Analysis of 454 sequencing error rate, error sources, and artifact recombination for detection of Low-frequency drug resistance mutations in HIV-1 DNA.

BACKGROUND: 454 sequencing technology is a promising approach for characterizing HIV-1 populations and for identifying low frequency mutations. The utility of 454 technology for determining allele frequencies and linkage associations in HIV infected individuals has not been extensively investigated. We evaluated the performance of 454 sequencing for characterizing HIV populations with defined allele frequencies. RESULTS: We constructed two HIV-1 RT clones. Clone A was a wild type sequence. Clone B was identical to clone A except it contained 13 introduced drug resistant mutations. The clones were mixed at ratios ranging from 1% to 50% and were amplified by standard PCR conditions and by PCR conditions aimed at reducing PCR-based recombination. The products were sequenced using 454 pyrosequencing. Sequence analysis from standard PCR amplification revealed that 14% of all sequencing reads from a sample with a 50:50 mixture of wild type and mutant DNA were recombinants. The majority of the recombinants were the result of a single crossover event which can happen during PCR when the DNA polymerase terminates synthesis prematurely. The incompletely extended template then competes for primer sites in subsequent rounds of PCR. Although less often, a spectrum of other distinct crossover patterns was also detected. In addition, we observed point mutation errors ranging from 0.01% to 1.0% per base as well as indel (insertion and deletion) errors ranging from 0.02% to nearly 50%. The point errors (single nucleotide substitution errors) were mainly introduced during PCR while indels were the result of pyrosequencing. We then used new PCR conditions designed to reduce PCR-based recombination. Using these new conditions, the frequency of recombination was reduced 27-fold. The new conditions had no effect on point mutation errors. We found that 454 pyrosequencing was capable of identifying minority HIV-1 mutations at frequencies down to 0.1% at some nucleotide positions. CONCLUSION: Standard PCR amplification results in a high frequency of PCR-introduced recombination precluding its use for linkage analysis of HIV populations using 454 pyrosequencing. We designed a new PCR protocol that resulted in a much lower recombination frequency and provided a powerful technique for linkage analysis and haplotype determination in HIV-1 populations. Our analyses of 454 sequencing results also demonstrated that at some specific HIV-1 drug resistant sites, mutations can reliably be detected at frequencies down to 0.1%.

The human papillomavirus type 8 E2 tethering protein targets the ribosomal DNA loci of host mitotic chromosomes.

For many papillomaviruses, the viral protein E2 tethers the viral genome to the host mitotic chromosomes to ensure persistent, long-term maintenance of the genome during cell division. Our previous studies of E2 proteins from different genera of papillomaviruses have shown that they bind to different regions of the host chromosomes during mitosis. For example, bovine papillomavirus type 1 (BPV-1) E2 binds to all chromosomes as small speckles in complex with the cellular protein Brd4. In contrast, the human papillomavirus type 8 (HPV-8) E2 protein binds as large speckles at the pericentromeric regions of chromosomes. Here we show that these speckles do not contain Brd4, and unlike that of BPV-1, the N-terminal Brd4-interacting domain of HPV-8 E2 is not required for chromosome binding. In contrast to BPV-1 E2, the HPV-8 E2 protein targets the short arms of acrocentric mitotic chromosomes. Furthermore, the E2 protein interacts with the repeated ribosomal DNA genes found in this location and colocalizes with UBF, the RNA polymerase I transcription factor. Therefore, HPV-8 E2 genome tethering occurs by a Brd4-independent mechanism through a novel interaction with specific regions of mitotic chromosomes. Thus, a wide range of viruses have adopted the strategy of linking their genomes to host chromosomes, but individual viruses use different chromosomal targets. Characterization of these targets will enable the development of antiviral therapies to eliminate the viral genomes from infected cells.

Dimerization of the papillomavirus E2 protein is required for efficient mitotic chromosome association and Brd4 binding.

The E2 proteins of several papillomaviruses link the viral genome to mitotic chromosomes to ensure retention and the efficient partitioning of genomes into daughter cells following cell division. Bovine papillomavirus type 1 E2 binds to chromosomes in a complex with Brd4, a cellular bromodomain protein. Interaction with Brd4 is also important for E2-mediated transcriptional regulation. The transactivation domain of E2 is crucial for interaction with the Brd4 protein; proteins lacking or mutated in this domain do not interact with Brd4. However, we found that the C-terminal DNA binding/dimerization domain of E2 is also required for efficient binding to Brd4. Mutations that eliminated the DNA binding function of E2 had no effect on the ability of E2 to interact with Brd4, but an E2 protein with a mutation that disrupted C-terminal dimerization bound Brd4 with greatly reduced efficiency. Furthermore, E2 proteins in which the C-terminal domains were replaced with the dimeric DNA binding domain of EBNA-1 or Gal4 bound efficiently to the Brd4 protein, but the replacement of the E2 C-terminal domain with a monomeric red fluorescent protein did not rescue efficient Brd4 binding. Thus, E2 bound to Brd4 most efficiently as a dimer. To prove this finding further, the E2 DNA binding domain was replaced with an FKBP12-derived domain in which dimerization was regulated by a bivalent ligand. This fusion protein bound Brd4 efficiently only in the presence of the ligand, confirming that a dimer of E2 was required. Correspondingly, E2 proteins that could dimerize were able to bind to mitotic chromosomes much more efficiently than monomeric E2 polypeptides.

PAPNC, a novel method to calculate nucleotide diversity from large scale next generation sequencing data.

Estimating viral diversity in infected patients can provide insight into pathogen evolution and emergence of drug resistance. With the widespread adoption of deep sequencing, it is important to develop tools to accurately calculate population diversity from very large datasets. Current methods for estimating diversity that are based on multiple alignments are not practical to apply to such data. In this study, the authors report a novel method (Pairwise Alignment Positional Nucleotide Counting, PAPNC) for estimating population diversity from 454 sequence data. The diversity measurements determined using this method were comparable to those calculated by average pairwise difference (APD) of multiply aligned sequences using MEGA5. Diversities were estimated for 9 patient plasma HIV samples sequenced with Titanium 454 technology and by single-genome sequencing (SGS). Diversities calculated from deep sequencing using PAPNC ranged from 0.002 to 0.021 while APD measurements calculated from SGS data ranged proximately from 0.001 to 0.018, with the difference being attributable to PCR error (contributing background diversity of 0.0016 in a control sample). Comparison of APDs estimated from 100 sets of sequences drawn at random from 454 generated data and from corresponding SGS data showed very close correlation between the two methods with R(2) of 0.96, and differing on average by about 1% (after correction for PCR error). The authors have developed a novel method that is good for calculating genetic diversities for large scale datasets from next generation sequencing. It can be implemented easily as a function in available variation calling programs like SAMtools or haplotype reconstruction software for nucleotide genetic diversity calculation. A Perl script implementing this method is available upon request.