Helminths and Cancers From the Evolutionary Perspective

Helminths include free-living and parasitic Platyhelminthes and Nematoda which infect millions of people worldwide. Some Platyhelminthes species of blood flukes (Schistosoma haematobium, Schistosoma japonicum, and Schistosoma mansoni) and liver flukes (Clonorchis sinensis and Opisthorchis viverrini) are known to be involved in human cancers. Other helminths are likely to be carcinogenic. Our main goals are to summarize the current knowledge of human cancers caused by Platyhelminthes, point out some helminth and human biomarkers identified so far, and highlight the potential contributions of phylogenetics and molecular evolution to cancer research. Human cancers caused by helminth infection include cholangiocarcinoma, colorectal hepatocellular carcinoma, squamous cell carcinoma, and urinary bladder cancer. Chronic inflammation is proposed as a common pathway for cancer initiation and development. Furthermore, different bacteria present in gastric, colorectal, and urogenital microbiomes might be responsible for enlarging inflammatory and fibrotic responses in cancers. Studies have suggested that different biomarkers are involved in helminth infection and human cancer development; although, the detailed mechanisms remain under debate. Different helminth proteins have been studied by different approaches. However, their evolutionary relationships remain unsolved. Here, we illustrate the strengths of homology identification and function prediction of uncharacterized proteins from genome sequencing projects based on an evolutionary framework. Together, these approaches may help identifying new biomarkers for disease diagnostics and intervention measures. This work has potential applications in the field of phylomedicine (evolutionary medicine) and may contribute to parasite and cancer research.

Evolutionary analysis of the cystatin family in three Schistosoma species

The cystatin family comprises cysteine protease inhibitors distributed in 3 subfamilies (I25A–C). Family members lacking cystatin activity are currently unclassified. Little is known about the evolution of Schistosoma cystatins, their physiological roles, and expression patterns in the parasite life cycle. The present study aimed to identify cystatin homologs in the predicted proteome of three Schistosoma species and other Platyhelminthes. We analyzed the amino acid sequence diversity focused in the identification of protein signatures and to establish evolutionary relationships among Schistosoma and experimentally validated human cystatins. Gene expression patterns were obtained from different developmental stages in Schistosoma mansoni using microarray data. In Schistosoma, only I25A and I25B proteins were identified, reflecting little functional diversification. I25C and unclassified subfamily members were not identified in platyhelminth species here analyzed. The resulting phylogeny placed cystatins in different clades, reflecting their molecular diversity. Our findings suggest that Schistosoma cystatins are very divergent from their human homologs, especially regarding the I25B subfamily. Schistosoma cystatins also differ significantly from other platyhelminth homologs. Finally, transcriptome data publicly available indicated that I25A and I25B genes are constitutively expressed thus could be essential for schistosome life cycle progression. In summary, this study provides insights into the evolution, classification, and functional diversification of cystatins in Schistosoma and other Platyhelminthes, improving our understanding of parasite biology and opening new frontiers in the identification of novel therapeutic targets against helminthiases.

Lipopolysaccharide-induced inhibition of transcription of tlr4 in vitro is reversed by dexamethasone and correlates with presence of conserved NFκB binding sites

Engagement of Toll-like receptor 4 (TLR4) by lipopolysaccharide (LPS) is a master trigger of the deleterious effects of septic shock. Horses and humans are considered the most sensitive species to septic shock, but the mechanisms explaining these phenomena remain elusive. Analysis of tlr4 promoters revealed high similarity among LPS-sensitive species (human, chimpanzee, and horse) and low similarity with LPS-resistant species (mouse and rat). Four conserved nuclear factor kappa B (NFκB) binding sites were found in the tlr4 promoter and two in the md2 promoter sequences that are likely to be targets for dexamethasone regulation. In vitro treatment of equine peripheral blood mononuclear cells (eqPBMC) with LPS decreased transcripts of tlr4 and increased transcription of md2 (myeloid differentiation factor 2) and cd14 (cluster of differentiation 14). Treatment with dexamethasone rescued transcription of tlr4 after LPS inhibition. LPS-induced transcription of md2 was inhibited in the presence of dexamethasone. Dexamethasone alone did not affect transcription of tlr4 and md2.

Eukaryotic protein kinases (ePKs) of the helminth parasite Schistosoma mansoni

BACKGROUND

Schistosomiasis remains an important parasitic disease and a major economic problem in many countries. The Schistosoma mansoni genome and predicted proteome sequences were recently published providing the opportunity to identify new drug candidates. Eukaryotic protein kinases (ePKs) play a central role in mediating signal transduction through complex networks and are considered druggable targets from the medical and chemical viewpoints. Our work aimed at analyzing the S. mansoni predicted proteome in order to identify and classify all ePKs of this parasite through combined computational approaches. Functional annotation was performed mainly to yield insights into the parasite signaling processes relevant to its complex lifestyle and to select some ePKs as potential drug targets.

RESULTS

We have identified 252 ePKs, which corresponds to 1.9% of the S. mansoni predicted proteome, through sequence similarity searches using HMMs (Hidden Markov Models). Amino acid sequences corresponding to the conserved catalytic domain of ePKs were aligned by MAFFT and further used in distance-based phylogenetic analysis as implemented in PHYLIP. Our analysis also included the ePK homologs from six other eukaryotes. The results show that S. mansoni has proteins in all ePK groups. Most of them are clearly clustered with known ePKs in other eukaryotes according to the phylogenetic analysis. None of the ePKs are exclusively found in S. mansoni or belong to an expanded family in this parasite. Only 16 S. mansoni ePKs were experimentally studied, 12 proteins are predicted to be catalytically inactive and approximately 2% of the parasite ePKs remain unclassified. Some proteins were mentioned as good target for drug development since they have a predicted essential function for the parasite.

CONCLUSIONS

Our approach has improved the functional annotation of 40% of S. mansoni ePKs through combined similarity and phylogenetic-based approaches. As we continue this work, we will highlight the biochemical and physiological adaptations of S. mansoni in response to diverse environments during the parasite development, vector interaction, and host infection.

Protein families reflect the metabolic diversity of organisms and provide support for functional prediction

Comparative genomics has shown that protein families vary significantly within and across organisms in both number and functional composition. In the present work, we tested how the diversity at the family level reflects biological differences among organisms and contributes to their unique characteristics. For this purpose, we collected sequence-similar proteins of three selected families from model bacteria: Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa. Protein relationships were identified using a phylogenomic approach to connect the functional diversity of enzymes to the metabolic capabilities of these organisms. All protein families studied have distinct functional compositions across the selected bacteria as supported by our Bayesian analysis. Some conserved functional features among family members included a shared reaction mechanism, cofactor usage, and/or ligand specificity. Many observations of the presence/absence of protein functions matched current knowledge of the physiology and biochemistry of the bacteria. In some cases, new functional predictions were made to family members previously uncharacterized. We believe that genome comparisons at the protein family level would also be useful in predicting metabolic diversity for organisms that are relatively unknown or currently uncultured in the laboratory.

EGenBio: a data management system for evolutionary genomics and biodiversity

Background

Evolutionary genomics requires management and filtering of large numbers of diverse genomic sequences for accurate analysis and inference on evolutionary processes of genomic and functional change. We developed Evolutionary Genomics and Biodiversity (EGenBio; ) to begin to address this.

Description

EGenBio is a system for manipulation and filtering of large numbers of sequences, integrating curated sequence alignments and phylogenetic trees, managing evolutionary analyses, and visualizing their output. EGenBio is organized into three conceptual divisions, Evolution, Genomics, and Biodiversity. The Genomics division includes tools for selecting pre-aligned sequences from different genes and species, and for modifying and filtering these alignments for further analysis. Species searches are handled through queries that can be modified based on a tree-based navigation system and saved. The Biodiversity division contains tools for analyzing individual sequences or sequence alignments, whereas the Evolution division contains tools involving phylogenetic trees. Alignments are annotated with analytical results and modification history using our PRAED format. A miscellaneous Tools section and Help framework are also available. EGenBio was developed around our comparative genomic research and a prototype database of mtDNA genomes. It utilizes MySQL-relational databases and dynamic page generation, and calls numerous custom programs.

Conclusion

EGenBio was designed to serve as a platform for tools and resources to ease combined analysis in evolution, genomics, and biodiversity.

Divergence of function in sequence-related groups of Escherichia coli proteins

The most prominent mechanism of molecular evolution is believed to have been duplication and divergence of genes. Proteins that belong to sequence-related groups in any one organism are candidates to have emerged from such a process and to share a common ancestor. Groups of proteins in Escherichia coli having sequence similarity are mostly composed of proteins with closely related function, but some groups comprise proteins with unrelated functions. In order to understand how function can change while sequences remain similar, we have examined some of these groups in detail. The enzymes analyzed in this work include representatives of amidotransferases, phosphotransferases, decarboxylases, and others. Most sequence-related groups contain enzymes that are in the same classes of Enzyme Commission (EC) numbers. We have concentrated on groups that are heterogeneous in that respect, and also on groups containing more than one enzyme of any pathway. We find that although the EC number may differ, the reaction chemistry of these sequence-related proteins is the same or very similar. Some of these families illustrate how diversification has taken place in evolution, using common features of either reaction chemistry or ligand specificity, or both, to create catalysts for different kinds of biochemical reactions. This information has relevance to the area of functional genomics in which the activities of gene products of unknown reading frames are attributed by analogy to the functions of sequence-related proteins of known function.

A functional update of the Escherichia coli K-12 genome

BACKGROUND

Since the genome of Escherichia coli K-12 was initially annotated in 1997, additional functional information based on biological characterization and functions of sequence-similar proteins has become available. On the basis of this new information, an updated version of the annotated chromosome has been generated.

RESULTS

The E. coli K-12 chromosome is currently represented by 4,401 genes encoding 116 RNAs and 4,285 proteins. The boundaries of the genes identified in the GenBank Accession U00096 were used. Some protein-coding sequences are compound and encode multimodular proteins. The coding sequences (CDSs) are represented by modules (protein elements of at least 100 amino acids with biological activity and independent evolutionary history). There are 4,616 identified modules in the 4,285 proteins. Of these, 48.9% have been characterized, 29.5% have an imputed function, 2.1% have a phenotype and 19.5% have no function assignment. Only 7% of the modules appear unique to E. coli, and this number is expected to be reduced as more genome data becomes available. The imputed functions were assigned on the basis of manual evaluation of functions predicted by BLAST and DARWIN analyses and by the MAGPIE genome annotation system.

CONCLUSIONS

Much knowledge has been gained about functions encoded by the E. coli K-12 genome since the 1997 annotation was published. The data presented here should be useful for analysis of E. coli gene products as well as gene products encoded by other genomes.