Erbay Yigit

A Method for Selectively Enriching Microbial DNA from Contaminating Vertebrate Host DNA

DNA samples derived from vertebrate skin, bodily cavities and body fluids contain both host and microbial DNA; the latter often present as a minor component. Consequently, DNA sequencing of a microbiome sample frequently yields reads originating from the microbe(s) of interest, but with a vast excess of host genome-derived reads. In this study, we used a methyl-CpG binding domain (MBD) to separate methylated host DNA from microbial DNA based on differences in CpG methylation density. MBD fused to the Fc region of a human antibody (MBD-Fc) binds strongly to protein A paramagnetic beads, forming an effective one-step enrichment complex that was used to remove human or fish host DNA from bacterial and protistan DNA for subsequent sequencing and analysis. We report enrichment of DNA samples from human saliva, human blood, a mock malaria-infected blood sample and a black molly fish. When reads were mapped to reference genomes, sequence reads aligning to host genomes decreased 50-fold, while bacterial and Plasmodium DNA sequences reads increased 8–11.5-fold. The Shannon-Wiener diversity index was calculated for 149 bacterial species in saliva before and after enrichment. Unenriched saliva had an index of 4.72, while the enriched sample had an index of 4.80. The similarity of these indices demonstrates that bacterial species diversity and relative phylotype abundance remain conserved in enriched samples. Enrichment using the MBD-Fc method holds promise for targeted microbiome sequence analysis across a broad range of sample types.

Genome and Metagenome Sequencing: Using the Human Methyl-Binding Domain to Partition Genomic DNA Derived from Plant Tissues

Premise of the study: Variation in the distribution of methylated CpG (methyl-CpG) in genomic DNA (gDNA) across the tree of life is biologically interesting and useful in genomic studies. We illustrate the use of human methyl-CpG-binding domain (MBD2) to fractionate angiosperm DNA into eukaryotic nuclear (methyl-CpG-rich) vs. organellar and prokaryotic (methyl-CpG-poor) elements for genomic and metagenomic sequencing projects. Methods: MBD2 has been used to enrich prokaryotic DNA in animal systems. Using gDNA from five model angiosperm species, we apply a similar approach to identify whether MBD2 can fractionate plant gDNA into methyl-CpG-depleted vs. enriched methyl-CpG elements. For each sample, three gDNA libraries were sequenced: (1) untreated gDNA, (2) a methyl-CpG-depleted fraction, and (3) a methyl-CpG-enriched fraction. Results: Relative to untreated gDNA, the methyl-depleted libraries showed a 3.2–11.2-fold and 3.4–11.3-fold increase in chloroplast DNA (cpDNA) and mitochondrial DNA (mtDNA), respectively. Methyl-enriched fractions showed a 1.8–31.3-fold and 1.3–29.0-fold decrease in cpDNA and mtDNA, respectively. Discussion: The application of MBD2 enabled fractionation of plant gDNA. The effectiveness was particularly striking for monocot gDNA (Poaceae). When sufficiently effective on a sample, this approach can increase the cost efficiency of sequencing plant genomes as well as prokaryotes living in or on plant tissues.

A Microbiome DNA Enrichment Method for Next‐Generation Sequencing Sample Preparation

“Microbiome” is used to describe the communities of microorganisms and their genes in a particular environment, including communities in association with a eukaryotic host or part of a host. One challenge in microbiome analysis concerns the presence of host DNA in samples. Removal of host DNA before sequencing results in greater sequence depth of the intended microbiome target population. This unit describes a novel method of microbial DNA enrichment in which methylated host DNA such as human genomic DNA is selectively bound and separated from microbial DNA before next‐generation sequencing (NGS) library construction. This microbiome enrichment technique yields a higher fraction of microbial sequencing reads and improved read quality resulting in a reduced cost of downstream data generation and analysis.

A fast solution to NGS library preparation with low nanogram DNA input.

Next-generation sequencing (NGS) has significantly impacted human genetics, enabling a comprehensive characterization of human genome as well as better understanding of many genomic abnormalities. By delivering massive DNA sequences at unprecedented speed and cost, NGS promises to make personalized medicine a reality in the foreseeable future. To date, library construction with clinical samples has been a challenge, primarily due to the limited quantities of sample DNA available. To overcome this challenge, we have developed a fast library preparation method using novel NEBNext reagents and adaptors, including a new DNA polymerase that has been optimized to minimize GC bias. This method enables library construction from an amount of DNA as low as 5 ng, and can be used for both intact and fragmented DNA. Moreover, the workflow is compatible with multiple NGS platforms.

Comparative analysis of strand-specific RNA sequencing approaches

Background Standard RNA sequencing approaches generally require double-stranded cDNA synthesis, which erases RNA strand information. Synthesis of a randomly primed double-stranded cDNA followed by addition of adaptors for next-generation sequencing leads to the loss of information about which strand was present in the original mRNA template. The polarity of the transcript is important for correct annotation of novel genes, identification of antisense transcripts with potential regulatory roles, and for correct determination of gene expression levels in the presence of antisense transcripts. Different strand-specific RNA-seq approaches have been developed to preserve information about strand polarity with different level of performances. Material and methods Using Illumina Deep Sequencing Technology, this work investigates the performance of two different directional RNA-Seq (strand-specific RNA-seq) strategies. One is based on direct ligation of adaptors to the RNA ends and the other is based on the labeling and excision of the second strand cDNA. The RNA-seq workflows present in this work have been improved over current more laborious RNA-seq methods. Their low RNA input and streamlined workflows make them compatible with high throughput and automation. We also analyze the effect of different RNA fragmentation methods (divalent cations plus heat versus enzymatic fragmentation). Results We will provide a comparative full data analysis of different strand-specific RNA methods (library performance, complexity, continuity of gene coverage, strand specificity, rRNA background). Conclusions Our results show improved methods for high-quality strand-specific RNA-seq library construction amenable to large-scale library construction and automation.