Daniel P. Aalberts

Codon influence on protein expression in E. coli correlates with mRNA levels

Degeneracy in the genetic code, which enables a single protein to be encoded by a multitude of synonymous gene sequences, has an important role in regulating protein expression, but substantial uncertainty exists concerning the details of this phenomenon. Here we analyse the sequence features influencing protein expression levels in 6,348 experiments using bacteriophage T7 polymerase to synthesize messenger RNA in Escherichia coli. Logistic regression yields a new codon-influence metric that correlates only weakly with genomic codon-usage frequency, but strongly with global physiological protein concentrations and also mRNA concentrations and lifetimes in vivo. Overall, the codon content influences protein expression more strongly than mRNA-folding parameters, although the latter dominate in the initial ~16 codons. Genes redesigned based on our analyses are transcribed with unaltered efficiency but translated with higher efficiency in vitro. The less efficiently translated native sequences show greatly reduced mRNA levels in vivo. Our results suggest that codon content modulates a kinetic competition between protein elongation and mRNA degradation that is a central feature of the physiology and also possibly the regulation of translation in E. coli.

Asymmetry in RNA pseudoknots: observation and theory

RNA can fold into a topological structure called a pseudoknot, composed of non-nested double-stranded stems connected by single-stranded loops. Our examination of the PseudoBase database of pseudoknotted RNA structures reveals asymmetries in the stem and loop lengths and provocative composition differences between the loops. By taking into account differences between major and minor grooves of the RNA double helix, we explain much of the asymmetry with a simple polymer physics model and statistical mechanical theory, with only one adjustable parameter.

Single-Strand Stacking Free Energy from DNA Beacon Kinetics

DNA beacons are short single-stranded chains which can form closed hairpin shapes through complementary base pairing at their ends. Contrary to the common polymer theory assumption that only their loop length matters, experiments show that their closing kinetics depend on the loop composition. We have modeled the closing kinetics and in so doing have obtained stacking enthalpies and entropies for single-stranded nucleic acids. The resulting change of persistence length with temperature effects the dynamics. With a Monte Carlo study, we answer another polymer question of how the closing time scales with chain length, finding tau approximately N(2.44+/-0.02). There is a significant crossover for shorter chains, bringing the effective exponent into good agreement with experiment.

A two-length-scale polymer theory for RNA loop free energies and helix stacking

The reliability of RNA secondary structure predictions is subject to the accuracy of the underlying free energy model. Mfold and other RNA folding algorithms are based on the Turner model, whose weakest part is its formulation of loop free energies, particularly for multibranch loops. RNA loops contain single-strand and helix-crossing segments, so we develop an enhanced two-length freely jointed chain theory and revise it for self-avoidance. Our resulting universal formula for RNA loop entropy has fewer parameters than the Turner/Mfold model, and yet simulations show that the standard errors for multibranch loop free energies are reduced by an order of magnitude. We further note that coaxial stacking decreases the effective length of multibranch loops and provides, surprisingly, an entropic stabilization of the ordered configuration in addition to the enthalpic contribution of helix stacking. Our formula is in good agreement with measured hairpin free energies. We find that it also improves the accuracy of folding predictions.

Visualizing RNA base-pairing probabilities with RNAbow diagrams

There are many effective ways to represent a minimum free energy RNA secondary structure that make it easy to locate its helices and loops. It is a greater challenge to visualize the thermal average probabilities of all folds in a partition function sum; dot plot representations are often puzzling. Therefore, we introduce the RNAbows visualization tool for RNA base pair probabilities. RNAbows represent base pair probabilities with line thickness and shading, yielding intuitive diagrams. RNAbows aid in disentangling incompatible structures, allow comparisons between clusters of folds, highlight differences between wild-type and mutant folds, and are also rather beautiful.

Quantifying optimal accuracy of local primary sequence bioinformatics methods

MOTIVATION Traditional bioinformatics methods scan primary sequences for local patterns. It is important to assess how accurate local primary sequence methods can be. RESULTS We study the problem of donor pre-mRNA splice site recognition, where the sequence overlaps between real and decoy datasets can be quantified, exposing the intrinsic limitations of the performance of local primary sequence methods. We assess the accuracy of primary sequence methods generally by studying how they scale with dataset size and demonstrate that our new primary sequence ranking methods have superior performance.

Towards understanding the ultra-fast dynamics of rhodopsin

The photoisomerization of rhodopsin in 200 femtoseconds is among the fastest and most efficient photochemical reactions known. We have developed a microscopic model to study rhodopsins dynamics which retains the collective quantum mechanics of the 7r electrons in the conjugated system. Our model is a generalization to three dimensions of Su, Schrieffer, and Heegers model for polyacetylene (CH),. Model parameters are inferred from comparison with ex- periments and ab initio calculations. The spatial structure and vibrational modes of the rhodopsin chromophore 11-cis retinal are calculated and shown to agree quite well with NMR and Raman spectroscopy measurements. Dynamics follow- ing photoexcitation are studied.

Reptation in a weak driving field

A simplified model of reptation is presented. The Master Equation of the model is systematically solved by expansion in powers of the strength of the driving field. From the explicit form of the probability distribution, exact conclusions can be drawn about the average shape of the polymer, its drift velocity, and the zero field diffusion constant. Correlations between segments of the chain are calculated and turn out to be large, even in the weak driving field limit. The results are compared with simulations of the model.

Codon Clarity or Conundrum

Synonymous variations in protein-coding sequences alter protein expression dynamics, which has important implications for cellular physiology and evolutionary fitness, but disentangling the underlying molecular mechanisms remains challenging.

Loop Entropy Assists Tertiary Order: Loopy Stabilization of Stacking Motifs

The free energy of an RNA fold is a combination of favorable base pairing and stacking interactions competing with entropic costs of forming loops. Here we show how loop entropy, surprisingly, can promote tertiary order. A general formula for the free energy of forming multibranch and other RNA loops is derived with a polymer-physics based theory. We also derive a formula for the free energy of coaxial stacking in the context of a loop. Simulations support the analytic formulas. The effects of stacking of unpaired bases are also studied with simulations.