Understanding Ancient Hominin Dispersals Using Artefactual Data: A Phylogeographic Analysis of Acheulean Handaxes

Background

Reconstructing the dispersal patterns of extinct hominins remains a challenging but essential goal. One means of supplementing fossil evidence is to utilize archaeological evidence in the form of stone tools. Based on broad dating patterns, it has long been thought that the appearance of Acheulean handaxe technologies outside of Africa was the result of hominin dispersals, yet independent tests of this hypothesis remain rare. Cultural transmission theory leads to a prediction of a strong African versus non-African phylogeographic pattern in handaxe datasets, if the African Acheulean hypothesis is to be supported.

Methodology/Principal Findings

Here, this prediction is tested using an intercontinental dataset of Acheulean handaxes and a biological phylogenetic method (maximum parsimony). The analyses produce a tree consistent with the phylogeographic prediction. Moreover, a bootstrap analysis provides evidence that this pattern is robust, and the maximum parsimony tree is also shown to be statistically different from a tree constrained by stone raw materials.

Conclusions/Significance

These results demonstrate that nested analyses of behavioural data, utilizing methods drawn from biology, have the potential to shed light on ancient hominin dispersals. This is an encouraging prospect for human palaeobiology since sample sizes for lithic artefacts are many orders of magnitude higher than those of fossil data. These analyses also suggest that the sustained occurrence of Acheulean handaxe technologies in regions such as Europe and the Indian subcontinent resulted from dispersals by African hominin populations.     

A comparison of phylogenetic network methods using computer simulation

Background

We present a series of simulation studies that explore the relative performance of several phylogenetic network approaches (statistical parsimony, split decomposition, union of maximum parsimony trees, neighbor-net, simulated history recombination upper bound, median-joining, reduced median joining and minimum spanning network) compared to standard tree approaches, (neighbor-joining and maximum parsimony) in the presence and absence of recombination.

Principal Findings

In the absence of recombination, all methods recovered the correct topology and branch lengths nearly all of the time when the substitution rate was low, except for minimum spanning networks, which did considerably worse. At a higher substitution rate, maximum parsimony and union of maximum parsimony trees were the most accurate. With recombination, the ability to infer the correct topology was halved for all methods and no method could accurately estimate branch lengths.

Conclusions

Our results highlight the need for more accurate phylogenetic network methods and the importance of detecting and accounting for recombination in phylogenetic studies. Furthermore, we provide useful information for choosing a network algorithm and a framework in which to evaluate improvements to existing methods and novel algorithms developed in the future.     

Phylogenetic relationships among arecoid palms (Arecaceae: Arecoideae)

Background and Aims

The Arecoideae is the largest and most diverse of the five subfamilies of palms (Arecaceae/Palmae), containing >50 % of the species in the family. Despite its importance, phylogenetic relationships among Arecoideae are poorly understood. Here the most densely sampled phylogenetic analysis of Arecoideae available to date is presented. The results are used to test the current classification of the subfamily and to identify priority areas for future research.

Methods

DNA sequence data for the low-copy nuclear genes PRK and RPB2 were collected from 190 palm species, covering 103 (96 %) genera of Arecoideae. The data were analysed using the parsimony ratchet, maximum likelihood, and both likelihood and parsimony bootstrapping.

Key Results and Conclusions

Despite the recovery of paralogues and pseudogenes in a small number of taxa, PRK and RPB2 were both highly informative, producing well-resolved phylogenetic trees with many nodes well supported by bootstrap analyses. Simultaneous analyses of the combined data sets provided additional resolution and support. Two areas of incongruence between PRK and RPB2 were strongly supported by the bootstrap relating to the placement of tribes Chamaedoreeae, Iriarteeae and Reinhardtieae; the causes of this incongruence remain uncertain. The current classification within Arecoideae was strongly supported by the present data. Of the 14 tribes and 14 sub-tribes in the classification, only five sub-tribes from tribe Areceae (Basseliniinae, Linospadicinae, Oncospermatinae, Rhopalostylidinae and Verschaffeltiinae) failed to receive support. Three major higher level clades were strongly supported: (1) the RRC clade (Roystoneeae, Reinhardtieae and Cocoseae), (2) the POS clade (Podococceae, Oranieae and Sclerospermeae) and (3) the core arecoid clade (Areceae, Euterpeae, Geonomateae, Leopoldinieae, Manicarieae and Pelagodoxeae). However, new data sources are required to elucidate ambiguities that remain in phylogenetic relationships among and within the major groups of Arecoideae, as well as within the Areceae, the largest tribe in the palm family.     

Non-Invasive Prenatal Detection of Trisomy 13 Using a Single Nucleotide Polymorphism- and Informatics-Based Approach

Purpose

To determine how a single nucleotide polymorphism (SNP)- and informatics-based non-invasive prenatal aneuploidy test performs in detecting trisomy 13.

Methods

Seventeen trisomy 13 and 51 age-matched euploid samples, randomly selected from a larger cohort, were analyzed. Cell-free DNA was isolated from maternal plasma, amplified in a single multiplex polymerase chain reaction assay that interrogated 19,488 SNPs covering chromosomes 13, 18, 21, X, and Y, and sequenced. Analysis and copy number identification involved a Bayesian-based maximum likelihood statistical method that generated chromosome- and sample-specific calculated accuracies.

Results

Of the samples that passed a stringent DNA quality threshold (94.1%), the algorithm correctly identified 15/15 trisomy 13 and 49/49 euploid samples, for 320/320 correct copy number calls.

Conclusions

This informatics- and SNP-based method accurately detects trisomy 13-affected fetuses non-invasively and with high calculated accuracy.     

Molecular sub-classification of renal epithelial tumors using meta-analysis of gene expression microarrays

Purpose

To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures.

Experimental Design

A search of publicly available databases was performed to identify microarray datasets with multiple histologic sub-types of renal cortical neoplasms. Meta-analytic techniques were utilized to identify differentially expressed genes for each histologic subtype. The lists of genes obtained from the meta-analysis were used to create predictive signatures through the use of a pair-based method. These signatures were organized into an algorithm to sub-classify renal neoplasms. The use of these signatures according to our algorithm was validated on several independent datasets.

Results

We identified three Gene Expression Omnibus datasets that fit our criteria to develop a training set. All of the datasets in our study utilized the Affymetrix platform. The final training dataset included 149 samples represented by the four most common histologic subtypes of renal cortical neoplasms: 69 clear cell, 41 papillary, 16 chromophobe, and 23 oncocytomas. When validation of our signatures was performed on external datasets, we were able to correctly classify 68 of the 72 samples (94%). The correct classification by subtype was 19/20 (95%) for clear cell, 14/14 (100%) for papillary, 17/19 (89%) for chromophobe, 18/19 (95%) for oncocytomas.

Conclusions

Through the use of meta-analytic techniques, we were able to create an algorithm that sub-classified renal neoplasms on a molecular level with 94% accuracy across multiple independent datasets. This algorithm may aid in selecting molecular therapies and may improve the accuracy of subtyping of renal cortical tumors.     

Statistical Parsimony Networks and Species Assemblages in Cephalotrichid Nemerteans (Nemertea)

Background

It has been suggested that statistical parsimony network analysis could be used to get an indication of species represented in a set of nucleotide data, and the approach has been used to discuss species boundaries in some taxa.

Methodology/Principal Findings

Based on 635 base pairs of the mitochondrial protein-coding gene cytochrome c oxidase I (COI), we analyzed 152 nemertean specimens using statistical parsimony network analysis with the connection probability set to 95%. The analysis revealed 15 distinct networks together with seven singletons. Statistical parsimony yielded three networks supporting the species status of Cephalothrix rufifrons, C. major and C. spiralis as they currently have been delineated by morphological characters and geographical location. Many other networks contained haplotypes from nearby geographical locations. Cladistic structure by maximum likelihood analysis overall supported the network analysis, but indicated a false positive result where subnetworks should have been connected into one network/species. This probably is caused by undersampling of the intraspecific haplotype diversity.

Conclusions/Significance

Statistical parsimony network analysis provides a rapid and useful tool for detecting possible undescribed/cryptic species among cephalotrichid nemerteans based on COI gene. It should be combined with phylogenetic analysis to get indications of false positive results, i.e., subnetworks that would have been connected with more extensive haplotype sampling.     

An improved probability mapping approach to assess genome mosaicism

Background

Maximum likelihood and posterior probability mapping are useful visualization techniques that are used to ascertain the mosaic nature of prokaryotic genomes. However, posterior probabilities, especially when calculated for four-taxon cases, tend to overestimate the support for tree topologies. Furthermore, because of poor taxon sampling four-taxon analyses suffer from sensitivity to the long branch attraction artifact. Here we extend the probability mapping approach by improving taxon sampling of the analyzed datasets, and by using bootstrap support values, a more conservative tool to assess reliability.

Results

Quartets of orthologous proteins were complemented with homologs from selected reference genomes. The mapping of bootstrap support values from these extended datasets gives results similar to the original maximum likelihood and posterior probability mapping. The more conservative nature of the plotted support values allows to focus further analyses on those protein families that strongly disagree with the majority or plurality of genes present in the analyzed genomes.

Conclusion

Posterior probability is a non-conservative measure for support, and posterior probability mapping only provides a quick estimation of phylogenetic information content of four genomes. This approach can be utilized as a pre-screen to select genes that might have been horizontally transferred. Better taxon sampling combined with subtree analyses prevents the inconsistencies associated with four-taxon analyses, but retains the power of visual representation. Nevertheless, a case-by-case inspection of individual multi-taxon phylogenies remains necessary to differentiate unrecognized paralogy and shared phylogenetic reconstruction artifacts from horizontal gene transfer events.

     

Phylogeny of the cycads based on multiple single-copy nuclear genes: congruence of concatenated parsimony,likelihood and species tree inference methods

Background and aims

Despite a recent new classification, a stable phylogeny for the cycads has been elusive, particularly regarding resolution of Bowenia, Stangeria and Dioon. In this study, five single-copy nuclear genes (SCNGs) are applied to the phylogeny of the order Cycadales. The specific aim is to evaluate several gene tree–species tree reconciliation approaches for developing an accurate phylogeny of the order, to contrast them with concatenated parsimony analysis and to resolve the erstwhile problematic phylogenetic position of these three genera.

Methods

DNA sequences of five SCNGs were obtained for 20 cycad species representing all ten genera of Cycadales. These were analysed with parsimony, maximum likelihood (ML) and three Bayesian methods of gene tree–species tree reconciliation, using Cycas as the outgroup. A calibrated date estimation was developed with Bayesian methods, and biogeographic analysis was also conducted.

Key Results

Concatenated parsimony, ML and three species tree inference methods resolve exactly the same tree topology with high support at most nodes. Dioon and Bowenia are the first and second branches of Cycadales after Cycas, respectively, followed by an encephalartoid clade (Macrozamia–Lepidozamia–Encephalartos), which is sister to a zamioid clade, of which Ceratozamia is the first branch, and in which Stangeria is sister to Microcycas and Zamia.

Conclusions

A single, well-supported phylogenetic hypothesis of the generic relationships of the Cycadales is presented. However, massive extinction events inferred from the fossil record that eliminated broader ancestral distributions within Zamiaceae compromise accurate optimization of ancestral biogeographical areas for that hypothesis. While major lineages of Cycadales are ancient, crown ages of all modern genera are no older than 12 million years, supporting a recent hypothesis of mostly Miocene radiations. This phylogeny can contribute to an accurate infrafamilial classification of Zamiaceae.     

Predicting protein phenotypes based on protein-protein interaction network

Background

Identifying associated phenotypes of proteins is a challenge of the modern genetics since the multifactorial trait often results from contributions of many proteins. Besides the high-through phenotype assays, the computational methods are alternative ways to identify the phenotypes of proteins.

Methodology/Principal Findings

Here, we proposed a new method for predicting protein phenotypes in yeast based on protein-protein interaction network. Instead of only the most likely phenotype, a series of possible phenotypes for the query protein were generated and ranked acording to the tethering potential score. As a result, the first order prediction accuracy of our method achieved 65.4% evaluated by Jackknife test of 1,267 proteins in budding yeast, much higher than the success rate (15.4%) of a random guess. And the likelihood of the first 3 predicted phenotypes including all the real phenotypes of the proteins was 70.6%.

Conclusions/Significance

The candidate phenotypes predicted by our method provided useful clues for the further validation. In addition, the method can be easily applied to the prediction of protein associated phenotypes in other organisms.     

Molecular phylogeny of the neotropical genus Christensonella (Orchidaceae, Maxillariinae): species delimitation and insights into chromosome evolution

Background and Aims

Species'' boundaries applied within Christensonella have varied due to the continuous pattern of variation and mosaic distribution of diagnostic characters. The main goals of this study were to revise the species'' delimitation and propose a more stable classification for this genus. In order to achieve these aims phylogenetic relationships were inferred using DNA sequence data and cytological diversity within Christensonella was examined based on chromosome counts and heterochromatin patterns. The results presented describe sets of diagnostic morphological characters that can be used for species'' identification.

Methods

Phylogenetic studies were based on sequence data of nuclear and plastid regions, analysed using maximum parsimony and maximum likelihood criteria. Cytogenetic observations of mitotic cells were conducted using CMA and DAPI fluorochromes.

Key Results

Six of 21 currently accepted species were recovered. The results also support recognition of the ‘C. pumila’ clade as a single species. Molecular phylogenetic relationships within the ‘C. acicularis–C. madida’ and ‘C. ferdinandiana–C. neowiedii’ species'' complexes were not resolved and require further study. Deeper relationships were incongruent between plastid and nuclear trees, but with no strong bootstrap support for either, except for the position of C. vernicosa. Cytogenetic data indicated chromosome numbers of 2n = 36, 38 and 76, and with substantial variation in the presence and location of CMA/DAPI heterochromatin bands.

Conclusions

The recognition of ten species of Christensonella is proposed according to the molecular and cytogenetic patterns observed. In addition, diagnostic morphological characters are presented for each recognized species. Banding patterns and chromosome counts suggest the occurrence of centric fusion/fission events, especially for C. ferdinandiana. The results suggest that 2n = 36 karyotypes evolved from 2n = 38 through descendent dysploidy. Patterns of heterochromatin distribution and other karyotypic data proved to be a valuable source of information to understand evolutionary patterns within Maxillariinae orchids.Key words: Chromosome number, Christensonella, Cymbidieae, cytotaxonomy, fluorochrome staining, Maxillaria, Maxillariinae, molecular phylogenetics, species delimitation     

High-throughput sequencing of six bamboo chloroplast genomes: phylogenetic implications for temperate woody bamboos (Poaceae: Bambusoideae)

Background

Bambusoideae is the only subfamily that contains woody members in the grass family, Poaceae. In phylogenetic analyses, Bambusoideae, Pooideae and Ehrhartoideae formed the BEP clade, yet the internal relationships of this clade are controversial. The distinctive life history (infrequent flowering and predominance of asexual reproduction) of woody bamboos makes them an interesting but taxonomically difficult group. Phylogenetic analyses based on large DNA fragments could only provide a moderate resolution of woody bamboo relationships, although a robust phylogenetic tree is needed to elucidate their evolutionary history. Phylogenomics is an alternative choice for resolving difficult phylogenies.

Methodology/Principal Findings

Here we present the complete nucleotide sequences of six woody bamboo chloroplast (cp) genomes using Illumina sequencing. These genomes are similar to those of other grasses and rather conservative in evolution. We constructed a phylogeny of Poaceae from 24 complete cp genomes including 21 grass species. Within the BEP clade, we found strong support for a sister relationship between Bambusoideae and Pooideae. In a substantial improvement over prior studies, all six nodes within Bambusoideae were supported with ≥0.95 posterior probability from Bayesian inference and 5/6 nodes resolved with 100% bootstrap support in maximum parsimony and maximum likelihood analyses. We found that repeats in the cp genome could provide phylogenetic information, while caution is needed when using indels in phylogenetic analyses based on few selected genes. We also identified relatively rapidly evolving cp genome regions that have the potential to be used for further phylogenetic study in Bambusoideae.

Conclusions/Significance

The cp genome of Bambusoideae evolved slowly, and phylogenomics based on whole cp genome could be used to resolve major relationships within the subfamily. The difficulty in resolving the diversification among three clades of temperate woody bamboos, even with complete cp genome sequences, suggests that these lineages may have diverged very rapidly.     

Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis

Introduction

Our objective was to utilise network analysis to identify protein clusters of greatest potential functional relevance in the pathogenesis of oligoarticular and rheumatoid factor negative (RF-ve) polyarticular juvenile idiopathic arthritis (JIA).

Methods

JIA genetic association data were used to build an interactome network model in BioGRID 3.2.99. The top 10% of this protein:protein JIA Interactome was used to generate a minimal essential network (MEN). Reactome FI Cytoscape 2.83 Plugin and the Disease Association Protein-Protein Link Evaluator (Dapple) algorithm were used to assess the functionality of the biological pathways within the MEN and to statistically rank the proteins. JIA gene expression data were integrated with the MEN and clusters of functionally important proteins derived using MCODE.

Results

A JIA interactome of 2,479 proteins was built from 348 JIA associated genes. The MEN, representing the most functionally related components of the network, comprised of seven clusters, with distinct functional characteristics. Four gene expression datasets from peripheral blood mononuclear cells (PBMC), neutrophils and synovial fluid monocytes, were mapped onto the MEN and a list of genes enriched for functional significance identified. This analysis revealed the genes of greatest potential functional importance to be PTPN2 and STAT1 for oligoarticular JIA and KSR1 for RF-ve polyarticular JIA. Clusters of 23 and 14 related proteins were derived for oligoarticular and RF-ve polyarticular JIA respectively.

Conclusions

This first report of the application of network biology to JIA, integrating genetic association findings and gene expression data, has prioritised protein clusters for functional validation and identified new pathways for targeted pharmacological intervention.     

Inferring angiosperm phylogeny from EST data with widespread gene duplication

Background

Most studies inferring species phylogenies use sequences from single copy genes or sets of orthologs culled from gene families. For taxa such as plants, with very high levels of gene duplication in their nuclear genomes, this has limited the exploitation of nuclear sequences for phylogenetic studies, such as those available in large EST libraries. One rarely used method of inference, gene tree parsimony, can infer species trees from gene families undergoing duplication and loss, but its performance has not been evaluated at a phylogenomic scale for EST data in plants.

Results

A gene tree parsimony analysis based on EST data was undertaken for six angiosperm model species and Pinus, an outgroup. Although a large fraction of the tentative consensus sequences obtained from the TIGR database of ESTs was assembled into homologous clusters too small to be phylogenetically informative, some 557 clusters contained promising levels of information. Based on maximum likelihood estimates of the gene trees obtained from these clusters, gene tree parsimony correctly inferred the accepted species tree with strong statistical support. A slight variant of this species tree was obtained when maximum parsimony was used to infer the individual gene trees instead.

Conclusion

Despite the complexity of the EST data and the relatively small fraction eventually used in inferring a species tree, the gene tree parsimony method performed well in the face of very high apparent rates of duplication.

     

Genomic Aberrations in an African American Colorectal Cancer Cohort Reveals a MSI-Specific Profile and Chromosome X Amplification in Male Patients

Objective

DNA aberrations that cause colorectal cancer (CRC) occur in multiple steps that involve microsatellite instability (MSI) and chromosomal instability (CIN). Herein, we studied CRCs from AA patients for their CIN and MSI status.

Experimental Design

Array CGH was performed on 30 AA colon tumors. The MSI status was established. The CGH data from AA were compared to published lists of 41 TSG and oncogenes in Caucasians and 68 cancer genes, proposed via systematic sequencing for somatic mutations in colon and breast tumors. The patient-by-patient CGH profiles were organized into a maximum parsimony cladogram to give insights into the tumors'' aberrations lineage.

Results

The CGH analysis revealed that CIN was independent of age, gender, stage or location. However, both the number and nature of aberrations seem to depend on the MSI status. MSI-H tumors clustered together in the cladogram. The chromosomes with the highest rates of CGH aberrations were 3, 5, 7, 8, 20 and X. Chromosome X was primarily amplified in male patients. A comparison with Caucasians revealed an overall similar aberration profile with few exceptions for the following genes; THRB, RAF1, LPL, DCC, XIST, PCNT, STS and genes on the 20q12-q13 cytoband. Among the 68 CAN genes, all showed some level of alteration in our cohort.

Conclusion

Chromosome X amplification in male patients with CRC merits follow-up. The observed CIN may play a distinctive role in CRC in AAs. The clustering of MSI-H tumors in global CGH data analysis suggests that chromosomal aberrations are not random.     

A Multi-Atlas Based Method for Automated Anatomical Rat Brain MRI Segmentation and Extraction of PET Activity

Introduction

Preclinical in vivo imaging requires precise and reproducible delineation of brain structures. Manual segmentation is time consuming and operator dependent. Automated segmentation as usually performed via single atlas registration fails to account for anatomo-physiological variability. We present, evaluate, and make available a multi-atlas approach for automatically segmenting rat brain MRI and extracting PET activies.

Methods

High-resolution 7T 2DT2 MR images of 12 Sprague-Dawley rat brains were manually segmented into 27-VOI label volumes using detailed protocols. Automated methods were developed with 7/12 atlas datasets, i.e. the MRIs and their associated label volumes. MRIs were registered to a common space, where an MRI template and a maximum probability atlas were created. Three automated methods were tested: 1/registering individual MRIs to the template, and using a single atlas (SA), 2/using the maximum probability atlas (MP), and 3/registering the MRIs from the multi-atlas dataset to an individual MRI, propagating the label volumes and fusing them in individual MRI space (propagation & fusion, PF). Evaluation was performed on the five remaining rats which additionally underwent [¹⁸F]FDG PET. Automated and manual segmentations were compared for morphometric performance (assessed by comparing volume bias and Dice overlap index) and functional performance (evaluated by comparing extracted PET measures).

Results

Only the SA method showed volume bias. Dice indices were significantly different between methods (PF>MP>SA). PET regional measures were more accurate with multi-atlas methods than with SA method.

Conclusions

Multi-atlas methods outperform SA for automated anatomical brain segmentation and PET measure’s extraction. They perform comparably to manual segmentation for FDG-PET quantification. Multi-atlas methods are suitable for rapid reproducible VOI analyses.     

Per-Event Probability of Hepatitis C Infection during Sharing of Injecting Equipment

Background

Shared injecting apparatus during drug use is the premier risk factor for hepatitis C virus (HCV) transmission.

Aims

To estimate the per-event probability of HCV infection during a sharing event, and the transmission probability of HCV from contaminated injecting apparatus.

Methods

Estimates were obtained using a maximum likelihood method with estimated IDU and sharing events obtained from behavioural data.

Settings

Cohort study in multiple correction centres in New South Wales, Australia

Participants

Subjects (N = 500) with a lifetime history of injecting drug use (IDU) who were followed up between 2005 and 2012. During follow-up, interviews for risk behaviours were taken and blood sampling (HCV-antibody and RNA testing) was performed.

Measurements

Self-reported frequencies of injecting drugs and sharing events, as well as other risk behaviours and details on the nature of injecting events.

Findings

The best estimate of the per-event probability of infection was 0.57% (CI: 0.32–1.05%). A sensitivity analysis on the likely effect of under-reporting of sharing of the injecting apparatus indicated that the per event infection probability may be as low as 0.17% (95% CI: 0.11%–0.25%). The transmission probability was similarly shown to range up to 6%, dependent on the presumed prevalence of the virus in injecting equipment.

Conclusions

The transmission probability of HCV during a sharing event is small. Hence, strategies to reduce the frequency and sharing of injecting equipment are required, as well as interventions focused on decreasing the per event risk.     

Proteomic analysis of the cyst stage of Entamoeba histolytica

Background

The category B agent of bioterrorism, Entamoeba histolytica has a two-stage life cycle: an infective cyst stage, and an invasive trophozoite stage. Due to our inability to effectively induce encystation in vitro, our knowledge about the cyst form remains limited. This also hampers our ability to develop cyst-specific diagnostic tools.

Aims

Three main aims were (i) to identify E. histolytica proteins in cyst samples, (ii) to enrich our knowledge about the cyst stage, and (iii) to identify candidate proteins to develop cyst-specific diagnostic tools.

Methods

Cysts were purified from the stool of infected individuals using Percoll (gradient) purification. A highly sensitive LC-MS/MS mass spectrometer (Orbitrap) was used to identify cyst proteins.

Results

A total of 417 non-redundant E. histolytica proteins were identified including 195 proteins that were never detected in trophozoite-derived proteomes or expressed sequence tag (EST) datasets, consistent with cyst specificity. Cyst-wall specific glycoproteins Jacob, Jessie and chitinase were positively identified. Antibodies produced against Jacob identified cysts in fecal specimens and have potential utility as a diagnostic reagent. Several protein kinases, small GTPase signaling molecules, DNA repair proteins, epigenetic regulators, and surface associated proteins were also identified. Proteins we identified are likely to be among the most abundant in excreted cysts, and therefore show promise as diagnostic targets.

Major Conclusions

The proteome data generated here are a first for naturally-occurring E. histolytica cysts, and they provide important insights into the infectious cyst form. Additionally, numerous unique candidate proteins were identified which will aid the development of new diagnostic tools for identification of E. histolytica cysts.