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A Microfluidic DNA Library Preparation Platform for Next-Generation Sequencing

PLoS ONE

Kim, Hanyoup; Jebrail, Mais J.; Sinha, Anupama S.; Bent, Zachary B.; Solberg, Owen D.; Williams, Kelly P.; Langevin, Stanley A.; Renzi, Ronald F.; Van De Vreugde, James L.; Meagher, Robert M.; Schoeniger, Joseph S.; Lane, Todd L.; Branda, Steven B.; Bartsch, Michael B.; Patel, Kamlesh D.

Next-generation sequencing (NGS) is emerging as a powerful tool for elucidating genetic information for a wide range of applications. Unfortunately, the surging popularity of NGS has not yet been accompanied by an improvement in automated techniques for preparing formatted sequencing libraries. To address this challenge, we have developed a prototype microfluidic system for preparing sequencer-ready DNA libraries for analysis by Illumina sequencing. Our system combines droplet-based digital microfluidic (DMF) sample handling with peripheral modules to create a fully-integrated, sample-in library-out platform. In this report, we use our automated system to prepare NGS libraries from samples of human and bacterial genomic DNA. E. coli libraries prepared on-device from 5 ng of total DNA yielded excellent sequence coverage over the entire bacterial genome, with >99% alignment to the reference genome, even genome coverage, and good quality scores. Furthermore, we produced a de novo assembly on a previously unsequenced multi-drug resistant Klebsiella pneumoniae strain BAA-2146 (KpnNDM). The new method described here is fast, robust, scalable, and automated. Our device for library preparation will assist in the integration of NGS technology into a wide variety of laboratories, including small research laboratories and clinical laboratories. © 2013 Kim et al.

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Identification of host response signatures of infection

Sinha, Anupama S.; Bent, Zachary B.

Biological weapons of mass destruction and emerging infectious diseases represent a serious and growing threat to our national security. Effective response to a bioattack or disease outbreak critically depends upon efficient and reliable distinguishing between infected vs healthy individuals, to enable rational use of scarce, invasive, and/or costly countermeasures (diagnostics, therapies, quarantine). Screening based on direct detection of the causative pathogen can be problematic, because culture- and probe-based assays are confounded by unanticipated pathogens (e.g., deeply diverged, engineered), and readily-accessible specimens (e.g., blood) often contain little or no pathogen, particularly at pre-symptomatic stages of disease. Thus, in addition to the pathogen itself, one would like to detect infection-specific host response signatures in the specimen, preferably ones comprised of nucleic acids (NA), which can be recovered and amplified from tiny specimens (e.g., fingerstick draws). Proof-of-concept studies have not been definitive, however, largely due to use of sub-optimal sample preparation and detection technologies. For purposes of pathogen detection, Sandia has developed novel molecular biology methods that enable selective isolation of NA unique to, or shared between, complex samples, followed by identification and quantitation via Second Generation Sequencing (SGS). The central hypothesis of the current study is that variations on this approach will support efficient identification and verification of NA-based host response signatures of infectious disease. To test this hypothesis, we re-engineered Sandia's sophisticated sample preparation pipelines, and developed new SGS data analysis tools and strategies, in order to pioneer use of SGS for identification of host NA correlating with infection. Proof-of-concept studies were carried out using specimens drawn from pathogen-infected non-human primates (NHP). This work provides a strong foundation for large-scale, highly-efficient efforts to identify and verify infection-specific host NA signatures in human populations.

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Characterization of Pathogens in Clinical Specimens via Suppression of Host Background for Efficient Second Generation Sequencing Analyses

Branda, Steven B.; Jebrail, Mais J.; Van De Vreugde, James L.; Langevin, Stanley A.; Bent, Zachary B.; Curtis, Deanna J.; Lane, Pamela L.; Carson, Bryan C.; La Bauve, Elisa L.; Patel, Kamlesh P.; Ricken, James B.; Schoeniger, Joseph S.; Solberg, Owen D.; Williams, Kelly P.; Misra, Milind; Powell, Amy J.; Pattengale, Nicholas D.; May, Elebeoba E.; Lane, Todd L.; Lindner, Duane L.; Young, Malin M.; VanderNoot, Victoria A.; Thaitrong, Numrin T.; Bartsch, Michael B.; Renzi, Ronald F.; Tran-Gyamfi, Mary B.; Meagher, Robert M.

Abstract not provided.

Copy of Automated Molecular Biology Platform Enabling Rapid & Efficient SGS Analysis of Pathogens in Clinical Samples

Branda, Steven B.; Jebrail, Mais J.; Van De Vreugde, James L.; Langevin, Stanley A.; Bent, Zachary B.; Curtis, Deanna J.; Lane, Pamela L.; Carson, Bryan C.; La Bauve, Elisa L.; Patel, Kamlesh P.; Ricken, James B.; Schoeniger, Joseph S.; Solberg, Owen D.; Williams, Kelly P.; Misra, Milind; Powell, Amy J.; Pattengale, Nicholas D.; May, Elebeoba E.; Lane, Todd L.; Lindner, Duane L.; Young, Malin M.; VanderNoot, Victoria A.; Thaitrong, Numrin T.; Bartsch, Michael B.; Renzi, Ronald F.; Tran-Gyamfi, Mary B.; Meagher, Robert M.

Abstract not provided.

Automated Molecular Biology Platform Enabling Rapid & Efficient SGS Analysis of Pathogens in Clinical Samples

Branda, Steven B.; Jebrail, Mais J.; Van De Vreugde, James L.; Langevin, Stanley A.; Bent, Zachary B.; Curtis, Deanna J.; Lane, Pamela L.; Carson, Bryan C.; La Bauve, Elisa L.; Patel, Kamlesh P.; Ricken, James B.; Schoeniger, Joseph S.; Solberg, Owen D.; Williams, Kelly P.; Misra, Milind; Powell, Amy J.; Pattengale, Nicholas D.; May, Elebeoba E.; Lane, Todd L.; Lindner, Duane L.; Young, Malin M.; VanderNoot, Victoria A.; Thaitrong, Numrin T.; Bartsch, Michael B.; Renzi, Ronald F.; Tran-Gyamfi, Mary B.; Meagher, Robert M.

Abstract not provided.

19 Results
19 Results