Biology subjects

Lee, S. H.

Publications and source records attributed to Lee, S. H..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Targeted degradation of pathologic tau aggregates via AUTOTAC ameliorates tauopathy

The pathogenesis of tauopathies including Alzheimers disease (AD) and progressive supranuclear palsy (PSP) involves the misfolding and aggregation of tau. Here, we employed AUTOTAC to induce the lysosomal degradation of intraneuronal tau aggregates. ATB2005A is a 734-Da chimera that simultaneously binds {beta}-sheet-rich tau aggregates and the autophagic receptor p62/SQSTM1, leading to autophagosomal sequestration and lysosomal co-degradation. In mouse models of tauopathies, orally administered ATB2005A lowered intraneuronal tau aggregates and exerted the therapeutic efficacy in neuroinflammation as well as cognition, behavior, and muscle movements. A Phase 2 clinical trial (U34401-4/2023/14) with companion dogs carrying canine cognitive dysfunction (CCD) demonstrated the efficacy of ATB2005A, as a veterinary medicine, to reverse the disease progression. ATB2005A is under Phase 1 clinical trial with human participants in Korea (202300697). These results validate AUTOTAC as a versatile platform for developing therapeutics to eradicate toxic protein aggregates in a wide range of proteinopathies.

neuroscience↗

bioRxiv2025

High-fidelity CRISPR genome editing of single-nucleotide mutation with near-complementary guide RNA via enhanced target binding kinetics

The CRISPR-Cas9 system is a powerful genome editing tool capable of precisely recognizing and cleaving specific DNA sequences, and has been extensively investigated as a strategy for correcting mutations associated with genetic diseases and cancer. However, conventional CRISPR genome engineering often fail to discriminate single-nucleotide mutations from wild-type alleles when the mutation is located outside the protospacer adjacent motif (PAM) sequence. To address this limitation, we developed a RNA engineering approach for designing near-complementary single guide RNA (sgRNA) that contain intentional mismatches within the seed region of the sgRNA. Single molecule kinetic analyses showed that the near-complementary sgRNA selectively reduces the binding affinity of CRISPR ribonucleoprotein complex by via differentiated increment in the dissociation rates to the wild-type target DNA compared to the mutant allele. The engineered kinetic characteristics of near-complementary sgRNAs enable highly specific genome editing of single-base mutations without reliance on PAM proximity. We demonstrate the application of the strategy to the a cancer-specific single-nucleotide G228A (-124C > T) mutation in the TERT promoter, frequently found in glioblastomas and other tumors, that does not generate a canonical PAM sequence. Our near-complementary sgRNA successfully induced selective editing of the mutant allele while sparing the wild-type sequence. Furthermore, single-molecule fluorescence resonance energy transfer (smFRET) analyss revealed distinct differences in binding kinetics between mutant and wild-type DNA, providing kinetic insight into the discrimination process. We conclude that the near-complementary sgRNA CRISPR editing strategy facilitates precise PAM-independent targeting of single-nucleotide mutations without protein engineering and offers a molecular framework for expanding the specificity and applicability of CRISPR-based genome and epigenome editing technologies.

biochemistry↗

bioRxiv2025

Drosophila Pyruvate Kinase Links Metabolic State with Circadian Output via TARANIS and PDF

The circadian clock generates [~]24-hour rhythms that anticipate daily environmental changes. Circadian clock and glucose metabolism are tightly interconnected, and both are disrupted in aging and disease. To examine how glucose hypometabolism impacts circadian rhythm, we downregulated glycolytic enzymes - Hexokinase-C (Hex-C), Phosphofructokinase (Pfk), and Pyruvate kinase (Pyk) - in Drosophila clock cells. Only Hex-C and Pyk knock-down (KD) altered period, lengthening and shortening rhythms, respectively. Notably, Pyk KD induced period shortening persisted in adult-specific KD (AKD), indicating a role independent of developmental effects. Pyk AKD reduced both PERIOD and Pigment-dispersing factor (PDF) protein levels, with PDF loss driving the short-period phenotype. Mechanistically, the transcriptional co-regulator TARANIS (TARA) was required: Pyk AKD lowered tara expression, while tara overexpression rescued PDF and circadian period. Our findings identify a novel PYK-TARA-PDF regulatory axis linking glycolytic activity to circadian neuropeptide output, providing mechanistic insight into how metabolic dysfunction contributes to circadian disruption in aging and neurodegenerative diseases.

neuroscience↗

bioRxiv2025

Optimizing twin prime editing components for scalable genome editing and therapy in spinocerebellar ataxia type 3

Recent advances in prime editing technologies using CRISPR modules fused with reverse transcriptase (RT) have enabled efficient and precise reprogramming of target genomic sequences. Twin prime editing using two coordinated prime editor complexes is a promising strategy for inducing extensive genomic modifications via reverse transcribed complementary templates. However, current twin prime editing systems still require improvements in editing efficiency, accuracy, and intended edit predictability. Here, efficiency and precision of twin prime editing were enhanced via engineering and optimizing conventional SpCas9(H840A)-RT-based prime editor components. A La domain-fused prime editor (La-SpCas9(H840A)-RT) and optimized pegRNAs were developed, achieving a 1.75 {+/-} 0.21-fold increase in gene editing efficiency at multiple genomic loci in human-derived cell lines without increasing off-target activity. La-SpCas9(H840A)-RT facilitated efficient [~]2.8 kb GFP transgene knock-in at target loci and eliminated the expanded polyQ tract in ATXN3 in patient-derived mutant cell lines modeling spinocerebellar ataxia type 3. The advanced twin prime editing platform expands genome engineering capabilities beyond existing CRISPR-based systems and holds great promise for diverse biotechnological and therapeutic applications.

bioengineering↗

bioRxiv2025

Systems-level Consequences of Low RAF Abundance for EGFR-ERK Signaling

The RAF kinases are central links between RAS, once activated by receptor tyrosine kinases (RTKs), and the extracellular signal-regulated kinases (ERK). In many cancer cells, RAFs are the least abundantly expressed RTK-ERK pathway proteins and can be present at just hundreds of copies per cell at the plasma membrane, but the consequences of limited RAF expression are unclear. By developing continuum and stochastic computational models of the epidermal growth factor receptor (EGFR)-ERK pathway, we showed that low RAF abundance creates stoichiometric bottlenecks between RTKs and ERK with concomitant stochastic RAF dynamics that propagate to weakly expressed downstream pathway proteins. Advanced sensitivity and Sloppiness analyses identified RAS activation and RAS-RAF interactions as strong determinants of signaling in low-RAF settings and revealed an efficient model fitting approach. RAF bottlenecks were predicted to impede ERK activation by oncogenic RAS mutants and explained a tendency for RAF1 membrane localization to be noisy. This work provides quantitative insight into a common, yet unexplored, regime for EGFR-ERK signaling and a systematic approach to develop and characterize dynamic models of receptor-mediated signaling. STATEMENT OF SIGNIFICANCERAF kinases connect receptors to the mitogenic ERK signaling pathway by translocating to the plasma membrane, but in a substantial fraction of cancer cell contexts RAFs are greatly outnumbered by other pathway proteins, potentially creating an unrecognized and consequential signaling bottleneck. We trained a novel computational model of EGFR-ERK signaling and characterized it comprehensively using integrated multivariate sensitivity analyses and Sloppiness analysis. The results revealed that low RAF abundance suppresses EGFR-mediated ERK activation, limits the effects of upstream oncogenic RAS mutants, and creates stochastic RAF dynamics that can propagate downstream. Thus, the canonical EGFR-ERK pathway exhibits divergent behaviors in a parameter space representative of a substantial fraction of cancer cell settings.

systems biology↗

bioRxiv2025

Unbiased genetics identifies a glutamatergic signaling network as a mediator of daily sleep patterns.

Sleep is a fundamental, conserved behavior important for survival. In many species, sleep behavior is controlled by poorly understood interactions between a system of circadian rhythms (CR), which promote sleep at ecologically appropriate times, and a homeostatic sleep drive that accumulates with time awake. The CR is a cellular phenomenon, driven by molecular oscillations of "clock genes" in nearly all cells. Emerging evidence indicates neuronal synapses are a key locus for the accumulation and resolution of sleep need, supporting a cellular basis of sleep need. Indeed, efforts to understand the genetic basis of sleep need identified Homer1a, a regulator of synapse homeostasis. To develop further insight into the genetic basis of sleep regulation, we measured daily sleep patterns in genetically diverse strains of mice from the Collaborative Cross. Strains with 1) highly consolidated light-phase sleep, or 2) fragmented, arrhythmic sleep, were identified for genetic analysis using quantitative trait loci (QTL) mapping. Excitingly, in F2 hybrids, 19 of 32 metrics of sleep and circadian behavior mapped to a narrow QTL containing GRM5, a postsynaptic glutamate receptor and binding partner of Homer1a, and GCPII, an astrocytic enzyme that regulates NAAG, a peptide agonist for the presynaptic/astrocytic glutamate receptor GRM3. Collectively, these genes form a coordinated glutamatergic signaling network across the tri-partite synapse. Pharmacology targeting GRM5, GCPII, and GRM3 strongly modulated sleep, functionally validating them as sleep-regulating genes. Our findings support a model in which synapses act as a cellular site for integration of circadian and sleep-need signals to regulate daily sleep patterns. Significance StatementSleep is a fundamental pillar of human health. Restorative sleep is supported by circadian rhythms (CR). Sleep and CR disruptions are prevalent in neuropsychiatric conditions and are increasingly understood as causal drivers of altered brain function and behavior. Therefore, sleep and CR are attractive therapeutic targets to improve health. However, the basic biological mechanisms that couple our need to sleep with the CR are not understood. Genetic discovery using diverse strains of mice identifies a glutamatergic signaling network coordinated across the synapse as an underlying genetic basis for daily sleep patterns. This work builds upon a growing body showing that excitatory synapses are a cellular site for the resolution of sleep need and interaction with the CR.

neuroscience↗

bioRxiv2025

Large-scale skin metagenomics reveals extensive prevalence, coordination, and functional adaptation of skin microbiome dermotypes across body sites

While skin microbiome studies have increasingly highlighted its importance in health and disease, our understanding of inter-individual heterogeneity in structure and function remains limited, impacting the ability to develop microbiome-based stratification and therapeutics. Powered by comprehensive skin microbiome characterization in a multi-ethnic population-based cohort (>3,550 shotgun metagenomes across 18 sampling sites), we established significant undescribed inter-individual heterogeneity and the extensive prevalence of distinct microbial configurations (17 species-resolution dermotypes) in seven out of nine body sites. Combining functional in silico and in vitro studies revealed insights into how these dermotypes assemble as a function of niche-dependent microbial interactions (e.g. hypoxia-dependent inhibition of S. hominis by S. epidermidis/M. luteus) and metabolic resource utilization (e.g. differential galactose and histidine metabolism). Integration of demographic, skin physiological, and behavioral data further identified >30 significant associations with host attributes. Cross-site analysis revealed remarkable coordination across disparate skin regions (predictive AUC-ROC>0.8) and bilateral consistency (Pearson {pi}>0.95), emphasizing the role of specific microbial and host factors in shaping dermotypes. Finally, we provide multiple lines of evidence that dermotype states impact the risk for skin discomfort (e.g. irritation, itch) and diseases (e.g. eczema), that when combined with our highly accurate dermotype classifiers (AUC-ROC>0.98), provide a new paradigm for understanding skin microbiome function and stratifying patients in the context of skin and other diseases.

genomics↗

bioRxiv2025

Generative frame interpolation enhances tracking of biological objects in time-lapse microscopy

Object tracking in microscopy videos is crucial for understanding biological processes. While existing methods often require fine-tuning tracking algorithms to fit the image dataset, here we explored an alternative paradigm: augmenting the image time-lapse dataset to fit the tracking algorithm. To test this approach, we evaluated whether generative video frame interpolation can augment the temporal resolution of time-lapse microscopy and facilitate object tracking in multiple biological contexts. We systematically compared the capacity of Latent Diffusion Model for Video Frame Interpolation (LDMVFI), Real-time Intermediate Flow Estimation (RIFE), Compression-Driven Frame Interpolation (CDFI), and Frame Interpolation for Large Motion (FILM) to generate synthetic microscopy images derived from interpolating real images. Our testing image time series ranged from fluorescently labeled nuclei to bacteria, yeast, cancer cells, and organoids. We showed that the off-the-shelf frame interpolation algorithms produced bio-realistic image interpolation even without dataset-specific retraining, as judged by high structural image similarity and the capacity to produce segmentations that closely resemble results from real images. Using a simple tracking algorithm based on mask overlap, we confirmed that frame interpolation significantly improved tracking across several datasets without requiring extensive parameter tuning and capturing complex trajectories that were difficult to resolve in the original image time series. Taken together, our findings highlight the potential of generative frame interpolation to improve tracking in time-lapse microscopy across diverse scenarios, suggesting that a generalist tracking algorithm for microscopy could be developed by combining deep learning segmentation models with generative frame interpolation.

cell biology↗

bioRxiv2025

Omics analysis reveals striking effects of progesterone receptor on mitochondria and mitochondria-mediated apoptosis independent of caspases in Breast Cancer cells

The role of progesterone receptor (PR) in breast cancer remains controversial with conflicting reports from clinical and laboratory studies. To address these discrepancies, we conducted an integrated omics analysis of effects of agonist-activated PR in MCF-7 cells with elevated PR expression. PR agonist R5020 exerted strong antiproliferative and proapoptotic effects in these cells. Quantitative proteomics identified 4,915 PR-regulated proteins and 678 phosphorylated peptides, with nearly 100% verifiable rate by Western blotting analysis. The proteomics data was closely correlated with transcriptomic data. Key pathways upregulated included hypoxia, p53 signalling, TNFA signalling via NFKB, epithelial-mesenchymal transition, and KRAS signalling, while E2F targets, G2/M checkpoint, and mitotic spindle assembly were downregulated. R5020 broadly suppressed cell cycle regulators, including CDKs, cyclins, DNA replication proteins, and all components of the Ndc80 complex and chromosomal passenger complexes. Concurrently, it elicited significant changes in 200 mitochondrial proteins, upregulating many proapoptotic factors (e.g., BNIP3, NIX, AIF/AIFM1, AIFM2, ENDOG, HtrA2/Omi, Smac/DIABLO) and downregulating anti-apoptotic proteins (BCL-2, BCL-XL). This culminated in mitochondria-mediated apoptosis independent of effector caspases. The omics analysis also detected previously reported upregulation of pro-growth proteins such as EGFR, IRS2, and CCND1, but the upregulation was functionally futile and inhibitory phosphorylation of IRS2 at S306 increased 4-fold. In conclusion, this omics study achieved to date the most comprehensive and holistic understanding of PR-regulated proteins and molecular networks that are strongly anti-proliferative and proapoptotic with significant involvement of mitochondria. These findings suggest that pure PR agonists warrant evaluation as first-line endocrine therapy for breast cancer with high PR expression.

cancer biology↗

bioRxiv2025

Keratinocyte Arginase1 Deficiency Impairs Healing and Antimicrobial Defence against Pseudomonas aeruginosa Infection

Wound infection is a major disruptor of wound healing. Keratinocytes, critical in repair and microbial responses, require the L-arginine hydrolysing enzyme arginase1, for effective healing. Wound pathogens such as Pseudomonas aeruginosa may also need L-arginine. We therefore investigated host-microbial interactions in the context of wound healing and L-arginine metabolism. Arginase-inhibited murine wounds challenged with P. aeruginosa, exhibited significantly delayed re-epithelialisation. This finding was recapitulated in vitro using P. aeruginosa-challenged, arginase1 deficient (shARG1) keratinocytes, associated with reduced epithelial proliferation and viability, and heightened inflammation. Whilst P. aeruginosa challenge promoted host metabolism of L-arginine, this was perturbed in wounded shARG1 keratinocytes. There was, however, heightened downstream polyamine metabolism in shARG1 cells when under P. aeruginosa challenge. Host keratinocyte arginase1 deficiency promoted bacterial growth in vitro, in line with a failure to upregulate the anti-microbial peptides, {beta}-defensins, in shARG1 scratches. This work demonstrates a pivotal role for keratinocyte arginase1 in wound infection. HIGHLIGHTSO_LIHost arginase is required for effective healing under P. aeruginosa challenge. C_LIO_LIP. aeruginosa enhances host keratinocyte L-arginine metabolism upon scratch. C_LIO_LIP. aeruginosa promotes polyamine metabolism in arginase1 deficient wounds in vitro. C_LIO_LIArginase1 is required for keratinocyte anti-microbial defence against P. aeruginosa. C_LI

microbiology↗

bioRxiv2024

Deep Gaussian Process with Uncertainty Estimation for Microsatellite Instability and Immunotherapy Response Prediction Based on Histology

Determining tumor microsatellite status has significant clinical value because tumors that are microsatellite instability-high (MSI-H) or mismatch repair deficient (dMMR) respond well to immune check-point inhibitors (ICIs) and oftentimes not to chemotherapeutics. We propose MSI-SEER, a deep Gaussian process-based Bayesian model that analyzes H&E whole-slide images in weakly-supervised-learning to predict microsatellite status in gastric and colorectal cancers. We performed extensive validation using multiple large datasets comprised of patients from diverse racial backgrounds. MSI-SEER achieved state-of-the-art performance with MSI prediction, which was by integrating uncertainty prediction. We achieved high accuracy for predicting ICI responsiveness by combining tumor MSI status with stroma-to-tumor ratio. Finally, MSI-SEERs tile-level predictions revealed novel insights into the role of spatial distribution of MSI-H regions in the tumor microenvironment and ICI response.

bioinformatics↗

bioRxiv2024

A brain-shuttled antibody targeting alpha synuclein aggregates for the treatment of synucleinopathies

Parkinsons disease and multiple system atrophy are members of a class of devastating neurodegenerative diseases called synucleinopathies, which are characterized by the presence of alpha-synuclein (-Syn) rich aggregates in the brains of patients. Passive immunotherapy targeting these aggregates is an attractive disease-modifying strategy. Such an approach must not only demonstrate target selectivity towards -Syn aggregates, but also achieve appropriate brain exposure to have the desired therapeutic effect. Here we present preclinical data for a next-generation antibody for the treatment of synucleinopathies. SAR446159 (ABL301) is a bispecific antibody composed of an -Syn-binding immunoglobulin (IgG) and an engineered insulin-like growth factor receptor 1 (IGF1R) binding single-chain variable fragment (scFv), acting as a shuttle to transport an antibody across the blood-brain barrier (BBB). SAR446159 binds tightly and preferentially to -Syn aggregates and prevents their seeding capacity in vitro and in vivo. Incubation with SAR446159 reduced -Syn preformed fibrils (PFFs) uptake in neurons and facilitated uptake and clearance by microglia. In wild type mice injected in the striatum with -Syn PFFs, treatment with SAR446159 reduced the spread of aSyn pathology as measured by phosphorylated -Syn staining and lessened the severity of motor phenotypes. Additionally, in 9-month-old transgenic mice overexpressing -Syn (mThy1--Syn, Line 61), repeated treatment with SAR446159 reduced markers of -Syn aggregation in the brain. SAR446159 had significantly higher brain and CSF penetration over a sustained period than its monospecific counterpart (1E4) in rats and monkeys. The binding properties of SAR446159 combined with its brain-shuttle technology make it a potent, next-generation immunotherapeutic for treating synucleinopathies.

neuroscience↗

bioRxiv2024

Kupffer cell and recruited macrophage heterogeneity orchestrate granuloma maturation and hepatic immunity in visceral leishmaniasis

In murine models of visceral leishmaniasis (VL), parasitization of resident Kupffer cells (resKCs) is responsible for early growth of Leishmania infantum in the liver, which leads to granuloma formation and eventual parasite control. We employed the chronic VL model, and revealed an open niche established by KCs death and their migration outside of the sinusoids, resulting in their gradual replacement by monocyte-derived KCs (moKCs). While early granulomas were composed of resKCs, late granulomas were found outside of the sinusoids and contained resKC-derived macrophages, and monocyte-derived macrophages (momacs). ResKCs and moKCs within the sinusoids were identified as homeostatic/regulatory cells, while resKC-derived macrophages and momacs within late granulomas were pro-inflammatory. Despite the infection being largely confined to the resKC-derived macrophages, in the absence of monocyte recruitment, parasite control was strongly compromised. Macrophage heterogeneity, involving migration and reprogramming of resKCs, along with recruitment of monocyte-derived cells, is a hallmark of granuloma maturation and hepatic immunity in VL.

immunology↗

bioRxiv2024

Computational Insights into the molecular dynamics of the binding of ligands in the Methanol Dehydrogenase

Methanol dehydrogenase (MDH) is a promising biocatalyst for industrial use, converting methanol to formaldehyde. Our molecular modeling revealed methanol binds to MDH with [~]7 kcal/mol free energy, while formaldehyde binds with [~]4 kcal/mol. This suggests methanol remains longer in the active site, and formaldehyde exits more readily post-reaction. These insights are crucial for designing more efficient MDH variants for industrial applications. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/602606v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@442a65org.highwire.dtl.DTLVardef@13b877eorg.highwire.dtl.DTLVardef@13c8ef6org.highwire.dtl.DTLVardef@cde32b_HPS_FORMAT_FIGEXP M_FIG C_FIG The left panel shows methanol and formaldehyde within the active site of methanol dehydrogenase, illustrating entry and release paths. The right panel presents the free energy profiles, indicating methanols stronger binding affinity and formaldehydes easier release post-reaction.

biophysics↗

bioRxiv2024

Senescent-like microglia limit remyelination through the senescence associated secretory phenotype

The capacity to regenerate myelin in the central nervous system (CNS) diminishes with age. This decline is particularly evident in multiple sclerosis (MS), which has been suggested to exhibit features of accelerated biological aging. Whether cellular senescence, a hallmark of aging, contributes to remyelination impairment remains unknown. Here, we show that senescent cells (SCs) accumulate within demyelinated lesions after injury, and their elimination enhances remyelination in young mice but not in aged mice. In young mice, we observed the upregulation of senescence-associated transcripts primarily in microglia after demyelination, followed by their reduction during remyelination. However, in aged mice, senescence-associated factors persisted within lesions, correlating with inefficient remyelination. We found that SC elimination enhanced remyelination in young mice but was ineffective in aged mice. Proteomic analysis of senescence-associated secretory phenotype (SASP) revealed elevated levels of CCL11/Eotaxin-1 in lesions, which was found to inhibit efficient oligodendrocyte maturation. These results suggest therapeutic targeting of SASP components, such as CCL11, may improve remyelination in aging and MS.

neuroscience↗

bioRxiv2024

DeepKin: precise estimation of in-depth relatedness and its application in UK Biobank

Accurately estimating relatedness between samples is crucial in genetics and epidemiological analysis. Using genome-wide single nucleotide polymorphisms (SNPs), it is now feasible to measure realized relatedness even in the absence of pedigree. However, the sampling variation in SNP-based measures and factors affecting method-of-moments relatedness estimators have not been fully explored, whilst static cut-off thresholds have traditionally been employed to classify relatedness levels for decades. Here, we introduce the deepKin framework as a moment-based relatedness estimation and inference method that incorporates data-specific cut-off threshold determination. It addresses the limitations of previous moment estimators by leveraging the sampling variance of the estimator to provide statistical inference and classification. Key principles in relatedness estimation and inference are provided, including inferring the critical value required to reject the hypothesis of unrelatedness, which we refer to as the deepest significant relatedness, determining the minimum effective number of markers, and understanding the impact on statistical power. Through simulations, we demonstrate that deepKin accurately infers both unrelated pairs and relatives with the support of sampling variance. We then apply deepKin to two subsets of the UK Biobank dataset. In the 3K Oxford subset, tested with four sets of SNPs, the SNP set with the largest effective number of markers and correspondingly the smallest expected sampling variance exhibits the most powerful inference for distant relatives. In the 430K British White subset, deepKin identifies 212,120 pairs of significant relatives and classifies them into six degrees. Additionally, cross-cohort significant relative ratios among 19 assessment centers located in different cities are geographically correlated, while within-cohort analyses indicate both an increase in close relatedness and a potential increase in diversity from north to south throughout the UK. Overall, deepKin presents a novel framework for accurate relatedness estimation and inference in biobank-scale datasets. For biobank-scale application we have implemented deepKin as an R package, available in the GitHub repository (https://github.com/qixininin/deepKin).

genetics↗

bioRxiv2024

Landscape profiling of PET depolymerases using a natural sequence cluster framework

Since the demonstration that rapid polyethylene terephthalate (PET) decomposition using enzymes is feasible, a number of efficient depolymerases have been reported with the aim of resolving the plastic pollution issues. However, sporadic studies on enzymes with PET hydrolysis activity hinder the understanding of the distribution of potential PETases hidden in natures repertoire, and subsequently, the identification of potent enzymes. Here, we present the clustering of 1,894 PETase candidates, which include the majority of known PETases, and describe their profiling. An archipelago landscape of 170 lineages shows distribution of 289 representative sequences with features associated with PET-degrading capabilities. A birds-eye view of the landscape identifies three highly promising yet unexplored PETase lineages and two potent PETases, Mipa-P and Kubu-P. The engineered Mipa-PM19 and Kubu-PM12 variants exhibit both high PET hydrolysis activity and thermal stability. In particular, Kubu-PM12 outperformed the engineered benchmarks in terms of PET depolymerization in harsh environments, such as with high substrate load and ethylene glycol as the solvent. Our landscape framework and the identified variants assist in the understanding of how biological processes respond to solid-state and non-natural PET plastics.

systems biology↗

bioRxiv2024

Development and Application of Decontamination Methods for the Re-Use of Laboratory Grade Plastic Pipette Tips

During the SARS-CoV-2 pandemic, a need for methods to decontaminate and reuse personal protective equipment (PPE) and medical plastics became a priority. In this investigation we aimed to develop a contamination evaluation protocol for laboratory pipette tips, after decontamination. Decontamination methods tested in this study included cleaning with a common laboratory detergent (2.5% Alconox(R) solution followed with steam decontamination), exposure of ozone vapor at 250 and 14400 PPM * minute, and exposure to cold atmospheric plasma (CAP). All tips (control and experimental groups) were introduced to the methods described, while tips exposed to DNA extracts of Aeromonas hydrophila (ATCC-23211) were assessed for experimental groups. Decontamination was determined by turnover ratio and log reduction in detectable genomic material on the contaminated products using real-time quantitative PCR (qPCR) assay. Our results showed, cleaning tips with lab detergents along with steam decontamination removed genetic material, resulting in the highest log reduction, compared with ozone or CAP treatments. Detergent/washing methods showed the highest turnover ratio (95.9 %) and log reduction (5.943). However, the excessive residue (post-cleaning) on the plastic, within inner filters, and tip boxes suggested that washing with lab detergents was not favorable for reuse. Ozone vapor at 14400 PPM * minutes showed the second highest turnover ratio (98.4 %) and log reduction (4.511). CAP exposure with tips inverted (the tip end exposed closer to the plasma flame) for 1 minute showed a turnover ratio of (68.3 %) and log reduction (4.002). Relatively, lower turnover ratio and log reduction of CAP could be attributed to development/optimization of treatment conditions, including increases in exposure time and relative to tip positioning.

molecular biology↗