I V Astrakhantseva, D S Campo, A Araujo, C-G Teo, Y Khudyakov, S Kamili
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引用次数: 22
Abstract
Distinguishing between acute and chronic HCV infections is clinically important given that early treatment of infected patients leads to high rates of sustained virological response. Analysis of 2179 clonal sequences derived from hypervariable region 1 (HVR1) of the HCV genome in samples obtained from patients with acute (n = 49) and chronic (n = 102) HCV infection showed that intra-host HVR1 diversity was 1.8 times higher in patients with chronic than acute infection. Significant differences in frequencies of 5 amino acids (positions 5, 7, 12, 16 and 18) and the average genetic distances among intra-host HVR1 variants were found using analysis of molecular variance. Differences were also observed in the polarity, volume and hydrophobicity of 10 amino acids (at positions 1, 4, 5, 12, 14, 15, 16, 21, 22 and 29). Based on these properties, a classification model could be constructed, which permitted HVR1 variants from acute and chronic cases to be discriminated with an accuracy of 88%. Progression from acute to chronic stage of HCV infection is accompanied by characteristic changes in amino acid composition of HVR1. Identifying these changes may permit diagnosis of recent HCV infection.
In Silico BiologyComputer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍:
The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.