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Biology subjects

Stadler, L. B.

Publications and source records attributed to Stadler, L. B..

3 recordsLinked to original sources

Long duration environmental biosensing by recording analyte detection in DNA using recombinase memory

Microbial biosensors that convert environmental information into real-time visual outputs are limited in their sensing abilities in complex environments, such as soil and wastewater. Alternative reporter outputs are needed that stably record the presence of analytes. Here, we test the performance of recombinase-memory biosensors that sense a sugar (arabinose) and a microbial communication molecule (3-oxo-C12- homoserine lactone) over 8 days ([~]70 generations) following analyte exposure. These biosensors use analyte sensing to trigger the expression of a recombinase which flips a segment of DNA, creating a genetic memory, and initiates fluorescent protein expression. The initial designs failed over time due to unintended DNA flipping in the absence of the analyte and loss of the flipped state after exposure to the analyte. Biosensor performance was improved by decreasing recombinase expression, removing the fluorescent protein output, and using qPCR to read out stored information. Application of memory biosensors in wastewater isolates achieved memory of analyte exposure in an uncharacterized Pseudomonas isolate. By returning these engineered isolates to their native environments, recombinase-memory systems are expected to enable longer duration and in situ investigation of microbial signaling, community shifts, and gene transfer beyond the reach of traditional environmental biosensors. IMPORTANCELiving microbial sensors can monitor chemicals and biomolecules in the environment in real-time, but they remain limited in their ability to function on the week, month, and year timescales. To determine if environmental microbes can be programmed to record the detection of analytes over longer timescales, we evaluated whether the sensing of a microbial signaling molecule could be recorded through a DNA rearrangement. We show that off-the-shelf DNA memory is suboptimal for long-duration information storage, use iterative design to enable robust functioning over more than a week, and demonstrate DNA memory in an uncharacterized wastewater Pseudomonas isolate. Memory biosensors will be useful for monitoring the role of quorum sensing in wastewater biofilm formation, and variations of this design are expected to enable studies of ecological processes in situ that are currently challenging to monitor using real-time biosensors and analytical instruments.

synthetic biology↗

Information storage across a microbial community using universal RNA memory

Biological recorders can code information in DNA, but they remain challenging to apply in complex microbial communities. To program microbiome information storage, a synthetic catalytic RNA (cat-RNA) was used to write information in ribosomal RNA (rRNA) about gene transfer host range. By reading out native and modified rRNA using amplicon sequencing, we find that 140 out of 279 wastewater microbial community members from twenty taxonomic orders participate in conjugation and observe differences in information storage across amplicon sequence variants. Twenty of the variants were only observed in modified rRNA amplicons, illustrating information storage sensitivity. This autonomous and reversible RNA-addressable memory (RAM) will enable biosurveillance and microbiome engineering across diverse ecological settings and studies of environmental controls on gene transfer and cellular uptake of extracellular materials. One-Sentence SummaryRibosomal RNA sequencing detects cellular events recorded across a wastewater microbial community using synthetic biology.

synthetic biology↗

Olivar: fully automated and variant aware primer design for multiplex tiled amplicon sequencing of pathogen genomes

Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 2 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly. Here we present Olivar, a first step towards a fully automated, variant-aware design of tiled amplicons for pathogen genomes. Olivar converts each nucleotide of the target genome into a numeric risk score, capturing undesired sequence features that should be avoided. In a direct comparison with PrimalScheme, we show that Olivar has fewer SNPs overlapping with primers and predicted PCR byproducts. We also compared Olivar head-to-head with ARTIC v4.1, the most widely used primer set for SARS-CoV-2 sequencing, and show Olivar yields similar read mapping rates ([~]90%) and better coverage to the manually designed ARTIC v4.1 amplicons. We also evaluated Olivar on real wastewater samples and found that Olivar had up to 3-fold higher mapping rates while retaining similar coverage. In summary, Olivar automates and accelerates the generation of tiled amplicons, even in situations of high mutation frequency and/or density. Olivar is available as a web application at https://olivar.rice.edu. Olivar can also be installed locally as a command line tool with Bioconda. Source code, installation guide and usage are available at https://github.com/treangenlab/Olivar.

bioinformatics↗