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. 2007 Jan;38(1):19-26.
doi: 10.1016/j.jcv.2006.10.001. Epub 2006 Nov 16.

Characterizing 56 complete SARS-CoV S-gene sequences from Hong Kong

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Characterizing 56 complete SARS-CoV S-gene sequences from Hong Kong

Julian W Tang et al. J Clin Virol. 2007 Jan.

Abstract

Background: The spike glycoprotein (S) gene of the severe acute respiratory syndrome-associated coronavirus (SARS-CoV) has been useful in analyzing the molecular epidemiology of the 2003 SARS outbreaks.

Objectives: To characterize complete SARS-CoV S-gene sequences from Hong Kong.

Study design: Fifty-six SARS-CoV S-gene sequences, obtained from patients who presented with SARS to the Prince of Wales Hospital during March-May 2003, were analysed using a maximum likelihood (ML) approach, together with 138 other (both human and animal) S-gene sequences downloaded from GenBank.

Results: The maximum-likelihood (ML) trees showed little evolution occurring within these 56 sequences. Analysis with the other sequences, showed three distinct SARS clusters, closely correlated to previously defined early, middle and late phases of the 2003 international SARS outbreaks. In addition, two new single nucleotide variations (SNVs), T21615A and T21901A, were discovered, not previously reported elsewhere.

Conclusions: The ML approach to the reconstruction of tree phylogenies is known to be superior to the more popular, less computationally and time-demanding neighbour-joining (NJ) approach. The ML analysis in this study confirms the previously reported SARS epidemiology analysed mostly using the NJ approach. The two new SNVs reported here are most likely due to the tissue-culture passaging of the clinical samples.

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Figures

Fig. 1
Fig. 1
Maximum likelihood phylogram of the SARS-CoV S-gene from 56 Hong Kong patients. Note: Constructed under a Kimura three-parameters with unequal base frequencies (K81uf) model of evolution with invariable (I) sites and a gamma (G) distributed rate of substitution (i.e. K81uf + I + G), as selected by Modeltest (v3.7) under the Akaike Information Criteria (AIC), using a nearest-neighbor interchange (NNI) heuristic search strategy in PAUP*. The dates in the sample names are dates of fever onset for that patient. The scale for the branch lengths is indicated (number of nucleotide substitutions per site). There were no branches with bootstrap values >70. GenBank accession numbers for the 56 S-gene sequences: DQ412574–DQ412629. CUHK: Chinese University of Hong Kong; TC: tissue cultured isolate; CS: clinical sample; NP: nasopharyngeal aspirate; UR: urine; NS: nasal swab; SP: sputum; ST: stool; TS: throat swab; RS: rectal swab; TG: throat gargle; TI: terminal ileal biopsy; RL: right lung biopsy; L: lung biopsy.
Fig. 2
Fig. 2
Maximum likelihood phylogram of the SARS-CoV S-gene from 56 Hong Kong samples and 138 downloaded S-gene sequences from GenBank. Note: Constructed under a Kimura three-parameters with unequal base frequencies (K81uf) model of evolution with invariable (I) sites and a gamma (G) distributed rate of substitution (i.e. K81uf + I + G), as selected by Modeltest (v3.7) under the Akaike Information Criteria (AIC), using a nearest-neighbor interchange (NNI) heuristic search strategy in PAUP*. The dates in the Hong Kong sample names are dates of fever onset for that patient, from whom the sample was taken. The scale for the branch lengths is indicated (number of nucleotide substitutions per site). The boxes highlight branches containing samples showing significant differences in their S-gene sequences from the rest of the group. Cluster 1: ‘mainland’ (solid-line box); cluster 2: ‘Guangdong’ (long-dashed line box); cluster 3: ‘worldwide’ (short-dotted line box). CUHK: Chinese University of Hong Kong; TC: tissue cultured isolate; CS: clinical sample; NP: nasopharyngeal aspirate; UR: urine; NS: nasal swab; SP: sputum; ST: stool; TS: throat swab; RS: rectal swab; TG: throat gargle; TI: terminal ileal biopsy; RL: right lung biopsy; L: lung biopsy. The names of the downloaded sequences from GenBank have been retained as far as possible, though some truncation has been applied in some cases.
Fig. 2
Fig. 2
Maximum likelihood phylogram of the SARS-CoV S-gene from 56 Hong Kong samples and 138 downloaded S-gene sequences from GenBank. Note: Constructed under a Kimura three-parameters with unequal base frequencies (K81uf) model of evolution with invariable (I) sites and a gamma (G) distributed rate of substitution (i.e. K81uf + I + G), as selected by Modeltest (v3.7) under the Akaike Information Criteria (AIC), using a nearest-neighbor interchange (NNI) heuristic search strategy in PAUP*. The dates in the Hong Kong sample names are dates of fever onset for that patient, from whom the sample was taken. The scale for the branch lengths is indicated (number of nucleotide substitutions per site). The boxes highlight branches containing samples showing significant differences in their S-gene sequences from the rest of the group. Cluster 1: ‘mainland’ (solid-line box); cluster 2: ‘Guangdong’ (long-dashed line box); cluster 3: ‘worldwide’ (short-dotted line box). CUHK: Chinese University of Hong Kong; TC: tissue cultured isolate; CS: clinical sample; NP: nasopharyngeal aspirate; UR: urine; NS: nasal swab; SP: sputum; ST: stool; TS: throat swab; RS: rectal swab; TG: throat gargle; TI: terminal ileal biopsy; RL: right lung biopsy; L: lung biopsy. The names of the downloaded sequences from GenBank have been retained as far as possible, though some truncation has been applied in some cases.

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