concentration serially diluted in some wells to compare intensities to that of test sample Result: analyte conc. in sample

  30. Many other assays are variants on this with different “transducing” methods e.g. fluorescence instead of dye color, measure mass of attached molecules instead of enzyme activity measure electrical effects of captured complex

  31. What determines sensitivity, incubation times? How can we measure binding strength to target vs other molecules in sample (-> false positives)? Next few classes will develop simple binding kinetics model to answer these questions

  32. Reaction (receptor binding) kinetics Let bm = total receptor conc. on sensor surface [moles/area] b(t) = conc of receptors that have bound analyte at time t Assume analytebinds receptor at rate ~ free analyte conc., c0,* free receptor conc., [bm – b(t)] and dissociates from receptor at rate ~b(t) db(t)/dt= konc0 [bm – b(t)] – koffb(t) kon and koff are proportionality constants

  33. db(t)/dt= konc0 [bm – b(t)] – koffb(t) Interpretation of binding constants kon = av. # “binding” collisions per sec each receptor molecule makes with an analyte molecule when analyteconc = 1 in whatever units you use, e.g. #/m3 or “molar”, M, moles/l Units of konare #/conc.*time, e.g. M-1s-1 koff = rate each receptor-analyte complex dissociates in #/s Define KD=koff/konUnits of KD are conc., e.g. M

  34. db(t)/dt= konc0 [bm – b(t)] – koffb(t) At steady-state, d/dt (b(t)) = 0, so konc0 [bm – b(t)] = koffb(t) => b(t)/bm=c0/KD /(1 + c0/KD)] LHS = fraction of receptors that have bound target Note it is natural to measure concentration of free target molecules in units of KD (unit check: are units of KD concentration?)

  35. b(t)/bm=c0/KD /(1 + c0/KD)] at steady state If c0= KD, half of receptors have bound analyte c0>> KD, fraction of receptors with analyte -> 1 c0<< KD, fraction of receptors with analyte~c0/KD i.e. most receptors are unoccupied

  36. db(t)/dt= konc0 [bm – b(t)] – koffb(t) More generally, if c0 considered constant (often not true!), b(t)/bm= fraction of receptors with analyte= A(1-e-Bt) where A = [c0/KD /(1 + c0/KD)] and B = konc0 + koff A = c0/KD /(1 + c0/KD) b(t)/bm time t = 1/B = koff-1/(1+c0/KD) Note exponential approach to equil. with characteristic time t

  37. c0/KD /(1 + c0/KD) b(t)/bm typical values kon~ 106/Ms ( =10-21m3/s) fairly constant koff~ 1/s to 1/103s (varies a lot) KD~mM (weak) to nM (tight binding) Note smaller KD <-> tighter binding (slower koff) time t = koff-1/(1 + c0 /KD)

  38. There are many caveats to this model, but it provides a simple way to begin to evaluate systems quantitatively The reasoning is completely general to other biochemical interactions Begin to think in terms of KD’s as natural measures of strength of interactions

  39. Main points: Biological molecules are often polymers of simpler subunits They interact by standard laws of physics but because their surfaces are highly variable (in charge, dipolarity, other weak interactions) they interact with each other in highly “molecule-specific” ways These interactions are often ~kBT so that complexes form and dissociate at room temperature

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