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2. Massively multiplexed nucleic acid detection with Cas13

Author

Ackerman, Cheri M., Myhrvold, Cameron, Thakku, Sri Gowtham, Freije, Catherine A., Metsky, Hayden C., Yang, David K., Ye, Simon H., Boehm, Chloe K., Kosoko-Thoroddsen, Tinna-Sólveig F., Kehe, Jared, Nguyen, Tien G., Carter, Amber, Kulesa, Anthony, Barnes, John R., Dugan, Vivien G., Hung, Deborah T., Blainey, Paul C., and Sabeti, Pardis C.

Published
2020
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9. Multiplexed and high-throughput neuronal fluorescence imaging with diffusible probes

Author

Guo, Syuan-Ming, primary, Veneziano, Remi, additional, Gordonov, Simon, additional, Li, Li, additional, Danielson, Eric, additional, Perez de Arce, Karen, additional, Park, Demian, additional, Kulesa, Anthony B., additional, Wamhoff, Eike-Christian, additional, Blainey, Paul C., additional, Boyden, Edward S., additional, Cottrell, Jeffrey R., additional, and Bathe, Mark, additional

Published
2019
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13. Optical High Content Nanoscopy of Epigenetic Marks Decodes Phenotypic Divergence in Stem Cells

Author

Kim, Joseph J., primary, Bennett, Neal K., additional, Devita, Mitchel S., additional, Chahar, Sanjay, additional, Viswanath, Satish, additional, Lee, Eunjee A., additional, Jung, Giyoung, additional, Shao, Paul P., additional, Childers, Erin P., additional, Liu, Shichong, additional, Kulesa, Anthony, additional, Garcia, Benjamin A., additional, Becker, Matthew L., additional, Hwang, Nathaniel S., additional, Madabhushi, Anant, additional, Verzi, Michael P., additional, and Moghe, Prabhas V., additional

Published
2017
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16. High-throughput automated microfluidic sample preparation for accurate microbial genomics

Author

Kim, Soohong, De Jonghe, Joachim, Kulesa, Anthony B., Feldman, David, Vatanen, Tommi, Bhattacharyya, Roby P., Berdy, Brittany, Gomez, James, Nolan, Jill, Epstein, Slava, and Blainey, Paul C.

Abstract

Low-cost shotgun DNA sequencing is transforming the microbial sciences. Sequencing instruments are so effective that sample preparation is now the key limiting factor. Here, we introduce a microfluidic sample preparation platform that integrates the key steps in cells to sequence library sample preparation for up to 96 samples and reduces DNA input requirements 100-fold while maintaining or improving data quality. The general-purpose microarchitecture we demonstrate supports workflows with arbitrary numbers of reaction and clean-up or capture steps. By reducing the sample quantity requirements, we enabled low-input (∼10,000 cells) whole-genome shotgun (WGS) sequencing of Mycobacterium tuberculosis and soil micro-colonies with superior results. We also leveraged the enhanced throughput to sequence ∼400 clinical Pseudomonas aeruginosa libraries and demonstrate excellent single-nucleotide polymorphism detection performance that explained phenotypically observed antibiotic resistance. Fully-integrated lab-on-chip sample preparation overcomes technical barriers to enable broader deployment of genomics across many basic research and translational applications.

Published
2017
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18. Points of Significance: Sampling distributions and the bootstrap.

Author

Kulesa, Anthony, Krzywinski, Martin, Blainey, Paul, and Altman, Naomi

Subjects
*STATISTICAL bootstrapping, *STATISTICAL sampling, *DATA analysis, *BACTERIAL mutation, *SAMPLING errors, *ESTIMATION theory, *COMPUTER simulation
Abstract

The bootstrap can be used to assess uncertainty of sample estimates. [ABSTRACT FROM AUTHOR]

Published
2015
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19. High-throughput automated microfluidic sample preparation for accurate microbial genomics

Author

David Feldman, Tommi Vatanen, James Gomez, Slava S. Epstein, Joachim De Jonghe, Soohong Kim, Brittany Berdy, Roby P. Bhattacharyya, Paul C. Blainey, Jill Nolan, Anthony Kulesa, Broad Institute, University of Cambridge, Department of Computer Science, Massachusetts General Hospital, Northeastern University, Aalto-yliopisto, Aalto University, Massachusetts Institute of Technology. Department of Biological Engineering, Massachusetts Institute of Technology. Department of Physics, Kim, Soohong, Kulesa, Anthony Benjamin, Feldman, David, and Blainey, Paul C

Subjects
0301 basic medicine, Science, Microfluidics, 030106 microbiology, General Physics and Astronomy, Sample (statistics), Genomics, Nanotechnology, Computational biology, Biology, Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, DNA sequencing, 03 medical and health sciences, Lab-On-A-Chip Devices, High-Throughput Screening Assays, Humans, Genomic library, Sample preparation, Throughput (business), Soil Microbiology, Gene Library, Oligonucleotide Array Sequence Analysis, ta113, Whole genome sequencing, Multidisciplinary, Whole Genome Sequencing, High-Throughput Nucleotide Sequencing, Drug Resistance, Microbial, Bacterial Infections, Mycobacterium tuberculosis, General Chemistry, 030104 developmental biology, Pseudomonas aeruginosa, Genome, Bacterial, Environmental Monitoring
Abstract

Low-cost shotgun DNA sequencing is transforming the microbial sciences. Sequencing instruments are so effective that sample preparation is now the key limiting factor. Here, we introduce a microfluidic sample preparation platform that integrates the key steps in cells to sequence library sample preparation for up to 96 samples and reduces DNA input requirements 100-fold while maintaining or improving data quality. The general-purpose microarchitecture we demonstrate supports workflows with arbitrary numbers of reaction and clean-up or capture steps. By reducing the sample quantity requirements, we enabled low-input (∼10,000 cells) whole-genome shotgun (WGS) sequencing of Mycobacterium tuberculosis and soil micro-colonies with superior results. We also leveraged the enhanced throughput to sequence ∼400 clinical Pseudomonas aeruginosa libraries and demonstrate excellent single-nucleotide polymorphism detection performance that explained phenotypically observed antibiotic resistance. Fully-integrated lab-on-chip sample preparation overcomes technical barriers to enable broader deployment of genomics across many basic research and translational applications., Burroughs Wellcome Fund (Career Award at the Scientific Interface), David H. Koch Institute for Integrative Cancer Research at MIT (Startup Funds), United States. Department of Energy. Joint Genome Institute (Emerging Technologies Opportunity Program Award), National Science Foundation (U.S.). Graduate Research Fellowship Program (1308852)

Published
2017

20. Sampling distributions and the bootstrap

Author

Paul C. Blainey, Anthony Kulesa, Martin Krzywinski, Naomi Altman, Massachusetts Institute of Technology. Department of Biological Engineering, Blainey, Paul C, and Kulesa, Anthony Benjamin

Subjects
Selection bias, Research design, Statistics::Theory, media_common.quotation_subject, MEDLINE, Reproducibility of Results, Cell Biology, Biology, Models, Theoretical, Biochemistry, Article, Sampling distribution, Research Design, Statistics, Statistics::Methodology, Computer Simulation, Molecular Biology, Selection Bias, Computer Science::Databases, Biotechnology, media_common, Research data
Abstract

The bootstrap can be used to assess uncertainty of sample estimates.

Published
2015

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