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Large-scale evolutionary surveillance of the 2009 H1N1 influenza A virus using resequencing arrays.

Lee CW, Koh CW, Chan YS, Aw PP, Loh KH, Han BL, Thien PL, Nai GY, Hibberd ML, Wong CW, Sung WK - Nucleic Acids Res. (2010)

Bottom Line: The accompanying base-calling software (EvolSTAR) introduces novel methods that utilize neighbourhood hybridization intensity profiles and substitution bias of probes on the microarray for mutation confirmation and recovery of ambiguous base queries.Our results demonstrate that EvolSTAR is highly accurate and has a much improved call rate.The high throughput and short turn-around time from sample to sequence and analysis results (30 h for 24 samples) makes this kit an efficient large-scale evolutionary biosurveillance tool.

View Article: PubMed Central - PubMed

Affiliation: Genome Institute of Singapore, Genome, 60 Biopolis Street, Singapore.

ABSTRACT
In April 2009, a new influenza A (H1N1 2009) virus emerged that rapidly spread around the world. While current variants of this virus have caused widespread disease, particularly in vulnerable groups, there remains the possibility that future variants may cause increased virulence, drug resistance or vaccine escape. Early detection of these virus variants may offer the chance for increased containment and potentially prevention of the virus spread. We have developed and field-tested a resequencing kit that is capable of interrogating all eight segments of the 2009 influenza A(H1N1) virus genome and its variants, with added focus on critical regions such as drug-binding sites, structural components and mutation hotspots. The accompanying base-calling software (EvolSTAR) introduces novel methods that utilize neighbourhood hybridization intensity profiles and substitution bias of probes on the microarray for mutation confirmation and recovery of ambiguous base queries. Our results demonstrate that EvolSTAR is highly accurate and has a much improved call rate. The high throughput and short turn-around time from sample to sequence and analysis results (30 h for 24 samples) makes this kit an efficient large-scale evolutionary biosurveillance tool.

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Visualization map of a 2009 influenza A(H1N1) virus with artificial reassortment of H3N2 segment 4. Visualization map of a 2009 influenza A(H1N1) virus with artificial reassortment of H3N2 segment 4. We independently amplified segments 1, 2, 3, 5, 6 and 7 of the 2009 influenza A(H1N1) virus and segment 4 of a H3N2 influenza A virus, and hybridized them onto our array. As expected, the sequence call for segment 4 [based on PM/MM probes from the segment 4 consensus of the 2009 influenza A(H1N1) virus] is poor in quality and coverage.
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Figure 9: Visualization map of a 2009 influenza A(H1N1) virus with artificial reassortment of H3N2 segment 4. Visualization map of a 2009 influenza A(H1N1) virus with artificial reassortment of H3N2 segment 4. We independently amplified segments 1, 2, 3, 5, 6 and 7 of the 2009 influenza A(H1N1) virus and segment 4 of a H3N2 influenza A virus, and hybridized them onto our array. As expected, the sequence call for segment 4 [based on PM/MM probes from the segment 4 consensus of the 2009 influenza A(H1N1) virus] is poor in quality and coverage.

Mentions: Although we are confident that our resequencing array can successfully generate complete sequences for the H1N1(2009) virus and its variants at the current stage, we cannot rule out the possibility of reassortments between the H1N1(2009) virus and other influenza viruses. Clearly, our resequencing array cannot fully sequence such events and will generate sequences with poor quality and coverage of the reassorted segments. To investigate the effects of a reassortment event on our array, we independently amplified segments 1, 2, 3, 5, 6 and 7 of the 2009 influenza A(H1N1) virus and segment 4 of a H3N2 influenza A virus, and hybridized them onto our array. The visualization map of this experiment is shown in Figure 9. As expected, the sequence call for segment 4 [based on PM/MM probes from the segment 4 consensus of the 2009 influenza A(H1N1) virus] is poor in quality and coverage. However, we observed that we were able to get good base calls from region 1150–1547. This region turns out to be the only significantly similar (70% matched) region between the segment 4 consensus of the 2009 influenza A(H1N1) virus and segment 4 of a H3N2 virus (CY039087). This shows that identifying regions of high similarity between the 2009 influenza A(H1N1) virus with other influenza viruses and checking if these regions have good sequence calls may be a plausible way of detecting reassortments. The drawback of this approach is that it will fail to detect reassortment of certain segments where there are no regions of high similarity between the H1N1(2009) virus and the parental influenza virus. It is also difficult to annotate and differentiate every region that the H1N1(2009) virus and all other influenza viruses share similarity with. We propose an alternative approach to detect reassortments. By analysing the PM/MM hybridization intensity fold-change of high confidence calls of all eight segments, we found that the average PM/MM hybridization intensity fold-change of high confidence calls in segments 1, 2, 3, 5, 6 and 7 belonging to the 2009 influenza A(H1N1) virus is ∼4.5 while the average PM/MM hybridization intensity fold-change of high confidence calls in segment 4 belonging to the H3N2 influenza A virus is only 1.9. The most likely reason for this huge drop in the average PM/MM hybridization intensity fold-change of high confidence calls is that the signal gained by most of the segment 4 PM probes on our array are through cross-hybridization to the segment 4 sequence of the H3N2 influenza A virus, and thus much lower than signal gained from true specific binding. Thus, by computing and comparing the average PM/MM hybridization intensity fold-change of high confidence calls in each segment, we can identify potential reassortments in a given H1N1(2009) virus sample. Virus samples with possible reassortments can then be sequenced using capillary sequencing or customized reassortment resequencing arrays.Figure 9.


Large-scale evolutionary surveillance of the 2009 H1N1 influenza A virus using resequencing arrays.

Lee CW, Koh CW, Chan YS, Aw PP, Loh KH, Han BL, Thien PL, Nai GY, Hibberd ML, Wong CW, Sung WK - Nucleic Acids Res. (2010)

Visualization map of a 2009 influenza A(H1N1) virus with artificial reassortment of H3N2 segment 4. Visualization map of a 2009 influenza A(H1N1) virus with artificial reassortment of H3N2 segment 4. We independently amplified segments 1, 2, 3, 5, 6 and 7 of the 2009 influenza A(H1N1) virus and segment 4 of a H3N2 influenza A virus, and hybridized them onto our array. As expected, the sequence call for segment 4 [based on PM/MM probes from the segment 4 consensus of the 2009 influenza A(H1N1) virus] is poor in quality and coverage.
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Figure 9: Visualization map of a 2009 influenza A(H1N1) virus with artificial reassortment of H3N2 segment 4. Visualization map of a 2009 influenza A(H1N1) virus with artificial reassortment of H3N2 segment 4. We independently amplified segments 1, 2, 3, 5, 6 and 7 of the 2009 influenza A(H1N1) virus and segment 4 of a H3N2 influenza A virus, and hybridized them onto our array. As expected, the sequence call for segment 4 [based on PM/MM probes from the segment 4 consensus of the 2009 influenza A(H1N1) virus] is poor in quality and coverage.
Mentions: Although we are confident that our resequencing array can successfully generate complete sequences for the H1N1(2009) virus and its variants at the current stage, we cannot rule out the possibility of reassortments between the H1N1(2009) virus and other influenza viruses. Clearly, our resequencing array cannot fully sequence such events and will generate sequences with poor quality and coverage of the reassorted segments. To investigate the effects of a reassortment event on our array, we independently amplified segments 1, 2, 3, 5, 6 and 7 of the 2009 influenza A(H1N1) virus and segment 4 of a H3N2 influenza A virus, and hybridized them onto our array. The visualization map of this experiment is shown in Figure 9. As expected, the sequence call for segment 4 [based on PM/MM probes from the segment 4 consensus of the 2009 influenza A(H1N1) virus] is poor in quality and coverage. However, we observed that we were able to get good base calls from region 1150–1547. This region turns out to be the only significantly similar (70% matched) region between the segment 4 consensus of the 2009 influenza A(H1N1) virus and segment 4 of a H3N2 virus (CY039087). This shows that identifying regions of high similarity between the 2009 influenza A(H1N1) virus with other influenza viruses and checking if these regions have good sequence calls may be a plausible way of detecting reassortments. The drawback of this approach is that it will fail to detect reassortment of certain segments where there are no regions of high similarity between the H1N1(2009) virus and the parental influenza virus. It is also difficult to annotate and differentiate every region that the H1N1(2009) virus and all other influenza viruses share similarity with. We propose an alternative approach to detect reassortments. By analysing the PM/MM hybridization intensity fold-change of high confidence calls of all eight segments, we found that the average PM/MM hybridization intensity fold-change of high confidence calls in segments 1, 2, 3, 5, 6 and 7 belonging to the 2009 influenza A(H1N1) virus is ∼4.5 while the average PM/MM hybridization intensity fold-change of high confidence calls in segment 4 belonging to the H3N2 influenza A virus is only 1.9. The most likely reason for this huge drop in the average PM/MM hybridization intensity fold-change of high confidence calls is that the signal gained by most of the segment 4 PM probes on our array are through cross-hybridization to the segment 4 sequence of the H3N2 influenza A virus, and thus much lower than signal gained from true specific binding. Thus, by computing and comparing the average PM/MM hybridization intensity fold-change of high confidence calls in each segment, we can identify potential reassortments in a given H1N1(2009) virus sample. Virus samples with possible reassortments can then be sequenced using capillary sequencing or customized reassortment resequencing arrays.Figure 9.

Bottom Line: The accompanying base-calling software (EvolSTAR) introduces novel methods that utilize neighbourhood hybridization intensity profiles and substitution bias of probes on the microarray for mutation confirmation and recovery of ambiguous base queries.Our results demonstrate that EvolSTAR is highly accurate and has a much improved call rate.The high throughput and short turn-around time from sample to sequence and analysis results (30 h for 24 samples) makes this kit an efficient large-scale evolutionary biosurveillance tool.

View Article: PubMed Central - PubMed

Affiliation: Genome Institute of Singapore, Genome, 60 Biopolis Street, Singapore.

ABSTRACT
In April 2009, a new influenza A (H1N1 2009) virus emerged that rapidly spread around the world. While current variants of this virus have caused widespread disease, particularly in vulnerable groups, there remains the possibility that future variants may cause increased virulence, drug resistance or vaccine escape. Early detection of these virus variants may offer the chance for increased containment and potentially prevention of the virus spread. We have developed and field-tested a resequencing kit that is capable of interrogating all eight segments of the 2009 influenza A(H1N1) virus genome and its variants, with added focus on critical regions such as drug-binding sites, structural components and mutation hotspots. The accompanying base-calling software (EvolSTAR) introduces novel methods that utilize neighbourhood hybridization intensity profiles and substitution bias of probes on the microarray for mutation confirmation and recovery of ambiguous base queries. Our results demonstrate that EvolSTAR is highly accurate and has a much improved call rate. The high throughput and short turn-around time from sample to sequence and analysis results (30 h for 24 samples) makes this kit an efficient large-scale evolutionary biosurveillance tool.

Show MeSH
Related in: MedlinePlus