J
James J. Collins
Researcher at Massachusetts Institute of Technology
Publications - 700
Citations - 105255
James J. Collins is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Synthetic biology & Population. The author has an hindex of 151, co-authored 669 publications receiving 89476 citations. Previous affiliations of James J. Collins include Baylor College of Medicine & University at Albany, SUNY.
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Patent
Compositions and methods to boost endogenous ros production from bacteria
TL;DR: In this article, compositions and methods comprising ROS target modulators that increase ROS flux and endogenous ROS production, thereby potentiating oxidative attack by antibiotics and biocides are presented and compared.
Transformation by Simian Virus 40 of Spleen Cells from a Hyperimmune Rabbit: Evidence for Synthesis of Immunoglobulin by the Transformed Cells (cloning/coprecipitation/autoradiography/differentiated)
TL;DR: In this article, a trans-formed cell line from a rabbit hyper-immunized with a Type III pneumococcal vaccine was found to be capable of producing rabbit immunoglobulin of the IgG class.
Journal ArticleDOI
Continuous bioactivity-dependent evolution of an antibiotic biosynthetic pathway.
TL;DR: This proof-of-principle study demonstrates that features of natural bioactivity-dependent evolution can be engineered to access unforeseen routes of improving metabolic pathways and product yields and improves antibiotic production in a new host.
Patent
Compositions and methods for antibiotic potentiation and drug discovery
Guillaume Cottarel,Jamey Wierzbowski,Kollol Pal,Michael A. Kohanski,Daniel J. Dwyer,James J. Collins,Michael Almstetter,Michael Thormann,Andreas Treml +8 more
TL;DR: In this paper, the authors provide methods for identifying target genes whose partial or complete functional inactivation potentiates the activity of an antibiotic agent, e.g., a quinolone antibiotic.
Journal ArticleDOI
Point-of-Care Devices to Detect Zika and Other Emerging Viruses.
TL;DR: This review describes the identification of lateral flow immunoassay monoclonal antibody pairs that detect and distinguish between closely related pathogens and that are used in combination with functionalized multicolored nanoparticles and computational methods to deconvolute data.