Sen-Lin Tang

Haloarchaeal viruses: how diverse are they?

Hypersaline lakes are highly productive microbial environments that provide many advantages for microbial ecologists, including stable communities of relatively low diversity (mainly haloarchaea). An important component of these communities is comprised of their non-cellular parasites, i.e., their viruses. Few viruses of halobacteria (haloviruses) have been isolated and studied even though a wide selection of host species have been formally described (and easily cultured) for ten years. Hypersaline waters have been shown to contain very high concentrations of virus-like particles (at least 10(7) particles/ml), particularly fusiform particles, but laboratory isolations of new haloviruses have been very slow and the detailed study of selected examples even slower. Here we provide an outline of the reported haloviruses, including fusiform and unpublished isolates from this laboratory, and we discuss their diversity and the future directions for this research.

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data

MOTIVATION Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. RESULTS The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). AVAILABILITY JAVA software of dynamic SOM tree algorithm is available upon request for academic use. SUPPLEMENTARY INFORMATION A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Binning sequences using very sparse labels within a metagenome

BackgroundIn metagenomic studies, a process called binning is necessary to assign contigs that belong to multiple species to their respective phylogenetic groups. Most of the current methods of binning, such as BLAST, k-mer and PhyloPythia, involve assigning sequence fragments by comparing sequence similarity or sequence composition with already-sequenced genomes that are still far from comprehensive. We propose a semi-supervised seeding method for binning that does not depend on knowledge of completed genomes. Instead, it extracts the flanking sequences of highly conserved 16S rRNA from the metagenome and uses them as seeds (labels) to assign other reads based on their compositional similarity.ResultsThe proposed seeding method is implemented on an unsupervised Growing Self-Organising Map (GSOM), and called Seeded GSOM (S-GSOM). We compared it with four well-known semi-supervised learning methods in a preliminary test, separating random-length prokaryotic sequence fragments sampled from the NCBI genome database. We identified the flanking sequences of the highly conserved 16S rRNA as suitable seeds that could be used to group the sequence fragments according to their species. S-GSOM showed superior performance compared to the semi-supervised methods tested. Additionally, S-GSOM may also be used to visually identify some species that do not have seeds.The proposed method was then applied to simulated metagenomic datasets using two different confidence threshold settings and compared with PhyloPythia, k-mer and BLAST. At the reference taxonomic level Order, S-GSOM outperformed all k-mer and BLAST results and showed comparable results with PhyloPythia for each of the corresponding confidence settings, where S-GSOM performed better than PhyloPythia in the ≥ 10 reads datasets and comparable in the ≥ 8 kb benchmark tests.ConclusionIn the task of binning using semi-supervised learning methods, results indicate S-GSOM to be the best of the methods tested. Most importantly, the proposed method does not require knowledge from known genomes and uses only very few labels (one per species is sufficient in most cases), which are extracted from the metagenome itself. These advantages make it a very attractive binning method. S-GSOM outperformed the binning methods that depend on already-sequenced genomes, and compares well to the current most advanced binning method, PhyloPythia.

HF2: a double-stranded DNA tailed haloarchaeal virus with a mosaic genome

HF2 is a haloarchaeal virus infecting two Halorubrum species (Family Halobacteriaceae). It is lytic, has a head‐and‐tail morphology and belongs to the Myoviridae (contractile tails). The linear double‐stranded DNA genome was sequenced and found to be 77 670 bp in length, with a mol% G+C of 55.8. A total of 121 likely open reading frames (ORFs) were identified, of which 37 overlapped at start and stop codons. The predicted proteins were usually acidic (average pI of 4.8), and less than about 12% of them had homologues in the sequence databases. Four complete tRNA‐like sequences (tRNA‐Arg, ‐Asx, ‐Pro and ‐Tyr) and an incomplete tRNA‐Thr were detected. A transcription map showed that most of the genome was transcribed and that the synthesis of transcripts occurred in a highly organized and reproducible pattern over a 5 h infection cycle. Transcripts often spanned multiple ORFs, suggesting that viral genes were organized into operons. The predicted ORF and observed transcript directions matched well and showed that transcription is mainly directed inwards from the genome termini, meeting at about 45–48 kb, and this was also a turning point in a cumulative GC‐skew plot. The low point in cumulative GC‐skew, near the left end, was a region rich in short repeats and lacking ORFs, which is likely to be an origin of replication. The HF2 genome is a mosaic of components from widely different sources, demonstrating clearly that viruses of haloarchaea, like their bacteriophage counterparts, are vectors for the exchange and transmission of genetic material between wide taxonomic distances, even across domains.

The dynamics of microbial partnerships in the coral Isopora palifera

Both bacteria and algal symbionts (genus Symbiodinium), the two major microbial partners in the coral holobiont, respond to fluctuations in the environment, according to current reports; however, little evidence yet indicates that both populations have any direct interaction with each other in seasonal fluctuation. In this study, we present field observations of a compositional change in bacteria and Symbiodinium in the coral Isopora palifera in three separate coral colonies following monthly sampling from February to November in 2008. Using massively parallel pyrosequencing, over 200 000 bacterial V6 sequences were classified to build the bacterial community profile; in addition, the relative composition and quantity of Symbiodinium clades C and D were determined by real-time PCR. The results showed that coral-associated bacterial and Symbiodinium communities were highly dynamic and dissimilar among the tagged coral colonies, suggesting that the effect of host specificity was insignificant. The coral-associated bacterial community was more diverse (Shannon index up to 6.71) than previous estimates in other corals and showed rapid seasonal changes. The population ratios between clade C and D groups of Symbiodinium varied in the tagged coral colonies through the different seasons; clade D dominated in most of the samples. Although significant association between bacteria and symbiont was not detected, this study presents a more detailed picture of changes in these two major microbial associates of the coral at the same time, using the latest molecular approaches.

Haloviruses HF1 and HF2: Evidence for a Recent and Large Recombination Event

Haloviruses HF1 and HF2 were isolated from the same saltern pond and are adapted to hypersaline conditions, where they infect a broad range of haloarchaeal species. The HF2 genome has previously been reported. The complete sequence of the HF1 genome has now been determined, mainly by PCR and primer walking. It was 75,898 bp in length and was 94.4% identical to the HF2 genome but about 1.8 kb shorter. A total of 117 open reading frames and five tRNA-like genes were predicted, and their database matches and characteristics were similar to those found in HF2. A comparison of the predicted restriction digest patterns based on nucleotide sequence with the observed restriction digest patterns of viral DNA showed that, unlike the case for HF2, some packaged HF1 DNA had cohesive termini. Except for a single base change, HF1 and HF2 were identical in sequence over the first 48 kb, a region that includes the early and middle genes. The remaining 28 kb of HF1 showed many differences from HF2, and the similarity of the two genomes over this late gene region was 87%. The abrupt shift in sequence similarity around 48 kb suggests a recent recombination event between either HF1 or HF2 and another HF-like halovirus that has swapped most of the right-end 28 kb. This example indicates there is a high level of recombination among viruses that live in this extreme environment.

Using Growing Self-Organising Maps to Improve the Binning Process in Environmental Whole-Genome Shotgun Sequencing

Metagenomic projects using whole-genome shotgun (WGS) sequencing produces many unassembled DNA sequences and small contigs. The step of clustering these sequences, based on biological and molecular features, is called binning. A reported strategy for binning that combines oligonucleotide frequency and self-organising maps (SOM) shows high potential. We improve this strategy by identifying suitable training features, implementing a better clustering algorithm, and defining quantitative measures for assessing results. We investigated the suitability of each of di-, tri-, tetra-, and pentanucleotide frequencies. The results show that dinucleotide frequency is not a sufficiently strong signature for binning 10 kb long DNA sequences, compared to the other three. Furthermore, we observed that increased order of oligonucleotide frequency may deteriorate the assignment result in some cases, which indicates the possible existence of optimal species-specific oligonucleotide frequency. We replaced SOM with growing self-organising map (GSOM) where comparable results are obtained while gaining 7%–15% speed improvement.

Influence of Species Specificity and Other Factors on Bacteria Associated with the Coral Stylophora pistillata in Taiwan

ABSTRACT Species of bacteria associated with Stylophora pistillata were determined by analyses of 16S ribosomal genes. Coral samples were taken from two distinct sites at Kenting, in the far south of Taiwan; three coral colonies at each site were tagged and sampled in the winter and summer of 2007. Six hundred 16S rRNA gene clones were selected and sequenced for diversity analysis and community comparison. LIBSHUFF and nonparametric multiple dimensional scaling analyses showed variations in the composition of the coral-associated bacteria in the different samples, suggesting that seasonal and geographic factors and variations in individual coral colonies were all vital drivers of the structure of the S. pistillata-associated bacterial community. To examine the association between species specificity and environmental impacts on the structure of the coral-associated bacterial community, we conducted an integrated, comparative analysis of 44 coral-associated bacterial data sets, including the present studys data. The clustering analysis suggests that the influence of spatial and temporal factors on the coral-associated bacteria population structure is considerable; nonetheless, the effect of species specificity is still detectable in some coral species, especially those from the Caribbean Sea.

Role of flagellins from A and B loci in flagella formation of Halobacterium salinarum.

Haloarchaeal flagella are composed of a number of distinct flagellin proteins, specified by genes in two separate operons (A and B). The roles of these flagellins were assessed by studying mutants of H. salinarum with insertions in either the A or the B operon. Cells of the flgA− mutant produced abnormally short, curved flagella that were distributed all over the cell surface. The flgA2− strain produced straight flagella, mainly found at the poles. The flgB− mutant had flagella of the same size and spiral shape as wild‐type cells, but these cells also showed unusual outgrowths, which appeared to be sacs filled with basal body‐like structures. In broth cultures of this mutant, the medium accumulated flagella with basal body‐like structures at their ends.

Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition

An approach to infer the unknown microbial population structure within a metagenome is to cluster nucleotide sequences based on common patterns in base composition, otherwise referred to as binning. When functional roles are assigned to the identified populations, a deeper understanding of microbial communities can be attained, more so than gene-centric approaches that explore overall functionality. In this study, we propose an unsupervised, model-based binning method with two clustering tiers, which uses a novel transformation of the oligonucleotide frequency-derived error gradient and GC content to generate coarse groups at the first tier of clustering; and tetranucleotide frequency to refine these groups at the secondary clustering tier. The proposed method has a demonstrated improvement over PhyloPythia, S-GSOM, TACOA and TaxSOM on all three benchmarks that were used for evaluation in this study. The proposed method is then applied to a pyrosequenced metagenomic library of mud volcano sediment sampled in southwestern Taiwan, with the inferred population structure validated against complementary sequencing of 16S ribosomal RNA marker genes. Finally, the proposed method was further validated against four publicly available metagenomes, including a highly complex Antarctic whale-fall bone sample, which was previously assumed to be too complex for binning prior to functional analysis.