| Swimming in Circles: Motion of Bacteria near Solid Boundaries Biophysical Journal, Volume 90, Issue 2, 15 January 2006, Pages 400-412 Eric Lauga, Willow R. DiLuzio, George M. Whitesides and Howard A. Stone Abstract Near a solid boundary, swims in clockwise circular motion. We provide a hydrodynamic model for this behavior. We show that circular trajectories are natural consequences of force-free and torque-free swimming and the hydrodynamic interactions with the boundary, which also leads to a hydrodynamic trapping of the cells close to the surface. We compare the results of the model with experimental data and obtain reasonable agreement. In particular, the radius of curvature of the trajectory is observed to increase with the length of the bacterium body. Abstract | Full Text | PDF (283 kb) |
| Multiple Subunit Fitting into a Low-Resolution Density Map of a Macromolecular Complex Using a Gaussian Mixture Model Biophysical Journal, Volume 95, Issue 10, 15 November 2008, Pages 4643-4658 Takeshi Kawabata Abstract Recently, electron microscopy measurement of single particles has enabled us to reconstruct a low-resolution 3D density map of large biomolecular complexes. If structures of the complex subunits can be solved by x-ray crystallography at atomic resolution, fitting these models into the 3D density map can generate an atomic resolution model of the entire large complex. The fitting of multiple subunits, however, generally requires large computational costs; therefore, development of an efficient algorithm is required. We developed a fast fitting program, “”, which employs a Gaussian mixture model (GMM) to represent approximated shapes of the 3D density map and the atomic models. A GMM is a distribution function composed by adding together several 3D Gaussian density functions. Because our model analytically provides an integral of a product of two distribution functions, it enables us to quickly calculate the fitness of the density map and the atomic models. Using the integral, two types of potential energy function are introduced: the attraction potential energy between a 3D density map and each subunit, and the repulsion potential energy between subunits. The restraint energy for symmetry is also employed to build symmetrical origomeric complexes. To find the optimal configuration of subunits, we randomly generated initial configurations of subunit models, and performed a steepest-descent method using forces and torques of the three potential energies. Comparison between an original density map and its GMM showed that the required number of Gaussian distribution functions for a given accuracy depended on both resolution and molecular size. We then performed test fitting calculations for simulated low-resolution density maps of atomic models of homodimer, trimer, and hexamer, using different search parameters. The results indicated that our method was able to rebuild atomic models of a complex even for maps of 30Å resolution if sufficient numbers (eight or more) of Gaussian distribution functions were employed for each subunit, and the symmetric restraints were assigned for complexes with more than three subunits. As a more realistic test, we tried to build an atomic model of the GroEL/ES complex by fitting 21-subunit atomic models into the 3D density map obtained by cryoelectron microscopy using the C7 symmetric restraints. A model with low root mean-square deviations (14.7Å) was obtained as the lowest-energy model, showing that our fitting method was reasonably accurate. Inclusion of other restraints from biological and biochemical experiments could further enhance the accuracy. Abstract | Full Text | PDF (1876 kb) |
| Fluorescence Imaging of Two-Photon Linear Dichroism: Cholesterol Depletion Disrupts Molecular Orientation in Cell Membranes Biophysical Journal, Volume 88, Issue 1, 1 January 2005, Pages 609-622 Richard K.P. Benninger, Björn Önfelt, Mark A.A. Neil, Daniel M. Davis and Paul M.W. French Abstract The plasma membrane of cells is an ordered environment, giving rise to anisotropic orientation and restricted motion of molecules and proteins residing in the membrane. At the same time as being an organized matrix of defined structure, the cell membrane is heterogeneous and dynamic. Here we present a method where we use fluorescence imaging of linear dichroism to measure the orientation of molecules relative to the cell membrane. By detecting linear dichroism as well as fluorescence anisotropy, the orientation parameters are separated from dynamic properties such as rotational diffusion and homo energy transfer (energy migration). The sensitivity of the technique is enhanced by using two-photon excitation for higher photo-selection compared to single photon excitation. We show here that we can accurately image lipid organization in whole cell membranes and in delicate structures such as membrane nanotubes connecting two cells. The speed of our wide-field imaging system makes it possible to image changes in orientation and anisotropy occurring on a subsecond timescale. This is demonstrated by time-lapse studies showing that cholesterol depletion rapidly disrupts the orientation of a fluorophore located within the hydrophobic region of the cell membrane but not of a surface bound probe. This is consistent with cholesterol having an important role in stabilizing and ordering the lipid tails within the plasma membrane. Abstract | Full Text | PDF (434 kb) |
Copyright © 2007 The Biophysical Society. All rights reserved.
Biophysical Journal, Volume 92, Issue 6, 2000-2006, 15 March 2007
doi:10.1529/biophysj.106.095059
Nucleic Acids
Pedro Licinio
,
and João Carlos O. Guerra
Departamento de Física, ICEx, UFMG, Belo Horizonte, Brazil
Address reprint requests to P. Licinio.Widely used DNA biotechnological applications such as PCR or cDNA expression profiling rely on the knowledge of sequence specific thermodynamic parameters such as strand melting temperature. Many physical properties of DNAsequences can be calculated from a number of algorithms in the context of nearest-neighbor (NN) models. NN models give linear representations for experimental measurements on nucleotide chains usually in terms of pairwise (dimer) sequence contributions. However, the notion that NN dimer parameters cannot be assigned from experiments by solving a set of simultaneous linear equations has been given since the development of these models in the context of polynucleotide thermodynamic studies 1. This puzzling conclusion is due to the consideration of intrinsic composition closure constraints that effectively reduce the number of degrees of freedom of the model. Dimer occurrence relations are well known, allowing for decomposition of sequence properties into arbitrarily chosen reduced dimer sets. As a corollary, so-far-unknown constraints must also link the full dimer set properties in some hidden way to restore full set unity. The dimer decomposition is overstated, since the dimer set size (16 for single strands and 10 for double strands) is greater than the number of degrees of freedom of the problem (13 and 8, respectively, for circular sequences). Alternative approaches have considered decompositions into irreducible and hence smaller sets of short sequences or dimer combinations 2,3,4,5. Comparison among different laboratory sets and physical interpretation of set values becomes a difficult task due to the arbitrariness of possible renderings. The extraction of simpler and more direct dimer contributions from such sets has remained an ill-posed problem with nonunique solutions, but still embraced by a large community of biochemists 6,7,8,9,10,11,12. To adopt the dimer set formulation further ad hoc regularization hypotheses have been taken by different authors, such as the singular value decomposition method 9,10. Here we adopt an entirely new approach to this problem by analyzing how the nucleotide intrinsic intermolecular symmetries contribute to the structure of NN sets. In this article, we first introduce a general quantum mechanics statement giving physical properties for a sequence of heterogeneous molecules, treated as subsystems assuming any of a given complete set of molecular states. The four-nucleotide set has a corresponding four-state representation. At this point, a careful choice of the number of degrees of freedom is made that projects the representation into a three-dimensional molecular class space. Luckily, the three independent molecular classes are readily associated to main biochemical classification of nucleotides as composed of purine-pyrimidine, amino-keto, and strong-weak bases. The representation of the four-nucleotide set as a tetrahedron in three dimensions is at the heart of this work. This representation has been used to generate DNA-walks for sequence composition analysis or display. The corresponding proper space metrics has also been recently used for phylogenetic sequence comparisons 13. We proceed to contract the original quantum mechanics statement into an irreducible formulation using the four-nucleotide tetrahedron representation. This molecular symmetrical decomposition is found to provide the right number of fundamental properties (free parameters). Next we relate this decomposition to the dimer set formulation. The comparison uncovers useful and so far hidden self-consistency relations among dimers. Finally these results are applied to the analysis of DNA free energy by introducing empirical end contributions to the model. A self-consistent set has thus been fit to free energy data from 108 short duplex oligomer sequences as available on the literature. The more compact and symmetrical self-consistent set, although modeled short by two variables, is shown to provide at least as good modeling for oligomer free-energy as standard NN dimer models. The far-reaching strength of this entirely novel theoretical modeling frame for DNA/RNA sequences resides in its compactness and symmetry. One of the immediate and practical consequences of the tetrahedral model is the disclosure of the implicit dimer self-consistency relations. The constraints discovered are to avoid unphysical values and thereby increase the precision of predictions relying on dimer set values. This work concludes with an analysis of error propagation, which manifests mostly for sequences with strong composition order trend.
Complexity in biological phenomena represents an enormous challenge and a rich field for the application and development of physical methods. To unfold simple biopolymer phenomena we start by a biochemical meaningful nucleotide representation into molecular classes and count on sound tools of quantum mechanics formulation. Quantum mechanics does not need to start with a complete spatio-temporal wave-function or Schrödinger representation. It may be well stated in the matrix or Heisenberg representation. What is needed from start is some base set for the description of the states of a system. For a system, we take a DNA/RNA sequence. The ensemble of sequence states is given by allowable sequence composition alone. We want to describe and isolate gross composition states. Inner electronic states or molecular conformation contributions, which would require a much finer level of quantum description, are so far intrinsically averaged. State transitions are of course forbidden if one neglects mutations. The sequence state will be given in terms of its molecular constitution, and a nucleotide set representation will condition the sequence representation.
The quantum mechanics expectation for any observable is given in terms of the corresponding operator E and system state |Ψ〉 as 〈Ψ|E|Ψ〉 in Dirac’s notation. The state of a system composed of n particles or molecules is usually expressed as the tensorial product of their component states |b(i)〉:
![]() | (1) |
![]() | (2) |
Further reduction of this development can be obtained considering implicit symmetries of the Hermitian E-matrix and its invariants under orthonormal base representations.
The most straightforward representation for a four-nucleotide set is a four-dimensional vector. Such “independent-nucleotides” representation has been implicitly adopted by many authors and leads to 4×4 matrixes or 16 parameter sets when considering nucleotide pairwise properties 5. This representation, however, already overstates the nucleotide composition problem from the beginning. The set representation should be more concisely established in a three-dimensional space. First note that, due to a normalization constraint, a variable composed (assuming any combination) of d+1 different possible states may be specified by a corresponding generalized d-dimensional composition diagram, even though, ultimately, only the corners of the diagram represent pure states. To give examples, properties for a ternary mixture are well represented in a two-dimensional triangular composition diagram for support, while a binary mixture is defined from a single concentration variable. A complete and symmetrical representation for the usual DNA (or RNA) four-nucleotide set can be given within a tetrahedral decomposition scheme into a three-dimensional orthonormal base set |x〉, |y〉, |z〉. The pure nucleotide states |b(i)〉 are given as 13
![]() | (3) |
Returning to the quantum mechanics formulation, we want to exploit the remaining invariants and redundancies from the structure of the matrix operators in Eq. (2) to further reduce its number of parameters. The three-dimensional nucleotide basis should be kept in mind. The sequence-dependent states of an observable will then assume discrete values given by a most compact expansion of its expectation as
![]() | (4) |
). The remaining cross terms of the self-matrix similarly contract to a vector since all pure nucleotide states |b(i)〉 also have cyclically multiplicative class components (bx=bybz, etc.). This contraction gives the second term as an order-independent or global-composition contribution, with components 〈V|=4 Re(Ey(1)z(1)Ez(1)x(1)Ex(1)y(1)). The third term is an NN or first-order sequence stacking contribution to the observable. The stacking matrix M is a second-rank tensor and has its elements given from the cross expectation matrix as Mμν=2 Re (Eμ(1)ν(2)). The symmetrical sum of the expectation matrix Hermitian conjugates result in a fully contracted real formulation.Decomposition of nucleotide sequence observable expectation as in Eq. (4) naturally leads to an irreducible 13-parameter description of physical properties (S, Vμ, Mμν), which we call the symmetrical set, within the NN approximation. Note that a traditional description of stacking dependent properties is often stated in terms of the NN dimer composition, i.e., as a linear combination of the 16 ordered 5′–3′ NN dimer set Eij:
![]() | (5) |
![]() | (6) |
reducing the number of independent dimers in the set to arbitrary 13. Similar arguments hold for linear oligomers.
In comparison, the decomposition of physical properties in the symmetrical set proposed here is in a fundamental level, since from the beginning it includes only a priori linearly independent terms and gives contributions to the observable in the hierarchic form of three expectation tensors of increasing rank, corresponding to different levels of analysis. The 16 NN expectations can otherwise be easily obtained as a linear combination of the 13 symmetrical-set tensor components. In that case it is useful to rewrite Eq. (4) in a form appropriate for NN dimer decomposition as
![]() | (7) |
Explicitly one has applying Eq. (3) to Eq. (7):
![]() | (8) |
For measurements concerning double strands, aside end effects, it is well known that complementary strand symmetry further reduces the problem to the statement of only 10 conjugated NN dimer pair values (see the expressions in Eq. (12) below) linked through two independent composition closure relations as
![]() | (9) |
![]() | (10) |
The double-strand expansion can be given as a function of a single strand sequence taking into account the fore mentioned implicit symmetries (by adding contributions from both strands to Eq. (7) taking into account Eq. (10) and then redefining the tensor set, i.e., E′b1b2≡Eb1b2+Eb′1b′2). It is clear in that case that
![]() | (11) |
From Eq. (11) and Eq. (8), decomposition for the 10 paired NNs gives a self-consistent set of expectations obeying
![]() | (12) |
![]() | (13) |
![]() | (14) |
![]() | (15) |
To compare this self-consistent formulation with double-strain DNA oligonucleotide free energy data, four extra terms corresponding to the different 5′ terminal compositions need to be considered with the dimer contributions of Eq. (7). End effects include duplex initiation and other duplex and solvent terminal interactions. However, only two parameters, that discriminate AT end pairing from CG end pairing, without 5′–3′ order discrimination, seem to be relevant and have often been included in general thermodynamic analysis of DNA 10,11,12. A symmetry penalty of entropic origin given as ln2RT=0.43kcal/mol, is also usually assigned for the physically distinct case of self-complementary sequences. We will adopt the same set of initiation and symmetry parameters here in order not to loose the focus on the NN set presentations.
The determination of oligonucleotide free energies has been a long-standing problem 1,14,15. SantaLucia et al. 10,11,12 has reviewed the data from seven laboratories and given a table of unified values for DNA dimer contributions to standard free energies at 37°C and 1M salt concentration: ΔG37. This unified data set is not self-consistent a priori. Adopting an ab initio approach, we proceed to fit the same set of thermodynamic data from 108 sequences used to establish the unified NN dimer parameter set 11; using the eight parameter tensor decomposition of dimer properties (Eq. (12)) plus three extra parameters: an entropic correction for symmetric self-complementary sequences; and terminal corrections for AT and CG initiations.
For example, the sequence AATG would be decomposed as
![]() | (16) |
![]() | (17) |
![]() | (18) |
| Table 1 NN standard free energies ΔG37 (in kcal/mol) |
| Dimer set | Unified | Self-consistent | ||
|---|---|---|---|---|
| TA | −0.58 | −0.57±0.04 | ||
| AT | −0.88 | −0.91±0.04 | ||
| AA-TT | −1.00 | −0.97±0.02 | ||
| AG-CT | −1.28 | −1.20±0.04 | ||
| GA-TC | −1.30 | −1.35±0.03 | ||
| AC-GT | −1.44 | −1.28±0.03 | ||
| CA-TG | −1.45 | −1.48±0.03 | ||
| GG-CC | −1.84 | −1.82±0.04 | ||
| CG | −2.17 | −2.14±0.04 | ||
| GC | −2.24 | −2.19±0.06 | ||
| A-T ending | 1.03 | 0.92±0.08 | ||
| C-G ending | 0.98 | 0.85±0.07 | ||
| Symmetry | 0.43 | 0.43 | ||
| The unified set proposed by SantaLucia 10 is compared to the self-consistent set. Both sets have been obtained by model fits to the same 108-sequence data set 11. |
The precision of the symmetrical set has been estimated from a resampling analysis including 100 random data subsets with 70 sequences as ±20 cal/mol for S and ±10 cal/mol for the remaining parameters. Accordingly, the self-consistent set for dimer free energies and deviations is given in Table 1. Comparing both dimer set results (see Table 1), deviations of the order of only 0.05kcal/mol per NN indicate that the unified set is already close to self-consistency within experimental error. However, we notice greater discrepancies in the free energies of AG and AC dimers, which were given as almost identical to the GA and CA NNs, respectively, for the unified set. We interpret these as mean values determined from the unified set analysis, within two underestimated energy splittings between AG and GA and between AC and CA NNs. These splittings only become well resolved through self-consistency requirements of the symmetrical set (see Fig. 3).
Entropy release is mainly due to freezing of the ribo-phosphate backbone degrees of freedom and is quite insensitive to base composition. Differential entropic contributions to Vz should be correspondingly small and 2Vz estimates the linear differential enthalpy contribution of a characteristic A/T to C/G single hydrogen-bonding energy difference of H∼1.1kcal/mol. This is of good order 16 and can be taken as a reference value since no precise estimate for this quantity is universally accepted. The mean contribution S∼1.4kcal/mol to the free energy can be interpreted in terms of a relatively high mean entropy release of ∼−23cal/(mol.K) 10 compensated by a mean enthalpy gain of −8.3kcal/mol, which amounts to include mean hydrogen-bonding energy of order 2.5H ∼−2.8kcal/mol and approximately two-times stronger mean stacking interactions. This is also in accordance with estimates of mean stacking interactions 16,17. Differential stacking contributions to the standard free energy, given by M matrix elements, are one order-of-magnitude weaker while no clear dominant feature appears. Finally we wish to point out that the symmetrical representation allows for the analysis of duplex dimer physical properties in terms of composition structure at three levels (Fig. 3). In the first level, properties are split according to the number of hydrogen bonds. This “Chargaff splitting” is an AT-CG (trans-composition) split controlled by z-coordinate alone and includes a nonlinear Mzz differential stacking correction to the linear Vz three-split. In the second level, a symmetrical splitting occurs for different dimer compositions (cis-composition). This is controlled by x,y-coordinates alone. For the third level, another symmetrical split occurs for dimers in opposite 5′3′ orientations (ordo-composition). Four pairs of expectations then become distinguished by nucleotide order and since only two parameters (Mxz and Myz) control their properties, it is this last splitting that also implies the self-consistency relations (Eqs. (14)). Composition order bias, producing highly unbalanced Mxz and Myz contributions, is seldom produced in ordinary sequences. It would be desirable to explicitly design and measure simple complementary ordered sequences such as GTAGTAG and GATGATG. Table 1 estimates a free energy difference of 5.78–4.40=1.38kcal/mol for the symmetrical set, against only 5.30–4.64=0.66kcal/mol for the unified set. Differential analysis of such oligomer pairs should thus provide compelling evidence against or toward the symmetrical model.
A geometrical representation of four-nucleotide sets as a tetrahedron (Eq. (3) and Fig. 2) allows for the association of the three most distinctive molecular group classifications with corresponding orthogonal cubic axis. Physical properties of nucleotide sequences may be calculated with an optimal set of tensor coefficients (Eq. (4)) assuming projections within this tetrahedral representation. The coefficients are expressed in hierarchical differential form, so lower levels of approximation are explicitly embodied in the description. This includes an ensemble mean expectation from scalar coefficient S alone, and a global composition approximation, as expressed through V-component contributions. The symmetrical set is shown to provide a frame for the analysis of DNA duplex free energy fully compatible with experimental data (Eq. (18)). Such a symmetrical set of coefficients allows for the translation among different decomposition frames. It also gives a proper irreducible representation for dimer properties (Eqs. (8)). It solves an old indeterminacy of dimer sets by establishing self-consistency relations among dimer coefficients (Eqs. (14)). A self-consistent dimer set is given in Table 1. Self-consistency relations provided by the present analysis should increase the predictive power of NN models since with lesser parameter number they should become more robust against fitting noise of experimental data. Experiments with order-biased sequences to test in depth the reliability of this model have been suggested.
We thank Brazilian agency CNPq and FAPEMIG for financial support.
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