Molecular convergence by differential domain acquisition is a hallmark of chromosomal passenger complex evolution

The chromosomal passenger complex (CPC) is a heterotetrameric regulator of eukaryotic cell division, consisting of an Aurora-type kinase and a scaffold built of INCENP, Borealin and Survivin. While most CPC components are conserved across eukaryotes, orthologs of the chromatin reader Survivin have previously only been found in animals and fungi, raising the question of how its essential role is carried out in other eukaryotes. By characterizing proteins that bind to the Arabidopsis Borealin ortholog, we identified BOREALIN RELATED INTERACTOR 1 and 2 (BORI1 and BORI2) as redundant Survivin-like proteins in the context of the CPC in plants. Loss of BORI function is lethal and a reduced expression of BORIs causes severe developmental defects. Similar to Survivin, we find that the BORIs bind to phosphorylated histone H3, relevant for correct CPC association with chromatin. However, this interaction is not mediated by a BIR domain as in previously recognized Survivin orthologs, but by an FHA domain, a widely conserved phosphate-binding module. We propose that the unifying criterion of Survivin-type proteins is a helix that facilitates complex formation with the other two scaffold components, and that the addition of a phosphate-binding domain, necessary for concentration at the inner centromere, evolved in parallel in different eukaryotic groups. Using sensitive similarity searches, we indeed find conservation of this helical domain between animals and plants, and identify the missing CPC component in most eukaryotic supergroups. Interestingly, we also detect Survivin orthologs without a defined phosphate-binding domain, possibly reflecting the situation in the last eukaryotic common ancestor.

Systematic in silico discovery of novel solute carrier-like proteins from proteomes

Solute carrier (SLC) proteins represent the largest superfamily of transmembrane transporters, the systematic analysis of which is hampered by their functional and structural heterogeneity, despite their biological importance. Based on available nomenclature systems, we suspected that many as yet unidentified SLC transporters exist in the human genome. Here, we present criteria for defining "SLC-likeness" and apply them to curate a set of "SLC-like" protein families from the Transporter Classification Database (TCDB) and Protein families (Pfam) databases. Computational sequence similarity searches then surprisingly yielded ~130 more proteins in human with SLC-like properties, compared to previous annotations. Several of these novel putative SLC transporter proteins actually have documented transport activity in the scientific literature. We complete our overview of the SLC-ome by presenting an algorithm to classify SLC-like proteins into protein families, investigating their known functions and evolutionary relationships to similar proteins from 6 other clinically relevant experimental organisms, and pinpointing structural orphans. We envision that our work will serve as a stepping stone for future studies of the biological function and the identification of the natural substrates of the many under-explored SLC transporters, as well as the development of new therapeutic applications, including strategies for personalized medicine and drug delivery.

Proximity Graphs for Similarity Searches: Experimental Survey and the New Connected-Partition Approach HGraph

Similarity searching is a widely used approach to retrieve complex data (images, videos, time series, etc.). Similarity searches aim at retrieving similar data according to the intrinsic characteristics of the data. Recently, graph-based methods have emerged as a very efficient alternative for similarity retrieval, with reports indicating they have outperformed methods of other categories in several situations. This work presents two main contributions to graph-based methods for similarity searches. The first contribution is a survey on the main graph types currently employed for similarity searches and an experimental evaluation of the most representative graphs in a common platform for exact and approximate search algorithms. The second contribution is a new graph-based method called HGraph, which is a connected-partition approach to build a proximity graph and answer similarity searches. Both of our contributions and results were published and received awards in international conferences.

Architecture Insight of Bifidobacterial α-L-Fucosidases

Fucosylated carbohydrates and glycoproteins from human breast milk are essential for the development of the gut microbiota in early life because they are selectively metabolized by bifidobacteria. In this regard, α-L-fucosidases play a key role in this successful bifidobacterial colonization allowing the utilization of these substrates. Although a considerable number of α-L-fucosidases from bifidobacteria have been identified by computational analysis, only a few of them have been characterized. Hitherto, α-L-fucosidases are classified into three families: GH29, GH95, and GH151, based on their catalytic structure. However, bifidobacterial α-L-fucosidases belonging to a particular family show significant differences in their sequence. Because this fact could underlie distinct phylogenetic evolution, here extensive similarity searches and comparative analyses of the bifidobacterial α-L-fucosidases identified were carried out with the assistance of previous physicochemical studies available. This work reveals four and two paralogue bifidobacterial fucosidase groups within GH29 and GH95 families, respectively. Moreover, Bifidobacterium longum subsp. infantis species exhibited the greatest number of phylogenetic lineages in their fucosidases clustered in every family: GH29, GH95, and GH151. Since α-L-fucosidases phylogenetically descended from other glycosyl hydrolase families, we hypothesized that they could exhibit additional glycosidase activities other than fucosidase, raising the possibility of their application to transfucosylate substrates other than lactose in order to synthesis novel prebiotics.

Architecture Insight of Bifidobacterial α-L-Fucosidases

Fucosylated carbohydrates and glycoproteins from human breast milk are essential for the development of the gut microbiota in early life because they are selectively metabolized by bifidobacteria. In this regard, α-L-fucosidases play a key role in this successful bifidobacterial colonization allowing the utilization of these substrates. Although a considerable number of α-L-fucosidases from bifidobacteria have been identified by computational analysis, only a few of them have been characterized. Hitherto, α-L-fucosidases are classified into 3 families, GH29, GH95 and GH151 based on their catalytic structure. However, bifidobacterial α-L-fucosidases belonging to a particular family show significant differences in their sequence. Because this fact could underlie distinct phylogenetic evolves, here extensive similarity searches and comparative analyses of the bifidobacterial α-L-fucosidases identified were carried out with the assistance of previous physicochemical studies available. This work reveals 4 and 2 paralogue bifidobacterial fucosidase groups within GH29 and GH95 families, respectively. Moreover, Bifidobacterium logum subsp. infantis species exhibited the greatest number of phylogenetic lineages in their fucosidases clustered in every family GH29, GH95 and GH151. Since α-L-fucosidases phylogenetically descended from other glycosyl hydrolase families, we hypothesized that could exhibit additional glycosidase activities other than fucosidase, raising the possibility about their application to transfucosylate other substrates than lactose in order to synthesis novel prebiotics.

NOD: a web server to predict New use of Old Drugs to facilitate drug repurposing

Computational methods accelerate the drug repurposing pipelines that are a quicker and cost-effective alternative to discovering new molecules. However, there is a paucity of web servers to conduct fast, focussed, and customized investigations for identifying new uses of old drugs. We present the NOD web server, which has the mentioned characteristics. NOD uses a sensitive sequence-guided approach to identify close and distant homologs of a protein of interest. NOD then exploits this evolutionary information to suggest potential compounds from the DrugBank database that can be repurposed against the input protein. NOD also allows expansion of the chemical space of the potential candidates through similarity searches. We have validated the performance of NOD against available experimental and/or clinical reports. In 65.6% of the investigated cases in a control study, NOD is able to identify drugs more effectively than the searches made in DrugBank. NOD is freely-available at http://pauling.mbu.iisc.ac.in/NOD/NOD/.

PHROG: families of prokaryotic virus proteins clustered using remote homology

Viruses are abundant, diverse and ancestral biological entities. Their diversity is high, both in terms of the number of different protein families encountered and in the sequence heterogeneity of each protein family. The recent increase in sequenced viral genomes constitutes a great opportunity to gain new insights into this diversity and consequently urges the development of annotation resources to help functional and comparative analysis. Here, we introduce PHROG (Prokaryotic Virus Remote Homologous Groups), a library of viral protein families generated using a new clustering approach based on remote homology detection by HMM profile-profile comparisons. Considering 17 473 reference (pro)viruses of prokaryotes, 868 340 of the total 938 864 proteins were grouped into 38 880 clusters that proved to be a 2-fold deeper clustering than using a classical strategy based on BLAST-like similarity searches, and yet to remain homogeneous. Manual inspection of similarities to various reference sequence databases led to the annotation of 5108 clusters (containing 50.6 % of the total protein dataset) with 705 different annotation terms, included in 9 functional categories, specifically designed for viruses. Hopefully, PHROG will be a useful tool to better annotate future prokaryotic viral sequences thus helping the scientific community to better understand the evolution and ecology of these entities.

Broadly sampled orthologous groups of eukaryotic proteins for the phylogenetic study of plastid-bearing lineages

Objectives Identifying orthology relationships among sequences is essential to understand evolution, diversity of life and ancestry among organisms. To build alignments of orthologous sequences, phylogenomic pipelines often start with all-vs-all similarity searches, followed by a clustering step. For the protein clusters (orthogroups) to be as accurate as possible, proteomes of good quality are needed. Here, our objective is to assemble a data set especially suited for the phylogenomic study of algae and formerly photosynthetic eukaryotes, which implies the proper integration of organellar data, to enable distinguishing between several copies of one gene (paralogs), taking into account their cellular compartment, if necessary. Data description We submitted 73 top-quality and taxonomically diverse proteomes to OrthoFinder. We obtained 47,266 orthogroups and identified 11,775 orthogroups with at least two algae. Whenever possible, sequences were functionally annotated with eggNOG and tagged after their genomic and target compartment(s). Then we aligned and computed phylogenetic trees for the orthogroups with IQ-TREE. Finally, these trees were further processed by identifying and pruning the subtrees exclusively composed of plastid-bearing organisms to yield a set of 31,784 clans suitable for studying photosynthetic organism genome evolution.

Compare the performance of the models in art classification

Because large numbers of artworks are preserved in museums and galleries, much work must be done to classify these works into genres, styles and artists. Recent technological advancements have enabled an increasing number of artworks to be digitized. Thus, it is necessary to teach computers to analyze (e.g., classify and annotate) art to assist people in performing such tasks. In this study, we tested 7 different models on 3 different datasets under the same experimental setup to compare their art classification performances when either using or not using transfer learning. The models were compared based on their abilities for classifying genres, styles and artists. Comparing the result with previous work shows that the model performance can be effectively improved by optimizing the model structure, and our results achieve state-of-the-art performance in all classification tasks with three datasets. In addition, we visualized the process of style and genre classification to help us understand the difficulties that computers have when tasked with classifying art. Finally, we used the trained models described above to perform similarity searches and obtained performance improvements.

The ubiquinone synthesis pathway is a promising drug target for Chagas disease

Chagas disease is caused by infection with the protozoan parasite Trypanosoma cruzi (T. cruzi). It was originally a Latin American endemic health problem, but now is expanding worldwide as a result of increasing migration. The currently available drugs for Chagas disease, benznidazole and nifurtimox, provoke severe adverse effects, and thus the development of new drugs is urgently required. Ubiquinone (UQ) is essential for respiratory chain and redox balance in trypanosomatid protozoans, therefore we aimed to provide evidence that inhibitors of the UQ biosynthesis have trypanocidal activities. In this study, inhibitors of the human COQ7, a key enzyme of the UQ synthesis, were tested for their trypanocidal activities because they were expected to cross-react and inhibit trypanosomal COQ7 due to their genetic homology. We show the trypanocidal activity of a newly found human COQ7 inhibitor, an oxazinoquinoline derivative. The structurally similar compounds were selected from the commercially available compounds by 2D and 3D ligand-based similarity searches. Among 38 compounds selected, 12 compounds with the oxazinoquinoline structure inhibited significantly the growth of epimastigotes of T. cruzi. The most effective 3 compounds also showed the significant antitrypanosomal activity against the mammalian stage of T. cruzi at lower concentrations than benznidazole, a commonly used drug today. We found that epimastigotes treated with the inhibitor contained reduced levels of UQ9. Further, the growth of epimastigotes treated with the inhibitors was partially rescued by UQ10 supplementation to the culture medium. These results suggest that the antitrypanosomal mechanism of the oxazinoquinoline derivatives results from inhibition of the trypanosomal UQ synthesis leading to a shortage of the UQ pool. Our data indicate that the UQ synthesis pathway of T. cruzi is a promising drug target for Chagas disease.