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Cited by 737

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Microfluidic Digital PCR Enables Multigene Analysis of Individual Environmental Bacteria

Ottesen, Elizabeth A., Hong, Jong Wook, Quake, Stephen R., Leadbetter, Jared R.·2006·Science

Abstract

Gene inventory and metagenomic techniques have allowed rapid exploration of bacterial diversity and the potential physiologies present within microbial communities. However, it remains nontrivial to discover the identities of environmental bacteria carrying two or more genes of interest. We have used microfluidic digital polymerase chain reaction (PCR) to amplify and analyze multiple, different genes obtained from single bacterial cells harvested from nature. A gene encoding a key enzyme involved in the mutualistic symbiosis occurring between termites and their gut microbiota was used as an experimental hook to discover the previously unknown ribosomal RNA–based species identity of several symbionts. The ability to systematically identify bacteria carrying a particular gene and to link any two or more genes of interest to single species residing in complex ecosystems opens up new opportunities for research on the environment.

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Crossref · 10.1126/science.1131370

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Metadata

Authors
Ottesen, E. A., Hong, J. W., Quake, S. R., & Leadbetter, J. R.
Venue
Science
Published
2006-12
Volume
314
Issue
5804
Pages
1464-1467
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W1984857185
Cited by
737
References
3
FWCI
30.55
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Microfluidic Digital PCR Enables Multigene Analysis of Individual Environmental Bacteria. https://app.cochat.ai/papers/10.1126/science.1131370
The paper
Ottesen, E. A., Hong, J. W., Quake, S. R., & Leadbetter, J. R. (2006). Microfluidic Digital PCR Enables Multigene Analysis of Individual Environmental Bacteria. Science. https://doi.org/10.1126/science.1131370

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.