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In silico prediction of protein–protein interaction between Glossina m. morsitans (Westwood, 1851) and Trypanosoma brucei (Kinetoplastida: Trypanosomatidae)

In silico prediction of protein–protein interaction between Glossina m. morsitans (Westwood,... Abstract Trypanosoma brucei is a pathogenic protozoa that causes chronic Human African Trypanosomiasis and African Animal Trypanosomiasis. The pathogenic parasite is transmitted to humans by the tsetse fly, Glossina m. morsitans. Trypanosomiasis control strategies have targeted either the tsetse vector or the parasite. Most of the biological processes in a living cell are controlled by protein–protein interactions (PPI). Prediction of vector host–parasite protein interactions could give an insight into the mechanism of blocking transmission through parasite interference and identify potential vaccine targets. Prediction of protein interactions and orthologous relatedness was done between Glossina m. morsitans (the vector host) and T. brucei (the parasite) using information on conserved orthologous protein interactions in other organisms (interologs). Orthologues from both species were identified using a Markov cluster algorithm of the OrthoMCL software. The Host-Pathogen Interaction Database (HPIDB) and BIANA Interolog Prediction server (BIPS) identified interologs in Glossina m. morsitans and T. brucei. Among the predicted proteins from BIPS were T. brucei tubulin alpha chain, tubulin beta chain, dynein light chain-putative and calmodulin, which were observed to act as hubs connecting to Glossina’s Ubiquitin-40S ribosomal protein S27a fusion protein, dyenin light chain type 1, heat shock protein cognate 3, Gamma-aminobutyric acid receptor-associated protein, putative glycerate kinase and Ribosomal protein S14b. These proteins are implicated in the cellular transportation mechanism of both the vector and the parasite as well as the host defense mechanism. Those predicted from HPIBD were Glossina s-adenosylmethionine synthetase, DNA helicase, ubiquitin protein ligase, AAA+-type ATPase, Rab protein 6, WD40 repeat-containing protein and serine/threonine protein phosphatase, observed to act as hubs connecting to parasitic s-adenosylmethionine synthetase, elongation factor 1-alpha 2, Histone H2A, katanin, lipoic acid synthetase, PolyUbiquitin and serine/threonine protein kinase. This study gives an important insight into the PPI involved in Glossina–Trypanosoma associations that may be involved in the immune response of Glossina m. morsitans and evasion by T. brucei. Some of the interactions may help in the trypanosome’s transformation within the vector host. These observations will give a better understanding of parasite transmission biology and may advance efforts towards transmission-blocking vaccines. Trypanosoma brucei, Glossina m. morsitans, protein–protein interaction, Trypanosomiasis Introduction African trypanosomiasis is caused by trypanosomes. The parasites transmit sleeping sickness to humans and nagana to livestock (Berriman, 2005). Once the infected tsetse fly bites a mammalian host during a blood meal, the host obtains the parasite, which differentiates into procyclic trypomastigotes in the midgut and salivary glands (Sharma et al., 2009). Knowledge of trypanosome propagation in the tsetse vector and the protein interactions that take place in the mammalian host is important in understanding the transmission dynamics of these parasites and identification of potential targets for drug and vaccine development. The trypanosome develops in the tsetse vector by first invading the midgut. This is where it differentiates into procyclic forms. The procyclic forms then move to salivary glands where they transform infective metacyclic trypanosomes found in the salivary gland. It is from the infected salivary glands that they are transmitted to the next mammalian host during a blood meal. During this transformation, the trypanosomes express several proteins within the tsetse fly that are required to invade, survive and become established in the vector (Rotureau and Van Den Abbeele, 2013). Parasitic diseases have been associated with the release of extracellular vesicles (EVs), acting both in parasite–parasite and parasite–host interactions. Extracellular vesicles that are important in the distribution and regulation of the immune system of the host carry as their cargo bioactive molecules such as proteins, DNA, mRNAs and miRNAs. The parasites use these proteins to regulate their targeted cells (Marcilla et al., 2014). In this work, interspecies protein–protein interactions and the proteins’ gene ontology were predicted between the extracellular Trypanosoma brucei parasite and Glossina m. morsitans proteins based on homology, with the assumption that interactions in other organisms are conserved between the target species (interolog mapping). The methodology (Fischer et al., 2011) used in this study, using the OrthoMCL software, has been shown to overcome the challenges that other similar software like INPARANOID and EGO face during eukaryotic ortholog group identification. OrthoMCL uses the Markov Cluster algorithm to identify orthologs in multiple genomes. OrthoMCL employs probability and graph flow theory for global comparison of genomes. The MCL algorithm has been found to be very reliable and fast when comparing complicated domain structures (Li, Stoeckert and Roos, 2003). Biana Interolog Prediction Server (BIPS) and HPIDB are servers in which the user can set the parameters freely for optimal results. The two databases are integrated and contain data from many sources like DIP and IntAct. The two databases give both overlapping and nonredundant HPIs. The results of this study are based on annotations only, with some of the results being affirmed by experimental work done by different authors. The significance of the predicted interactions between T. brucei and Glossina m. morsitans proteins was inferred from the literature indicating their involvement in the parasitic infection as well as manipulation of the host immune mechanism in pathogenesis. Methodology Datasets This study used a dataset consisting of proteins from Glossina m. morsitans and T. brucei downloaded from the National Centre for Biotechnology Information (NCBI), from a combination of all the NCBI source databases (PDB, RefSeq and UniProtKB/Swiss-Prot). The proteins, in FASTA format, were downloaded and sent to a file destination. Obtaining orthologues Linux Operating System commands and OrthoMCL software were used to obtain orthologues from the downloaded vector and parasite proteins (Chen et al., 2006). The protein sequences were filtered by rejecting low-quality sequences that were shorter than 10 amino acids, had more than 20% stop codons and 20% nonstandard amino acids (an amino acid that occurs naturally in cells but does not participate in peptide synthesis). This was sorted by the orthomclFilterFasta program. The sequences were compared to each other to obtain quality sequences using the BLASTp program. MySQL was used to construct a database that was used for querying and constituted all the sequences that were obtained by the orthomclFilterFasta program both for the Glossina m. morsitans and T. brucei proteins, masked with SEG (Fischer et al., 2011) at an E-value cutoff of 1e-5. ‘percent match length’ score was computed for each matching pair of sequences, by counting from the shorter sequences the number of amino acids that participate in any high scoring pairs (HSP), dividing that by the length of the shorter sequence and multiplying by 100. Percent identity was taken from the best HSP per hit. Matches with percent match <50% were filtered out using the orthomclBlastParser program. Sequences from the two FASTA files (Glossina m. morsitans and T. brucei) that were reciprocal best hits (i.e., the first sequence finds the second sequence as its best hit in the second species and vice versa) with the same e-value and bit score were identified as a pair of orthologues using the orthomclPairs program. To ensure correct grouping of the pairs as potential orthologues, co-orthologues and in-paralogs normalization of the e-values was done. Clustering was done using MCL (Li, Stoeckert and Roos, 2003). An inflation value of 1.5 was applied to ensure balance in sensitivity and selectivity of the groups. From the orthologue group, two different orthologue files belonging to T. brucei and Glossina m. morsitans were obtained and the Uniq command was used to detect and remove duplicate entries in the files to produce only unique orthologues. The retrieval of the FASTA sequences of the orthologues was done using BATCH ENREZ either in split or complete form and these were used in the subsequent analysis. The OrthoMCL approach includes ‘recent’ paralogues to the orthologue group. This method works similarly to the INPARANOID approach though it differs in that the ‘recent’ paralogues must be more similar to each other. Protein–protein interaction prediction The Host–Pathogen Interaction Database The The Host–Pathogen Interaction Database (HPIDB) (www.agbase.msstate.edu/hpi/main.html) was used for host–pathogen protein–protein interaction prediction. Searches for homologous host–pathogen interactions were carried out by filling in the two forms on the HPIDB interface. Form A was used to upload pathogen unique orthologue sequences in FASTA format. The output format was set as top hit, and the database to search against was set as ‘All Pathogen proteins’. Blossum62 matrix, an E-value of 0.00001, 50% identity and 50% query coverage filter were applied. Form B was used to upload the host FASTA sequences with top hit output format, and the database to search against was set as ‘All host proteins’. Blossum62 matrix, 70% identity, 70% query coverage and an E-value of 0.00001 were the parameters set for form B. The HPIDB output gave information on the experimental method that was used for interaction detection and also the type of interaction predicted as being either physical association, direct interaction or association. Biana Interolog Prediction Server This database was used as a tool for prediction of protein–protein interactions between Glossina m. morsitans and T. brucei. The unique orthologues of Glossina m. morsitans were split into two files and uploaded. The taxonomy of predicted partner proteins was set as T. brucei. The default homology conditions were applied in the prediction with the Blast E-value of ≤1e-10, joint E-value of ≤1e-10, % identity ≥80, Joint identities ≥80, query sequence coverage ≥80 and template sequence coverage ≥90. All the other filtering parameters were used at the default settings. Functional annotation of the predicted interactions The gene ontology attributes of the interacting proteins were identified using GOSlimviewer tool (http://www.agbase.msstate.edu/cgi-bin/tools/goslimviewer_select.pl). This gave the GO term(s) for molecular function, cellular component and the biological process of the predicted interacting proteins. Results and discussion MCL groups A total of 47 889 proteins belonging to T. brucei and 2832 belonging to Glossina m. morsitans were downloaded from the NCBI. Cleaning of the FASTA sequences resulted in 47 879 and 2832T. brucei and Glossina sequences, respectively. The output from the MCL program was three files of sequences. These were 3456 orthologues, 3734 co-orthologues and 682 715 in-paralogues. The number of unique orthologues obtained from the orthologues file was as follows: 776 from Glossina and 3139 from T. brucei. Predicted T. brucei and Glossina m. morsitans protein interaction A total of 322 interactions were inferred between 126 parasite proteins and 49 vector proteins. The interactions were inferred by HPIDB and BIPS on the basis of similarity of sequences between both the parasite and host proteins. The two prediction servers gave different interactions resulting in a large number of interactions that could be studied further for potential therapeutic development. Most of the predicted interactions were found in salivary glands where the parasite thrives best after overcoming the vector’s defense mechanism in the midgut. The infection and attachment of T. brucei to the tsetse salivary gland epithelium is vital to the life cycle of the parasite as it ensures that the saliva of the tsetse remains infected during its whole lifespan (Matetovici, Caljon and Van Den Abbeele, 2016). OrthoMCL approach This approach identifies recent paralogues by making sure that they are more similar than those sequences from other species. It then includes them in the orthologue group. As compared to the INPARANOID approach, which employs a similar concept, OrthoMCL is more stringent in the identification of the recent paralogues. OrthoMCL does not assume that pairwise comparison is only limited to two species like the INPARANOID approach does. EGO is another approach for identification of recent paralogues, although the lack of true orthologues and multiple orthologues with functional redundancy could easily mislead it in incomplete datasets of genomes. Li, Stoeckert and Roos (2003) have shown successful implementation of OrthoMCL with it being used to perform an all against all comparison of several genome datasets. Functions of predicted interactions Parasites’ nutrition Malaria parasites, trypanosomes and Leishmania are all parasitic protozoa that obtain nutrients from their vector and mammalian hosts by engaging endocytic proteins found in their plasma membranes. Glossina m. morsitans’ S-adenosylmethionine synthetase (ADD19751.1) was predicted to physically associate with isoforms of S-adenosylmethionine synthetase from T. brucei (Table 1). S-adenosylmethionine enzyme is involved in S-adenosine methionine (Adomet) synthesis, which is important as a propylamino donor in polyamine biosynthesis. Polyamines are essential for parasite growth and their biosynthesis has been targeted for drug discovery efforts in T. cruzi and the Trypanosoma brucei parasites (Reguera et al., 2007). In tsetse flies, fat body cells take up alanine from the hemolymph for proline production. Proline plays a role in parasite nutrition in T. brucei infected fat bodies. Trypanosoma brucei’s Tubulin alpha chain (TBA_TRYBR) interaction with Tubulin beta-1 chain from the infected fat body of Glossina m. morsitans (Table 2) is, therefore, an important interaction. L-proline is essential in the growth and development of T. brucei’s procyclic stage as an important source of energy and carbon (Mantilla et al., 2017). During flight, the tsetse uses proline as a carbon source and speculations are that in situ the parasite’s procyclic forms utilize proline (Atyame Nten et al., 2010). Table 1. Predicted interactions from HPIDB Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Open in new tab Table 1. Predicted interactions from HPIDB Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Open in new tab Table 2. Predicted interactions from BIPS Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Open in new tab Table 2. Predicted interactions from BIPS Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Open in new tab Parasitic DNA repair, growth and survival Isoforms of DNA helicase (ADD20025.1 and ADD19284.1) from Glossina m.morsitans were predicted to associate with both the isoforms of Elongation factor 1-alpha and Histone H2A from T. brucei (Table 1). Glossina m. morsitans DNA helicase isoforms’ interaction with the isoforms of elongation factor 1(EF-1) -alpha and H2A from T. brucei may infer an association solely either within the parasite or within the vector and not an association between the parasite and vector. These proteins are nuclear proteins. The nuclei of Glossina m. morsitans and T. brucei are separate entities. As T. brucei is an extracellular parasite such interaction is physiologically impossible as nuclear proteins do not exchange over long distances with the nuclei of other species. This intraspecies interaction, therefore, may be implicated in the replication, repair and reorganization of the kDNA in the parasite. The reactive oxygen species in the vector’s midgut lead to lethal double-strand breaks (DSBs) in the parasite’s DNA. It is important for a cell to be able to detect and initiate the repair of DSBs in DNA. DNA damage causes the phosphorylation of histone H2A at the Ser129 position. Phosphorylation enables cell survival in DNA DSB-causing agents (Downs et al., 2004). The trypanosomes’ mitochondrial kinetoplast DNA (kDNA) at the base of the motile flagellum in T. brucei is associated with DNA helicases, DNA polymerases, DNA ligases and topoisomerases that play a major role in the replication and reassembly of the kDNA into a network during cell division (Beck et al., 2013). EF-l alpha bundles and severs microtubule and actin filaments during cell division (Ridgley et al., 1996), which is important for the parasite’s protein synthesis, cell growth and motility. Glossina m. morsitans’ AAA+-type ATPase (ADD18768.1) direct interaction prediction with isoforms of katanin, lipoic acid synthetase and lipopyl synthase of T. brucei (Table 1) may also be important in microtubule (MT) severing during the parasite’s cell division mediated by ATP-driven katanin, an AAA+ family protein (Johjima et al., 2015). Lipoic acid synthase (LASY) is the enzyme involved in the synthesis of lipoic acid, which is a potent mitochondrial antioxidant and could be important to T. brucei procyclic cells in antioxidation of excessive amounts of reactive oxygen species (ROS) (Padmalayam et al., 2009). Calmodulin (Q382N3_9TRYP), from T. brucei, was predicted to interact with Glossina m.morsitans multifunctional chaperone, calmodulin and Casein kinase II alpha subunit (Table 2). Trypanosoma brucei induces upregulation of the host protein, Ca2+/calmodulin-dependent protein kinase (CaMK), which is among the stage-specific regulators of morphological differentiation of Plasmodium, Trypanosoma and Leishmania parasites (Kariithi et al., 2016). Parasite’s defense mechanism SUMO-conjugating enzyme, parasitic ubiquitin-conjugating enzyme and the actin family are implicated in the parasite’s survival. Kariithi et al. (2016) reported that one of the parasite’s survival tactics is to alter the binding partners, locations and/or functions of specific proteins and to antagonize other protein modifications. Sumoylation is a posttranslational modification mediated by SUMO protein and is one of the quickest ways of achieving these changes. SUMO-conjugating enzymes (ADD18803.1 and ADD18802.1) from Glossina m. morsitans were predicted to physically associate with Vacuolar ATP synthase, the Ubiquitin-conjugating enzyme and the Actin family (ActinA, ActinB, Actin1, and Actin2) of T. brucei (Table 1). Trypanosoma brucei may benefit from this interaction by using the sumoylation mechanism synergy mediated by the vector’s SUMO-conjugating enzyme and its own ubiquitin-conjugating enzyme to modify the behavior of vector proteins that are produced during the immune response. Sumoylation could affect the ability of Glossina immune response proteins to interact with those of T. brucei, hence killing it. Ubiquitin plays a role in the formation of endocytosis/exosome and as a sorting signal during endocytosis and early endosomal protein trafficking (Geiger et al., 2010). Padmalayam et al. (2009) reported that actin plays an important role in vesicular endocytosis, which could be implicated in the transportation and degradation process of ubiquitin-conjugated proteins in the parasite. Baker et al. (2015) showed that Vacuolar ATP synthase (V-ATPase) catalyzes ATP hydrolysis to enable transport of solutes and lower pH of lysosomes, which may be used in the degradation of sumoylated vector proteins. Dynein light chain-putative (Q4FKD8_9TRYP) from T. brucei was predicted to interact with Glossina m. morsitans’ microtubule-binding protein, Dynein light chain-type 1, Actin 87E, Actin 5C, Actin 57B, Putative glycerate kinase, Tubulin beta chain, Tubulin alpha chain, Ribosomal protein S14b and Tubulin beta-1 chain from the infected fat body (Table 2). Daher et al. (2010) demonstrated the involvement of Dynein light chain 1 (LC1) in the control of flagellar motility in Trypanosoma brucei and Chlamydomonas reinhardtii by interacting with the dynein γ heavy chain. Molecular motors involving myosin, kinesin and dynein complexes facilitate the motility/mobility and the transport of proteins and vesicles in eukaryotic cells. These motor proteins are ATP-driven, converting chemical energy into mechanical work. Glycerate kinase is involved in the energy production required by the motor proteins. Vesicle trafficking by the parasite is dependent on this interaction that aids the parasite survival. Glossina m. morsitans immune response The fat body is the major immune organ in the vector’s immune response, with other effector molecules that are expressed in the midgut increasingly becoming recognized as playing a role in immune reactions. WD40 repeat-containing protein (ADD20373.1) and ubiquitin protein ligase (ADD20484.1) from Glossina m. morsitans were predicted to directly interact with PolyUbiquitin from T. brucei (Table 1). Weiss et al. (2013) reported the involvement of WD40 repeat proteins in cellular processes like regulation of vesicle formation, transcriptional regulation, vesicular trafficking, RNA processing and control of cell division. Recruitment of the ubiquitin-conjugating enzyme (E2) by ubiquitin ligase (E3) leads to the transfer of ubiquitin to target proteins, aiding their degradation in the proteosome. This interaction may be important to Glossina m.morsitans in that it is able to control the parasites’ cell trafficking, DNA repair and cell cycle. This could also be important in the vector’s refractoriness to the parasite. Serine/threonine protein phosphatase (ADD20508.1) from Glossina m.morsitans was predicted to have a direct interaction with serine/threonine protein kinase from T. brucei (Table 1). Serine/threonine protein kinases function by phosphorylation of serine and threonine amino acids in T. brucei. Protein kinases regulate different cellular processes such as cell cycle progression, transcriptional control and differentiation in trypanosomes (Naula, Parsons and Mottram, 2005). Serine/threonine phosphatases on the other hand reverse the action of protein kinases, leading to programmed cell death (apoptosis). This interaction could assist the vector’s attempt to clear the parasite. Trypanosoma brucei’s tubulin alpha chain (TBA_TRYBR) was predicted to interact with eight proteins from the salivary gland (Actin 57B, Actin5C, ATP synthase subunit alpha, Tubulin beta chain, Ubiquitin/40S ribosomal protein S27a fusion protein, Actin 87E, Dynein light chain-type 1 and GTP-binding nuclear protein) (Table 2). Tubulin beta chain (TBB_TRYBR) from Trypanosoma brucei was also predicted to interact with 14 proteins from the salivary gland of the vector–host Glossina m. morsitans. The proteins include the Ribosomal protein S3, Heat shock protein cognate 3, Gamma-aminobutyric acid receptor-associated protein, ADP/ATP translocase, Actin 57B, Actin 5C, ATP synthase subunit alpha, Ubiquitin-40S ribosomal protein S27a fusion protein, Actin 87E, Dynein light chain-type 1, putative glycerate kinase, tubulin beta chain, tubulin alpha chain and tubulin beta-1 chain from the infected fat body. Matetovici, Caljon and Van Den Abbeele (2016) showed that Actin 5C functions as an extracellular pathogen recognition factor in A. gambiae, being involved in antibacterial defense by interaction with the extracellular immune factor AgMDL1. Actin functions as a Plasmodium antagonist and limits parasite infection in the gut. α-tubulin and β-tubulin-1 overexpression are induced by the presence of the T. brucei parasites in the salivary glands. HSP cognate 3 from Glossina m. morsitans was predicted to interact with tubulin beta chain (TBB_TRYBR) from T. brucei (Table 2). Hsp or stress proteins are usually overexpressed due to thermal stress, environmental insults or trauma (Mattson et al., 2004). Parasitic tubulin beta chain (TBB_TRYBR) was also predicted to interact with the vector’s gamma-aminobutyric acid receptor-associated protein (GABARAP) (Table 2), which is involved in autophagy mediated by the autophagosome. GABARAP is a member of the intracellular membrane trafficking and/or fusion protein family and is implicated in plasma membrane targeting and/or recycling of GABAA receptors. GABARAP is located on intracellular membranes like the trans-Golgi network, binding to the γ2 subunit of GABAA receptors. It interacts with microtubules and the N-ethylmaleimide-sensitive factor and is important during autophagosome formation and engulfing of cytosolic cargo into double-membrane vesicles, which leads to degradation upon fusion with lysosomes (Bavro et al., 2002). This interaction could benefit the vector in the clearance of the parasite. Conclusions This study predicted protein interactions that are critical to the survival of Glossina m. morsitans and T. brucei. The interactions could be involved in parasitic cytoskeleton movement, immune response and parasite development in the host. The predicted proteins provide potential therapeutic targets for transmission-blocking vaccines that can be used in the control of trypanosomiasis, with the most promising interaction being T. brucei’s Tubulin alpha and beta chains and Tubulin beta-1 chain from the infected fat body of Glossina m. morsitans, which is known to aid in the parasite’s nutrition in the midgut. Parasitic microtubules are spatially and functionally distributed (Bhargava and Chatterji, 2014). They include nuclear spindle fibers, subpellicular microtubules that play a role in cellular morphology and provide additional stability to the parasite, axonemal tubulin for locomotion of the parasite, and the microtubules that make a network that facilitates transport of molecular cargo. In kinetoplastid parasites like trypanosome species, when the parasite moves from the vector to the host, the cell undergoes morphological and motility changes. This change is facilitated by intracellular cytoskeleton modifications. The microtubules in the conoid are at the core of host cell invasion. They also assist in cell division and gliding motility, which are very important attributes in the invasion of host cells. Tubulin is therefore functionally and structurally an important protein in the infection, replication and invasive stages of T. brucei, making it a potential therapeutic target. Author Biography Eunice Muriithi is pursuing her postgraduate studies in Molecular Biology and Bioinformatics. Her current interest is in proteomics, genomics and computational approaches used in systems biology to study molecular mechanisms that facilitate disease development and transmission, infection and immune responses. Future plans are in doing doctoral studies and research in cancer disease development and immunity. Acknowledgements The authors acknowledge Milcah Wagio Kigoni (International Institute of Tropical Agriculture) for her immense technical assistance during the study. References Atyame Nten , C. 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( 1996 ) ELMICAL PARASITOLOGY Genomic organization and expression of elongation factor-1 cc genes in Trypanosoma brucei , Molecular and Biochemical Parasitology , 79 , 119 – 123 . Google Scholar Crossref Search ADS PubMed WorldCat Rotureau , B. and Van Den Abbeele , J. ( 2013 ) Through the dark continent: African trypanosome development in the tsetse fly , Frontiers in Cellular and Infection Microbiology , 3 ( September ), 53 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Sharma , R. , Gluenz , E., Peacock , L. et al. . ( 2009 ) The heart of darkness: growth and form of _Trypanosoma brucei_ in the tsetse fly , Trends in Parasitology , 25 ( 11 ), 517 – 524 . Google Scholar Crossref Search ADS PubMed WorldCat Weiss , B. L. , Wang , J., Maltz , M. A. et al. . ( 2013 ) Trypanosome infection establishment in the tsetse fly gut is influenced by microbiome-regulated host immune barriers , PLoS Pathogens , 9 ( 4 ), e1003318 . Google Scholar Crossref Search ADS PubMed WorldCat Author notes Supervisors: Johnson Kinyua; Steven Ger Nyanjom © The Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com © The Author(s) 2018. Published by Oxford University Press. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BioScience Horizons Oxford University Press

In silico prediction of protein–protein interaction between Glossina m. morsitans (Westwood, 1851) and Trypanosoma brucei (Kinetoplastida: Trypanosomatidae)

In silico prediction of protein–protein interaction between Glossina m. morsitans (Westwood, 1851) and Trypanosoma brucei (Kinetoplastida: Trypanosomatidae)

BioScience Horizons , Volume 11 – Jan 1, 2018

Abstract

Abstract Trypanosoma brucei is a pathogenic protozoa that causes chronic Human African Trypanosomiasis and African Animal Trypanosomiasis. The pathogenic parasite is transmitted to humans by the tsetse fly, Glossina m. morsitans. Trypanosomiasis control strategies have targeted either the tsetse vector or the parasite. Most of the biological processes in a living cell are controlled by protein–protein interactions (PPI). Prediction of vector host–parasite protein interactions could give an insight into the mechanism of blocking transmission through parasite interference and identify potential vaccine targets. Prediction of protein interactions and orthologous relatedness was done between Glossina m. morsitans (the vector host) and T. brucei (the parasite) using information on conserved orthologous protein interactions in other organisms (interologs). Orthologues from both species were identified using a Markov cluster algorithm of the OrthoMCL software. The Host-Pathogen Interaction Database (HPIDB) and BIANA Interolog Prediction server (BIPS) identified interologs in Glossina m. morsitans and T. brucei. Among the predicted proteins from BIPS were T. brucei tubulin alpha chain, tubulin beta chain, dynein light chain-putative and calmodulin, which were observed to act as hubs connecting to Glossina’s Ubiquitin-40S ribosomal protein S27a fusion protein, dyenin light chain type 1, heat shock protein cognate 3, Gamma-aminobutyric acid receptor-associated protein, putative glycerate kinase and Ribosomal protein S14b. These proteins are implicated in the cellular transportation mechanism of both the vector and the parasite as well as the host defense mechanism. Those predicted from HPIBD were Glossina s-adenosylmethionine synthetase, DNA helicase, ubiquitin protein ligase, AAA+-type ATPase, Rab protein 6, WD40 repeat-containing protein and serine/threonine protein phosphatase, observed to act as hubs connecting to parasitic s-adenosylmethionine synthetase, elongation factor 1-alpha 2, Histone H2A, katanin, lipoic acid synthetase, PolyUbiquitin and serine/threonine protein kinase. This study gives an important insight into the PPI involved in Glossina–Trypanosoma associations that may be involved in the immune response of Glossina m. morsitans and evasion by T. brucei. Some of the interactions may help in the trypanosome’s transformation within the vector host. These observations will give a better understanding of parasite transmission biology and may advance efforts towards transmission-blocking vaccines. Trypanosoma brucei, Glossina m. morsitans, protein–protein interaction, Trypanosomiasis Introduction African trypanosomiasis is caused by trypanosomes. The parasites transmit sleeping sickness to humans and nagana to livestock (Berriman, 2005). Once the infected tsetse fly bites a mammalian host during a blood meal, the host obtains the parasite, which differentiates into procyclic trypomastigotes in the midgut and salivary glands (Sharma et al., 2009). Knowledge of trypanosome propagation in the tsetse vector and the protein interactions that take place in the mammalian host is important in understanding the transmission dynamics of these parasites and identification of potential targets for drug and vaccine development. The trypanosome develops in the tsetse vector by first invading the midgut. This is where it differentiates into procyclic forms. The procyclic forms then move to salivary glands where they transform infective metacyclic trypanosomes found in the salivary gland. It is from the infected salivary glands that they are transmitted to the next mammalian host during a blood meal. During this transformation, the trypanosomes express several proteins within the tsetse fly that are required to invade, survive and become established in the vector (Rotureau and Van Den Abbeele, 2013). Parasitic diseases have been associated with the release of extracellular vesicles (EVs), acting both in parasite–parasite and parasite–host interactions. Extracellular vesicles that are important in the distribution and regulation of the immune system of the host carry as their cargo bioactive molecules such as proteins, DNA, mRNAs and miRNAs. The parasites use these proteins to regulate their targeted cells (Marcilla et al., 2014). In this work, interspecies protein–protein interactions and the proteins’ gene ontology were predicted between the extracellular Trypanosoma brucei parasite and Glossina m. morsitans proteins based on homology, with the assumption that interactions in other organisms are conserved between the target species (interolog mapping). The methodology (Fischer et al., 2011) used in this study, using the OrthoMCL software, has been shown to overcome the challenges that other similar software like INPARANOID and EGO face during eukaryotic ortholog group identification. OrthoMCL uses the Markov Cluster algorithm to identify orthologs in multiple genomes. OrthoMCL employs probability and graph flow theory for global comparison of genomes. The MCL algorithm has been found to be very reliable and fast when comparing complicated domain structures (Li, Stoeckert and Roos, 2003). Biana Interolog Prediction Server (BIPS) and HPIDB are servers in which the user can set the parameters freely for optimal results. The two databases are integrated and contain data from many sources like DIP and IntAct. The two databases give both overlapping and nonredundant HPIs. The results of this study are based on annotations only, with some of the results being affirmed by experimental work done by different authors. The significance of the predicted interactions between T. brucei and Glossina m. morsitans proteins was inferred from the literature indicating their involvement in the parasitic infection as well as manipulation of the host immune mechanism in pathogenesis. Methodology Datasets This study used a dataset consisting of proteins from Glossina m. morsitans and T. brucei downloaded from the National Centre for Biotechnology Information (NCBI), from a combination of all the NCBI source databases (PDB, RefSeq and UniProtKB/Swiss-Prot). The proteins, in FASTA format, were downloaded and sent to a file destination. Obtaining orthologues Linux Operating System commands and OrthoMCL software were used to obtain orthologues from the downloaded vector and parasite proteins (Chen et al., 2006). The protein sequences were filtered by rejecting low-quality sequences that were shorter than 10 amino acids, had more than 20% stop codons and 20% nonstandard amino acids (an amino acid that occurs naturally in cells but does not participate in peptide synthesis). This was sorted by the orthomclFilterFasta program. The sequences were compared to each other to obtain quality sequences using the BLASTp program. MySQL was used to construct a database that was used for querying and constituted all the sequences that were obtained by the orthomclFilterFasta program both for the Glossina m. morsitans and T. brucei proteins, masked with SEG (Fischer et al., 2011) at an E-value cutoff of 1e-5. ‘percent match length’ score was computed for each matching pair of sequences, by counting from the shorter sequences the number of amino acids that participate in any high scoring pairs (HSP), dividing that by the length of the shorter sequence and multiplying by 100. Percent identity was taken from the best HSP per hit. Matches with percent match <50% were filtered out using the orthomclBlastParser program. Sequences from the two FASTA files (Glossina m. morsitans and T. brucei) that were reciprocal best hits (i.e., the first sequence finds the second sequence as its best hit in the second species and vice versa) with the same e-value and bit score were identified as a pair of orthologues using the orthomclPairs program. To ensure correct grouping of the pairs as potential orthologues, co-orthologues and in-paralogs normalization of the e-values was done. Clustering was done using MCL (Li, Stoeckert and Roos, 2003). An inflation value of 1.5 was applied to ensure balance in sensitivity and selectivity of the groups. From the orthologue group, two different orthologue files belonging to T. brucei and Glossina m. morsitans were obtained and the Uniq command was used to detect and remove duplicate entries in the files to produce only unique orthologues. The retrieval of the FASTA sequences of the orthologues was done using BATCH ENREZ either in split or complete form and these were used in the subsequent analysis. The OrthoMCL approach includes ‘recent’ paralogues to the orthologue group. This method works similarly to the INPARANOID approach though it differs in that the ‘recent’ paralogues must be more similar to each other. Protein–protein interaction prediction The Host–Pathogen Interaction Database The The Host–Pathogen Interaction Database (HPIDB) (www.agbase.msstate.edu/hpi/main.html) was used for host–pathogen protein–protein interaction prediction. Searches for homologous host–pathogen interactions were carried out by filling in the two forms on the HPIDB interface. Form A was used to upload pathogen unique orthologue sequences in FASTA format. The output format was set as top hit, and the database to search against was set as ‘All Pathogen proteins’. Blossum62 matrix, an E-value of 0.00001, 50% identity and 50% query coverage filter were applied. Form B was used to upload the host FASTA sequences with top hit output format, and the database to search against was set as ‘All host proteins’. Blossum62 matrix, 70% identity, 70% query coverage and an E-value of 0.00001 were the parameters set for form B. The HPIDB output gave information on the experimental method that was used for interaction detection and also the type of interaction predicted as being either physical association, direct interaction or association. Biana Interolog Prediction Server This database was used as a tool for prediction of protein–protein interactions between Glossina m. morsitans and T. brucei. The unique orthologues of Glossina m. morsitans were split into two files and uploaded. The taxonomy of predicted partner proteins was set as T. brucei. The default homology conditions were applied in the prediction with the Blast E-value of ≤1e-10, joint E-value of ≤1e-10, % identity ≥80, Joint identities ≥80, query sequence coverage ≥80 and template sequence coverage ≥90. All the other filtering parameters were used at the default settings. Functional annotation of the predicted interactions The gene ontology attributes of the interacting proteins were identified using GOSlimviewer tool (http://www.agbase.msstate.edu/cgi-bin/tools/goslimviewer_select.pl). This gave the GO term(s) for molecular function, cellular component and the biological process of the predicted interacting proteins. Results and discussion MCL groups A total of 47 889 proteins belonging to T. brucei and 2832 belonging to Glossina m. morsitans were downloaded from the NCBI. Cleaning of the FASTA sequences resulted in 47 879 and 2832T. brucei and Glossina sequences, respectively. The output from the MCL program was three files of sequences. These were 3456 orthologues, 3734 co-orthologues and 682 715 in-paralogues. The number of unique orthologues obtained from the orthologues file was as follows: 776 from Glossina and 3139 from T. brucei. Predicted T. brucei and Glossina m. morsitans protein interaction A total of 322 interactions were inferred between 126 parasite proteins and 49 vector proteins. The interactions were inferred by HPIDB and BIPS on the basis of similarity of sequences between both the parasite and host proteins. The two prediction servers gave different interactions resulting in a large number of interactions that could be studied further for potential therapeutic development. Most of the predicted interactions were found in salivary glands where the parasite thrives best after overcoming the vector’s defense mechanism in the midgut. The infection and attachment of T. brucei to the tsetse salivary gland epithelium is vital to the life cycle of the parasite as it ensures that the saliva of the tsetse remains infected during its whole lifespan (Matetovici, Caljon and Van Den Abbeele, 2016). OrthoMCL approach This approach identifies recent paralogues by making sure that they are more similar than those sequences from other species. It then includes them in the orthologue group. As compared to the INPARANOID approach, which employs a similar concept, OrthoMCL is more stringent in the identification of the recent paralogues. OrthoMCL does not assume that pairwise comparison is only limited to two species like the INPARANOID approach does. EGO is another approach for identification of recent paralogues, although the lack of true orthologues and multiple orthologues with functional redundancy could easily mislead it in incomplete datasets of genomes. Li, Stoeckert and Roos (2003) have shown successful implementation of OrthoMCL with it being used to perform an all against all comparison of several genome datasets. Functions of predicted interactions Parasites’ nutrition Malaria parasites, trypanosomes and Leishmania are all parasitic protozoa that obtain nutrients from their vector and mammalian hosts by engaging endocytic proteins found in their plasma membranes. Glossina m. morsitans’ S-adenosylmethionine synthetase (ADD19751.1) was predicted to physically associate with isoforms of S-adenosylmethionine synthetase from T. brucei (Table 1). S-adenosylmethionine enzyme is involved in S-adenosine methionine (Adomet) synthesis, which is important as a propylamino donor in polyamine biosynthesis. Polyamines are essential for parasite growth and their biosynthesis has been targeted for drug discovery efforts in T. cruzi and the Trypanosoma brucei parasites (Reguera et al., 2007). In tsetse flies, fat body cells take up alanine from the hemolymph for proline production. Proline plays a role in parasite nutrition in T. brucei infected fat bodies. Trypanosoma brucei’s Tubulin alpha chain (TBA_TRYBR) interaction with Tubulin beta-1 chain from the infected fat body of Glossina m. morsitans (Table 2) is, therefore, an important interaction. L-proline is essential in the growth and development of T. brucei’s procyclic stage as an important source of energy and carbon (Mantilla et al., 2017). During flight, the tsetse uses proline as a carbon source and speculations are that in situ the parasite’s procyclic forms utilize proline (Atyame Nten et al., 2010). Table 1. Predicted interactions from HPIDB Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Open in new tab Table 1. Predicted interactions from HPIDB Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Open in new tab Table 2. Predicted interactions from BIPS Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Open in new tab Table 2. Predicted interactions from BIPS Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Open in new tab Parasitic DNA repair, growth and survival Isoforms of DNA helicase (ADD20025.1 and ADD19284.1) from Glossina m.morsitans were predicted to associate with both the isoforms of Elongation factor 1-alpha and Histone H2A from T. brucei (Table 1). Glossina m. morsitans DNA helicase isoforms’ interaction with the isoforms of elongation factor 1(EF-1) -alpha and H2A from T. brucei may infer an association solely either within the parasite or within the vector and not an association between the parasite and vector. These proteins are nuclear proteins. The nuclei of Glossina m. morsitans and T. brucei are separate entities. As T. brucei is an extracellular parasite such interaction is physiologically impossible as nuclear proteins do not exchange over long distances with the nuclei of other species. This intraspecies interaction, therefore, may be implicated in the replication, repair and reorganization of the kDNA in the parasite. The reactive oxygen species in the vector’s midgut lead to lethal double-strand breaks (DSBs) in the parasite’s DNA. It is important for a cell to be able to detect and initiate the repair of DSBs in DNA. DNA damage causes the phosphorylation of histone H2A at the Ser129 position. Phosphorylation enables cell survival in DNA DSB-causing agents (Downs et al., 2004). The trypanosomes’ mitochondrial kinetoplast DNA (kDNA) at the base of the motile flagellum in T. brucei is associated with DNA helicases, DNA polymerases, DNA ligases and topoisomerases that play a major role in the replication and reassembly of the kDNA into a network during cell division (Beck et al., 2013). EF-l alpha bundles and severs microtubule and actin filaments during cell division (Ridgley et al., 1996), which is important for the parasite’s protein synthesis, cell growth and motility. Glossina m. morsitans’ AAA+-type ATPase (ADD18768.1) direct interaction prediction with isoforms of katanin, lipoic acid synthetase and lipopyl synthase of T. brucei (Table 1) may also be important in microtubule (MT) severing during the parasite’s cell division mediated by ATP-driven katanin, an AAA+ family protein (Johjima et al., 2015). Lipoic acid synthase (LASY) is the enzyme involved in the synthesis of lipoic acid, which is a potent mitochondrial antioxidant and could be important to T. brucei procyclic cells in antioxidation of excessive amounts of reactive oxygen species (ROS) (Padmalayam et al., 2009). Calmodulin (Q382N3_9TRYP), from T. brucei, was predicted to interact with Glossina m.morsitans multifunctional chaperone, calmodulin and Casein kinase II alpha subunit (Table 2). Trypanosoma brucei induces upregulation of the host protein, Ca2+/calmodulin-dependent protein kinase (CaMK), which is among the stage-specific regulators of morphological differentiation of Plasmodium, Trypanosoma and Leishmania parasites (Kariithi et al., 2016). Parasite’s defense mechanism SUMO-conjugating enzyme, parasitic ubiquitin-conjugating enzyme and the actin family are implicated in the parasite’s survival. Kariithi et al. (2016) reported that one of the parasite’s survival tactics is to alter the binding partners, locations and/or functions of specific proteins and to antagonize other protein modifications. Sumoylation is a posttranslational modification mediated by SUMO protein and is one of the quickest ways of achieving these changes. SUMO-conjugating enzymes (ADD18803.1 and ADD18802.1) from Glossina m. morsitans were predicted to physically associate with Vacuolar ATP synthase, the Ubiquitin-conjugating enzyme and the Actin family (ActinA, ActinB, Actin1, and Actin2) of T. brucei (Table 1). Trypanosoma brucei may benefit from this interaction by using the sumoylation mechanism synergy mediated by the vector’s SUMO-conjugating enzyme and its own ubiquitin-conjugating enzyme to modify the behavior of vector proteins that are produced during the immune response. Sumoylation could affect the ability of Glossina immune response proteins to interact with those of T. brucei, hence killing it. Ubiquitin plays a role in the formation of endocytosis/exosome and as a sorting signal during endocytosis and early endosomal protein trafficking (Geiger et al., 2010). Padmalayam et al. (2009) reported that actin plays an important role in vesicular endocytosis, which could be implicated in the transportation and degradation process of ubiquitin-conjugated proteins in the parasite. Baker et al. (2015) showed that Vacuolar ATP synthase (V-ATPase) catalyzes ATP hydrolysis to enable transport of solutes and lower pH of lysosomes, which may be used in the degradation of sumoylated vector proteins. Dynein light chain-putative (Q4FKD8_9TRYP) from T. brucei was predicted to interact with Glossina m. morsitans’ microtubule-binding protein, Dynein light chain-type 1, Actin 87E, Actin 5C, Actin 57B, Putative glycerate kinase, Tubulin beta chain, Tubulin alpha chain, Ribosomal protein S14b and Tubulin beta-1 chain from the infected fat body (Table 2). Daher et al. (2010) demonstrated the involvement of Dynein light chain 1 (LC1) in the control of flagellar motility in Trypanosoma brucei and Chlamydomonas reinhardtii by interacting with the dynein γ heavy chain. Molecular motors involving myosin, kinesin and dynein complexes facilitate the motility/mobility and the transport of proteins and vesicles in eukaryotic cells. These motor proteins are ATP-driven, converting chemical energy into mechanical work. Glycerate kinase is involved in the energy production required by the motor proteins. Vesicle trafficking by the parasite is dependent on this interaction that aids the parasite survival. Glossina m. morsitans immune response The fat body is the major immune organ in the vector’s immune response, with other effector molecules that are expressed in the midgut increasingly becoming recognized as playing a role in immune reactions. WD40 repeat-containing protein (ADD20373.1) and ubiquitin protein ligase (ADD20484.1) from Glossina m. morsitans were predicted to directly interact with PolyUbiquitin from T. brucei (Table 1). Weiss et al. (2013) reported the involvement of WD40 repeat proteins in cellular processes like regulation of vesicle formation, transcriptional regulation, vesicular trafficking, RNA processing and control of cell division. Recruitment of the ubiquitin-conjugating enzyme (E2) by ubiquitin ligase (E3) leads to the transfer of ubiquitin to target proteins, aiding their degradation in the proteosome. This interaction may be important to Glossina m.morsitans in that it is able to control the parasites’ cell trafficking, DNA repair and cell cycle. This could also be important in the vector’s refractoriness to the parasite. Serine/threonine protein phosphatase (ADD20508.1) from Glossina m.morsitans was predicted to have a direct interaction with serine/threonine protein kinase from T. brucei (Table 1). Serine/threonine protein kinases function by phosphorylation of serine and threonine amino acids in T. brucei. Protein kinases regulate different cellular processes such as cell cycle progression, transcriptional control and differentiation in trypanosomes (Naula, Parsons and Mottram, 2005). Serine/threonine phosphatases on the other hand reverse the action of protein kinases, leading to programmed cell death (apoptosis). This interaction could assist the vector’s attempt to clear the parasite. Trypanosoma brucei’s tubulin alpha chain (TBA_TRYBR) was predicted to interact with eight proteins from the salivary gland (Actin 57B, Actin5C, ATP synthase subunit alpha, Tubulin beta chain, Ubiquitin/40S ribosomal protein S27a fusion protein, Actin 87E, Dynein light chain-type 1 and GTP-binding nuclear protein) (Table 2). Tubulin beta chain (TBB_TRYBR) from Trypanosoma brucei was also predicted to interact with 14 proteins from the salivary gland of the vector–host Glossina m. morsitans. The proteins include the Ribosomal protein S3, Heat shock protein cognate 3, Gamma-aminobutyric acid receptor-associated protein, ADP/ATP translocase, Actin 57B, Actin 5C, ATP synthase subunit alpha, Ubiquitin-40S ribosomal protein S27a fusion protein, Actin 87E, Dynein light chain-type 1, putative glycerate kinase, tubulin beta chain, tubulin alpha chain and tubulin beta-1 chain from the infected fat body. Matetovici, Caljon and Van Den Abbeele (2016) showed that Actin 5C functions as an extracellular pathogen recognition factor in A. gambiae, being involved in antibacterial defense by interaction with the extracellular immune factor AgMDL1. Actin functions as a Plasmodium antagonist and limits parasite infection in the gut. α-tubulin and β-tubulin-1 overexpression are induced by the presence of the T. brucei parasites in the salivary glands. HSP cognate 3 from Glossina m. morsitans was predicted to interact with tubulin beta chain (TBB_TRYBR) from T. brucei (Table 2). Hsp or stress proteins are usually overexpressed due to thermal stress, environmental insults or trauma (Mattson et al., 2004). Parasitic tubulin beta chain (TBB_TRYBR) was also predicted to interact with the vector’s gamma-aminobutyric acid receptor-associated protein (GABARAP) (Table 2), which is involved in autophagy mediated by the autophagosome. GABARAP is a member of the intracellular membrane trafficking and/or fusion protein family and is implicated in plasma membrane targeting and/or recycling of GABAA receptors. GABARAP is located on intracellular membranes like the trans-Golgi network, binding to the γ2 subunit of GABAA receptors. It interacts with microtubules and the N-ethylmaleimide-sensitive factor and is important during autophagosome formation and engulfing of cytosolic cargo into double-membrane vesicles, which leads to degradation upon fusion with lysosomes (Bavro et al., 2002). This interaction could benefit the vector in the clearance of the parasite. Conclusions This study predicted protein interactions that are critical to the survival of Glossina m. morsitans and T. brucei. The interactions could be involved in parasitic cytoskeleton movement, immune response and parasite development in the host. The predicted proteins provide potential therapeutic targets for transmission-blocking vaccines that can be used in the control of trypanosomiasis, with the most promising interaction being T. brucei’s Tubulin alpha and beta chains and Tubulin beta-1 chain from the infected fat body of Glossina m. morsitans, which is known to aid in the parasite’s nutrition in the midgut. Parasitic microtubules are spatially and functionally distributed (Bhargava and Chatterji, 2014). They include nuclear spindle fibers, subpellicular microtubules that play a role in cellular morphology and provide additional stability to the parasite, axonemal tubulin for locomotion of the parasite, and the microtubules that make a network that facilitates transport of molecular cargo. In kinetoplastid parasites like trypanosome species, when the parasite moves from the vector to the host, the cell undergoes morphological and motility changes. This change is facilitated by intracellular cytoskeleton modifications. The microtubules in the conoid are at the core of host cell invasion. They also assist in cell division and gliding motility, which are very important attributes in the invasion of host cells. Tubulin is therefore functionally and structurally an important protein in the infection, replication and invasive stages of T. brucei, making it a potential therapeutic target. Author Biography Eunice Muriithi is pursuing her postgraduate studies in Molecular Biology and Bioinformatics. Her current interest is in proteomics, genomics and computational approaches used in systems biology to study molecular mechanisms that facilitate disease development and transmission, infection and immune responses. Future plans are in doing doctoral studies and research in cancer disease development and immunity. Acknowledgements The authors acknowledge Milcah Wagio Kigoni (International Institute of Tropical Agriculture) for her immense technical assistance during the study. References Atyame Nten , C. 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Google Scholar Crossref Search ADS PubMed WorldCat Author notes Supervisors: Johnson Kinyua; Steven Ger Nyanjom © The Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com © The Author(s) 2018. Published by Oxford University Press.

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Abstract

Abstract Trypanosoma brucei is a pathogenic protozoa that causes chronic Human African Trypanosomiasis and African Animal Trypanosomiasis. The pathogenic parasite is transmitted to humans by the tsetse fly, Glossina m. morsitans. Trypanosomiasis control strategies have targeted either the tsetse vector or the parasite. Most of the biological processes in a living cell are controlled by protein–protein interactions (PPI). Prediction of vector host–parasite protein interactions could give an insight into the mechanism of blocking transmission through parasite interference and identify potential vaccine targets. Prediction of protein interactions and orthologous relatedness was done between Glossina m. morsitans (the vector host) and T. brucei (the parasite) using information on conserved orthologous protein interactions in other organisms (interologs). Orthologues from both species were identified using a Markov cluster algorithm of the OrthoMCL software. The Host-Pathogen Interaction Database (HPIDB) and BIANA Interolog Prediction server (BIPS) identified interologs in Glossina m. morsitans and T. brucei. Among the predicted proteins from BIPS were T. brucei tubulin alpha chain, tubulin beta chain, dynein light chain-putative and calmodulin, which were observed to act as hubs connecting to Glossina’s Ubiquitin-40S ribosomal protein S27a fusion protein, dyenin light chain type 1, heat shock protein cognate 3, Gamma-aminobutyric acid receptor-associated protein, putative glycerate kinase and Ribosomal protein S14b. These proteins are implicated in the cellular transportation mechanism of both the vector and the parasite as well as the host defense mechanism. Those predicted from HPIBD were Glossina s-adenosylmethionine synthetase, DNA helicase, ubiquitin protein ligase, AAA+-type ATPase, Rab protein 6, WD40 repeat-containing protein and serine/threonine protein phosphatase, observed to act as hubs connecting to parasitic s-adenosylmethionine synthetase, elongation factor 1-alpha 2, Histone H2A, katanin, lipoic acid synthetase, PolyUbiquitin and serine/threonine protein kinase. This study gives an important insight into the PPI involved in Glossina–Trypanosoma associations that may be involved in the immune response of Glossina m. morsitans and evasion by T. brucei. Some of the interactions may help in the trypanosome’s transformation within the vector host. These observations will give a better understanding of parasite transmission biology and may advance efforts towards transmission-blocking vaccines. Trypanosoma brucei, Glossina m. morsitans, protein–protein interaction, Trypanosomiasis Introduction African trypanosomiasis is caused by trypanosomes. The parasites transmit sleeping sickness to humans and nagana to livestock (Berriman, 2005). Once the infected tsetse fly bites a mammalian host during a blood meal, the host obtains the parasite, which differentiates into procyclic trypomastigotes in the midgut and salivary glands (Sharma et al., 2009). Knowledge of trypanosome propagation in the tsetse vector and the protein interactions that take place in the mammalian host is important in understanding the transmission dynamics of these parasites and identification of potential targets for drug and vaccine development. The trypanosome develops in the tsetse vector by first invading the midgut. This is where it differentiates into procyclic forms. The procyclic forms then move to salivary glands where they transform infective metacyclic trypanosomes found in the salivary gland. It is from the infected salivary glands that they are transmitted to the next mammalian host during a blood meal. During this transformation, the trypanosomes express several proteins within the tsetse fly that are required to invade, survive and become established in the vector (Rotureau and Van Den Abbeele, 2013). Parasitic diseases have been associated with the release of extracellular vesicles (EVs), acting both in parasite–parasite and parasite–host interactions. Extracellular vesicles that are important in the distribution and regulation of the immune system of the host carry as their cargo bioactive molecules such as proteins, DNA, mRNAs and miRNAs. The parasites use these proteins to regulate their targeted cells (Marcilla et al., 2014). In this work, interspecies protein–protein interactions and the proteins’ gene ontology were predicted between the extracellular Trypanosoma brucei parasite and Glossina m. morsitans proteins based on homology, with the assumption that interactions in other organisms are conserved between the target species (interolog mapping). The methodology (Fischer et al., 2011) used in this study, using the OrthoMCL software, has been shown to overcome the challenges that other similar software like INPARANOID and EGO face during eukaryotic ortholog group identification. OrthoMCL uses the Markov Cluster algorithm to identify orthologs in multiple genomes. OrthoMCL employs probability and graph flow theory for global comparison of genomes. The MCL algorithm has been found to be very reliable and fast when comparing complicated domain structures (Li, Stoeckert and Roos, 2003). Biana Interolog Prediction Server (BIPS) and HPIDB are servers in which the user can set the parameters freely for optimal results. The two databases are integrated and contain data from many sources like DIP and IntAct. The two databases give both overlapping and nonredundant HPIs. The results of this study are based on annotations only, with some of the results being affirmed by experimental work done by different authors. The significance of the predicted interactions between T. brucei and Glossina m. morsitans proteins was inferred from the literature indicating their involvement in the parasitic infection as well as manipulation of the host immune mechanism in pathogenesis. Methodology Datasets This study used a dataset consisting of proteins from Glossina m. morsitans and T. brucei downloaded from the National Centre for Biotechnology Information (NCBI), from a combination of all the NCBI source databases (PDB, RefSeq and UniProtKB/Swiss-Prot). The proteins, in FASTA format, were downloaded and sent to a file destination. Obtaining orthologues Linux Operating System commands and OrthoMCL software were used to obtain orthologues from the downloaded vector and parasite proteins (Chen et al., 2006). The protein sequences were filtered by rejecting low-quality sequences that were shorter than 10 amino acids, had more than 20% stop codons and 20% nonstandard amino acids (an amino acid that occurs naturally in cells but does not participate in peptide synthesis). This was sorted by the orthomclFilterFasta program. The sequences were compared to each other to obtain quality sequences using the BLASTp program. MySQL was used to construct a database that was used for querying and constituted all the sequences that were obtained by the orthomclFilterFasta program both for the Glossina m. morsitans and T. brucei proteins, masked with SEG (Fischer et al., 2011) at an E-value cutoff of 1e-5. ‘percent match length’ score was computed for each matching pair of sequences, by counting from the shorter sequences the number of amino acids that participate in any high scoring pairs (HSP), dividing that by the length of the shorter sequence and multiplying by 100. Percent identity was taken from the best HSP per hit. Matches with percent match <50% were filtered out using the orthomclBlastParser program. Sequences from the two FASTA files (Glossina m. morsitans and T. brucei) that were reciprocal best hits (i.e., the first sequence finds the second sequence as its best hit in the second species and vice versa) with the same e-value and bit score were identified as a pair of orthologues using the orthomclPairs program. To ensure correct grouping of the pairs as potential orthologues, co-orthologues and in-paralogs normalization of the e-values was done. Clustering was done using MCL (Li, Stoeckert and Roos, 2003). An inflation value of 1.5 was applied to ensure balance in sensitivity and selectivity of the groups. From the orthologue group, two different orthologue files belonging to T. brucei and Glossina m. morsitans were obtained and the Uniq command was used to detect and remove duplicate entries in the files to produce only unique orthologues. The retrieval of the FASTA sequences of the orthologues was done using BATCH ENREZ either in split or complete form and these were used in the subsequent analysis. The OrthoMCL approach includes ‘recent’ paralogues to the orthologue group. This method works similarly to the INPARANOID approach though it differs in that the ‘recent’ paralogues must be more similar to each other. Protein–protein interaction prediction The Host–Pathogen Interaction Database The The Host–Pathogen Interaction Database (HPIDB) (www.agbase.msstate.edu/hpi/main.html) was used for host–pathogen protein–protein interaction prediction. Searches for homologous host–pathogen interactions were carried out by filling in the two forms on the HPIDB interface. Form A was used to upload pathogen unique orthologue sequences in FASTA format. The output format was set as top hit, and the database to search against was set as ‘All Pathogen proteins’. Blossum62 matrix, an E-value of 0.00001, 50% identity and 50% query coverage filter were applied. Form B was used to upload the host FASTA sequences with top hit output format, and the database to search against was set as ‘All host proteins’. Blossum62 matrix, 70% identity, 70% query coverage and an E-value of 0.00001 were the parameters set for form B. The HPIDB output gave information on the experimental method that was used for interaction detection and also the type of interaction predicted as being either physical association, direct interaction or association. Biana Interolog Prediction Server This database was used as a tool for prediction of protein–protein interactions between Glossina m. morsitans and T. brucei. The unique orthologues of Glossina m. morsitans were split into two files and uploaded. The taxonomy of predicted partner proteins was set as T. brucei. The default homology conditions were applied in the prediction with the Blast E-value of ≤1e-10, joint E-value of ≤1e-10, % identity ≥80, Joint identities ≥80, query sequence coverage ≥80 and template sequence coverage ≥90. All the other filtering parameters were used at the default settings. Functional annotation of the predicted interactions The gene ontology attributes of the interacting proteins were identified using GOSlimviewer tool (http://www.agbase.msstate.edu/cgi-bin/tools/goslimviewer_select.pl). This gave the GO term(s) for molecular function, cellular component and the biological process of the predicted interacting proteins. Results and discussion MCL groups A total of 47 889 proteins belonging to T. brucei and 2832 belonging to Glossina m. morsitans were downloaded from the NCBI. Cleaning of the FASTA sequences resulted in 47 879 and 2832T. brucei and Glossina sequences, respectively. The output from the MCL program was three files of sequences. These were 3456 orthologues, 3734 co-orthologues and 682 715 in-paralogues. The number of unique orthologues obtained from the orthologues file was as follows: 776 from Glossina and 3139 from T. brucei. Predicted T. brucei and Glossina m. morsitans protein interaction A total of 322 interactions were inferred between 126 parasite proteins and 49 vector proteins. The interactions were inferred by HPIDB and BIPS on the basis of similarity of sequences between both the parasite and host proteins. The two prediction servers gave different interactions resulting in a large number of interactions that could be studied further for potential therapeutic development. Most of the predicted interactions were found in salivary glands where the parasite thrives best after overcoming the vector’s defense mechanism in the midgut. The infection and attachment of T. brucei to the tsetse salivary gland epithelium is vital to the life cycle of the parasite as it ensures that the saliva of the tsetse remains infected during its whole lifespan (Matetovici, Caljon and Van Den Abbeele, 2016). OrthoMCL approach This approach identifies recent paralogues by making sure that they are more similar than those sequences from other species. It then includes them in the orthologue group. As compared to the INPARANOID approach, which employs a similar concept, OrthoMCL is more stringent in the identification of the recent paralogues. OrthoMCL does not assume that pairwise comparison is only limited to two species like the INPARANOID approach does. EGO is another approach for identification of recent paralogues, although the lack of true orthologues and multiple orthologues with functional redundancy could easily mislead it in incomplete datasets of genomes. Li, Stoeckert and Roos (2003) have shown successful implementation of OrthoMCL with it being used to perform an all against all comparison of several genome datasets. Functions of predicted interactions Parasites’ nutrition Malaria parasites, trypanosomes and Leishmania are all parasitic protozoa that obtain nutrients from their vector and mammalian hosts by engaging endocytic proteins found in their plasma membranes. Glossina m. morsitans’ S-adenosylmethionine synthetase (ADD19751.1) was predicted to physically associate with isoforms of S-adenosylmethionine synthetase from T. brucei (Table 1). S-adenosylmethionine enzyme is involved in S-adenosine methionine (Adomet) synthesis, which is important as a propylamino donor in polyamine biosynthesis. Polyamines are essential for parasite growth and their biosynthesis has been targeted for drug discovery efforts in T. cruzi and the Trypanosoma brucei parasites (Reguera et al., 2007). In tsetse flies, fat body cells take up alanine from the hemolymph for proline production. Proline plays a role in parasite nutrition in T. brucei infected fat bodies. Trypanosoma brucei’s Tubulin alpha chain (TBA_TRYBR) interaction with Tubulin beta-1 chain from the infected fat body of Glossina m. morsitans (Table 2) is, therefore, an important interaction. L-proline is essential in the growth and development of T. brucei’s procyclic stage as an important source of energy and carbon (Mantilla et al., 2017). During flight, the tsetse uses proline as a carbon source and speculations are that in situ the parasite’s procyclic forms utilize proline (Atyame Nten et al., 2010). Table 1. Predicted interactions from HPIDB Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Open in new tab Table 1. Predicted interactions from HPIDB Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Vector protein . Tissue localization . Description . Interacting parasite protein . Description . Type of interaction . ADD19751.1 Salivary gland s-adenosylmethionine synthetase AAX80290.1 s-adenosylmethionine synthetase Physical association ADD20025.1 Salivary gland DNA helicase XP_011777437.1 Elongation factor 1-alpha 2 Association XP_846259.1 Histone H2A Association ADD18803.1 Salivary gland SUMO-conjugating enzyme XP_011776680.1 Actin Physical association XP_822280.1 Vacuolar ATP synthase Physical association XP_951548.1 Ubiquitin-conjugating enzyme Direct interaction ADD18768.1 Salivary gland AAA+-type ATPase AAZ10362.1 Katanin Direct interaction CBH16724.1 Lipoic acid synthetase Direct interaction ADD20484.1 Salivary gland ubiquitin protein ligase EAN79944.1 PolyUbiquitin Direct interaction ADD20373.1 Salivary gland WD40 repeat-containing protein EAN79944.1 PolyUbiquitin Direct interaction ADD20508.1 Salivary gland serine/threonine protein phosphatase AAX80677.1 Serine/threonine protein kinase Direct interaction Open in new tab Table 2. Predicted interactions from BIPS Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Open in new tab Table 2. Predicted interactions from BIPS Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Parasite protein . Description . Interacting vector protein . Tissue localization . Description . TBA_TRYBR Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19407.1 Salivary gland Tubulin beta chain ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD18812.1 Salivary gland GTP-binding nuclear protein TBB_TRYBR Tubulin beta chain ADD20422.1 Salivary gland Ribosomal protein S3 ADD20300.1 Salivary gland Heat shock protein cognate 3 ADD18723.1 Salivary gland Gamma-aminobutyric acid receptor-associated protein ADD19328.1 Salivary gland ADP/ATP translocase ADD19431.1 Salivary gland Actin 57B ADD19978.1 Salivary gland Actin 5C ADD20170.1 Salivary gland ATP synthase subunit alpha ADD19064.1 Salivary gland Ubiquitin/40S ribosomal protein S27a fusion protein ADD19714.1 Salivary gland Actin 87E ADD20179.1 Salivary gland Dynein light chain type 1 ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD19945.1 Salivary gland Tubulin alpha chain ABD60995.1 Infected fat body Tubulin beta-1 chain Q4FKD8_9TRYP Dynein light chain, putative ADD19302.1 Salivary gland Microtubule-binding protein ADD20179.1 Salivary gland Dynein light chain type 1 ADD19714.1 Salivary gland Actin 87E ADD19978.1 Salivary gland Actin 5C ADD19431.1 Salivary gland Actin 57B ADD19886.1 Salivary gland Putative glycerate kinase ADD19407.1 Salivary gland Tubulin beta chain ADD20158.1 Salivary gland Tubulin beta chain ABD60995.1 Infected fat body Tubulin beta-1 chain ADD19945.1 Salivary gland Tubulin alpha chain ADD19428.1 Salivary gland Ribosomal protein S14b Q382N3_9TRYP Calmodulin ADD20369.1 Salivary gland Multifunctional chaperone ADD19704.1 Salivary gland Calmodulin ADD18484.1 Salivary gland Casein kinase II alpha subunit Open in new tab Parasitic DNA repair, growth and survival Isoforms of DNA helicase (ADD20025.1 and ADD19284.1) from Glossina m.morsitans were predicted to associate with both the isoforms of Elongation factor 1-alpha and Histone H2A from T. brucei (Table 1). Glossina m. morsitans DNA helicase isoforms’ interaction with the isoforms of elongation factor 1(EF-1) -alpha and H2A from T. brucei may infer an association solely either within the parasite or within the vector and not an association between the parasite and vector. These proteins are nuclear proteins. The nuclei of Glossina m. morsitans and T. brucei are separate entities. As T. brucei is an extracellular parasite such interaction is physiologically impossible as nuclear proteins do not exchange over long distances with the nuclei of other species. This intraspecies interaction, therefore, may be implicated in the replication, repair and reorganization of the kDNA in the parasite. The reactive oxygen species in the vector’s midgut lead to lethal double-strand breaks (DSBs) in the parasite’s DNA. It is important for a cell to be able to detect and initiate the repair of DSBs in DNA. DNA damage causes the phosphorylation of histone H2A at the Ser129 position. Phosphorylation enables cell survival in DNA DSB-causing agents (Downs et al., 2004). The trypanosomes’ mitochondrial kinetoplast DNA (kDNA) at the base of the motile flagellum in T. brucei is associated with DNA helicases, DNA polymerases, DNA ligases and topoisomerases that play a major role in the replication and reassembly of the kDNA into a network during cell division (Beck et al., 2013). EF-l alpha bundles and severs microtubule and actin filaments during cell division (Ridgley et al., 1996), which is important for the parasite’s protein synthesis, cell growth and motility. Glossina m. morsitans’ AAA+-type ATPase (ADD18768.1) direct interaction prediction with isoforms of katanin, lipoic acid synthetase and lipopyl synthase of T. brucei (Table 1) may also be important in microtubule (MT) severing during the parasite’s cell division mediated by ATP-driven katanin, an AAA+ family protein (Johjima et al., 2015). Lipoic acid synthase (LASY) is the enzyme involved in the synthesis of lipoic acid, which is a potent mitochondrial antioxidant and could be important to T. brucei procyclic cells in antioxidation of excessive amounts of reactive oxygen species (ROS) (Padmalayam et al., 2009). Calmodulin (Q382N3_9TRYP), from T. brucei, was predicted to interact with Glossina m.morsitans multifunctional chaperone, calmodulin and Casein kinase II alpha subunit (Table 2). Trypanosoma brucei induces upregulation of the host protein, Ca2+/calmodulin-dependent protein kinase (CaMK), which is among the stage-specific regulators of morphological differentiation of Plasmodium, Trypanosoma and Leishmania parasites (Kariithi et al., 2016). Parasite’s defense mechanism SUMO-conjugating enzyme, parasitic ubiquitin-conjugating enzyme and the actin family are implicated in the parasite’s survival. Kariithi et al. (2016) reported that one of the parasite’s survival tactics is to alter the binding partners, locations and/or functions of specific proteins and to antagonize other protein modifications. Sumoylation is a posttranslational modification mediated by SUMO protein and is one of the quickest ways of achieving these changes. SUMO-conjugating enzymes (ADD18803.1 and ADD18802.1) from Glossina m. morsitans were predicted to physically associate with Vacuolar ATP synthase, the Ubiquitin-conjugating enzyme and the Actin family (ActinA, ActinB, Actin1, and Actin2) of T. brucei (Table 1). Trypanosoma brucei may benefit from this interaction by using the sumoylation mechanism synergy mediated by the vector’s SUMO-conjugating enzyme and its own ubiquitin-conjugating enzyme to modify the behavior of vector proteins that are produced during the immune response. Sumoylation could affect the ability of Glossina immune response proteins to interact with those of T. brucei, hence killing it. Ubiquitin plays a role in the formation of endocytosis/exosome and as a sorting signal during endocytosis and early endosomal protein trafficking (Geiger et al., 2010). Padmalayam et al. (2009) reported that actin plays an important role in vesicular endocytosis, which could be implicated in the transportation and degradation process of ubiquitin-conjugated proteins in the parasite. Baker et al. (2015) showed that Vacuolar ATP synthase (V-ATPase) catalyzes ATP hydrolysis to enable transport of solutes and lower pH of lysosomes, which may be used in the degradation of sumoylated vector proteins. Dynein light chain-putative (Q4FKD8_9TRYP) from T. brucei was predicted to interact with Glossina m. morsitans’ microtubule-binding protein, Dynein light chain-type 1, Actin 87E, Actin 5C, Actin 57B, Putative glycerate kinase, Tubulin beta chain, Tubulin alpha chain, Ribosomal protein S14b and Tubulin beta-1 chain from the infected fat body (Table 2). Daher et al. (2010) demonstrated the involvement of Dynein light chain 1 (LC1) in the control of flagellar motility in Trypanosoma brucei and Chlamydomonas reinhardtii by interacting with the dynein γ heavy chain. Molecular motors involving myosin, kinesin and dynein complexes facilitate the motility/mobility and the transport of proteins and vesicles in eukaryotic cells. These motor proteins are ATP-driven, converting chemical energy into mechanical work. Glycerate kinase is involved in the energy production required by the motor proteins. Vesicle trafficking by the parasite is dependent on this interaction that aids the parasite survival. Glossina m. morsitans immune response The fat body is the major immune organ in the vector’s immune response, with other effector molecules that are expressed in the midgut increasingly becoming recognized as playing a role in immune reactions. WD40 repeat-containing protein (ADD20373.1) and ubiquitin protein ligase (ADD20484.1) from Glossina m. morsitans were predicted to directly interact with PolyUbiquitin from T. brucei (Table 1). Weiss et al. (2013) reported the involvement of WD40 repeat proteins in cellular processes like regulation of vesicle formation, transcriptional regulation, vesicular trafficking, RNA processing and control of cell division. Recruitment of the ubiquitin-conjugating enzyme (E2) by ubiquitin ligase (E3) leads to the transfer of ubiquitin to target proteins, aiding their degradation in the proteosome. This interaction may be important to Glossina m.morsitans in that it is able to control the parasites’ cell trafficking, DNA repair and cell cycle. This could also be important in the vector’s refractoriness to the parasite. Serine/threonine protein phosphatase (ADD20508.1) from Glossina m.morsitans was predicted to have a direct interaction with serine/threonine protein kinase from T. brucei (Table 1). Serine/threonine protein kinases function by phosphorylation of serine and threonine amino acids in T. brucei. Protein kinases regulate different cellular processes such as cell cycle progression, transcriptional control and differentiation in trypanosomes (Naula, Parsons and Mottram, 2005). Serine/threonine phosphatases on the other hand reverse the action of protein kinases, leading to programmed cell death (apoptosis). This interaction could assist the vector’s attempt to clear the parasite. Trypanosoma brucei’s tubulin alpha chain (TBA_TRYBR) was predicted to interact with eight proteins from the salivary gland (Actin 57B, Actin5C, ATP synthase subunit alpha, Tubulin beta chain, Ubiquitin/40S ribosomal protein S27a fusion protein, Actin 87E, Dynein light chain-type 1 and GTP-binding nuclear protein) (Table 2). Tubulin beta chain (TBB_TRYBR) from Trypanosoma brucei was also predicted to interact with 14 proteins from the salivary gland of the vector–host Glossina m. morsitans. The proteins include the Ribosomal protein S3, Heat shock protein cognate 3, Gamma-aminobutyric acid receptor-associated protein, ADP/ATP translocase, Actin 57B, Actin 5C, ATP synthase subunit alpha, Ubiquitin-40S ribosomal protein S27a fusion protein, Actin 87E, Dynein light chain-type 1, putative glycerate kinase, tubulin beta chain, tubulin alpha chain and tubulin beta-1 chain from the infected fat body. Matetovici, Caljon and Van Den Abbeele (2016) showed that Actin 5C functions as an extracellular pathogen recognition factor in A. gambiae, being involved in antibacterial defense by interaction with the extracellular immune factor AgMDL1. Actin functions as a Plasmodium antagonist and limits parasite infection in the gut. α-tubulin and β-tubulin-1 overexpression are induced by the presence of the T. brucei parasites in the salivary glands. HSP cognate 3 from Glossina m. morsitans was predicted to interact with tubulin beta chain (TBB_TRYBR) from T. brucei (Table 2). Hsp or stress proteins are usually overexpressed due to thermal stress, environmental insults or trauma (Mattson et al., 2004). Parasitic tubulin beta chain (TBB_TRYBR) was also predicted to interact with the vector’s gamma-aminobutyric acid receptor-associated protein (GABARAP) (Table 2), which is involved in autophagy mediated by the autophagosome. GABARAP is a member of the intracellular membrane trafficking and/or fusion protein family and is implicated in plasma membrane targeting and/or recycling of GABAA receptors. GABARAP is located on intracellular membranes like the trans-Golgi network, binding to the γ2 subunit of GABAA receptors. It interacts with microtubules and the N-ethylmaleimide-sensitive factor and is important during autophagosome formation and engulfing of cytosolic cargo into double-membrane vesicles, which leads to degradation upon fusion with lysosomes (Bavro et al., 2002). This interaction could benefit the vector in the clearance of the parasite. Conclusions This study predicted protein interactions that are critical to the survival of Glossina m. morsitans and T. brucei. The interactions could be involved in parasitic cytoskeleton movement, immune response and parasite development in the host. The predicted proteins provide potential therapeutic targets for transmission-blocking vaccines that can be used in the control of trypanosomiasis, with the most promising interaction being T. brucei’s Tubulin alpha and beta chains and Tubulin beta-1 chain from the infected fat body of Glossina m. morsitans, which is known to aid in the parasite’s nutrition in the midgut. Parasitic microtubules are spatially and functionally distributed (Bhargava and Chatterji, 2014). They include nuclear spindle fibers, subpellicular microtubules that play a role in cellular morphology and provide additional stability to the parasite, axonemal tubulin for locomotion of the parasite, and the microtubules that make a network that facilitates transport of molecular cargo. In kinetoplastid parasites like trypanosome species, when the parasite moves from the vector to the host, the cell undergoes morphological and motility changes. This change is facilitated by intracellular cytoskeleton modifications. The microtubules in the conoid are at the core of host cell invasion. They also assist in cell division and gliding motility, which are very important attributes in the invasion of host cells. Tubulin is therefore functionally and structurally an important protein in the infection, replication and invasive stages of T. brucei, making it a potential therapeutic target. Author Biography Eunice Muriithi is pursuing her postgraduate studies in Molecular Biology and Bioinformatics. Her current interest is in proteomics, genomics and computational approaches used in systems biology to study molecular mechanisms that facilitate disease development and transmission, infection and immune responses. Future plans are in doing doctoral studies and research in cancer disease development and immunity. Acknowledgements The authors acknowledge Milcah Wagio Kigoni (International Institute of Tropical Agriculture) for her immense technical assistance during the study. References Atyame Nten , C. 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Google Scholar Crossref Search ADS PubMed WorldCat Author notes Supervisors: Johnson Kinyua; Steven Ger Nyanjom © The Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com © The Author(s) 2018. Published by Oxford University Press.

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BioScience HorizonsOxford University Press

Published: Jan 1, 2018

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