Using synthetic biology to record information in DNA and RNA within wastewater microbes and communities

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dc.contributor.advisorStadler, Lauren B.
dc.contributor.advisorSilberg, Jonathan J.
dc.creatorKalvapalle, Prashant Bharadwaj
dc.date.accessioned2023-09-01T20:39:50Z
dc.date.created2023-08
dc.date.issued2023-08-02
dc.date.submittedAugust 2023
dc.date.updated2023-09-01T20:39:50Z
dc.description.abstractMicroorganisms form the bedrock of key ecological processes that make the Earth habitable. Microbial communities regulate carbon and nitrogen cycles, influencing greenhouse gas concentrations and agricultural productivity. As such, understanding these microbial processes is critical to address climate change and food security and to advance sustainable practices. Microbial communities within wastewater are also critical to public health, such as through the exchange of genetic material, which can result in more virulent pathogens, and resistance to known antibiotic treatments. Engineered microbial sensors can be developed to gather information and understand the influence of physicochemical conditions of the environment. To date, the majority of biosensors developed rely on fluorescent outputs, which are challenging to apply in environmental matrices that are opaque, and contain autofluorescent particles or microbes. In addition, few biosensors have been applied over timescales relevant to ecological processes, and there is a need for biosensors that function over week-long timescales in situ. In this thesis, I describe biosensors that record signals by modifying DNA and RNA, which are designed to monitor chemical exposures and gene exchange within natural environments, respectively. I benchmark the performance of these sensor systems within undomesticated, wastewater microbes. I demonstrate that the DNA biosensor can record analog information about the exposure to a sugar arabinose and microbial communication molecule 3-oxo-C12-homoserine lactone. I describe strategies that can be used to allow these DNA memory biosensors to record information during 9 day incubations. Additionally, I demonstrate that a new type of RNA memory sensor is able to function in a wide variety of wastewater taxa, which writes information in 16S ribosomal RNA. In the first proof-of-concept experiments, I show this sensor can record information in more than 100 microbes in parallel. Together, the tools extend the tools available to environmental microbiologists for detecting microbial processes in complex environments, leading to insights of environmental and public health importance. The longer duration DNA biosensor will be useful for studying the bioavailability of chemicals in situ, while the community distributed RNA memory sensor will be useful for identifying the taxonomic range of gene transfer recipients in a high-throughput manner.
dc.embargo.lift2024-02-01
dc.embargo.terms2024-02-01
dc.format.mimetypeapplication/pdf
dc.identifier.citationKalvapalle, Prashant Bharadwaj. "Using synthetic biology to record information in DNA and RNA within wastewater microbes and communities." (2023) Diss., Rice University. https://hdl.handle.net/1911/115267.
dc.identifier.urihttps://hdl.handle.net/1911/115267
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectbiosensor
dc.subjectintegrase
dc.subjectgenetic memory
dc.subjectquorum sensing
dc.subjectrecombinase
dc.subjectwastewater
dc.subjectsynthetic biology
dc.subjectribozyme
dc.subject16S rRNA
dc.subjectconjugation
dc.subjecthorizontal gene transfer
dc.subjectamplicon sequencing
dc.titleUsing synthetic biology to record information in DNA and RNA within wastewater microbes and communities
dc.typeThesis
dc.type.materialText
thesis.degree.departmentSystems, Synthetic and Physical Biology
thesis.degree.disciplineSystems/Synthetic/Phys Biology
thesis.degree.grantorRice University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
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