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Sandia Academic Alliance Program Collaboration Report: 2020-2021 Accomplishments

Peebles, Diane E.; Horton, Rebecca D.; Claudet, Andre C.; Miner, Nadine E.; Patel, Kamlesh P.; Windsor, Matthew W.; Stites, Mallory C.; Treece, Amy T.

University partnerships play an essential role in sustaining Sandia’s vitality as a national laboratory. The SAA is an element of Sandia’s broader University Partnerships program, which facilitates recruiting and research collaborations with dozens of universities annually. The SAA program has two three-year goals. SAA aims to realize a step increase in hiring results, by growing the total annual inexperienced hires from each out-of-state SAA university. SAA also strives to establish and sustain strategic research partnerships by establishing several federally sponsored collaborations and multi-institutional consortiums in science & technology (S&T) priorities such as autonomy, advanced computing, hypersonics, quantum information science, and data science. The SAA program facilitates access to talent, ideas, and Research & Development facilities through strong university partnerships. Earlier this year, the SAA program and campus executives hosted John Myers, Sandia’s former Senior Director of Human Resources (HR) and Communications, and senior-level staff at Georgia Tech, U of Illinois, Purdue, UNM, and UT Austin. These campus visits provided an opportunity to share the history of the partnerships from the university leadership, tours of research facilities, and discussions of ongoing technical work and potential recruiting opportunities. These visits also provided valuable feedback to HR management that will help Sandia realize a step increase in hiring from SAA schools. The 2020-2021 Collaboration Report is a compilation of accomplishments in 2020 and 2021 from SAA and Sandia’s valued SAA university partners.

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Library preparation for the Oxford Minion sequencer with 'ASPIRE': Automated sample PrEP by indexed rotary exchange

21st International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2017

Jayamohan, Harikrishnan J.; Sinha, Anupama S.; Krishnakumar, Raga K.; Edwards, Harrison E.; Younis, Tariq A.; Trevithick, Jacob D.; Patel, Kamlesh P.; Bartsch, Michael B.

We report a prototype system to automate the DNA library preparation of bacterial genomes for analysis with the Oxford MinION nanopore sequencer as a first step towards a universal bacterial pathogen identification and biosurveillance tool. The ASPIRE (Automated Sample Preparation by Indexed Rotary Exchange) platform incorporates a rotary hydrophobic substrate that provides sequential delivery of sample and reagent droplets to heater and magnetic bead trapping modules via a single capillary coupled to a syringe pump. We have applied ASPIRE-based library preparation to lambda-phage and E. coli genomic DNA (gDNA) and verified its ability to produce libraries with DNA yield and ultimate sequenced read size distribution, quality, and reference-mapping percentages comparable to those obtained for benchtop prep methods.

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Systematic and stochastic influences on the performance of the MinION nanopore sequencer across a range of nucleotide bias

Scientific Reports

Krishnakumar, Raga K.; Sinha, Anupama S.; Bird, Sara W.; Jayamohan, Harikrishnan; Edwards, Harrison S.; Schoeniger, Joseph S.; Patel, Kamlesh P.; Branda, Steven B.; Bartsch, Michael B.

Emerging sequencing technologies are allowing us to characterize environmental, clinical and laboratory samples with increasing speed and detail, including real-time analysis and interpretation of data. One example of this is being able to rapidly and accurately detect a wide range of pathogenic organisms, both in the clinic and the field. Genomes can have radically different GC content however, such that accurate sequence analysis can be challenging depending upon the technology used. Here, we have characterized the performance of the Oxford MinION nanopore sequencer for detection and evaluation of organisms with a range of genomic nucleotide bias. We have diagnosed the quality of base-calling across individual reads and discovered that the position within the read affects base-calling and quality scores. Finally, we have evaluated the performance of the current state-of-the-art neural network-based MinION basecaller, characterizing its behavior with respect to systemic errors as well as context- and sequence-specific errors. Overall, we present a detailed characterization the capabilities of the MinION in terms of generating high-accuracy sequence data from genomes with a wide range of nucleotide content. This study provides a framework for designing the appropriate experiments that are the likely to lead to accurate and rapid field-forward diagnostics.

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Real-Time Automated Pathogen Identification by Enhanced Ribotyping (RAPIER) LDRD Final Report

Bartsch, Michael B.; Bird, Sara W.; Branda, Steven B.; Edwards, Harrison E.; Jayamohan, Harikrishnan J.; Krishnakumar, Raga K.; Patel, Kamlesh P.; Schoeniger, Joseph S.; Sinha, Anupama S.

Funded through the IHNS/E&HS investment area for FY16-18, the RAPIER LDRD sought to evaluate the potential benefits and applicability of the new Oxford MinION nanopore sequencer to pathogen diagnostic applications in biodefense, biosurveillance, and global/public health. The project had four primary objectives: 1) to investigate the performance of the MinION sequencer while building facility with its operation, 2) to develop microfluidic library prep automation facilitating the use of the MinION in field-forward or point-of-care applications, 3) to leverage CRISPR/Cas9 technology to enable targeted identification of bacterial pathogens, and 4) to capitalize on the real- time data output capabilities of the MinION to enable rapid sequence-based diagnostics. While the rapid evolution of the MinION sequencing technology during the course of the project posed a number of challenges and required a reassessment of initial project priorities, it also provided unique opportunities, notably culminating in our development of the RUBRIC real-time selective sequencing software.

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The rotary zone thermal cycler: A low-power system enabling automated rapid PCR

PLoS ONE

Bartsch, Michael B.; Edwards, Harrison S.; Lee, Daniel; Moseley, Caroline E.; Tew, Karen E.; Renzi, Ronald F.; Van De Vreugde, James L.; Kim, Hanyoup; Knight, Daniel L.; Sinha, Anupama S.; Branda, Steven B.; Patel, Kamlesh P.

Advances in molecular biology, microfluidics, and laboratory automation continue to expand the accessibility and applicability of these methods beyond the confines of conventional, centralized laboratory facilities and into point of use roles in clinical, military, forensic, and field-deployed applications. As a result, there is a growing need to adapt the unit operations of molecular biology (e.g., aliquoting, centrifuging, mixing, and thermal cycling) to compact, portable, low-power, and automation-ready formats. Here we present one such adaptation, the rotary zone thermal cycler (RZTC), a novel wheel-based device capable of cycling up to four different fixed-temperature blocks into contact with a stationary 4-microliter capillarybound sample to realize 1-3 second transitions with steady state heater power of less than 10 W. We demonstrate the utility of the RZTC for DNA amplification as part of a highly integrated rotary zone PCR (rzPCR) system that uses low-volume valves and syringe-based fluid handling to automate sample loading and unloading, thermal cycling, and between-run cleaning functionalities in a compact, modular form factor. In addition to characterizing the performance of the RZTC and the efficacy of different online cleaning protocols, we present preliminary results for rapid single-plex PCR, multiplex short tandem repeat (STR) amplification, and second strand cDNA synthesis.

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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.

FISH 'N' Chips : a single cell genomic analyzer for the human microbiome

Meagher, Robert M.; Patel, Kamlesh P.; Light, Yooli K.; Liu, Peng L.; Singh, Anup K.

Uncultivable microorganisms likely play significant roles in the ecology within the human body, with subtle but important implications for human health. Focusing on the oral microbiome, we are developing a processor for targeted isolation of individual microbial cells, facilitating whole-genome analysis without the need for isolation of pure cultures. The processor consists of three microfluidic modules: identification based on 16S rRNA fluorescence in situ hybridization (FISH), fluorescence-based sorting, and encapsulation of individual selected cells into small droplets for whole genome amplification. We present here a technique for performing microscale FISH and flow cytometry, as a prelude to single cell sorting.

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Host suppression and bioinformatics for sequence-based characterization of unknown pathogens

Misra, Milind; Patel, Kamlesh P.; Kaiser, Julia N.; Meagher, Robert M.; Branda, Steven B.; Schoeniger, Joseph S.

Bioweapons and emerging infectious diseases pose formidable and growing threats to our national security. Rapid advances in biotechnology and the increasing efficiency of global transportation networks virtually guarantee that the United States will face potentially devastating infectious disease outbreaks caused by novel ('unknown') pathogens either intentionally or accidentally introduced into the population. Unfortunately, our nation's biodefense and public health infrastructure is primarily designed to handle previously characterized ('known') pathogens. While modern DNA assays can identify known pathogens quickly, identifying unknown pathogens currently depends upon slow, classical microbiological methods of isolation and culture that can take weeks to produce actionable information. In many scenarios that delay would be costly, in terms of casualties and economic damage; indeed, it can mean the difference between a manageable public health incident and a full-blown epidemic. To close this gap in our nation's biodefense capability, we will develop, validate, and optimize a system to extract nucleic acids from unknown pathogens present in clinical samples drawn from infected patients. This system will extract nucleic acids from a clinical sample, amplify pathogen and specific host response nucleic acid sequences. These sequences will then be suitable for ultra-high-throughput sequencing (UHTS) carried out by a third party. The data generated from UHTS will then be processed through a new data assimilation and Bioinformatic analysis pipeline that will allow us to characterize an unknown pathogen in hours to days instead of weeks to months. Our methods will require no a priori knowledge of the pathogen, and no isolation or culturing; therefore it will circumvent many of the major roadblocks confronting a clinical microbiologist or virologist when presented with an unknown or engineered pathogen.

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Microfluidic-based cell sorting of Francisella tularensis infected macrophages using optical forces

Analytical Chemistry

Perroud, Thomas D.; Kaiser, Julia N.; Sy, Jay C.; Lane, Todd L.; Branda, Catherine B.; Singh, Anup K.; Patel, Kamlesh P.

We have extended the principle of optical tweezers as a noninvasive technique to actively sort hydrodynamically focused cells based on their fluorescence signal in a microfluidic device. This micro fluorescence-activated cell sorter (μFACS) uses an infrared laser to laterally deflect cells into a collection channel. Green-labeled macrophages were sorted from a 40/60 ratio mixture at a through-put of 22 cells/s over 30 min achieving a 93% sorting purity and a 60% recovery yield. To rule out potential photoinduced cell damage during optical deflection, we investigated the response of mouse macrophage to brief exposures (<4 ms) of focused 1064-nm laser light (9.6 W at the sample). We found no significant difference in viability, cell proliferation, activation state, and functionality between infrared-exposed and unexposed cells. Activation state was measured by the phosphorylation of ERK and nuclear translocation of NF-κB, while functionality was assessed in a similar manner, but after a lipopolysaccharide challenge. To demonstrate the selective nature of optical sorting, we isolated a subpopulation of macrophages highly infected with the fluorescently labeled pathogen Francisella tularensis subsp. novicida. A total of 10 738 infected cells were sorted at a throughput of 11 cells/s with 93% purity and 39% recovery. © 2008 American Chemical Society.

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Results 1–50 of 72
Results 1–50 of 72