Unintended spread of a biosafety level 2 recombinant retrovirus

<p>Abstract</p> <p>Background</p> <p>Contamination of vertebrate cell lines with animal retroviruses has been documented repeatedly before. Although such viral contaminants can be easily identified with high sensitivity by PCR, it is impossible to screen for all potential contaminants. Therefore, we explored two novel methods to identify viral contaminations in cell lines without prior knowledge of the kind of contaminant.</p> <p>Results</p> <p>The first hint for the presence of contaminating retroviruses in one of our cell lines was obtained by electron microscopy of exosome-like vesicles released from the supernatants of transfected 293T cells. Random amplification of particle associated RNAs (PAN-PCR) from supernatant of contaminated 293T cells and sequencing of the amplicons revealed several nucleotide sequences showing highest similarity to either murine leukemia virus (MuLV) or squirrel monkey retrovirus (SMRV). Subsequent mass spectrometry analysis confirmed our findings, since we could identify several peptide sequences originating from monkey and murine retroviral proteins. Quantitative PCRs were established for both viruses to test currently cultured cell lines as well as liquid nitrogen frozen cell stocks. Gene fragments for both viruses could be detected in a broad range of permissive cell lines from multiple species. Furthermore, experimental infections of cells negative for these viruses showed that both viruses replicate rapidly to high loads. We decided to further analyze the genomic sequence of the MuLV-like contaminant virus. Surprisingly it was neither identical to MuLV nor to the novel xenotropic MuLV related retrovirus (XMRV) but showed 99% identity to a synthetic retrovirus which was engineered in the 1980s.</p> <p>Conclusion</p> <p>The high degree of nucleotide identity suggests unintended spread of a biosafety level 2 recombinant virus, which could also affect the risk assessment of gene-modified organisms released from contaminated cell cultures. The study further indicates that both mass spectrometry and PAN-PCR are powerful methods to identify viral contaminations in cell lines without prior knowledge of the kind of contaminant. Both methods might be useful tools for testing cell lines before using them for critical purposes.</p

Refining and Developing Features Describing Dementia-related Changes in Structural and Functional Imaging

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Multiple Discriminant Analysis of SPECT Data for Alzheimer’s Disease, Frontotemporal Dementia and Asymptomatic Controls

Multiple discriminant analysis (MDA) is a generalization of the Fisher discriminant analysis (FDA) and makes it possible to discriminate more than two classes by projecting the data onto a subspace. In this work, it was applied to technetium- 99methylcysteinatedimer (99mTc-ECD) SPECT datasets of 10 Alzheimer’s disease (AD) patients, 11 frontotemporal dementia (FTD) patients and 11 asymptomatic controls (CTR). Principal component analysis (PCA) was used for dimensionality reduction, followed by projection of the data onto a discrimination plane via MDA. In order to separate the different groups, linear boundaries were calculated by applying FDA to two classes at a time (linear machine). By executing the F-test for different numbers of principal components and examining the corresponding classification accuracy, an optimal discrimination plane based on the first three principal components was determined. In order to further assess the method, another dataset comprising patients with early-onset AD and FTD (beginning or suspected disease) was projected by the same method onto this discrimination plane, resulting in a correct classification for most cases. The successful iscrimination of another dataset on the same plane indicates that the model is well suited to account fordisease-specific characteristics within the classes, even for patients with early-onset AD and FTD