Biology subjects

Lee, H. H.

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

At least 19 recordsLinked to original sources

bioRxiv2025

A scalable transposon mutagenesis system for non-model bacteria

Transposon mutagenesis enables genome-wide interrogation of gene function with a single self-contained genetic construct. However, its application to non-model bacteria remains limited because transposition efficiency depends on multiple host factors that are difficult to predict a priori including transposase activity, antibiotic resistance marker performance, and regulatory element compatibility. Here, we present a scalable system to identify functional transposon configurations in non-model bacteria through pooled library screening. We selected 18 promoters across multiple bacterial phyla to independently drive expression of the transposase and antibiotic resistance marker, generating 324 promoter combinatorial variants for each of six antibiotic resistance markers. We developed a high-throughput, automated workflow to deliver all 1,944 mariner-based transposon variants in a single experiment and applied this to 92 non-model bacteria spanning multiple phyla. From this, we identified functional transposons for 43 strains, with high-level mutagenesis (102-104 unique insertions) in 13 species, including seven with no previously described transposon mutagenesis. We then expanded to a dual-transposase system, mariner or Tn5, and devised a single transposon insertion sequencing method for high-throughput screening of 3,888 configurations. To demonstrate the practical utility of our screening approach, we used a top-performing variant to generate a genome-wide transposon mutant library for Comamonas testosteroni KF-1, a bacterium that metabolizes plastic- and lignin-derived polymers. We assayed this C. testosteroni mutant library to identify enzymatic pathways, transporter genes, and regulators essential for the metabolism of plastics-associated monomer terephthalate and lignin-associated monomer 4-hydroxybenzoate. Together, this work establishes a scalable approach to construct and identify genetic perturbation systems in non-model bacteria, expanding our ability to systematically probe gene function across the bacterial tree of life.

synthetic biology↗

bioRxiv2025

A genetic platform for a biocementation bacterium

Sporosarcina pasteurii is the most widely studied bacterium for microbially-induced calcium carbonate precipitation (MICP), a process of intense interest for materials and construction applications. Despite two decades of investigation, S. pasteurii has remained genetically intractable, limiting our mechanistic understanding of biomineralization pathways and constraining efforts to engineer scalable solutions. Here, we present the first genetic toolkit for S. pasteurii, including a stable replicating plasmid, a conjugation-based DNA delivery protocol, engineered inducible promoters, and methods for genome modification. Using homologous recombination, we precisely deleted 5.7 kb of the genome spanning two operons encoding urease activity and demonstrated complete loss of biocementation. We also screened a library of engineered transposon constructs for activity in S. pasteurii and generated a genome-wide mutant library with >15,000 unique insertion sites. Using this library, we identified putative genes affecting ureolytic growth, revealing previously inaccessible aspects of S. pasteurii genetics. This work establishes S. pasteurii as a genetically tractable platform for rational engineering of MICP and constitutes the first genetic modification capability within the Sporosarcina genus.

synthetic biology↗

bioRxiv2025

Active learning guides automated discovery of DNA delivery via electroporation for non-model microbes

Delivery of recombinant DNA is foundational for understanding and engineering a target organism. Electroporation can be applied to any cell type, yet identification of a working protocol for new organisms remains bespoke and laborious because no systematic framework exists, and appropriate instrumentation is lacking. Here, we describe an automated high-throughput platform which uses active learning to discover electroporation protocols for non-model microbes. We first devised a 24-condition electroporation screen, based on systematic evaluation and selection of key parameters, that can be applied to any microbe. Facilitated by a custom-built fully-programmable electroporator, we successfully identified electroporation protocols for eight non-model bacteria using this screen alone. We then combined this electroporation screen with our pooled POSSUM plasmid library to simultaneously evaluate 408 experimental conditions per organism and identified both a protocol and a replicating plasmid for five non-model Proteobacteria spanning three major classes (alpha-, beta-, and gamma-). We report the first electroporation protocols for Shewanella indica, Shewanella putrefaciens 200, Shewanella putrefaciens 95, Halomonas elongata, Piscinibacter sakaiensis, and Duganella zoogloeoides, as well as multiple alternative protocols for Shewanella amazonensis, Shewanella oneidensis, Azospirillum brasilense, Cupriavidus necator, Pseudomonas alcaliphila, and Escherichia coli. Finally, we developed an active learning pipeline to guide the selection of parameters based on gathered experimental data. Using our robotic platform, we iteratively tested 538 conditions over three iterations to improve electroporation for the emerging industrial chassis C. necator, achieving 8.6-fold higher transformation efficiency than state of the art. This work establishes a discovery platform for DNA delivery to diverse and recalcitrant microbes that can be extended broadly to non-model organisms in our biosphere.

microbiology↗

bioRxiv2025

Functional genomics in a microbe that degrades and metabolizes PET plastic

Piscinibacter sakaiensis (formerly Ideonella sakaiensis) was the first bacterial species known to both completely degrade and assimilate polyethylene terephthalate (PET). However, the absence of efficient genetic tools has limited direct engineering of this organism, forcing most efforts to rely on heterologous expression of PET-degrading enzymes in model hosts. Here, we establish foundational genetic tools to engineer P. sakaiensis. We identify a functional plasmid origin of replication, multiple new selectable markers, and a transposon system for the strain. We use these tools to construct a genome-wide, barcoded transposon mutant library for pooled high-throughput functional screens. We apply this mutant library to growth on PET and identify metabolic and physiological genes that impact PET biodegradation. We also use this library to reveal mutants with improved DNA uptake for genome engineering. Together, these advances provide a platform for functional genomics in P. sakaiensis and positions this naturally evolved plastic-degrading bacterium as an engineerable chassis for synthetic biology and sustainable materials research.

microbiology↗

bioRxiv2025

A reference set of functional plasmids for Vibrio natriegens

New microbial hosts with superior phenotypes, such as fast growth, are attractive for research and biotechnology, but often lack systematic evaluation of functional genetic parts. A reference set of working plasmids would increase reproducibility and encourage use of these hosts. Here, we use the POSSUM toolkit, a collection of 23 origins-of-replication and 6 antibiotic markers, to identify functional genetic parts for strains of Vibrio natriegens. We applied this to the wild-type strain ATCC 14048 and an engineered variant NBx CyClone, evaluating 414 combinations of origins of replication and antibiotic selection conditions. We show that both strains support five replicons (pNG2, pSa, pSC101ts, p15A, and RSF1010) with NBx CyClone supporting an extra replicon RK2. The assay can be performed in under a week and is compatible with multiple DNA delivery methods. This work demonstrates the feasibility of rapidly establishing reference information to accelerate the adoption of new microbial hosts.

synthetic biology↗

bioRxiv2025

Lamin B loss in nuclear blebs is rupture dependent while increased DNA damage is rupture independent

The nucleus houses genetic information and functions separate from the rest of the cell. Loss of nuclear shape results in nuclear ruptures. Nuclear blebs are deformations identified by decreased DNA density, while lamin B levels vary drastically. To determine if decreased lamin B levels are due to nuclear rupture, we used immunofluorescence to measure levels of lamin B and emerin, a nuclear envelope protein that enriches to sites of nuclear rupture. We observed that cell types that exhibit decreased levels of lamin B also show an enrichment of emerin in nuclear blebs. Oppositely, in other cell types, nuclear blebs display maintained levels of lamin B1 and showed no emerin enrichment. To determine how nuclear rupture affects DNA damage, we time lapse imaged nuclear rupture dynamics then fixed the same cells to conduct immunofluorescence of {gamma}H2AX and emerin. We find that DNA damage levels are higher in blebbed nuclei independent of nuclear rupture. Thus, we confirm that lamin B1 loss in nuclear blebs is due to nuclear rupture and blebbed nuclei have increased DNA damage that is independent of rupture. Summary statement (180-200 characters): We measured lamin B and DNA damage in blebbed nuclei to determine the effect of nuclear rupture. We find that nuclear rupture causes loss of lamin B in nuclear blebs but that increased DNA damage in blebbed nuclei is independent of rupture.

cell biology↗

bioRxiv2025

An arginine switch drives the stepwise activation of β-arrestin

{beta}-arrestins ({beta}arrs) play a crucial role in regulating G protein-coupled receptor (GPCR) signaling and trafficking. Canonically, interactions of {beta}arr with the phosphorylated intracellular GPCR-tail induce a multi-step conformational transition that results in the activation of {beta}arr. Depending on the specific interaction pattern with the receptor, {beta}arrs adopt multiple conformational states, each tightly linked to a specific functional outcome of {beta}arr recruitment. Despite its physiological relevance, the structural determinants of {beta}arr activation remain poorly understood. Using a combination of molecular dynamics simulations, biochemical and cell-based experiments, we reveal how specific interactions with a prototypical GPCR promote the unbinding of the {beta}arr2 C-tail--a crucial step in arrestin activation. Importantly, we observe that the expulsion of the C-tail is promoted by the displacement of a conserved arginine residue (Arg394) within the {beta}arr polar core, which we dub "the arginine switch." Our study uncovers a previously unknown molecular switch that, upon engagement, destabilizes the polar core as a crucial step in the GPCR-induced {beta}arr activation.

biochemistry↗

bioRxiv2024

Predicting microbial growth conditions from amino acid composition

The ability to grow a microbe in the laboratory enables reproducible study and engineering of its genetics. Unfortunately, the majority of microbes in the tree of life remain uncultivated because of the effort required to identify culturing conditions. Predictions of viable growth conditions to guide experimental testing would be highly desirable. While carbon and energy sources can be computationally predicted with annotated genes, it is harder to predict other requirements for growth such as oxygen, temperature, salinity, and pH. Here, we developed genome-based computational models capable of predicting oxygen tolerance (92% balanced accuracy), optimum temperature (R2=0.73), salinity (R2=0.81) and pH (R2=0.48) for novel taxonomic microbial families without requiring functional gene annotations. Using growth conditions and genome sequences of 15,596 bacteria and archaea, we found that amino acid frequencies are predictive of growth requirements. As little as two amino acids can predict oxygen tolerance with 88% balanced accuracy. Using cellular localization of proteins to compute amino acid frequencies improved prediction of pH (R2 increase of 0.36). Because these models do not rely on the presence or absence of specific genes, they can be applied to incomplete genomes, requiring as little as 10% completeness. We applied our models to predict growth requirements for all 85,205 species of sequenced bacteria and archaea and found that uncultivated species are enriched in thermophiles, anaerobes, and acidophiles. Finally, we applied our models to 3,349 environmental samples with metagenome-assembled genomes and showed that individual microbes within a community have differing growth requirements. This work guides identification of growth constraints for laboratory cultivation of diverse microbes.

microbiology↗

bioRxiv2024

Design and construction towards a pan-microbial toolkit

Establishing genetic tractability in non-model microbes requires identifying genetic parts that function in a target host. However, the paucity and purported narrow host range of available parts means that successful identification is governed by serendipity. Instead, a more comprehensive and scalable process would be desirable. Here, we describe the design principles for a pan-microbial genetic toolkit in which phylogenetically-diverse parts can be assembled and tested for function in microbes using high-throughput readouts. The architecture is based on Golden Gate Assembly, which simplifies the addition of parts and the construction of combinatorial libraries. We used this framework to develop two modules: first, the POSSUM (Plasmid Origins and Selection MarkerS for Undomesticated Microbes) module for identification of replicating plasmids in non-model microbes which includes 29 plasmid origin of replication sequences, 23 selection markers, and 30 unique DNA sequences for tracking by sequencing; second, the MACKEREL (Modular, NGS-trACKable ExpRession ELement) module, for identification of functional gene expression cassettes which includes 426 bacterial promoter-RBS sequences driving fluorescent reporter expression, trackable by flow cytometry. We demonstrate the use of these libraries to screen for functional promoter-RBS variants in 6 non-model microbes. Continued efforts to expand this pan-microbial toolbox will accelerate efforts to improve genetic tractability and guide research across the tree of life.

synthetic biology↗

bioRxiv2023

An agarose disk electroporation method for ex vivo retinal tissue cultured at the air-liquid interface reveals electrical stimulus-induced cell cycle reentry in retinal cells

It is advantageous to culture the ex vivo murine retina along with many other tissue types at the air-liquid interface. However, gene delivery to these cultures can be challenging. Electroporation is a fast and robust method of gene delivery, but typically requires submergence in a liquid buffer to allow electric current flow. We have developed a submergence-free electroporation technique using that allows for efficient gene delivery to the ex vivo murine retina. This method advances our ability to use ex vivo retinal tissue for genetic studies and can easily be adapted for any tissue cultured at an air-liquid interface. Use of this method has revealed valuable insights on the state of ex vivo retinal tissues and the effects of electrical stimulation on retinal cells. MotivationTissues cultured at the air-liquid interface, such as retinal tissue, are adhered to a filter membrane with media underneath but not fully submerged. If tissues are fully submerged in liquid, they detach from the membrane and become damaged. Electroporation typically requires tissue submergence for electric current flow. We have developed a submergence-free electroporation method using an agarose disk for electric current delivery that can efficiently and consistently electroporate ex vivo retinal tissue cultured at an air-liquid interface without the need to submerge the tissue and disrupt the culture system.

cell biology↗

bioRxiv2023

Mefloquine-induced conformational shift in Cx36 N-terminal helix leading to channel closure mediated by lipid bilayer

Connexin 36 (Cx36) forms interneuronal gap junctions, establishing electrical synapses for rapid synaptic transmission. In disease conditions, inhibiting Cx36 gap junction channels (GJCs) is beneficial, as it prevents abnormal synchronous neuronal firing and apoptotic signal propagation, mitigating seizures and progressive cell death. Here, we present cryo-electron microscopy structures of human Cx36 GJC in complex with known channel inhibitors, such as mefloquine, arachidonic acid, and 1-hexanol. Notably, these inhibitors competitively bind to the binding pocket of the N-terminal helices (NTH), inducing a conformational shift from the pore-lining NTH (PLN) state to the flexible NTH (FN) state. This leads to the obstruction of the channel pore by flat double-layer densities of lipids. These studies elucidate the molecular mechanisms of how Cx36 GJC can be modulated by inhibitors, providing valuable insights into potential therapeutic applications.

biochemistry↗

bioRxiv2023

MicrobeMod: A computational toolkit for identifying prokaryotic methylation and restriction-modification with nanopore sequencing

Bacteria and archaea use restriction-modification (R-M) systems to distinguish self from foreign DNA by methylating their genomes with DNA methyltransferases with diverse sequence specificities, and these immunity systems often vary at the strain level. Identifying active methylation patterns and R-M systems can reveal barriers to the introduction of recombinant DNA or phage infection. Here, we present the computational MicrobeMod toolkit for identifying 5mC and 6mA methylation sequence motifs and R-M systems in bacterial genomes using nanopore sequencing of native DNA. We benchmark this approach on a set of reference E. coli strains expressing methyltransferases with known specificities. We then applied these analyses to 31 diverse bacterial and archaeal organisms to reveal the methylation patterns of strains with previously unexplored epigenetics, finding that prokaryotic 5-methylcytosine may be more common than previously reported. In summary, MicrobeMod can rapidly reveal new epigenetics within a prokaryotic genome sequenced with Oxford Nanopore R10.4.1 flow cells at sequencing depths as low as 10x and only requires native DNA. This toolkit can be used to advance fundamental knowledge of bacterial methylation and guide strategies to overcome R-M barriers of genetic tractability in non-model microbes.

microbiology↗

bioRxiv2023

Characterizing Low-cost Registration for Photographic Images to Computed Tomography

Mapping information from photographic images to volumetric medical imaging scans is essential for linking spaces with physical environments, such as in image-guided surgery. Current methods of accurate photographic image to computed tomography (CT) image mapping can be computationally intensive and/or require specialized hardware. For general purpose 3-D mapping of bulk specimens in histological processing, a cost-effective solution is necessary. Here, we compare the integration of a commercial 3-D camera and cell phone imaging with a surface registration pipeline. Using surgical implants and chuck-eye steak as phantom tests, we obtain 3-D CT reconstruction and sets of photographic images from two sources: Canfield Imagings H1 camera and an iPhone 14 Pro. We perform surface reconstruction from the photographic images using commercial tools and open-source code for Neural Radiance Fields (NeRF) respectively. We complete surface registration of the reconstructed surfaces with the iterative closest point (ICP) method. Manually placed landmarks were identified at three locations on each of the surfaces. Registration of the Canfield surfaces for three objects yields landmark distance errors of 1.747, 3.932, and 1.692 mm, while registration of the respective iPhone camera surfaces yields errors of 1.222, 2.061, and 5.155 mm. Photographic imaging of an organ sample prior to tissue sectioning provides a low-cost alternative to establish correspondence between histological samples and 3-D anatomical samples.

bioengineering↗

bioRxiv2023

Structure of recombinant formate dehydrogenase from Methylobacterium extorquens (MeFDH1)

Formate dehydrogenase (FDH) is critical for the conversion between formate and carbon dioxide. Despite its importance, the structural complexity of FDH and difficulties in the production of the enzyme have made it difficult to elucidate its unique physicochemical properties. Here, we purified recombinant Methylobacterium extorquens AM1 FDH (MeFDH1) and used cryo-electron microscopy to determine its structure. We resolved a heterodimeric MeFDH1 structure at a resolution of 2.8 [A], showing a noncanonical active site and a well-embedded Fe-S redox chain relay. In particular, the tungsten bis-molybdopterin guanine dinucleotide active site showed an open configuration with the flexible C-terminal cap domain, suggesting structural and dynamic heterogeneity in the enzyme. SIGNIFICANCE- A recombinant MeFDH1 from an inducible expression system - Structural characterization of recombinant MeFDH1 for its catalytic activity - A dynamic, open configuration of the C-terminal cap domain

biophysics↗

bioRxiv2023

The Salivary Microbiome and Predicted Metabolite Production are Associated with Progression from Barrett's Esophagus to Esophageal Adenocarcinoma

Esophageal adenocarcinoma (EAC) is rising in incidence and associated with poor survival, and established risk factors do not explain this trend. Microbiome alterations have been associated with progression from the precursor Barretts esophagus (BE) to EAC, yet the oral microbiome, tightly linked to the esophageal microbiome and easier to sample, has not been extensively studied in this context. We aimed to assess the relationship between the salivary microbiome and neoplastic progression in BE to identify microbiome-related factors that may drive EAC development. We collected clinical data and oral health and hygiene history and characterized the salivary microbiome from 250 patients with and without BE, including 78 with advanced neoplasia (high grade dysplasia or early adenocarcinoma). We assessed differential relative abundance of taxa by 16S rRNA gene sequencing and associations between microbiome composition and clinical features and used microbiome metabolic modeling to predict metabolite production. We found significant shifts and increased dysbiosis associated with progression to advanced neoplasia, with these associations occurring independent of tooth loss, and the largest shifts were with the genus Streptococcus. Microbiome metabolic models predicted significant shifts in the metabolic capacities of the salivary microbiome in patients with advanced neoplasia, including increases in L- lactic acid and decreases in butyric acid and L-tryptophan production. Our results suggest both a mechanistic and predictive role for the oral microbiome in esophageal adenocarcinoma. Further work is warranted to identify the biological significance of these alterations, to validate metabolic shifts, and to determine whether they represent viable therapeutic targets for prevention of progression in BE.

microbiology↗

bioRxiv2023

A scalable framework for high-throughput identification of functional origins of replication in non-model bacteria

Microbial genetic manipulation requires access to engineerable plasmids that can be programmed to perturb genes, pathways and genomes. The extensive repertoire of plasmids available for model microbes, such as Escherichia coli, has facilitated fundamental biology studies and synthetic biology applications. However, the scarcity of plasmids for non-model microbes hinders efforts to broaden our biological knowledge and constrains the development of biotechnological solutions. In this study, we introduce a molecular toolkit and multiplexed screen to evaluate functional plasmids in non-model microbes. We constructed a collection of genetic parts consisting of 22 origins of replication (ORIs), 20 antibiotic selectable markers, and 30 molecular barcodes, which can be assembled combinatorially to create a library of plasmids trackable by next-generation DNA sequencing. We demonstrate our approach by delivering a pooled library of 22 ORIs to 12 bacterial species including extremophiles, electroactive bacteria and bioproduction strains. We report, for the first time, DNA delivery by conjugation and functional ORIs for Halomonas alkaliphila, Halomonas neptunia, and Shewanella electrodiphila. Furthermore, we expand the list of functional ORIs for Duganella zoogloeoides, Pseudomonas alcaliphila, Shewanella oneidensis and Shewanella putrefaciens. This screen provides a scalable high-throughput system to rapidly build and identify functional plasmids to establish genetic tractability in non-model microbes.

synthetic biology↗

bioRxiv2023

Implementation considerations for deep learning with diffusion MRI streamline tractography

One area of medical imaging that has recently experienced innovative deep learning advances is diffusion MRI (dMRI) streamline tractography with recurrent neural networks (RNNs). Unlike traditional imaging studies which utilize voxel-based learning, these studies model dMRI features at points in continuous space off the voxel grid in order to propagate streamlines, or virtual estimates of axons. However, implementing such models is nontrivial, and an open-source implementation is not yet widely available. Here, we describe a series of considerations for implementing tractography with RNNs and demonstrate they allow one to approximate a deterministic streamline propagator with comparable performance to existing algorithms. We release this trained model and the associated implementations leveraging popular deep learning libraries. We hope the availability of these resources will lower the barrier of entry into this field, spurring further innovation.

bioengineering↗

bioRxiv2023

Convolutional-recurrent neural networks approximate diffusion tractography from T1-weighted MRI and associated anatomical context

Diffusion MRI (dMRI) streamline tractography is the gold-standard for in vivo estimation of white matter (WM) pathways in the brain. However, the high angular resolution dMRI acquisitions capable of fitting the microstructural models needed for tractography are often time-consuming and not routinely collected clinically, restricting the scope of tractography analyses. To address this limitation, we build on recent advances in deep learning which have demonstrated that streamline propagation can be learned from dMRI directly without traditional model fitting. Specifically, we propose learning the streamline propagator from T1w MRI to facilitate arbitrary tractography analyses when dMRI is unavailable. To do so, we present a novel convolutional-recurrent neural network (CoRNN) trained in a teacher-student framework that leverages T1w MRI, associated anatomical context, and streamline memory from data acquired for the Human Connectome Project. We characterize our approach under two common tractography paradigms, WM bundle analysis and structural connectomics, and find approximately a 5-15% difference between measures computed from streamlines generated with our approach and those generated using traditional dMRI tractography. When placed in the literature, these results suggest that the accuracy of WM measures computed from T1w MRI with our method is on the level of scan-rescan dMRI variability and raise an important question: is tractography truly a microstructural phenomenon, or has dMRI merely facilitated its discovery and implementation?

bioengineering↗