Tandem repeats in proteins: from sequence to structure

The role of variable DNA tandem repeats in bacterial adaptation

DNA tandem repeats (TRs), also designated as satellite DNA, are inter- or intragenic nucleotide sequences that are repeated two or more times in a head-to-tail manner. Because TR tracts are prone to strand-slippage replication and recombination events that cause the TR copy number to increase or decrease, loci containing TRs are hypermutable. An increasing number of examples illustrate that bacteria can exploit this instability of TRs to reversibly shut down or modulate the function of specific genes, allowing them to adapt to changing environments on short evolutionary time scales without an increased overall mutation rate. In this review, we discuss the prevalence and distribution of inter- and intragenic TRs in bacteria and the mechanisms of their instability. In addition, we review evidence demonstrating a role of TR variations in bacterial adaptation strategies, ranging from immune evasion and tissue tropism to the modulation of environmental stress tolerance. Nevertheless, while bioinformatic analysis reveals that most bacterial genomes contain a few up to several dozens of intra- and intergenic TRs, only a small fraction of these have been functionally studied to date.

Selection of specific protein binders for pre-defined targets from an optimized library of artificial helicoidal repeat proteins (alphaRep)

We previously designed a new family of artificial proteins named αRep based on a subgroup of thermostable helicoidal HEAT-like repeats. We have now assembled a large optimized αRep library. In this library, the side chains at each variable position are not fully randomized but instead encoded by a distribution of codons based on the natural frequency of side chains of the natural repeats family. The library construction is based on a polymerization of micro-genes and therefore results in a distribution of proteins with a variable number of repeats. We improved the library construction process using a “filtration” procedure to retain only fully coding modules that were recombined to recreate sequence diversity. The final library named Lib2.1 contains 1.7×10⁹ independent clones. Here, we used phage display to select, from the previously described library or from the new library, new specific αRep proteins binding to four different non-related predefined protein targets. Specific binders were selected in each case. The results show that binders with various sizes are selected including relatively long sequences, with up to 7 repeats. ITC-measured affinities vary with K_d values ranging from micromolar to nanomolar ranges. The formation of complexes is associated with a significant thermal stabilization of the bound target protein. The crystal structures of two complexes between αRep and their cognate targets were solved and show that the new interfaces are established by the variable surfaces of the repeated modules, as well by the variable N-cap residues. These results suggest that αRep library is a new and versatile source of tight and specific binding proteins with favorable biophysical properties.

Graph-based modeling of tandem repeats improves global multiple sequence alignment

Tandem repeats (TRs) are often present in proteins with crucial functions, responsible for resistance, pathogenicity and associated with infectious or neurodegenerative diseases. This motivates numerous studies of TRs and their evolution, requiring accurate multiple sequence alignment. TRs may be lost or inserted at any position of a TR region by replication slippage or recombination, but current methods assume fixed unit boundaries, and yet are of high complexity. We present a new global graph-based alignment method that does not restrict TR unit indels by unit boundaries. TR indels are modeled separately and penalized using the phylogeny-aware alignment algorithm. This ensures enhanced accuracy of reconstructed alignments, disentangling TRs and measuring indel events and rates in a biologically meaningful way. Our method detects not only duplication events but also all changes in TR regions owing to recombination, strand slippage and other events inserting or deleting TR units. We evaluate our method by simulation incorporating TR evolution, by either sampling TRs from a profile hidden Markov model or by mimicking strand slippage with duplications. The new method is illustrated on a family of type III effectors, a pathogenicity determinant in agriculturally important bacteria Ralstonia solanacearum. We show that TR indel rate variation contributes to the diversification of this protein family.

Sensitivity of immune response quality to influenza helix 190 antigen structure displayed on a modular virus-like particle

Biomolecular engineering enables synthesis of improved proteins through synergistic fusion of modules from unrelated biomolecules. Modularization of peptide antigen from an unrelated pathogen for presentation on a modular virus-like particle (VLP) represents a new and promising approach to synthesize safe and efficacious vaccines. Addressing a key knowledge gap in modular VLP engineering, this study investigates the underlying fundamentals affecting the ability of induced antibodies to recognize the native pathogen. Specifically, this quality of immune response is correlated to the peptide antigen module structure. We modularized a helical peptide antigen element, helix 190 (H190) from the influenza hemagglutinin (HA) receptor binding region, for presentation on murine polyomavirus VLP, using two strategies aimed to promote H190 helicity on the VLP. In the first strategy, H190 was flanked by GCN4 structure-promoting elements within the antigen module; in the second, dual H190 copies were arrayed as tandem repeats in the module. Molecular dynamics simulation predicted that tandem repeat arraying would minimize secondary structural deviation of modularized H190 from its native conformation. In vivo testing supported this finding, showing that although both modularization strategies conferred high H190-specific immunogenicity, tandem repeat arraying of H190 led to a strikingly higher immune response quality, as measured by ability to generate antibodies recognizing a recombinant HA domain and split influenza virion. These findings provide new insights into the rational engineering of VLP vaccines, and could ultimately enable safe and efficacious vaccine design as an alternative to conventional approaches necessitating pathogen cultivation.

Detecting repetitions and periodicities in proteins by tiling the structural space

The notion of energy landscapes provides conceptual tools for understanding the complexities of protein folding and function. Energy landscape theory indicates that it is much easier to find sequences that satisfy the “Principle of Minimal Frustration” when the folded structure is symmetric (Wolynes, P. G. Symmetry and the Energy Landscapes of Biomolecules. Proc. Natl. Acad. Sci. U.S.A.1996, 93, 14249–14255). Similarly, repeats and structural mosaics may be fundamentally related to landscapes with multiple embedded funnels. Here we present analytical tools to detect and compare structural repetitions in protein molecules. By an exhaustive analysis of the distribution of structural repeats using a robust metric, we define those portions of a protein molecule that best describe the overall structure as a tessellation of basic units. The patterns produced by such tessellations provide intuitive representations of the repeating regions and their association toward higher order arrangements. We find that some protein architectures can be described as nearly periodic, while in others clear separations between repetitions exist. Since the method is independent of amino acid sequence information, we can identify structural units that can be encoded by a variety of distinct amino acid sequences.

RAPHAEL: recognition, periodicity and insertion assignment of solenoid protein structures

MOTIVATION

Repeat proteins form a distinct class of structures where folding is greatly simplified. Several classes have been defined, with solenoid repeats of periodicity between ca. 5 and 40 being the most challenging to detect. Such proteins evolve quickly and their periodicity may be rapidly hidden at sequence level. From a structural point of view, finding solenoids may be complicated by the presence of insertions or multiple domains. To the best of our knowledge, no automated methods are available to characterize solenoid repeats from structure.

RESULTS

Here we introduce RAPHAEL, a novel method for the detection of solenoids in protein structures. It reliably solves three problems of increasing difficulty: (1) recognition of solenoid domains, (2) determination of their periodicity and (3) assignment of insertions. RAPHAEL uses a geometric approach mimicking manual classification, producing several numeric parameters that are optimized for maximum performance. The resulting method is very accurate, with 89.5% of solenoid proteins and 97.2% of non-solenoid proteins correctly classified. RAPHAEL periodicities have a Spearman correlation coefficient of 0.877 against the manually established ones. A baseline algorithm for insertion detection in identified solenoids has a Q(2) value of 79.8%, suggesting room for further improvement. RAPHAEL finds 1931 highly confident repeat structures not previously annotated as solenoids in the Protein Data Bank records.

Repeat or not repeat?--Statistical validation of tandem repeat prediction in genomic sequences

Tandem repeats (TRs) represent one of the most prevalent features of genomic sequences. Due to their abundance and functional significance, a plethora of detection tools has been devised over the last two decades. Despite the longstanding interest, TR detection is still not resolved. Our large-scale tests reveal that current detectors produce different, often nonoverlapping inferences, reflecting characteristics of the underlying algorithms rather than the true distribution of TRs in genomic data. Our simulations show that the power of detecting TRs depends on the degree of their divergence, and repeat characteristics such as the length of the minimal repeat unit and their number in tandem. To reconcile the diverse predictions of current algorithms, we propose and evaluate several statistical criteria for measuring the quality of predicted repeat units. In particular, we propose a model-based phylogenetic classifier, entailing a maximum-likelihood estimation of the repeat divergence. Applied in conjunction with the state of the art detectors, our statistical classification scheme for inferred repeats allows to filter out false-positive predictions. Since different algorithms appear to specialize at predicting TRs with certain properties, we advise applying multiple detectors with subsequent filtering to obtain the most complete set of genuine repeats.