- Methodology article
- Open Access
Acquisition of genome information from single-celled unculturable organisms (radiolaria) by exploiting genome profiling (GP)
© Kouduka et al; licensee BioMed Central Ltd. 2006
- Received: 09 December 2005
- Accepted: 02 June 2006
- Published: 02 June 2006
There is no effective method to obtain genome information from single-celled unculturable organisms such as radiolarians. Even worse, such organisms are often very difficult to collect. Sequence analysis of 18S rDNA has been carried out, but obtaining the data has been difficult and it has provided a rather limited amount of genome information. In this paper, we have developed a method which provides a sufficient amount of data from an unculturable organism. The effectiveness of this method was demonstrated by applying it to the provisional classification of a set of unculturable organisms (radiolarians).
Dendrogram was drawn regarding the single-celled unculturable species based on the similarity score termed PaSS, offering a consistent result with the conventional taxonomy of them built up based on phenotypes. This fact has shown that genome profiling-based technology developed here can obtain genome information being sufficient for identifying and classifying species from a single-celled organism.
Since this method is so simple, general, and yet powerful, it can be applied to various organisms and cells, especially single-celled, uncluturable ones, for their genome analysis.
- Genome Profile
- Unculturable Organism
- Group Average Method
- Alkaline Extraction Method
- Double Stranded State
Even in the post-genomic era, genome information is often difficult to obtain. This is especially true for organisms that are difficult to collect due to the extremes of their living environment. Radiolaria are protozoa used in the study of geology and environmental and ecological sciences because they leave a fossil of hard skeletal material that can provide a record of more than 500 million years. Studies on Radiolaria have progressed since the early work by Haeckel [1, 2], which was based on phenotypic analysis. The diverse shapes of their skeletons have been useful characteristics for the identification of species. However, there is a need to obtain genomic information about these organisms in order to more fully understand their diversity and phylogeny. Recently, the gene encoding a small subunit of ribosomal RNA (18S rDNA) has been used for classifying species of Radiolaria, which are taxonomically controversial [3–5]. This is by no means an easy task not only because of the difficulty in collecting samples, but also the additional complication that each organism is composed of only a single cell, and methods for culturing Radiolaria in the laboratory are not available. This means that only a single set of genomic DNA molecules can be obtained for experiments such as PCR. Species identification and/or classification from a single cell has an ultimate value for various purposes: genome analysis of precious specimens using only a minute fraction of the available sample or tracing alterations in the genome of somatic cells (e.g., differences between the genomes of the cells from the brain and heart). It will be also useful for settling controversial classification problems regarding Radiolarian . The sequence information obtained from 18 S rDNA is often insufficient to identify and classify species in detail, wanting a method which can provide a more amount of information. This challenge is addressed in this paper: the authors developed a general way to obtain genome information from a single cell. For this purpose, a triple-session of random PCR was successfully employed. The experimental results obtained by genome profiling (GP) [7–10] of a group of Radiolaria gave consistent data from a taxonomical viewpoint. The authenticity of the results, including sequence analysis data, is extensively discussed.
Experimental materials and genome profiling
Organisms used in this study and their taxonomic classification
A species belonging to Acantharia$
A species belonging to Foraminifera$
A species belonging to Phaeodaria$
A species belonging to Phaeodaria$
A species belonging to Diatomophyceae$
Escherichia coli (S26)
PaSS and clustering analyses
Distance between the constituent elements at each taxon measured with PaSS.
0.656 (± 0.034)
0.761 (± 0.090)
0.782 (± 0.056)
0.822 (± 0.034)
Reliability tested by sequencing
Since there are no published genome sequences for any radiolarians or related organisms, the results obtained here must be critically evaluated based on other available information. Currently, the most common approach is to sequence the 18S rDNA; however, it is very difficult to carry out both GP and 18S rDNA sequencing experiments with single-celled and unculturable organisms (only a single copy of each DNA molecule is available). However, anyhow, we tried to amplify the 18S rDNA genes with specific PCR primers (see Materials and Methods) using the template DNA used for GP as the template (which, naturally, contations random PCR products also). We were not always able to amplify the target molecule (18S rDNA). This may be due to a stochastic or inevitable loss of the template DNA when dealing with a single copy. Though we can expect least to obtain 18S rDNA from the mixture of DNAs obtains after genome profiling, DNA molecules amplified using the primers designed for 18S rDNA from the genome of one sample (Dictyocoryne profunda) happened to have around the expected molecular size (200 bp) and were sequenced. After searching the database (DDBJ) with FASTA, the sequence obtained was found not to be the same as any of those reported to date (data not shown). Sequences currently in the database included Didymocyrtis tetrathalamus, Dictyocoryne profunda, and Dictyocoryne truncatum. In addition to these, Acantharea (11 entries), Phaeodarea (3 entries), Polycystinea (20 entries) have been reported. The results of our analysis are as follows: i) the sequence obtained was so novel that it had not been reported previously, ii) it had the highest similarity (66.7 %) with partial 18S rDNA of a protozoan, Euglena spathirhyncha, iii) none of the small subunit ribosomal DNA sequences of organisms that might be expected as contaminants, such as algae, planktonic organisms, fungi or bacteria were highly ranked within the top 200 sequences. Therefore, although the result could not be reproducibly tested, as the same genome cannot be obtained again, it is very plausible that the DNA sequence we obtained and used for GP analysis was that of a Radiolarian 18S rDNA that had never been sequenced. At the same time, we also sequenced the random PCR products of samples A2, A3-1, 2, B, D-1 and others (70 reads in total, 305 nucleotides on average; data not shown) and found that: i) the sequences obtained were quite novel with no registered sequences having more than 70 % similarity except one E. coli sequence (99 % similarity) and two algae sequences (81 % and 77 % similarities), and ii) according to the FASTA search, sequences with the highest similarity with the query sequences were not those of probable contaminants but those of protozoa, which are related to Radiolaria. According to the first finding, an accidental contamination of E. coli DNA must have happened during the experiment. It may also mean that some of our samples were contaminated with algae. However, since they are not major representatives in the sequencing results for 70 clones, they must not have contributed significantly to the spiddos generated in the GP experiments. It is already known that a minor population of DNAs can not be represented in GP unless they have exceptionally strong binding sites for a primer or highly repetitive sequences that can be amplified by random PCR. Therefore, these findings provide supporting evidence that the random PCR products were derived from the genomes of Radiolaria.
In conclusion, the results presented here, including the data indicating that GPs of Radiolarians provided a taxonomically-consistent clustering result (Figs. 2 and 3), indicate that genome profiles for Radiolarians can be obtained from a single cell. Here, we need to recall the fact that GPs obtained here may consist of composite genomes, e.g., those of host and parasitic/symbiotic organisms which can not be observed by the conventional microscopic techniques (though employing more sophisticated technologies such as SEM will make it possible). In other words, some of GPs reported here may represent a metagenome, or 'an ensemble of genomes' (originally, GP was developed based on the idea that the genome is the whole ensemble of DNAs contained in a cell ). If so, it is reasonable to register such GPs as being representative of Radiolaria since we cannot separate the symbiotic genomes effectively, and this type of partnership is often permanent. We think this fact dose not devaluate the methodology established here.
In this paper we developed a potent method to obtain genome information from unculturable and single-celled organisms. This was demonstrated by the experiments applied to radiolarians sampled in the field. Final confirmation can only be obtained by the repeating similar experiments using other fresh experimental materials. Therefore, the classification reported here should be considered to be rather tentative, but the GP method shows promise for solving controversial classification problems. We believe this is the first success in which the genomes of unculturable, single-celled organisms were treated quantitatively and systematically to extract genomic information for comparison.
DNA of radiolarians and the other organisms
The samples of protozoa were collected from surface seawater during 2003–2005. Protozoa, such as species belonging to Phaeodaria and Acantharia, Foraminifera, and Diatomophyceae were obtained from the shores off of Sado Island, Japan. Radiolarians, including Dictyocoryne truncatum, Dictyocoryne profunda, Didymocyrtis tetrathalamus, Spongaster tetras, Dictyocoryne truncatum, Eucyrtidium hexasticum, Hymeniastrum euclidis were from the shores off of Okinawa Island, Japan. The collected organisms are listed in Table 1 with their taxonomical classification and sampling date and location. Photomicrographs of some of the organisms are shown in Fig. 1a. The plankton-net collected microbes were dissolved in sterile water. Then we prepared each organism as a single cell by sucking it together with a small aliquot(less than 1 μl including a cell) under the microscopic view without contaminating the other visible organisms and diluted it with pure alcohol of more than 1 ml. An aliquot (1 μl) of this solution which contains the cell was used for PCR. Thus, the sample cells used here were microscopically pure but it can not rule out the possibility of being contaminated with intracellular organisms (symbionts) or externally invisible virus-like organisms (though its probability is less than a millionth of that of finding in the original sea water due to the repeated dilution). The other organisms dealt here (Saccharomyces cerevisiae, Escherichia coli, and Bacillus subtilis) were reported previously [10, 13].
Each sample was purified by picking up a single-cell in an aliquot. Preparation of DNA was carried out by the alkaline extraction method . Briefly, the procedures adopted here are as follows: 1) An aliquot containing a single cell which had been identified by phenotype under the microscope was transferred into an Eppendorf tube; 2) After adding 3 μl of 0.5 M NaOH, the sample solution was incubated at 94°C for 5 min and then at 64°C for 60 min; 3) the sample solution was neutralized with 5 μl of 200 mM Tris-HCl (pH 8.0) buffer, and incubated at 65°C.
Genome profiling (GP)
Spiddos and PaSS
Genome profiles obtained by GP are highly informative but difficult to manage due to their complexity. However, this inconvenience was overcome by introducing the featuring points, designated as spiddos (species identification dots), which can represent genome profiles compactly . The featuring points, or spiddos, correspond to the points where structural transitions of DNA occur, such as double-stranded to single-stranded DNA . Spiddos can be used to provide a sufficient amount of information for identifying species . One can easily increase the amount of information about the genome by adding spiddos obtained by another GP operated with a different primer. Because the number of possible primers is so large (1.6 × 107 for dodecanucleotides), many GPs (thus, spiddos) can be obtained if necessary. Using spiddos, we can define the pattern similarity score (PaSS) of the genomes between two species as follows:
where and correspond to the normalized positional vectors (composed of two elements, mobility and temperature) for spiddos Pi and Pi' collected from two genome profiles (discriminated with or without a prime), respectively, and i denotes the serial number of spiddos. A database site has been constructed (On-web GP ) in order to provide semi-automatic data processing . The PaSS value thus obtained is empirically known to be a good measure to quantify the closeness between two species (or cells) .
After calculating the average PaSS value (), a representative PaSS value for a particular level of taxon T, was obtained over the constituents at a particular level of taxon using the following equations.
The group average method  was used for the clustering analysis of the genomes of the organisms examined here. With this method, a separate element is integrated into a cluster if the distance is smaller than or equal to a finite value between the element and at least one member of the cluster.
Sequencing and FASTA analysis
Some of the random PCR products (DNA) were cloned and analyzed by sequencing. In addition, a part of the 18S rDNA was subjected to sequencing. This product was obtained by PCR-amplification using the mixture of random PCR products plus the template genome DNA as a template source and the primers, F (GAGGGCAAGTCTGGT) and R (ACGACGGTATCTGAT), which were designed as in the preceding study . The sequencing was done by adopting the TA cloning method (Invitrogen, Carlsbad, California, USA). The DNA sequencer, DSQ-2000L (Shimadzu, Kyoto, Japan) was used for this purpose. Experimentally obtained DNA sequences were analyzed with FASTA against all of the genomes and genes in the database. DNA segments of more than 55 % similarity were carefully analyzed based on their annotations so as to determine the source of the DNA sequences.
Authors are grateful for the technical assistance of Mohammed Naimuddin, Takehiro Watanabe, Ayumu Saito and Daisuke Sato. This study was supported in part by the grant REDS (Project of the Saitama Prefecture Collaboration of Regional Entities for the Advancement of Technological Excellence supported by JST) and also by a Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology, Japan (no. 17654100).
- Haeckel E: Report on the Radiolaria collected by HMS Challenger during the years 1873–1876. Rep Sci Res. 1887, 18: 1-1803. Voyage HMS Challenger 1873–1876 ZoolGoogle Scholar
- Yasugi R, Koseki O, Hurutani M, Hidaka T: Iwanami Biology Encyclopedia. 1996, Tokyo, Japan: Iwanami Press, 4Google Scholar
- Gast RJ, Caron DA: Molecular Phylogeny of Symbiotic Dinoflagellates from Planktonic Foraminifera and Radiolaria. Mol Biol Evol. 1996, 13: 1192-1197.PubMedView ArticleGoogle Scholar
- Gutell RR, Larsen N, Woese CR: Lessons from an evolving rRNA: 16S and 23S rRNA structures from a comparative perspective. Microbiol Rev. 1994, 58: 10-26.PubMedPubMed CentralGoogle Scholar
- Zettler LA, Sogin ML, Caron DA: Phylogenetic relationships between the Acantharea and the Polycystinea: A molecular perspective on Haeckel's Radiolaria. Proc Natl Acad Sci USA. 1997, 94: 11411-11416. 10.1073/pnas.94.21.11411.PubMedPubMed CentralView ArticleGoogle Scholar
- Polet S, Berney C, Fahrni J, Pawlowski J: Small-Subunit Ribosomal RNA Gene Sequences of Phaeodarea Challenge the Monophyly of Haeckel's Radiolaria. Protist. 2004, 155: 53-63. 10.1078/1434461000164.PubMedView ArticleGoogle Scholar
- Hamano K, Takasawa T, Kurazono T, Okuyama Y, Nishigaki K: Genome Profiling-Establishment and practical evaluation of its methodology. Nikkashi. 1996, 1996: 54-61.Google Scholar
- Nishigaki K, Amano N, Takasawa T: DNA Profiling: An approach of systematic characterization, classification, and comparison of genomic DNAs. Chem Lett. 1991, 1991: 1097-1100. 10.1246/cl.1991.1097.View ArticleGoogle Scholar
- Nishigaki K, Naimuddin M, Hamano K: Genome profiling: a realistic solution for genotype-based identification of species. J Biochem. 2000, 128: 107-112.PubMedView ArticleGoogle Scholar
- Nishigaki K, Saito A, Hasegawa T, Naimuddin M: Whole genomesequence-enabled prediction of sequences performed for random PCR products of Escherichia coli. Nucleic Acids Res. 2000, 28: 1879-1884. 10.1093/nar/28.9.1879.PubMedPubMed CentralView ArticleGoogle Scholar
- Biyani M, Nishigaki K: Hundredfold productivity of genome analysis by introduction of microtemperature-gradient gel electrophoresis. Electrophoresis. 2001, 22: 23-28. 10.1002/1522-2683(200101)22:1<23::AID-ELPS23>3.0.CO;2-Z.PubMedView ArticleGoogle Scholar
- Naimuddin M, Kurazono T, Nishigaki K: Commonly conserved genetic fragments revealed by genome profiling can serve as tracers of evolution. Nucleic Acids Res. 2002, 30 (10): e42-10.1093/nar/30.10.e42.PubMedPubMed CentralView ArticleGoogle Scholar
- Naimuddin M, Kurazono T, Zhangc Y, Watanabe T, Yamaguchi M, Nishigaki K: Species-identification dots: a potent tool for developing genome microbiology. Gene. 2000, 261: 243-250. 10.1016/S0378-1119(00)00502-3.PubMedView ArticleGoogle Scholar
- Downs GM: Barnard, J. M. Clustering Methods and Their Uses in Computational Chemistry. Reviews in Computational Chemistry. 2002, Wiley: Hoboken, NJ, 18: 11-Google Scholar
- Anderson OR: Radiolaria. 1983, New York: Springer-VerlagView ArticleGoogle Scholar
- Nikolaev SI, Berney C, Fahrni JF, Bolivar I, Polet S, Mylnikov AP, Aleshin VV, Petrov NB, Pawlowski J: The twilight of Heliozoa and rise of Rhizaria, an emerging supergroup of amoeboid eukaryotes. Proc Natl Acad Sci USA. 2004, 101 (21): 8066-10.1073/pnas.0308602101.PubMedPubMed CentralView ArticleGoogle Scholar
- Naimuddin M, Nishigaki K: Genome analysis technologies toward species identification by genotype. Brief Fune Genomics Proteomics. 2003, 1: 356-71. 10.1093/bfgp/1.4.356.View ArticleGoogle Scholar
- Wang H, Qin M, Cutler AJ: A simple method of preparing plant samples for PCR. Nucleic Acids Res. 1993, 21: 4153-4154.PubMedPubMed CentralView ArticleGoogle Scholar
- Nishigaki K, Husimi Y, Masuda M, Kaneko K, Tanaka T: Strand dissociation and cooperative melting of double-stranded DNAs detected by denaturant gradient gel electrophoresis. J Biochem. 1984, 95: 627-35.PubMedGoogle Scholar
- On-web GP. [http://gp.fms.saitama-u.ac.jp/]
- Watanabe T, Saito A, Takeuchi Y, Naimuddin M, Nishigaki K: A database for the provisional identification of species using only genotypes: web-based genome profiling. Genome Biol. 2002, 3: 00101.1-10.1186/gb-2002-3-2-research0010.View ArticleGoogle Scholar
- Voet D, Voet J: Biochemistry. 1995, J Wiley & Sons, New York: NY, 2Google Scholar
- Madigan MT, Martinko JM, Parker J: Brock biology of microorganisms. 1997, Prentice-Hall, Inc., Upper Saddle River, NJ, 8Google Scholar
- NCBI PubMed – Entrez Taxonomy. [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?CMD=Limits&DB=taxonomy]
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