The interaction of a Trypanosoma brucei KH-domain protein with a ribonuclease is implicated in ribosome processing.

Ribosomal RNA maturation is best understood in yeast. While substantial efforts have been made to explore parts of these essential pathways in animals, the similarities and uniquenesses of rRNA maturation factors in non-Opisthokonts remain largely unexplored. Eukaryotic ribosome synthesis requires the coordinated activities of hundreds of Assembly Factors (AFs) that transiently associate with pre-ribosomes, many of which are essential. Pno1 and Nob1 are two of six AFs that are required for the cytoplasmic maturation of the 20S pre-rRNA to 18S rRNA in yeast where it has been almost exclusively analyzed. Specifically, Nob1 ribonucleolytic activity generates the mature 3'-end of 18S rRNA. We identified putative Pno1 and Nob1 homologues in the protist Trypanosoma brucei, named TbPNO1 and TbNOB1, and set out to explore their rRNA maturation role further as they are both essential for normal growth. TbPNO1 is a nuclear protein with limited cytosolic localization relative to its yeast homologue. Like in yeast, it interacts directly with TbNOB1, with indications of associations with a larger AF-containing complex. Interestingly, in the absence of TbPNO1, TbNOB1 exhibits non-specific degradation activity on RNA substrates, and its cleavage activity becomes specific only in the presence of TbPNO1, suggesting that TbPNO1-TbNOB1 interaction is essential for regulation and site-specificity of TbNOB1 activity. These results highlight a conserved role of the TbPNO1-TbNOB1 complex in 18S rRNA maturation across eukaryotes; yet reveal a novel role of their interaction in regulation of TbNOB1 enzymatic activity.

Naphthalene-based RNA editing inhibitor blocks RNA editing activities and editosome assembly in Trypanosoma brucei.

RNA editing, catalyzed by the multiprotein editosome complex, is an essential step for the expression of most mitochondrial genes in trypanosomatid pathogens. It has been shown previously that Trypanosoma brucei RNA editing ligase 1 (TbREL1), a core catalytic component of the editosome, is essential in the mammalian life stage of these parasitic pathogens. Because of the availability of its crystal structure and absence from human, the adenylylation domain of TbREL1 has recently become the focus of several studies for designing inhibitors that target its adenylylation pocket. Here, we have studied new and existing inhibitors of TbREL1 to better understand their mechanism of action. We found that these compounds are moderate to weak inhibitors of adenylylation of TbREL1 and in fact enhance adenylylation at higher concentrations of protein. Nevertheless, they can efficiently block deadenylylation of TbREL1 in the editosome and, consequently, result in inhibition of the ligation step of RNA editing. Further experiments directly showed that the studied compounds inhibit the interaction of the editosome with substrate RNA. This was supported by the observation that not only the ligation activity of TbREL1 but also the activities of other editosome proteins such as endoribonuclease, terminal RNA uridylyltransferase, and uridylate-specific exoribonuclease, all of which require the interaction of the editosome with the substrate RNA, are efficiently inhibited by these compounds. In addition, we found that these compounds can interfere with the integrity and/or assembly of the editosome complex, opening the exciting possibility of using them to study the mechanism of assembly of the editosome components.

Sequence-based functional annotation: what if most of the genes are unique to a genome?

The genomes of trypanosomatids are distantly related to other eukaryotes, with significant numbers of hypothetical or conserved hypothetical trypanosomatid-specific genes, whose functions cannot be determined using homology-dependent annotation methods. Here, we describe homology-independent methods to infer biological functions of genes based solely on their sequences. These approaches are not limited to trypanosomatid genomes and provide grounds for analysis of genomes of Plasmodium falciparum and other parasites associated with neglected tropical diseases. A critical evaluation of the current state of annotation of parasitic genomes endorses the need to exploit homology-independent computational methods, which can identify protein functions, potentially including essential genes, and provide a plethora of valuable information on interaction networks and regulatory elements.

Universal function-specificity of codon usage.

Synonymous codon usage has long been known as a factor that affects average expression level of proteins in fast-growing microorganisms, but neither its role in dynamic changes of expression in response to environmental changes nor selective factors shaping it in the genomes of higher eukaryotes have been fully understood. Here, we propose that codon usage is ubiquitously selected to synchronize the translation efficiency with the dynamic alteration of protein expression in response to environmental and physiological changes. Our analysis reveals that codon usage is universally correlated with gene function, suggesting its potential contribution to synchronized regulation of genes with similar functions. We directly show that coexpressed genes have similar synonymous codon usages within the genomes of human, yeast, Caenorhabditis elegans and Escherichia coli. We also demonstrate that perturbing the codon usage directly affects the level or even direction of changes in protein expression in response to environmental stimuli. Perturbing tRNA composition also has tangible phenotypic effects on the cell. By showing that codon usage is universally function-specific, our results expand, to almost all organisms, the notion that cells may need to dynamically alter their intracellular tRNA composition in order to adapt to their new environment or physiological role.

Genome-wide computational identification of functional RNA elements in Trypanosoma brucei.

BACKGROUND: Post-transcriptional regulation of gene expression is the dominant regulatory mechanism in trypanosomatids as their mRNAs are transcribed from polycistronic units. A few cis-acting RNA elements in 3'-untranslated regions of mRNAs have been identified in trypanosomatids, which affect the mRNA stability or translation rate in different life stages of these parasites. Other functional RNAs (fRNAs) also play essential roles in these organisms. However, there has been no genome-wide analysis for identification of fRNAs in trypanosomatids. RESULTS: Functional RNAs, including non-coding RNAs (ncRNAs) and cis-acting RNA elements involved in post-transcriptional gene regulation, were predicted based on two independent computational analyses of the genome of Trypanosoma brucei. In the first analysis, the predicted candidate ncRNAs were identified based on conservation with the related trypanosomatid Leishmania braziliensis. This prediction had a substantially low estimated false discovery rate, and a considerable number of the predicted ncRNAs represented novel classes with unknown functions. In the second analysis, we identified a number of function-specific regulatory motifs, based on which we devised a classifier that can be used for homology-independent function prediction in T. brucei. CONCLUSION: This first genome-wide analysis of fRNAs in trypanosomatids restricts the search space of experimental approaches and, thus, can significantly expedite the process of characterization of these elements. Our classifier for function prediction based on cis-acting regulatory elements can also, in combination with other methods, provide the means for homology-independent annotation of trypanosomatid genomes.

MAD-DPD: designing highly degenerate primers with maximum amplification specificity.

This work introduces minimum accumulative degeneracy, a variant of the degenerate primer design problem, which is particularly useful when a large number of sequences are to be covered by a set of restricted number of primers. A primer set, which is designed on a minimum accumulative degeneracy basis, especially helps to reduce nonspecific PCR amplification of undesired DNA fragments, as fewer primer species are present in PCR. A Boltzmann machine is designed to solve the minimum accumulative degeneracy degenerate primer design problem, called the MAD-DPD Boltzmann machine. This algorithm shows great flexibility, as it can be determined either to solve the problem with strict fidelity to covering all input sequences or to exclude some input sequences if it results in less degenerate primers. This Boltzmann machine is successfully implemented in designing a new set of primers for amplification of antibody variable fragments from mouse spleen cells, which theoretically covers more diverse antibody sequences than currently available primers. The MAD-DPD Boltzmann machine is available online at bioinf.cs.ipm.ir/download/MAD_DPD08172007.zip.

Sequence-based prediction of protein-protein interactions by means of codon usage.

We introduce a novel approach to predict interaction of two proteins solely by analyzing their coding sequences. We found that similarity in codon usage is a strong predictor of protein-protein interactions and, for high specificity values, is as sensitive as the most powerful current prediction methods. Furthermore, combining codon usage with other predictors results in a 75% increase in sensitivity at a precision of 50%, compared to prediction without considering codon usage.

Designing multiple degenerate primers via consecutive pairwise alignments.

BACKGROUND: Different algorithms have been proposed to solve various versions of degenerate primer design problem. For one of the most general cases, multiple degenerate primer design problem, very few algorithms exist, none of them satisfying the criterion of designing low number of primers that cover high number of sequences. Besides, the present algorithms require high computation capacity and running time. RESULTS: PAMPS, the method presented in this work, usually results in a 30% reduction in the number of degenerate primers required to cover all sequences, compared to the previous algorithms. In addition, PAMPS runs up to 3500 times faster. CONCLUSION: Due to small running time, using PAMPS allows designing degenerate primers for huge numbers of sequences. In addition, it results in fewer primers which reduces the synthesis costs and improves the amplification sensitivity.

Amino acid and codon usage profiles: adaptive changes in the frequency of amino acids and codons.

In the work presented, the changes in codon and amino acid contents have been studied as a function of environmental conditions by comparing pairs of homologs in a group of extremophilic/non-extremophilic genomes. Our results obtained based on such analysis highlights a number of notable observations: (i) the overall preference of amino acid usages in the proteins of a given organism is significantly affected by major environmental factors. The changes in amino acid preferences (amino acid usage profiles) in an extremophile compared to its non-extremophile relative recurs in the organisms of similar extreme habitats. (ii) On the other hand, changes in codon usage preferences in these extremophilic/non-extremophilic pairs, lack such persistency not only in different genome-pairs but also in the individual genes of a specific pair. (iii) We have noted a correlation between cellular function and codon usage profiles of the genes in the studied pairs. (iv) Based on this correlation, we could obtain a decent prediction of cellular functions solely based on codon usage profile data. (v) Comparisons made between two sets of randomly generated genomes suggest that different patterns of codon usage changes in genes of different functional categories result in a partial resistance towards the changes in the concentration of a given amino acid. This buffering capacity might explain the observed differences in codon usage trends in genes of different functions. In the end, we suggest codon usage and amino acid profiles as powerful tools that can be utilized to improve function predictions and genome-environment mappings.

Solvent accessibility, residue charge and residue volume, the three ingredients of a robust amino acid substitution matrix.

Cost measure matrices or different amino acid indices have been widely used for studies in many fields of biology. One major criticism of these studies might be based on the unavailability of an unbiased and yet effective amino acid substitution matrix. Throughout this study we have devised a cost measure matrix based on the solvent accessibility, residue charge, and residue volume indices. Performed analyses on this novel substitution matrix (i.e. solvent accessibility charge volume (SCV) matrix) support the uncontaminated nature of this matrix regarding the genetic code. Although highly similar to a number of previously available cost measure matrices, the SCV matrix results in a more significant optimality in the error-buffering capacity of the genetic code when compared to many other amino acid substitution matrices. Besides, a method to compare an SCV-based scoring matrix with a number of widely used matrices has been devised, the results of which highlights the robustness of this matrix in protein family discrimination.

Error minimization explains the codon usage of highly expressed genes in Escherichia coli.

Different organisms use synonymous codons with different preferences. Several measures have been introduced to compute the extent of codon usage bias within a gene or genome, among which the codon adaptation index (CAI) has been shown to be well correlated with mRNA levels of Escherichia coli. In this work an error adaptation index (eAI) is introduced, which estimates the level at which a gene can tolerate the effects of mistranslations. It is shown that the eAI has a strong correlation with CAI, as well as with mRNA levels, which suggests that the codons of highly expressed genes are selected so that mistranslation would have the minimum possible effect on the structure and function of the related proteins.

Applying a neural network to predict the thermodynamic parameters for an expanded nearest-neighbor model.

Predicting the secondary and tertiary structure of RNAs largely depends on our capabilities in estimating the thermodynamics of RNA duplexes. In this work, an expanded nearest-neighbor model, designated INN-48, is established. The thermodynamic parameters of this model are predicted using both multiple linear regression analysis and neural network analysis. It is suggested that due to the increase in the number of parameters and the insufficiency of the existing data, neural network analysis results in more reliable predictions. Furthermore, it is suggested that INN-48 can be used to estimate the thermodynamics of RNA duplex formation for longer sequences, whereas INN-HB, the previous model on which INN-48 is based, can be used for short sequences.

The impact of including tRNA content on the optimality of the genetic code.

Statistical and biochemical studies have revealed nonrandom patterns in codon assignments. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, since it is known that, when an amino acid is converted to another due to error, the biochemical properties of the resulted amino acid are usually very similar to those of the original one. In this study, we have taken into consideration both relative frequencies of amino acids and relative gene copy frequencies of tRNAs in genomic sequences in order to introduce a fitness function which models the mistranslational probabilities more accurately in modern organisms. The relative gene copy frequencies of tRNAs are used as estimates of the tRNA content. We also altered the rule previously used for the calculation of the probabilities of single base mutation occurrences. Our model signifies higher optimality of the genetic code towards load minimization and suggests the presence of a coevolution of tRNA frequency and the genetic code.

Optimality of codon usage in Escherichia coli due to load minimization.

The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, an ability which in term is designated "load minimization". One parameter involved in calculating the load minimizing property of the genetic code is codon usage. In most bacteria, synonymous codons are not used with equal frequencies. Different factors have been proposed to contribute to codon usage preference. It has been shown that the codon preference is correlated with the composition of the tRNA pool. Selection for translational efficiency and translational accuracy both result in such a correlation. In this work, it is shown that codon usage bias in Escherichia coli works so as to minimize the consequences of translational errors, i.e. optimized for load minimization.

Designing a neural network for the constraint optimization of the fitness functions devised based on the load minimization of the genetic code.

Nonrandom patterns in codon assignments are supported by many statistical and biochemical studies in the last two decades. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, an ability, which in term is designated "load minimization". Prior studies have included many attempts at quantitative estimation of the fraction of randomly generated codes, which in terms of load minimization, score higher than the canonical genetic code. In this study, a neural network, which estimates a highly optimized genetic code in a relatively short period of time has been devised. Several fitness functions were used throughout this text. Meanwhile, we have made use of two cost measure matrices, PAM74-100 and mutation matrix.

On the optimality of the genetic code, with the consideration of coevolution theory by comparison of prominent cost measure matrices.

Statistical and biochemical studies have revealed non-random patterns in codon assignments. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslation errors and point mutations, since it is known that when an amino acid is converted to another due to error, the biochemical properties of the resulted amino acid are usually very similar to those of the original one. In this study, using altered forms of the fitness functions used in the prior studies, we have optimized the parameters involved in the calculation of the error minimizing property of the genetic code so that the genetic code outscores the random codes as much as possible. This work also compares two prominent matrices, the Mutation Matrix and Point Accepted Mutations 74-100 (PAM(74-100)). It has been resulted that the hypothetical properties of the coevolution theory of the genetic code are already considered in PAM(74-100), giving more evidence on the existence of bias towards the genetic code in this matrix. Furthermore, our results indicate that PAM(74-100) is biased towards the single base mistranslation occurrences in second codon position as well as the frequency of amino acids. Thus PAM(74-100) is not a suitable substitution matrix for the studies conducted on the evolution of the genetic code.

Correspondence regarding Bharanidharan et al., "Correlations between nucleotide frequencies and amino acid composition in 115 bacterial species".

Bharanidharan et al. [Biochem. Biophys. Res. Commun. 315 (2004) 1097-1103] claimed that the frequencies of most amino acids are determined by the dinucleotide composition of the genome. Here, regarding a methodological problem in their work, it is suggested that the standard deviations of amino acid frequencies should be determined to indicate how significant a certain deviation from the predicted frequency is. Furthermore, using a different method that is expected to be more reliable, we suggest that the dinucleotide composition cannot explain the observed frequencies of most amino acids, and the deviations of amino acid frequencies from what dinucleotide composition predicts are larger than to be expected by chance.

How reliable re-adjustment is: correspondence regarding A. Fuglsang, "The 'effective number of codons' revisited".

A. Fuglsang [Biochem. Biophys. Res. Commun. 317 (2004) 957-964] suggested that effective number of codons for individual amino acids (Nc-values) should be re-adjusted to the number of synonymous codons of those amino acids, in order to prevent the overestimation of the effective number of codons. Here, it is shown that re-adjustment at the level of individual amino acids results in loss of considerable amounts of information. Furthermore, we have shown that theoretical Nc-values are functions of GC3s (and GC1s); as a result, when an amino acid Nc-value exceeds the related theoretical Nc-value, the implication of re-adjustment depends on the GC composition of the gene.