Biology subjects

Kim, D. E.

Publications and source records attributed to Kim, D. E..

8 recordsLinked to original sources

bioRxiv2026

Environmental control of morphological color changes in the Bigfin Reef Squid, Sepioteuthis lessoniana

Phenotypic plasticity enables organisms to adjust their traits in response to environmental conditions, yet studies of animal coloration--particularly in cephalopods--have largely focused on rapid neural control while overlooking slower, substrate-level changes. Here, we investigate whether morphological color change contributes to phenotypic plasticity in the bigfin reef squid (Sepioteuthis lessoniana). Hatchlings were reared in contrasting light (white) and dark (black) environments for 14 weeks, and chromatophore organization was quantified across developmental stages (4, 9, and 14 weeks) and body regions (dorsal and ventral) using high-resolution imaging and automated analysis. We find that environmental context and age interact to shape both the density and size of black, yellow, and red chromatophores, revealing a consistent trade-off between chromatophore number and expansion. Black-reared individuals maintain higher chromatophore densities, whereas white-reared individuals exhibit fewer but larger cells, particularly at later developmental stages. These effects are region-specific and align with the emergence of countershading, suggesting ecological tuning of pigmentation architecture. Our results demonstrate that the cellular substrate underlying color change is itself plastic and dynamically remodeled across development. We propose a hierarchical model in which slow morphological plasticity defines the functional limits of rapid neural color change. This work expands current frameworks of cephalopod coloration by integrating developmental, environmental, and cellular mechanisms, and highlights the importance of multi-timescale plasticity in adaptive visual signaling.

ecology↗

bioRxiv2026

Miniprotein inhibitors of the Staphylococcus aureus efflux transporter NorA

Multidrug efflux pumps transport antibiotics across the cellular membrane resulting in resistance conferred to the host organism. Efflux pump inhibitors (EPIs) potentiate the efficacy of antibiotics by blocking drug efflux and hold promise as adjuvant therapeutics in the fight against multidrug resistant pathogenic bacteria. A hurdle in the field has been the lack of selectivity of small molecule EPIs which often display off-target toxicity due to non-specific binding. To tackle this specificity challenge, we aimed to maximize an inhibitors binding surface area to efflux pumps by designing miniprotein EPIs using computational protein design and an E. coli co-expression assay to screen inhibition in cells. We used S. aureus NorA as a model efflux transporter since it confers drug resistance to fluoroquinolones, puromycin, and other cytotoxic compounds. Starting from a focused miniprotein library of only 86 members, we identified inhibitors in the screen that blocked NorA transport under active efflux conditions in vitro. Our most promising inhibitor I-23 was validated by solving a cryo-EM structure of the miniprotein in complex with NorA, which stabilized the transporter in the outward-open conformation. I-23 has a ferredoxin-like fold with one of its {beta}-hairpins inserted into the substrate binding pocket of NorA and other parts of the globular fold occupying the shallow pocket and making extensive intermolecular contacts with NorA. An arginine residue on the tip of the hairpin loop was positioned near an anionic patch required for NorA antibiotic efflux. The identified structural motifs in this work could be employed to explore the molecular properties of peptidoglycan penetration; full realization of the therapeutic potential of the designed miniprotein inhibitors will require determining the principles for facilitating passage of [~]7 to 8 kDa miniproteins across the peptidoglycan bacterial cell wall.

biochemistry↗

bioRxiv2026

Topological reprogramming transforms an integral membrane oligosaccharyltransferase into a water-soluble glycosylation catalyst

Glycosyltransferases (GTs) catalyze the formation of new glycosidic bonds and thus are vital for synthesizing natures vast repertoire of glycans and glycoconjugates and for engineering glycan-related medicines and materials. However, obtaining detailed structural and functional insights for the >750,000 known GTs is limited by difficulties associated with their efficient recombinant expression. Members of the GT-C fold, in particular, pose the most significant expression challenges due to the integration and folding requirements of their multiple membrane-spanning regions. Here, we address this challenge by engineering water-soluble variants of an archetypal GT-C fold enzyme, namely the oligosaccharyltransferase PglB from Campylobacter jejuni (CjPglB), which possesses 13 hydrophobic transmembrane helices. To render CjPglB water-soluble, we leveraged two advanced protein engineering methods: one that is universal called SIMPLEx (solubilization of IMPs with high levels of expression) and the other that is custom tailored called WRAPs (water-soluble RFdiffused amphipathic proteins). Each approach was able to transform CjPglB into a water-soluble enzyme that could be readily expressed in the cytoplasm of Escherichia coli cells at yields in the 3-6 mg/L range. Importantly, solubilization was achieved without the need for detergents and with retention of catalytic function. Collectively, our findings demonstrate that both SIMPLEx and WRAPs are promising platforms for advancing the molecular characterization of even the most structurally complex GTs, while also enabling broader GT-mediated glycosylation capabilities within synthetic glycobiology applications.

synthetic biology↗

bioRxiv2025

De novo design of miniprotein agonists and antagonists targeting G protein-coupled receptors

G protein-coupled receptors (GPCRs) play key roles in physiology and are central targets for drug discovery and development, but the design of protein agonists and antagonists has been challenging as GPCRs are integral membrane proteins and conformationally dynamic. Here we describe computational de novo design methods and a high throughput "receptor diversion" microscopy-based screen for generating GPCR binding miniproteins with high affinity, potency and selectivity, and the use of these methods to generate agonists for MRGPRX1, NK1R and CCR5, as well as antagonists for CXCR4, CCR5, OXTR, GLP1R, GIPR, GCGR, PTH1R and CGRPR.. Cryo-electron microscopy data reveals atomic-level agreement between designed and experimentally determined structures for CGRPR- and CXCR4-bound antagonists and MRGPRX1-bound agonists. Our de novo design and screening approach opens new frontiers in GPCR drug discovery and development.

bioengineering↗

bioRxiv2025

Massively parallel assessment of designed protein solution properties using mass spectrometry and peptide barcoding

Library screening and selection methods can determine the binding activities of individual members of large protein libraries given a physical link between protein and nucleotide sequence, which enables identification of functional molecules by DNA sequencing. However, the solution properties of individual protein molecules cannot be probed using such approaches because they are completely altered by DNA attachment. Mass spectrometry enables parallel evaluation of protein properties amenable to physical fractionation such as solubility and oligomeric state, but current approaches are limited to libraries of 1,000 or fewer proteins. Here, we improved mass spectrometry barcoding by co-synthesizing proteins with barcodes optimized to be highly multiplexable and minimally perturbative, scaling to libraries of >5,000 proteins. We use these barcodes together with mass spectrometry to assay the solution behavior of libraries of de novo-designed monomeric scaffolds, oligomers, binding proteins and nanocages, rapidly identifying design failure modes and successes.

biochemistry↗

bioRxiv2025

Solubilization of Membrane Proteins using designed protein WRAPS

The development of therapies and vaccines targeting integral membrane proteins has been complicated by their extensive hydrophobic surfaces, which can make production and structural characterization difficult. Here we describe a general deep learning-based design approach for solubilizing native membrane proteins while preserving their sequence, fold, and function using genetically encoded de novo protein WRAPs (Water-soluble RFdiffused Amphipathic Proteins) that surround the lipid-interacting hydrophobic surfaces, rendering them stable and water-soluble without the need for detergents. We design WRAPs for both beta-barrel outer membrane and helical multi-pass transmembrane proteins, and show that the solubilized proteins retain the binding and enzymatic functions of the native targets with enhanced stability. Syphilis vaccine development has been hindered by difficulties in characterizing and producing the outer membrane protein antigens; we generated soluble versions of four Treponema pallidum outer membrane beta barrels which are potential syphilis vaccine antigens. A 4.0 [A] cryo-EM map of WRAPed TP0698 is closely consistent with the design model. WRAPs should be broadly useful for facilitating biochemical and structural characterization of integral membrane proteins, enabling therapeutic discovery by screening against purified soluble targets, and generating antigenically intact immunogens for vaccine development.

biochemistry↗

bioRxiv2024

Parametrically guided design of beta barrels and transmembrane nanopores using deep learning

Francis Cricks global parameterization of coiled coil geometry has been widely useful for guiding design of new protein structures and functions. However, design guided by similar global parameterization of beta barrel structures has been less successful, likely due to the deviations from ideal barrel geometry required to maintain inter-strand hydrogen bonding without introducing backbone strain. Instead, beta barrels have been designed using 2D structural blueprints; while this approach has successfully generated new fluorescent proteins, transmembrane nanopores, and other structures, it requires expert knowledge and provides only indirect control over the global shape. Here we show that the simplicity and control over shape and structure provided by parametric representations can be generalized beyond coiled coils by taking advantage of the rich sequence-structure relationships implicit in RoseTTAFold based design methods. Starting from parametrically generated barrel backbones, both RFjoint inpainting and RFdiffusion readily incorporate backbone irregularities necessary for proper folding with minimal deviation from the idealized barrel geometries. We show that for beta barrels across a broad range of beta sheet parameterizations, these methods achieve high in silico and experimental success rates, with atomic accuracy confirmed by an X-ray crystal structure of a novel barrel topology, and de novo designed 12, 14, and 16 stranded transmembrane nanopores with conductances ranging from 200 to 500 pS. By combining the simplicity and control of parametric generation with the high success rates of deep learning based protein design methods, our approach makes the design of proteins where global shape confers function, such as beta barrel nanopores, more precisely specifiable and accessible. SignificanceDe novo beta barrel proteins have previously been designed using "blueprint" based methods which require expert knowledge of the rules of folding and provide only indirect control of the overall barrel shape by specifying structural features such as glycine kinks and beta bulges. The barrel shape can be directly modeled using global parametric methods, but to date such methods have not succeeded in generating folded proteins, likely due to the absence of such structural features. Here, we describe methods that combine the simplicity and control of parametric barrel specification with the high success rates of deep learning based protein design methods to successfully design new beta barrel folds of different and pre-specified sizes, including both soluble designs and transmembrane nanopores.

biochemistry↗

bioRxiv2021

Biosynthetic Glycan Labeling

Glycans are ubiquitous and play important biological roles, yet chemical methods for probing their structure and function within cells remain limited. Strategies for studying other biomacromolecules, such as proteins, often exploit chemoselective reactions for covalent modification, capture, or imaging. Unlike amino acids that constitute proteins, glycan building blocks lack distinguishing reactivity because they are composed primarily of polyol isomers. Moreover, encoding glycan variants through genetic manipulation is complex. Therefore, we formulated a new, generalizable strategy for chemoselective glycan modification that directly takes advantage of cellular glycosyltransferases. Many of these enzymes are selective for the products they generate yet promiscuous in their donor preferences. Thus, we designed reagents with bioorthogonal handles that function as glycosyltransferase substrate surrogates. We validated the feasibility of this approach by synthesizing and testing probes of D-arabinofuranose (D-Araf), a monosaccharide found in bacteria and an essential component of the cell wall that protects mycobacteria, including Mycobacterium tuberculosis. The result is the first probe capable of selectively labeling arabinofuranose-containing glycans. Our studies serve as a platform for developing new chemoselective labeling agents for other privileged monosaccharides. This probe revealed an asymmetric distribution of D-Araf residues during mycobacterial cell growth and could be used to detect mycobacteria in THP1-derived macrophages.

biochemistry↗