Local fitness landscape of the green fluorescent protein.

Fitness landscapes depict how genotypes manifest at the phenotypic level and form the basis of our understanding of many areas of biology, yet their properties remain elusive. Previous studies have analysed specific genes, often using their function as a proxy for fitness, experimentally assessing the effect on function of single mutations and their combinations in a specific sequence or in different sequences. However, systematic high-throughput studies of the local fitness landscape of an entire protein have not yet been reported. Here we visualize an extensive region of the local fitness landscape of the green fluorescent protein from Aequorea victoria (avGFP) by measuring the native function (fluorescence) of tens of thousands of derivative genotypes of avGFP. We show that the fitness landscape of avGFP is narrow, with 3/4 of the derivatives with a single mutation showing reduced fluorescence and half of the derivatives with four mutations being completely non-fluorescent. The narrowness is enhanced by epistasis, which was detected in up to 30% of genotypes with multiple mutations and mostly occurred through the cumulative effect of slightly deleterious mutations causing a threshold-like decrease in protein stability and a concomitant loss of fluorescence. A model of orthologous sequence divergence spanning hundreds of millions of years predicted the extent of epistasis in our data, indicating congruence between the fitness landscape properties at the local and global scales. The characterization of the local fitness landscape of avGFP has important implications for several fields including molecular evolution, population genetics and protein design.

Structural modeling of the ExuR and UxuR transcription factors of E. coli: search for the ligands affecting their regulatory properties.

Gammaproteobacteria get energy for their growth from different carbon sources using either glycolysis or alternative metabolic pathways induced in stress conditions. These metabolic switches are coordinated by complex interplay of regulatory proteins sensing concentrations of available metabolites by mechanisms yet to be understood. Here, we use two transcriptional regulators, ExuR and UxuR, controlling d-galacturonate (d-gal) and d-glucuronate metabolism in Escherichia coli, as the targets for computational search of low-molecular compounds capable to bind their ligand-binding domains. Using a flexible molecular docking, we modeled the interactions of these proteins with substrates and intermediates of glycolysis, Ashwell and Entner-Doudoroff pathways. For UxuR, the two preferred sites of ligand binding were found: one is located within the C-terminal domain, while another occupies the interdomain space. For ExuR, the only one preferred site was detected in the interdomain area. Availability of this area to different ligands suggests that, similar to the Lac repressor, the DNA-binding properties of UxuR and ExuR may be changed by repositioning of their domains. Experimental assays confirmed the ability of ligands with highest affinities to bind the regulatory proteins and affect their interaction with DNA. d-gal that is carried into the cell by the ExuT transporter appeared to be the best ligand for repressor of the exuT transcription, ExuR. For UxuR, the highest affinity was found for d-fructuronate transported by GntP, which biosynthesis is repressed by UxuR. Providing a feedback loop to balance the concentrations of different nutrients, such ligand-mediated modulation can also coordinate switching between different metabolic pathways in bacteria.

A model of substitution trajectories in sequence space and long-term protein evolution.

The nature of factors governing the tempo and mode of protein evolution is a fundamental issue in evolutionary biology. Specifically, whether or not interactions between different sites, or epistasis, are important in directing the course of evolution became one of the central questions. Several recent reports have scrutinized patterns of long-term protein evolution claiming them to be compatible only with an epistatic fitness landscape. However, these claims have not yet been substantiated with a formal model of protein evolution. Here, we formulate a simple covarion-like model of protein evolution focusing on the rate at which the fitness impact of amino acids at a site changes with time. We then apply the model to the data on convergent and divergent protein evolution to test whether or not the incorporation of epistatic interactions is necessary to explain the data. We find that convergent evolution cannot be explained without the incorporation of epistasis and the rate at which an amino acid state switches from being acceptable at a site to being deleterious is faster than the rate of amino acid substitution. Specifically, for proteins that have persisted in modern prokaryotic organisms since the last universal common ancestor for one amino acid substitution approximately ten amino acid states switch from being accessible to being deleterious, or vice versa. Thus, molecular evolution can only be perceived in the context of rapid turnover of which amino acids are available for evolution.

Epistasis as the primary factor in molecular evolution.

The main forces directing long-term molecular evolution remain obscure. A sizable fraction of amino-acid substitutions seem to be fixed by positive selection, but it is unclear to what degree long-term protein evolution is constrained by epistasis, that is, instances when substitutions that are accepted in one genotype are deleterious in another. Here we obtain a quantitative estimate of the prevalence of epistasis in long-term protein evolution by relating data on amino-acid usage in 14 organelle proteins and 2 nuclear-encoded proteins to their rates of short-term evolution. We studied multiple alignments of at least 1,000 orthologues for each of these 16 proteins from species from a diverse phylogenetic background and found that an average site contained approximately eight different amino acids. Thus, without epistasis an average site should accept two-fifths of all possible amino acids, and the average rate of amino-acid substitutions should therefore be about three-fifths lower than the rate of neutral evolution. However, we found that the measured rate of amino-acid substitution in recent evolution is 20 times lower than the rate of neutral evolution and an order of magnitude lower than that expected in the absence of epistasis. These data indicate that epistasis is pervasive throughout protein evolution: about 90 per cent of all amino-acid substitutions have a neutral or beneficial impact only in the genetic backgrounds in which they occur, and must therefore be deleterious in a different background of other species. Our findings show that most amino-acid substitutions have different fitness effects in different species and that epistasis provides the primary conceptual framework to describe the tempo and mode of long-term protein evolution.

Stop codons in bacteria are not selectively equivalent.

BACKGROUND: The evolution and genomic stop codon frequencies have not been rigorously studied with the exception of coding of non-canonical amino acids. Here we study the rate of evolution and frequency distribution of stop codons in bacterial genomes. RESULTS: We show that in bacteria stop codons evolve slower than synonymous sites, suggesting the action of weak negative selection. However, the frequency of stop codons relative to genomic nucleotide content indicated that this selection regime is not straightforward. The frequency of TAA and TGA stop codons is GC-content dependent, with TAA decreasing and TGA increasing with GC-content, while TAG frequency is independent of GC-content. Applying a formal, analytical model to these data we found that the relationship between stop codon frequencies and nucleotide content cannot be explained by mutational biases or selection on nucleotide content. However, with weak nucleotide content-dependent selection on TAG, -0.5 < Nes < 1.5, the model fits all of the data and recapitulates the relationship between TAG and nucleotide content. For biologically plausible rates of mutations we show that, in bacteria, TAG stop codon is universally associated with lower fitness, with TAA being the optimal for G-content < 16% while for G-content > 16% TGA has a higher fitness than TAG. CONCLUSIONS: Our data indicate that TAG codon is universally suboptimal in the bacterial lineage, such that TAA is likely to be the preferred stop codon for low GC content while the TGA is the preferred stop codon for high GC content. The optimization of stop codon usage may therefore be useful in genome engineering or gene expression optimization applications.

Translation termination in pyrrolysine-utilizing archaea.

Although some data link archaeal and eukaryotic translation, the overall mechanism of protein synthesis in archaea remains largely obscure. Both archaeal (aRF1) and eukaryotic (eRF1) single release factors recognize all three stop codons. The archaeal genus Methanosarcinaceae contains two aRF1 homologs, and also uses the UAG stop to encode the 22nd amino acid, pyrrolysine. Here we provide an analysis of the last stage of archaeal translation in pyrrolysine-utilizing species. We demonstrated that only one of two Methanosarcina barkeri aRF1 homologs possesses activity and recognizes all three stop codons. The second aRF1 homolog may have another unknown function. The mechanism of pyrrolysine incorporation in the Methanosarcinaceae is discussed.

Conversion and compensatory evolution of the gamma-crystallin genes and identification of a cataractogenic mutation that reverses the sequence of the human CRYGD gene to an ancestral state.

We identified a mutation in the CRYGD gene (P23S) of the gamma-crystallin gene cluster that is associated with a polymorphic congenital cataract that occurs with frequency of approximately 0.3% in a human population. To gain insight into the molecular mechanism of the pathogenesis of gamma-crystallin isoforms, we undertook an evolutionary analysis of the available mammalian and newly obtained primate sequences of the gamma-crystallin genes. The cataract-associated serine at site 23 corresponds to the ancestral state, since it was found in CRYGD of a lower primate and all the surveyed nonprimate mammals. Crystallin proteins include two structurally similar domains, and substitutions in mammalian CRYGD protein at site 23 of the first domain were always associated with substitutions in the structurally reciprocal sites 109 and 136 of the second domain. These data suggest that the cataractogenic effect of serine at site 23 in the N-terminal domain of CRYGD may be compensated indirectly by amino acid changes in a distal domain. We also found that gene conversion was a factor in the evolution of the gamma-crystallin gene cluster throughout different mammalian clades. The high rate of gene conversion observed between the functional CRYGD gene and two primate gamma-crystallin pseudogenes (CRYGEP1 and CRYGFP1) coupled with a surprising finding of apparent negative selection in primate pseudogenes suggest a deleterious impact of recently derived pseudogenes involved in gene conversion in the gamma-crystallin gene cluster.

Selection for functional uniformity of tuf duplicates in gamma-proteobacteria.

Having an extra copy of a gene is thought to provide some functional redundancy, which results in a higher rate of evolution in duplicated genes. In this article, we estimate the impact of gene duplication on the selection of tuf paralogs, and we find that in the absence of gene conversion, tuf paralogs have evolved significantly slower than when gene conversion has been a factor in their evolution. Thus, tuf gene copies evolve under a selective pressure that ensures their functional uniformity, and gene conversion reduces selection against amino acid substitutions that affect the function of the encoded protein, EF-Tu.

A tetrapeptide-based method for polyproline II-type secondary structure prediction.

We describe a new method for polyproline II-type (PPII) secondary structure prediction based on tetrapeptide conformation properties using data obtained from all globular proteins in the Protein Data Bank (PDB). This is the first method for PPII prediction with a relatively high level of accuracy (approximately 60%). Our method uses only frequencies of different conformations among oligopeptides without any additional parameters. We also attempted to predict alpha-helices and beta-strands using the same approach. We find that the application of our method reveals interrelation between sequence and structure even for very short oligopeptides (tetrapeptides).

A very large diversity space of synthetically accessible compounds for use with drug design programs.

We have constructed a very large virtual diversity space containing more than 10(13) chemical compounds. The diversity space is built from about 400 combinatorial libraries, which have been expanded by choosing sizeable collections of suitable R-groups that can be attached to each link point of their scaffolds. These R-group collections have been created by selecting reagents that have drug-like properties from catalogs of available chemicals. As members of known combinatorial libraries, the compounds in the diversity space are in general synthetically accessible and useful as potential drug leads. Hence, the diversity space can be used as a vast source of compounds by a de novo drug design program. For example, we have used such a program to generate inhibitors of HIV integrase enzyme that exhibited activity in the micromolar range.

From analysis of protein structural alignments toward a novel approach to align protein sequences.

Alignment of protein sequences is a key step in most computational methods for prediction of protein function and homology-based modeling of three-dimensional (3D)-structure. We investigated correspondence between "gold standard" alignments of 3D protein structures and the sequence alignments produced by the Smith-Waterman algorithm, currently the most sensitive method for pair-wise alignment of sequences. The results of this analysis enabled development of a novel method to align a pair of protein sequences. The comparison of the Smith-Waterman and structure alignments focused on their inner structure and especially on the continuous ungapped alignment segments, "islands" between gaps. Approximately one third of the islands in the gold standard alignments have negative or low positive score, and their recognition is below the sensitivity limit of the Smith-Waterman algorithm. From the alignment accuracy perspective, the time spent by the algorithm while working in these unalignable regions is unnecessary. We considered features of the standard similarity scoring function responsible for this phenomenon and suggested an alternative hierarchical algorithm, which explicitly addresses high scoring regions. This algorithm is considerably faster than the Smith-Waterman algorithm, whereas resulting alignments are in average of the same quality with respect to the gold standard. This finding shows that the decrease of alignment accuracy is not necessarily a price for the computational efficiency.