Prevalence of Cryptosporidium spp., Enterocytozoon bieneusi,Encephalitozoon spp. and Giardia intestinalis in Wild,Semi-Wild and Captive Orangutans (Pongo abelii and Pongo pygmaeus) on Sumatra and Borneo,Indonesia

Background

Orangutans are critically endangered primarily due to loss and fragmentation of their natural habitat. This could bring them into closer contact with humans and increase the risk of zoonotic pathogen transmission.

Aims

To describe the prevalence and diversity of Cryptosporidium spp., microsporidia and Giardia intestinalis in orangutans at seven sites on Sumatra and Kalimantan, and to evaluate the impact of orangutans’ habituation and location on the occurrence of these zoonotic protists.

Result

The overall prevalence of parasites in 298 examined animals was 11.1%. The most prevalent microsporidia was Encephalitozoon cuniculi genotype II, found in 21 animals (7.0%). Enterocytozoon bieneusi genotype D (n = 5) and novel genotype Pongo 2 were detected only in six individuals (2.0%). To the best of our knowledge, this is the first report of these parasites in orangutans. Eight animals were positive for Cryptosporidium spp. (2.7%), including C. parvum (n = 2) and C. muris (n = 6). Giardia intestinalis assemblage B, subtype MB6, was identified in a single individual. While no significant differences between the different human contact level groups (p = 0.479–0.670) or between the different islands (p = 0.992) were reported in case of E. bieneusi or E. cuniculi, Cryptosporidium spp. was significantly less frequently detected in wild individuals (p < 2×10⁻¹⁶) and was significantly more prevalent in orangutans on Kalimantan than on Sumatra (p < 2×10⁻¹⁶).

Conclusion

Our results revealed that wild orangutans are significantly less frequently infected by Cryptosporidium spp. than captive and semi-wild animals. In addition, this parasite was more frequently detected at localities on Kalimantan. In contrast, we did not detect any significant difference in the prevalence of microsporidia between the studied groups of animals. The sources and transmission modes of infections were not determined, as this would require repeated sampling of individuals, examination of water sources, and sampling of humans and animals sharing the habitat with orangutans.     

Predicting transmembrane beta-barrels in proteomes

Very few methods address the problem of predicting beta-barrel membrane proteins directly from sequence. One reason is that only very few high-resolution structures for transmembrane beta-barrel (TMB) proteins have been determined thus far. Here we introduced the design, statistics and results of a novel profile-based hidden Markov model for the prediction and discrimination of TMBs. The method carefully attempts to avoid over-fitting the sparse experimental data. While our model training and scoring procedures were very similar to a recently published work, the architecture and structure-based labelling were significantly different. In particular, we introduced a new definition of beta- hairpin motifs, explicit state modelling of transmembrane strands, and a log-odds whole-protein discrimination score. The resulting method reached an overall four-state (up-, down-strand, periplasmic-, outer-loop) accuracy as high as 86%. Furthermore, accurately discriminated TMB from non-TMB proteins (45% coverage at 100% accuracy). This high precision enabled the application to 72 entirely sequenced Gram-negative bacteria. We found over 164 previously uncharacterized TMB proteins at high confidence. Database searches did not implicate any of these proteins with membranes. We challenge that the vast majority of our 164 predictions will eventually be verified experimentally. All proteome predictions and the PROFtmb prediction method are available at http://www.rostlab.org/ services/PROFtmb/.     

LOC3D: annotate sub-cellular localization for protein structures

LOC3D (http://cubic.bioc.columbia.edu/db/LOC3d/) is both a weekly-updated database and a web server for predictions of sub-cellular localization for eukaryotic proteins of known three-dimensional (3D) structure. Localization is predicted using four different methods: (i) PredictNLS, prediction of nuclear proteins through nuclear localization signals; (ii) LOChom, inferring localization through sequence homology; (iii) LOCkey, inferring localization through automatic text analysis of SWISS-PROT keywords; and (iv) LOC3Dini, ab initio prediction through a system of neural networks and vector support machines. The final prediction is based on the method that predicts localization with the highest confidence. The LOC3D database currently contains predictions for >8700 eukaryotic protein chains taken from the Protein Data Bank (PDB). The web server can be used to predict sub-cellular localization for proteins for which only a predicted structure is available from threading servers. This makes the resource of particular interest to structural genomics initiatives.     

Comparing function and structure between entire proteomes

More than 30 organisms have been sequenced entirely. Here, we applied a variety of simple bioinformatics tools to analyze 29 proteomes for representatives from all three kingdoms: eukaryotes, prokaryotes, and archaebacteria. We confirmed that eukaryotes have relatively more long proteins than prokaryotes and archaes, and that the overall amino acid composition is similar among the three. We predicted that approximately 15%-30% of all proteins contained transmembrane helices. We could not find a correlation between the content of membrane proteins and the complexity of the organism. In particular, we did not find significantly higher percentages of helical membrane proteins in eukaryotes than in prokaryotes or archae. However, we found more proteins with seven transmembrane helices in eukaryotes and more with six and 12 transmembrane helices in prokaryotes. We found twice as many coiled-coil proteins in eukaryotes (10%) as in prokaryotes and archaes (4%-5%), and we predicted approximately 15%-25% of all proteins to be secreted by most eukaryotes and prokaryotes. Every tenth protein had no known homolog in current databases, and 30%-40% of the proteins fell into structural families with >100 members. A classification by cellular function verified that eukaryotes have a higher proportion of proteins for communication with the environment. Finally, we found at least one homolog of experimentally known structure for approximately 20%-45% of all proteins; the regions with structural homology covered 20%-30% of all residues. These numbers may or may not suggest that there are 1200-2600 folds in the universe of protein structures. All predictions are available at http://cubic.bioc.columbia.edu/genomes.     

Improved tumor selectivity of radiolabeled peptides by receptor and antigen dual targeting in the neurotensin receptor model

Radiolabeled peptides are emerging tools for diagnosis and therapy of tumors overexpressing receptors. However, binding to receptors expressed by nontumor tissues may cause toxicity. The objective of this study was to specifically enhance the binding affinity of labeled peptides to tumor cells, as opposed to receptor-positive nontumor cells, to ensure targeting selectivity. This was achieved by the simultaneous binding of hapten-bearing peptides to their receptor and to a tumor-associated antigen, mediated by a bispecific antibody directed to the tumor antigen and to the hapten. Binding of labeled neurotensin analogues bearing the DTPA(indium) hapten (NT-DTPA(111In)) to human colorectal carcinoma cells (HT29), which express the neurotensin receptor (NTR1) and carcinoembryonic antigen (CEA), was studied in the presence of a bispecific antibody (BsmAb) directed to CEA and to DTPA(indium). In vitro dual binding of NT-DTPA in the presence of BsmAb was about 6.5-fold higher than monovalent binding to NTR1 and 3.5-fold higher than the sum of the monovalent bindings to NTR1 or to CEA, suggesting cooperativity. Increased binding under bivalent conditions translated into increased internalization. In vivo pretargeting with BsmAb enhanced tumor uptake and tumor retention. Hapten bearing peptides binding simultaneously an overexpressed cell-surface receptor and a tumor antigen show increased selectivity to target tumor cells as compared to cells only expressing the cell surface receptor. Better resistance to enzymatic degradation and optimized administration protocols should further enhance in vivo targeting selectivity and may allow the development of radiopharmaceuticals labeled with isotopes suitable for radiotherapy such as 131I or 90Y.