Zhi-Ping Feng

Genome Sequencing and Analysis of the Tasmanian Devil and Its Transmissible Cancer

Summary The Tasmanian devil (Sarcophilus harrisii), the largest marsupial carnivore, is endangered due to a transmissible facial cancer spread by direct transfer of living cancer cells through biting. Here we describe the sequencing, assembly, and annotation of the Tasmanian devil genome and whole-genome sequences for two geographically distant subclones of the cancer. Genomic analysis suggests that the cancer first arose from a female Tasmanian devil and that the clone has subsequently genetically diverged during its spread across Tasmania. The devil cancer genome contains more than 17,000 somatic base substitution mutations and bears the imprint of a distinct mutational process. Genotyping of somatic mutations in 104 geographically and temporally distributed Tasmanian devil tumors reveals the pattern of evolution and spread of this parasitic clonal lineage, with evidence of a selective sweep in one geographical area and persistence of parallel lineages in other populations. PaperClip

The immune gene repertoire of an important viral reservoir, the Australian black flying fox

BackgroundBats are the natural reservoir host for a range of emerging and re-emerging viruses, including SARS-like coronaviruses, Ebola viruses, henipaviruses and Rabies viruses. However, the mechanisms responsible for the control of viral replication in bats are not understood and there is little information available on any aspect of antiviral immunity in bats. Massively parallel sequencing of the bat transcriptome provides the opportunity for rapid gene discovery. Although the genomes of one megabat and one microbat have now been sequenced to low coverage, no transcriptomic datasets have been reported from any bat species. In this study, we describe the immune transcriptome of the Australian flying fox, Pteropus alecto, providing an important resource for identification of genes involved in a range of activities including antiviral immunity.ResultsTowards understanding the adaptations that have allowed bats to coexist with viruses, we have de novo assembled transcriptome sequence from immune tissues and stimulated cells from P. alecto. We identified about 18,600 genes involved in a broad range of activities with the most highly expressed genes involved in cell growth and maintenance, enzyme activity, cellular components and metabolism and energy pathways. 3.5% of the bat transcribed genes corresponded to immune genes and a total of about 500 immune genes were identified, providing an overview of both innate and adaptive immunity. A small proportion of transcripts found no match with annotated sequences in any of the public databases and may represent bat-specific transcripts.ConclusionsThis study represents the first reported bat transcriptome dataset and provides a survey of expressed bat genes that complement existing bat genomic data. In addition, these data provide insight into genes relevant to the antiviral responses of bats, and form a basis for examining the roles of these molecules in immune response to viral infection.

The Architecture and Evolution of Cancer Neochromosomes

We isolated and analyzed, at single-nucleotide resolution, cancer-associated neochromosomes from well- and/or dedifferentiated liposarcomas. Neochromosomes, which can exceed 600 Mb in size, initially arise as circular structures following chromothripsis involving chromosome 12. The core of the neochromosome is amplified, rearranged, and corroded through hundreds of breakage-fusion-bridge cycles. Under selective pressure, amplified oncogenes are overexpressed, while coamplified passenger genes may be silenced epigenetically. New material may be captured during punctuated chromothriptic events. Centromeric corrosion leads to crisis, which is resolved through neocentromere formation or native centromere capture. Finally, amplification terminates, and the neochromosome core is stabilized in linear form by telomere capture. This study investigates the dynamic mutational processes underlying the life history of a special form of cancer mutation.

Discovery and molecular characterization of a Bcl-2–regulated cell death pathway in schistosomes

Schistosomiasis is an infectious disease caused by parasites of the phylum platyhelminthe. Here, we describe the identification and characterization of a Bcl-2–regulated apoptosis pathway in Schistosoma japonicum and S. mansoni. Genomic, biochemical, and cell-based mechanistic studies provide evidence for a tripartite pathway, similar to that in humans including BH3-only proteins that are inhibited by prosurvival Bcl-2–like molecules, and Bax/Bak-like proteins that facilitate mitochondrial outer-membrane permeabilization. Because Bcl-2 proteins have been successfully targeted with “BH3 mimetic” drugs, particularly in the treatment of cancer, we investigated whether schistosome apoptosis pathways could provide targets for future antischistosomal drug discovery efforts. Accordingly, we showed that a schistosome prosurvival protein, sjA, binds ABT-737, a well-characterized BH3 mimetic. A crystal structure of sjA bound to a BH3 peptide provides direct evidence for the feasibility of developing BH3 mimetics to target Bcl-2 prosurvival proteins in schistosomes, suggesting an alternative application for this class of drugs beyond cancer treatment.

Large-scale prediction of long disordered regions in proteins using random forests

BackgroundMany proteins contain disordered regions that lack fixed three-dimensional (3D) structure under physiological conditions but have important biological functions. Prediction of disordered regions in protein sequences is important for understanding protein function and in high-throughput determination of protein structures. Machine learning techniques, including neural networks and support vector machines have been widely used in such predictions. Predictors designed for long disordered regions are usually less successful in predicting short disordered regions. Combining prediction of short and long disordered regions will dramatically increase the complexity of the prediction algorithm and make the predictor unsuitable for large-scale applications. Efficient batch prediction of long disordered regions alone is of greater interest in large-scale proteome studies.ResultsA new algorithm, IUPforest-L, for predicting long disordered regions using the random forest learning model is proposed in this paper. IUPforest-L is based on the Moreau-Broto auto-correlation function of amino acid indices (AAIs) and other physicochemical features of the primary sequences. In 10-fold cross validation tests, IUPforest-L can achieve an area of 89.5% under the receiver operating characteristic (ROC) curve. Compared with existing disorder predictors, IUPforest-L has high prediction accuracy and is efficient for predicting long disordered regions in large-scale proteomes.ConclusionThe random forest model based on the auto-correlation functions of the AAIs within a protein fragment and other physicochemical features could effectively detect long disordered regions in proteins. A new predictor, IUPforest-L, was developed to batch predict long disordered regions in proteins, and the server can be accessed from http://dmg.cs.rmit.edu.au/IUPforest/IUPforest-L.php

Evolution of coding and non-coding genes in HOX clusters of a marsupial.

BackgroundThe HOX gene clusters are thought to be highly conserved amongst mammals and other vertebrates, but the long non-coding RNAs have only been studied in detail in human and mouse. The sequencing of the kangaroo genome provides an opportunity to use comparative analyses to compare the HOX clusters of a mammal with a distinct body plan to those of other mammals.ResultsHere we report a comparative analysis of HOX gene clusters between an Australian marsupial of the kangaroo family and the eutherians. There was a strikingly high level of conservation of HOX gene sequence and structure and non-protein coding genes including the microRNAs miR-196a, miR-196b, miR-10a and miR-10b and the long non-coding RNAs HOTAIR, HOTAIRM1 and HOX A11AS that play critical roles in regulating gene expression and controlling development. By microRNA deep sequencing and comparative genomic analyses, two conserved microRNAs (miR-10a and miR-10b) were identified and one new candidate microRNA with typical hairpin precursor structure that is expressed in both fibroblasts and testes was found. The prediction of microRNA target analysis showed that several known microRNA targets, such as miR-10, miR-414 and miR-464, were found in the tammar HOX clusters. In addition, several novel and putative miRNAs were identified that originated from elsewhere in the tammar genome and that target the tammar HOXB and HOXD clusters.ConclusionsThis study confirms that the emergence of known long non-coding RNAs in the HOX clusters clearly predate the marsupial-eutherian divergence 160 Ma ago. It also identified a new potentially functional microRNA as well as conserved miRNAs. These non-coding RNAs may participate in the regulation of HOX genes to influence the body plan of this marsupial.

The N-terminal domains of SOCS proteins: a conserved region in the disordered N-termini of SOCS4 and 5.

Suppressors of cytokine signaling (SOCS) proteins function as negative regulators of cytokine signaling and are involved in fine tuning the immune response. The structure and role of the SH2 domains and C‐terminal SOCS box motifs of the SOCS proteins are well characterized, but the long N‐terminal domains of SOCS4–7 remain poorly understood. Here, we present bioinformatic analyses of the N‐terminal domains of the mammalian SOCS proteins, which indicate that these domains of SOCS4, 5, 6, and 7 are largely disordered. We have also identified a conserved region of about 70 residues in the N‐terminal domains of SOCS4 and 5 that is predicted to be more ordered than the surrounding sequence. The conservation of this region can be traced as far back as lower vertebrates. As conserved regions with increased structural propensity that are located within long disordered regions often contain molecular recognition motifs, we expressed the N‐terminal conserved region of mouse SOCS4 for further analysis. This region, mSOCS486–155, has been characterized by circular dichroism and nuclear magnetic resonance spectroscopy, both of which indicate that it is predominantly unstructured in aqueous solution, although it becomes helical in the presence of trifluoroethanol. The high degree of sequence conservation of this region across different species and between SOCS4 and SOCS5 nonetheless implies that it has an important functional role, and presumably this region adopts a more ordered conformation in complex with its partners. The recombinant protein will be a valuable tool in identifying these partners and defining the structures of these complexes. Proteins 2011.

Peroxidase catalysed cross-linking of an intrinsically unstructured protein via dityrosine bonds in the oocyst wall of the apicomplexan parasite, Eimeria maxima

Apicomplexan parasites such as Eimeria maxima possess a resilient oocyst wall that protects them upon excretion in host faeces and in the outside world, allowing them to survive between hosts. The wall is formed from the contents of specialised organelles - wall-forming bodies - found in macrogametes of the parasites. The presence of dityrosine in the oocyst wall suggests that peroxidase-catalysed dityrosine cross-linking of tyrosine-rich proteins from wall-forming bodies forms a matrix that is a crucial component of oocyst walls. Bioinformatic analyses showed that one of these tyrosine-rich proteins, EmGAM56, is an intrinsically unstructured protein, dominated by random coil (52-70%), with some α-helix (28-43%) but a relatively low percentage of β-sheet (1-11%); this was confirmed by nuclear magnetic resonance and circular dichroism. Furthermore, the structural integrity of EmGAM56 under extreme temperatures and pH indicated its disordered nature. The intrinsic lack of structure in EmGAM56 could facilitate its incorporation into the oocyst wall in two ways: first, intrinsically unstructured proteins are highly susceptible to proteolysis, explaining the several differently-sized oocyst wall proteins derived from EmGAM56; and, second, its flexibility could facilitate cross-linking between these tyrosine-rich derivatives. An in vitro cross-linking assay was developed using a recombinant 42kDa truncation of EmGAM56. Peroxides, in combination with plant or fungal peroxidases, catalysed the rapid formation of dityrosine cross-linked polymers of the truncated EmGAM56, as determined by western blotting and HPLC, confirming this proteins propensity to form dityrosine bonds.

Predicting disordered regions in proteins using the profiles of amino acid indices

BackgroundIntrinsically unstructured or disordered proteins are common and functionally important. Prediction of disordered regions in proteins can provide useful information for understanding protein function and for high-throughput determination of protein structures.ResultsIn this paper, algorithms are presented to predict long and short disordered regions in proteins, namely the long disordered region prediction algorithm DRaai-L and the short disordered region prediction algorithm DRaai-S. These algorithms are developed based on the Random Forest machine learning model and the profiles of amino acid indices representing various physiochemical and biochemical properties of the 20 amino acids.ConclusionExperiments on DisProt3.6 and CASP7 demonstrate that some sets of the amino acid indices have strong association with the ordered and disordered status of residues. Our algorithms based on the profiles of these amino acid indices as input features to predict disordered regions in proteins outperform that based on amino acid composition and reduced amino acid composition, and also outperform many existing algorithms. Our studies suggest that the profiles of amino acid indices combined with the Random Forest learning model is an important complementary method for pinpointing disordered regions in proteins.

Coarse‐grained dynamics of the receiver domain of NtrC: Fluctuations, correlations and implications for allosteric cooperativity

Receiver domains are key molecular switches in bacterial signaling. Structural studies have shown that the receiver domain of the nitrogen regulatory protein C (NtrC) exists in a conformational equilibrium encompassing both inactive and active states, with phosphorylation of Asp54 allosterically shifting the equilibrium towards the active state. To analyze dynamical fluctuations and correlations in NtrC as it undergoes activation, we have applied a coarse‐grained dynamics algorithm using elastic network models. Normal mode analysis reveals possible dynamical pathways for the transition of NtrC from the inactive state to the active state. The diagonalized correlation between the inactive and the active (phosphorylated) state shows that most correlated motions occur around the active site of Asp54 and in the region Thr82 to Tyr101. This indicates a coupled correlation of dynamics in the “Thr82‐Tyr101” motion. With phosphorylation inducing significant flexibility changes around the active site and α3 and α4 helices, we find that this activation makes the active‐site region and the loops of α3/β4 and α4/β5 more stable. This means that phosphorylation entropically favors the receiver domain in its active state, and the induced conformational changes occur in an allosteric manner. Analyses of the local flexibility and long‐range correlated motion also suggest a dynamics criterion for determining the allosteric cooperativity of NtrC, and may be applicable to other proteins. Proteins 2008.