A novel series of compositionally biased substitution matrices for comparing Plasmodium proteins

Computational approaches for identifying disease-causing mutations in proteins

Advancements in genome sequencing have expanded the scope of investigating mutations in proteins across different diseases. Amino acid mutations in a protein alter its structure, stability and function and some of them lead to diseases. Identification of disease-causing mutations is a challenging task and it will be helpful for designing therapeutic strategies. Hence, mutation data available in the literature have been curated and stored in several databases, which have been effectively utilized for developing computational methods to identify deleterious mutations (drivers), using sequence and structure-based properties of proteins. In this chapter, we describe the contents of specific databases that have information on disease-causing and neutral mutations followed by sequence and structure-based properties. Further, characteristic features of disease-causing mutations will be discussed along with computational methods for identifying cancer hotspot residues and disease-causing mutations in proteins.

Distribution of Plasmodium falciparum K13 gene polymorphisms across transmission settings in Ghana

Malaria is a significant global health concern, with a majority of cases in Sub-Saharan African nations. Numerous antimalarial drugs have been developed to counter the rampant prevalence of Plasmodium falciparum malaria. Artemisinin-based Combination Therapy (ACT) has served as the primary treatment of uncomplicated malaria in Ghana since 2005. However, a growing concern has emerged due to the escalating reports of ACT resistance, particularly in Southeast Asia, and its encroachment into Africa. Specifically, mutations in the Kelch propeller domain on chromosome 13 (Pfk13) have been linked to ACT resistance. Yet, our understanding of mutation prevalence in Africa remains largely uncharted. In this study, we compared Pfk13 sequences obtained from 172 P. falciparum samples across three ecological and transmission zones in Ghana. We identified 27 non-synonymous mutations among these sequences, of which two of the mutations, C580Y (found in two samples from the central region) and Y493H (found in one sample from the north), had previously been validated for their association with artemisinin resistance, a phenomenon widespread in Southeast Asia. The Pfk13 gene diversity was most pronounced in the northern savannah than the central forest and south coastal regions, where transmission rates are lower. The observed mutations were not significantly associated with geographical regions, suggesting a frequent spread of mutations across the country. The ongoing global surveillance of artemisinin resistance remains pivotal, and our findings provides insights into the potential spread of resistant parasites in West Africa. Furthermore, the identification of novel codon mutations in this study raises their potential association to ACT resistance, warranting further investigation through in vitro assays to ascertain their functional significance.

Substitution scoring matrices for proteins - An overview

Sequence analysis is the primary and simplest approach to discover structural, functional and evolutionary details of related proteins. All the alignment based approaches of sequence analysis make use of amino acid substitution matrices, and the accuracy of the results largely depends on the type of scoring matrices used to perform alignment tasks. An amino acid substitution matrix is a 20 × 20 matrix in which the individual elements encapsulate the rates at which each of the 20 amino acid residues in proteins are substituted by other amino acid residues over time. In contrast to most globular/ordered proteins whose amino acids composition is considered as standard, there are several classes of proteins (e.g., transmembrane proteins) in which certain types of amino acid (e.g., hydrophobic residues) are enriched. These compositional differences among various classes of proteins are manifested in their underlying residue substitution frequencies. Therefore, each of the compositionally distinct class of proteins or protein segments should be studied using specific scoring matrices that reflect their distinct residue substitution pattern. In this review, we describe the development and application of various substitution scoring matrices peculiar to proteins with standard and biased compositions. Along with most commonly used standard matrices (PAM, BLOSUM, MD and VTML) that act as default parameters in various homologs search and alignment tools, different substitution scoring matrices specific to compositionally distinct class of proteins are discussed in detail.

The ranging of amino acids substitution matrices of various types in accordance with the alignment accuracy criterion

Background

The alignment of character sequences is important in bioinformatics. The quality of this procedure is determined by the substitution matrix and parameters of the insertion-deletion penalty function. These matrices are derived from sequence alignment and thus reflect the evolutionary process. Currently, in addition to evolutionary matrices, a large number of different background matrices have been obtained. To make an optimal choice of the substitution matrix and the penalty parameters, we conducted a numerical experiment using a representative sample of existing matrices of various types and origins.

Results

We tested both the classical evolutionary matrix series (PAM, Blosum, VTML, Pfasum); structural alignment based matrices, contact energy matrix, and matrix based on the properties of the genetic code. This study presents results for two test set types: first, we simulated sequences that reflect the divergent evolution; second, we performed tests on Balibase sequences. In both cases, we obtained the dependences of the alignment quality (Accuracy, Confidence) on the evolutionary distance between sequences and the evolutionary distance to which the substitution matrices correspond. Optimization of a combination of matrices and the penalty parameters was carried out for local and global alignment on the values of penalty function parameters.

Consequently, we found that the best alignment quality is achieved with matrices corresponding to the largest evolutionary distance. These matrices prove to be universal, i.e. suitable for aligning sequences separated by both large and small evolutionary distances. We analysed the correspondence of the correlation coefficients of matrices to the alignment quality. It was found that matrices showing high quality alignment have an above average correlation value, but the converse is not true.

Conclusions

This study showed that the best alignment quality is achieved with evolutionary matrices designed for long distances: Gonnet, VTML250, PAM250, MIQS, and Pfasum050. The same property is inherent in matrices not only of evolutionary origin, but also of another background corresponding to a large evolutionary distance. Therefore, matrices based on structural data show alignment quality close enough to its value for evolutionary matrices. This agrees with the idea that the spatial structure is more conservative than the protein sequence.

Plasmodium falciparum Kelch Propeller Polymorphisms in Clinical Isolates from Ghana from 2007 to 2016

The continuous surveillance of polymorphisms in the kelch propeller domain of Plasmodium falciparum from Africa is important for the discovery of the actual markers of artemisinin resistance in the region. The information on the markers is crucial for control strategies involving chemotherapy and chemoprophylaxis for residents and nonimmune travelers to the country. Polymorphisms in the kelch propeller domain of Ghanaian malaria parasites from three different ecological zones at several time periods were assessed. A total of 854 archived samples (2007 to 2016) collected from uncomplicated malaria patients aged ≤9 years old from 10 sentinel sites were used. Eighty-four percent had wild-type sequences (PF3D7_1343700), while many of the mutants had mostly nonsynonymous mutations clustered around codons 404 to 650. Variants with different amino acid changes of the codons associated with artemisinin (ART) resistance validated markers were observed in Ghanaian isolates: frequencies for I543I, I543S, I543V, R561P, R561R, and C580V were 0.12% each and 0.6% for R539I. Mutations reported from African parasites, A578S (0.23%) and Q613L (0.23%), were also observed. Three persisting nonsynonymous (NS) mutations, N599Y (0.005%), K607E (0.004%), and V637G (0.004%), were observed in 3 of the 5 time periods nationally. The presence of variants of the validated markers of artemisinin resistance as well as persisting polymorphisms after 14 years of artemisinin-based combination therapy use argues for continuous surveillance of the markers. The molecular markers of artemisinin resistance and the observed variants will be monitored subsequently as part of ongoing surveillance of antimalarial drug efficacy/resistance studies in the country.

Genomic epidemiology of artemisinin resistant malaria

The current epidemic of artemisinin resistant Plasmodium falciparum in Southeast Asia is the result of a soft selective sweep involving at least 20 independent kelch13 mutations. In a large global survey, we find that kelch13 mutations which cause resistance in Southeast Asia are present at low frequency in Africa. We show that African kelch13 mutations have originated locally, and that kelch13 shows a normal variation pattern relative to other genes in Africa, whereas in Southeast Asia there is a great excess of non-synonymous mutations, many of which cause radical amino-acid changes. Thus, kelch13 is not currently undergoing strong selection in Africa, despite a deep reservoir of variations that could potentially allow resistance to emerge rapidly. The practical implications are that public health surveillance for artemisinin resistance should not rely on kelch13 data alone, and interventions to prevent resistance must account for local evolutionary conditions, shown by genomic epidemiology to differ greatly between geographical regions.

DOI:http://dx.doi.org/10.7554/eLife.08714.001

Malaria is an infectious disease caused by a microscopic parasite called Plasmodium, which is transferred between humans by mosquitos. One species of malaria parasite called Plasmodium falciparum can cause particularly severe and life-threatening forms of the disease. Currently, the most widely used treatment for P. falciparum infections is artemisinin combination therapy, a treatment that combines the drug artemisinin (or a closely related molecule) with another antimalarial drug. However, resistance to artemisinin has started to spread throughout Southeast Asia.

Artemisinin resistance is caused by mutations in a parasite gene called kelch13, and researchers have identified over 20 different mutations in P. falciparum that confer artemisinin resistance. The diversity of mutations involved, and the fact that the same mutation can arise independently in different locations, make it difficult to track the spread of resistance using conventional molecular marker approaches.

Here, Amato, Miotto et al. sequenced the entire genomes of more than 3,000 clinical samples of P. falciparum from Southeast Asia and Africa, collected as part of a global network of research groups called the MalariaGEN Plasmodium falciparum Community Project. Amato, Miotto et al. found that African parasites had independently acquired many of the same kelch13 mutations that are known to cause resistance to artemisinin in Southeast Asia. However the kelch13 mutations seen in Africa remained at low levels in the parasite population, and appeared to be under much less pressure for evolutionary selection than those found in Southeast Asia.

These findings demonstrate that the emergence and spread of resistance to antimalarial drugs does not depend solely on the mutational process, but also on other factors that influence whether the mutations will spread in the population. Understanding how this is affected by different patterns of drug treatments and other environmental conditions will be important in developing more effective strategies for combating malaria.

DOI:http://dx.doi.org/10.7554/eLife.08714.002

Revisiting amino acid substitution matrices for identifying distantly related proteins

Motivation: Although many amino acid substitution matrices have been developed, it has not been well understood which is the best for similarity searches, especially for remote homology detection. Therefore, we collected information related to existing matrices, condensed it and derived a novel matrix that can detect more remote homology than ever.

Results: Using principal component analysis with existing matrices and benchmarks, we developed a novel matrix, which we designate as MIQS. The detection performance of MIQS is validated and compared with that of existing general purpose matrices using SSEARCH with optimized gap penalties for each matrix. Results show that MIQS is able to detect more remote homology than the existing matrices on an independent dataset. In addition, the performance of our developed matrix was superior to that of CS-BLAST, which was a novel similarity search method with no amino acid matrix. We also evaluated the alignment quality of matrices and methods, which revealed that MIQS shows higher alignment sensitivity than that with the existing matrix series and CS-BLAST. Fundamentally, these results are expected to constitute good proof of the availability and/or importance of amino acid matrices in sequence analysis. Moreover, with our developed matrix, sophisticated similarity search methods such as sequence–profile and profile–profile comparison methods can be improved further.

Availability and implementation: Newly developed matrices and datasets used for this study are available at http://csas.cbrc.jp/Ssearch/.

Contact:k-tomii@aist.go.jp

Supplementary information:Supplementary data are available at Bioinformatics online

The parasite specific substitution matrices improve the annotation of apicomplexan proteins

Background

A number of apicomplexan genomes have been sequenced successfully in recent years and this would help in understanding the biology of apicomplexan parasites. The members of the phylum Apicomplexa are important protozoan parasites (Plasmodium, Toxoplasma and Cryptosporidium etc) that cause some of the deadly diseases in humans and animals. In our earlier studies, we have shown that the standard BLOSUM matrices are not suitable for compositionally biased apicomplexan proteins. So we developed a novel series (SMAT and PfFSmat60) of substitution matrices which performed better in comparison to standard BLOSUM matrices and developed ApicoAlign, a sequence search and alignment tool for apicomplexan proteins. In this study, we demonstrate the higher specificity of these matrices and make an attempt to improve the annotation of apicomplexan kinases and proteases.

Results

The ROC curves proved that SMAT80 performs best for apicomplexan proteins followed by compositionally adjusted BLOSUM62 (PSI-BLAST searches), BLOSUM90 and BLOSUM62 matrices in terms of detecting true positives. The poor E-values and/or bit scores given by SMAT80 matrix for the experimentally identified coccidia-specific oocyst wall proteins against hematozoan (non-coccidian) parasites further supported the higher specificity of the same. SMAT80 uniquely detected (missed by BLOSUM) orthologs for 1374 apicomplexan hypothetical proteins against SwissProt database and predicted 70 kinases and 17 proteases. Further analysis confirmed the conservation of functional residues of kinase domain in one of the SMAT80 detected kinases. Similarly, one of the SMAT80 detected proteases was predicted to be a rhomboid protease.

Conclusions

The parasite specific substitution matrices have higher specificity for apicomplexan proteins and are helpful in detecting the orthologs missed by BLOSUM matrices and thereby improve the annotation of apicomplexan proteins which are hypothetical or with unknown function.

Local structural differences in homologous proteins: specificities in different SCOP classes

The constant increase in the number of solved protein structures is of great help in understanding the basic principles behind protein folding and evolution. 3-D structural knowledge is valuable in designing and developing methods for comparison, modelling and prediction of protein structures. These approaches for structure analysis can be directly implicated in studying protein function and for drug design. The backbone of a protein structure favours certain local conformations which include α-helices, β-strands and turns. Libraries of limited number of local conformations (Structural Alphabets) were developed in the past to obtain a useful categorization of backbone conformation. Protein Block (PB) is one such Structural Alphabet that gave a reasonable structure approximation of 0.42 Å. In this study, we use PB description of local structures to analyse conformations that are preferred sites for structural variations and insertions, among group of related folds. This knowledge can be utilized in improving tools for structure comparison that work by analysing local structure similarities. Conformational differences between homologous proteins are known to occur often in the regions comprising turns and loops. Interestingly, these differences are found to have specific preferences depending upon the structural classes of proteins. Such class-specific preferences are mainly seen in the all-β class with changes involving short helical conformations and hairpin turns. A test carried out on a benchmark dataset also indicates that the use of knowledge on the class specific variations can improve the performance of a PB based structure comparison approach. The preference for the indel sites also seem to be confined to a few backbone conformations involving β-turns and helix C-caps. These are mainly associated with short loops joining the regular secondary structures that mediate a reversal in the chain direction. Rare β-turns of type I’ and II’ are also identified as preferred sites for insertions.

Normalized global alignment for protein sequences

Global alignment is used to compare proteins in different fields, for example in phylogenetic research. In order to reduce the length and composition dependence of global alignment scores, Z-score is computed with a Monte-Carlo algorithm. This technique requires a great number of sequence alignments on shuffled sequences, leading to a high computational cost. In this work, a normalized global alignment score is introduced in order to correct the length dependence of global alignments. This score is defined as the best ratio between the score of an alignment and its length, and an algorithm to compute it based on fractional programming is implemented. The properties and effectiveness of normalized global alignment applied to protein comparison are analyzed. Experiments with proteins selected from the SCOP ASTRAL database were run to study relationship of normalized global alignment with Z-score and performance in homologous detection. Results show that normalized global alignment has a computational cost equivalent to 2.5 Needleman-Wunsch runs and a linear relationship with Z-score. This linearity allows us to use normalized global alignment as a cheap substitute to a computationally expensive Z-score. Experiments show that normalized global alignment improves the ability to identify homologous proteins. Software used to compute normalized global alignments is available from http://www3.uji.es/∼peris/nga.

ApicoAlign: an alignment and sequence search tool for apicomplexan proteins

BACKGROUND

Over the recent years, a number of genomes have been successfully sequenced and this was followed by genome annotation projects to help understand the biological capabilities of newly sequenced genomes. To improve the annotation of Plasmodium falciparum proteins, we earlier developed parasite specific matrices (PfSSM) and demonstrated their (Smat80 and PfFSmat60) better performance over standard matrices (BLOSUM and PAM). Here we extend that study to nine apicomplexan species other than P. falciparum and develop a web application ApicoAlign for improving the annotation of apicomplexan proteins.

RESULTS

The SMAT80 and PfFSmat60 matrices perform better for apicomplexan proteins compared to BLOSUM in detecting the orthologs and improving the alignment of these proteins with their potential orthologs respectively. Database searches against non-redundant (nr) database have shown that SMAT80 gives superior performance compared to BLOSUM series in terms of E-values, bit scores, percent identity, alignment length and mismatches for most of the apicomplexan proteins studied here. Using these matrices, we were able to find orthologs for rhomboid proteases of P. berghei, P. falciparum & P. vivax and large subunit of U2 snRNP auxiliary factor of Cryptosporidium parvum in Arabidopsis thaliana. We also show improved pairwise alignments of proteins from Apicomplexa viz. Cryptosporidium parvum and P. falciparum with their orthologs from other species using the PfFSmat60 matrix.

CONCLUSIONS

The SMAT80 and PfFSmat60 substitution matrices perform better for apicomplexan proteins compared to BLOSUM series. Since they can be helpful in improving the annotation of apicomplexan genomes and their functional characterization, we have developed a web server ApicoAlign for finding orthologs and aligning apicomplexan proteins.

A novel substitution matrix fitted to the compositional bias in Mollicutes improves the prediction of homologous relationships

Background

Substitution matrices are key parameters for the alignment of two protein sequences, and consequently for most comparative genomics studies. The composition of biological sequences can vary importantly between species and groups of species, and classical matrices such as those in the BLOSUM series fail to accurately estimate alignment scores and statistical significance with sequences sharing marked compositional biases.

Results

We present a general and simple methodology to build matrices that are especially fitted to the compositional bias of proteins. Our approach is inspired from the one used to build the BLOSUM matrices and is based on learning substitution and amino acid frequencies on real sequences with the corresponding compositional bias. We applied it to the large scale comparison of Mollicute AT-rich genomes. The new matrix, MOLLI60, was used to predict pairwise orthology relationships, as well as homolog families among 24 Mollicute genomes. We show that this new matrix enables to better discriminate between true and false orthologs and improves the clustering of homologous proteins, with respect to the use of the classical matrix BLOSUM62.

Conclusions

We show in this paper that well-fitted matrices can improve the predictions of orthologous and homologous relationships among proteins with a similar compositional bias. With the ever-increasing number of sequenced genomes, our approach could prove valuable in numerous comparative studies focusing on atypical genomes.

Revisiting the Plasmodium falciparum RIFIN family: from comparative genomics to 3D-model prediction

Background

Subtelomeric RIFIN genes constitute the most abundant multigene family in Plasmodium falciparum. RIFIN products are targets for the human immune response and contribute to the antigenic variability of the parasite. They are transmembrane proteins grouped into two sub-families (RIF_A and RIF_B). Although recent data show that RIF_A and RIF_B have different sub-cellular localisations and possibly different functions, the same structural organisation has been proposed for members of the two sub-families. Despite recent advances, our knowledge of the regulation of RIFIN gene expression is still poor and the biological role of the protein products remain obscure.

Results

Comparative studies on RIFINs in three clones of P. falciparum (3D7, HB3 and Dd2) by Multidimensional scaling (MDS) showed that gene sequences evolve differently in the 5'upstream, coding, and 3'downstream regions, and suggested a possible role of highly conserved 3' downstream sequences. Despite the expected polymorphism, we found that the overall structure of RIFIN repertoires is conserved among clones suggesting a balance between genetic drift and homogenisation mechanisms which guarantees emergence of novel variants but preserves the functionality of genes. Protein sequences from a bona fide set of 3D7 RIFINs were submitted to predictors of secondary structure elements. In contrast with the previously proposed structural organisation, no signal peptide and only one transmembrane helix were predicted for the majority of RIF_As. Finally, we developed a strategy to obtain a reliable 3D-model for RIF_As. We generated 265 possible structures from 53 non-redundant sequences, from which clustering and quality assessments selected two models as the most representative for putative RIFIN protein structures.

Conclusion

First, comparative analyses of RIFIN repertoires in different clones of P. falciparum provide insights on evolutionary mechanisms shaping the multigene family. Secondly, we found that members of the two sub-families RIF_As and RIF_Bs have different structural organization in accordance with recent experimental results. Finally, representative models for RIF_As have an "Armadillo-like" fold which is known to promote protein-protein interactions in diverse contexts.