DNA contamination - a pragmatic clinical view

The presence of contaminating gDNA in RNA preparations is a frequent cause of false positives in RT-PCR-based analysis. However, in some cases, this cannot be avoided, especially when there are no exons–intron junctions in the lncRNA sequences. Due to the lack of exons in few of long noncoding RNAs (lncRNAs) and the lack of DNAse treatment step in most studies reported so far, serious questions are raised about the specificity of lncRNA detection and the potential of reporting false-positive results. We hypothesized that minute amounts of gDNA usually co-extracted with RNA could give false-positive signals since primers would specifically bind to gDNA due to the lack of junction. In the current study, we evaluated the effect of gDNA and other forms of DNA like extrachromosomal circular DNAs (eccDNAs) contamination and the importance of including a DNAse treatment step on lncRNAsexpression.As a model, we have chosen as one of the most widely studied lncRNAs in cancer namely MALAT1, which lacks exons. When we tested this hypothesis in plasma and primary tissue samples from NSCLC patients, our findings clearly indicated that results on MALAT1 expression are highly affected by the presence of DNA contamination and that the DNAse treatment step is absolutely necessary to avoid false positive results.

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Real-Time PCR Determination of Escherichia coli Genomic DNA Contamination in Plasmid Preparations

Analytical Biochemistry ◽

10.1006/abio.2001.5480 ◽

2002 ◽

Vol 301 (1) ◽

pp. 151-153 ◽

Cited By ~ 10

Author(s):

Adrián Vilalta ◽

Vanessa Whitlow ◽

Terrie Martin

Keyword(s):

Escherichia Coli ◽

Real Time ◽

Real Time Pcr ◽

Genomic Dna ◽

Dna Contamination

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Molecular diagnosis of orthopaedic device infection direct from sonication fluid by metagenomic sequencing

10.1101/118026 ◽

2017 ◽

Author(s):

Teresa L. Street ◽

Nicholas D. Sanderson ◽

Bridget L. Atkins ◽

Andrew J. Brent ◽

Kevin Cole ◽

...

Keyword(s):

Diagnostic Information ◽

Species Level ◽

Metagenomic Sequencing ◽

Tissue Samples ◽

Bacterial Dna ◽

Dna Contamination ◽

Prosthetic Joint ◽

Device Infection ◽

Fluid Culture ◽

Orthopaedic Device

AbstractCulture of multiple periprosthetic tissue samples is the current gold-standard for microbiological diagnosis of prosthetic joint infections (PJI). Additional diagnostic information may be obtained through sonication fluid culture of explants. However, current techniques can have relatively low sensitivity, with prior antimicrobial therapy and infection by fastidious organisms influencing results. We assessed if metagenomic sequencing of complete bacterial DNA extracts obtained direct from sonication fluid can provide an alternative rapid and sensitive tool for diagnosis of PJI.We compared metagenomic sequencing with standard aerobic and anaerobic culture in 97 sonication fluid samples from prosthetic joint and other orthopaedic device infections. Reads from Illumina MiSeq sequencing were taxonomically classified using Kraken. Using 50 samples (derivation set), we determined optimal thresholds for the number and proportion of bacterial reads required to identify an infection and validated our findings in 47 independent samples.Compared to sonication fluid culture, the species-level sensitivity of metagenomic sequencing was 61/69(88%,95%CI 77-94%) (derivation samples 35/38[92%,79-98%]; validation 26/31[84%,66-95%]), and genus-level sensitivity was 64/69(93%,84-98%). Species-level specificity, adjusting for plausible fastidious causes of infection, species found in concurrently obtained tissue samples, and prior antibiotics, was 85/97(88%,79-93%) (derivation 43/50[86%,73-94%], validation 42/47[89%,77-96%]). High levels of human DNA contamination were seen despite use of laboratory methods to remove it. Rigorous laboratory good practice was required to prevent bacterial DNA contamination.We demonstrate metagenomic sequencing can provide accurate diagnostic information in PJI. Our findings combined with increasing availability of portable, random-access sequencing technology offers the potential to translate metagenomic sequencing into a rapid diagnostic tool in PJI.

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Sensitive detection of DNA contamination in tumor samples via microhaplotypes

10.1101/2020.12.18.423488 ◽

2020 ◽

Author(s):

Brett Whitty ◽

John F. Thompson

Keyword(s):

Sequence Data ◽

Accurate Determination ◽

Sensitive Detection ◽

European Ancestry ◽

Somatic Variation ◽

Dna Mixtures ◽

Accurate Identification ◽

Sample Contamination ◽

Dna Contamination ◽

Low Levels

AbstractBackgroundLow levels of sample contamination can have disastrous effects on the accurate identification of somatic variation in tumor samples. Detection of sample contamination in DNA is generally based on observation of low frequency variants that suggest more than a single source of DNA is present. This strategy works with standard DNA samples but is especially problematic in solid tumor FFPE samples because there can be huge variations in allele frequency (AF) due to massive copy number changes arising from large gains and losses across the genome. The tremendously variable allele frequencies make detection of contamination challenging. A method not based on individual AF is needed for accurate determination of whether a sample is contaminated and to what degree.MethodsWe used microhaplotypes to determine whether sample contamination is present. Microhaplotypes are sets of variants on the same sequencing read that can be unambiguously phased. Instead of measuring AF, the number and frequency of microhaplotypes is determined. Contamination detection becomes based on fundamental genomic properties, linkage disequilibrium (LD) and the diploid nature of human DNA, rather than variant frequencies. We optimized microhaplotype content based on 164 single nucleotide variant sets located in genes already sequenced within a cancer panel. Thus, contamination detection uses existing sequence data and does not require sequencing of any extraneous regions. The content is chosen based on LD data from the 1000 Genomes Project to be ancestry agnostic, providing the same sensitivity for contamination detection with samples from individuals of African, East Asian, and European ancestry.ResultsDetection of contamination at 1% and below is possible using this design. The methods described here can also be extended to other DNA mixtures such as forensic and non-invasive prenatal testing samples where DNA mixes of 1% or less can be similarly detected.ConclusionsThe microhaplotype method allows sensitive detection of DNA contamination in FFPE tumor samples. These methods provide a foundation for examining DNA mixtures in a variety of contexts. With the appropriate panels and high sequencing depth, low levels of secondary DNA can be detected and this can be valuable in a variety of applications.

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