Biology subjects

Tarr, M.

Publications and source records attributed to Tarr, M..

3 recordsLinked to original sources

bioRxiv2025

A high throughput assay to detect enzymatic polyethylene oxidation

Biological plastics deconstruction and upcycling have emerged as a sustainable alternative to traditional recycling technologies for plastics waste. The discovery and engineering of efficient thermostable poly(ethylene terephthalate) (PET) hydrolases has made biological PET recycling possible at scale; however, enzymes for non-PET plastics, which account for approximately 70% of all plastics produced, remain largely undiscovered. To accelerate the discovery of such enzymes, a high throughput screening (HTS) platform is needed. Here, we develop a HTS liquid-based assay to detect one of the first committed steps of polyolefin degradation, oxidation of the C-H bond to an aldehyde. We test 4-hydrazino-7-nitro-2,1,3-benxoxadiozole hydrazine (NBD-H), which reacts with generated aldehydes to form a fluorescent hydrazone, on oxidized low-density polyethylene (LDPE) films. Hydrazone generation correlated well with established carbonyl index metrics for polymer oxidation (R2 = 0.97). Moreover, we demonstrate that the probe reliably identifies LDPE-active dye decolorizing peroxidases (DyPs) that generate aldehydes on LDPE films, serving as effective screen as demonstrated by a receiver operating characteristic area under the curve of 0.95. Due to the rapid fluorescent readout and parallelization in microarray plates, this assay enables screening thousands of enzymes in 24 hours compared to time-consuming established approaches, accelerating discovery of enzymes that catalyze the first step of polyolefin biodeconstruction.

biochemistry↗

bioRxiv2025

Biological polyethylene deconstruction initiated by oxidation from DyP peroxidases

Polyethylene (PE) is the most commonly used plastic on Earth due to its favorable material properties such as high ductility, mechanical strength, and bond homogeneity that make the material resistant to deconstruction. However, the lack of robust recycling infrastructure for PE end-of-life management is leading to an estimated 4 million tons of environmental accumulation annually, with implications for human and environmental health. Biological deconstruction and upcycling could potentially aid in PE waste management by allowing for high-yield conversion of waste plastics to high value products, although such processes are not yet possible. In this work, we mined the gut of low-density PE (LDPE) fed mealworms that can reduce LDPE molecular weight by >40% and discovered dye decolorizing peroxidases (DyPs) that oxidized LDPE, initiating biological deconstruction. A plastic-active DyP is characterized by a hydrophobic loop near its active site that helps mediate binding and tunes activity. LDPE oxidation is driven by surface exposed residues proximal to the active site enabling activity on polymeric substrates. Our work provides robust evidence for enzymatic LDPE deconstruction and identifies molecular targets for further development to realize scalable biological LDPE upcycling. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=41 SRC="FIGDIR/small/640435v1_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@146b8fborg.highwire.dtl.DTLVardef@1a72adorg.highwire.dtl.DTLVardef@5ece5forg.highwire.dtl.DTLVardef@3ee20a_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2023

Neural Selectivity for Real-World Object Size In Natural Images

1Real-world size is a functionally important high-level visual property of objects that supports interactions with our physical environment. Critically, real-world-size is robust over changes in visual appearance as projected onto our retinae such that large and small objects are correctly perceived to have different real-world sizes. To better understand the neural basis of this phenomenon, we examined whether the neural coding of real-world size holds for objects embedded in complex natural scene images, as well as whether real-world size effects are present for both inanimate and animate objects, whether low- and mid-level visual features can account for size selectivity, and whether neural size tuning is best described by a linear, logarithmic, or exponential neural coding function. To address these questions, we used a large-scale dataset of fMRI responses to natural images combined with per-voxel regression and contrasts. Importantly, the resultant pattern of size selectivity for objects embedded in natural scenes was aligned with prior results using isolated objects. Extending this finding, we also found that size coding exists for both animate and inanimate objects, that low-level visual features cannot account for neural size preferences, and size tuning functions have different shapes for large versus small preferring voxels. Together, these results indicate that real-world size is an ecologically significant dimension in the larger space of behaviorally-relevant cortical representations that support interactions with the world around us.

neuroscience↗