Biology subjects

Copeland, M.

Publications and source records attributed to Copeland, M..

9 recordsLinked to original sources

bioRxiv2026

Bacterial RNA polymerase exemplifies a general physical mechanism for accelerating protein-DNA association

Bacterial RNA polymerases (RNAPs) have two flexibly tethered subunit C-terminal domains (-CTDs) that bind DNA. Interaction between -CTDs and some promoter DNA motifs is known to accelerate transcription initiation, but the physical mechanism by which it does so is unclear. We used single-molecule multiwavelength fluorescence microscopy to test how the diffusion-limited binding kinetics of core RNAP to non-promoter DNA differ from those of mutant RNAPs that lack one or both -CTDs. We find that even though -CTDs and their tethers are small compared to the complete RNAP molecule, the presence of two -CTDs accelerates DNA binding by [~]10-fold and [~]55-fold respectively relative to RNAP constructs in which one or both -CTDs are deleted. In contrast, the presence of -CTDs did not have a detectable effect on RNAP-DNA complex lifetimes in the absence of RNA synthesis. We explain how -CTDs achieve the dramatic acceleration of RNAP binding to DNA using a quantitative three-state kinetic model that includes a transient binding intermediate where only the -CTD(s) are bound to DNA, tethering the rest of the RNAP in the vicinity of DNA. The model and assumed parameters are validated using Brownian dynamics simulations of the DNA association reactions for two-, one-, or zero-CTD RNAP constructs. The combination of single-molecule experiments, mathematical theory, and simulations suggests that adding a flexible DNA-binding tether is a general physical mechanism which can accelerate the diffusion-limited binding of a large protein like RNAP to DNA and quantitatively defines the conditions under which this acceleration can occur. Significance StatementLarge enzymes that must associate with DNA to perform their biological functions are expected to bind DNA only slowly because of slow enzyme diffusion. However, some DNA-binding enzymes have one or more additional small DNA-binding domains that can diffuse rapidly but are attached to the enzyme through an unstructured flexible tether. Combining single-molecule experiments, theory, and computation, we present evidence for a general mechanism by which such tethered domains can accelerate enzyme binding to DNA by orders of magnitude, while not significantly changing the duration of the DNA-bound state. We demonstrate this effect for the flexibly-tethered -subunit C-terminal domain of bacterial RNA polymerase. The mechanism may allow the polymerase to rapidly bind DNA while minimizing non-functional sequestration on the genome.

biophysics↗

bioRxiv2026

Dismantling Chromosomal Stasis Across the Eukaryotic Tree of Life

Chromosome number shapes genome organization, recombination, and speciation, yet how fast it evolves across the tree of life has never been measured. We analyzed 63,682 karyotypes across 55 eukaryotic clades and found that dysploidy rates vary by 844-fold, from approximately 0.0008 to 0.7 events per million years. This variation does not follow kingdom boundaries or deep phylogeny; intraclade variance exceeds interclade differences by more than an order of magnitude. Even birds, the textbook example of chromosomal stasis, exceed the global median rate once microchromosome dynamics are resolved. Contrasting the stasis of Odonata with the volatility of Orchidaceae reveals that life history and population structure, rather than deep phylogenetic constraints, govern the tempo of karyotypic change.

evolutionary biology↗

bioRxiv2026

Reconstituting Mouse Embryogenesis Ex Utero from Gastrulation to Fetal Development Reveals Maternally Independent Metabolic Programs

Mammalian development takes place inside the maternal uterus, creating technological constraints that make difficult the study of embryogenesis in live developing embryos. A central challenge for understanding the role of metabolism in mammalian development is discriminating placental and uterine-regulated signals from embryo-intrinsic processes independent of maternal influence, a process that until now has remained inseparable during gastrulation and organogenesis1-3. Ex utero culture systems allowing continuous growth of embryos during pre-gastrulation to organogenesis4,5 offer a promising solution to this challenge. Here, we present optimized ex utero culture platforms that support faithful development of mouse embryos from gastrulation (embryonic day 6.5/7.5) through the fetal period (embryonic day [~]12.5) and harnessed these platforms for dissecting metabolic transitions in vivo during embryogenesis independently of uterus and placenta. We characterized the metabolome of in utero and ex utero whole embryos, fetal organs and culture medium between embryonic days E6.5 and E12.5 by liquid chromatography mass-spectrometry (LC-MS) metabolomics, isotope tracing, and single cell transcriptomics. These datasets present a comprehensive overview of the dynamic embryonic metabolism during gastrulation and organogenesis in utero and ex utero. This analysis revealed that the midgestational metabolic switch occurring at E10.5-E11.5 is faithfully recapitulated ex utero, indicating that this transition is intrinsically programmed in embryonic tissues and does not require direct maternal or placental cues. Notably, oxygen availability modulated the extent of this transition, but elevated oxygen was insufficient to induce it prematurely, demonstrating that the switch is developmentally timed and only partially environmental-responsive. We further harnessed the ex utero platform for identifying and perturbing a mitochondrial redox shift at E7.5-E8.5 that is critical for developmental progress after gastrulation. These findings uncover the remarkable metabolic plasticity of the mammalian embryo, demonstrating its capacity to sustain growth independently of maternal inputs from the establishment of the body plan through the onset of the fetal period. Moreover, they highlight the use of long-term ex utero culture as a unique framework for dissecting the mechanisms that shape embryogenesis under physiological and experimentally perturbed conditions, while functionally uncoupling embryonic programs from maternal and placental influences.

developmental biology↗

bioRxiv2026

Counting strands in outer membrane beta-barrels

Beta-barrel structures are critical components of bacterial outer membranes, where they facilitate transport, cell signaling, antibiotic resistance, and structural integrity. A key feature of beta-barrels is their strand count, which influences pore diameter, binding site locations, and functional properties. However, because of breaks in strands and the presence of strands in periplasmic domains and plug domains, manual counting is inefficient and current algorithms do not accurately determine barrel strand count. To address this, we refined our previous beta-barrel structural assessment tool, PolarBearal, to improve strand number identification in large-scale datasets. To enhance the accuracy of barrel strand number labeling, our updated algorithm integrates three structural criteria, namely inter-residue vector angles, hydrogen-bonding distances, and strand connectivity. Using this algorithm, we labeled strand numbers for 571,760 predicted outer membrane beta-barrel structures obtained from the AlphaFold2 database. Our algorithm has 97% accuracy in strand number assignments, and the resulting dataset facilitates assessment of the homogeneity of strand counts for different types of outer membrane proteins. The strand labeling also provides insights on beta-barrel strand distribution and evolutionary patterns, supporting further research in protein structure prediction and design. SignificanceThis work contributes an accurate, automated method for counting beta-barrel strands in bacterial outer membrane proteins. Methodological ImpactThe algorithm achieves 97% accuracy in strand counting, solving a technical problem that has hindered large-scale structural analysis. Previous manual methods were inefficient, and existing algorithms failed to handle the structural complexities of real beta-barrel proteins, including strand breaks and additional domains. Scale of ContributionBy annotating over 571,000 predicted structures from the AlphaFold2 database, this work represents the largest systematic characterization of beta-barrel strand distributions to date. This labeled dataset provides a resource for the structural biology community. Broader ApplicationsThis tool enables researchers understand structure-function relationships in outer membrane proteins, supporting advances in protein design, drug development targeting bacterial membranes.

bioinformatics↗

bioRxiv2024

Discovery of neuronal cell types by pairing whole cell reconstructions with RNA expression profiles

Effective classification of neuronal cell types requires both molecular and morphological descriptors to be collected in situ at single-cell resolution. However, current spatial transcriptomics techniques are not compatible with imaging workflows that successfully reconstruct the morphology of complete axonal projections. Here, we introduce a new method, which we call morphoFISH, that combines tissue clearing, submicron whole-brain two photon imaging, and Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH) to assign molecular identities to fully reconstructed neurons in the mouse brain. We used morphoFISH to molecularly identify a previously unknown population of cingulate neurons projecting ipsilaterally to the dorsal striatum and contralaterally to higher-order thalamus. By pairing whole-brain morphometry, improved techniques for nucleic acid preservation and spatial gene expression, morphoFISH offers a quantitative solution for discovery of multimodal cell types and complements existing techniques for characterization of increasingly fine-grained cellular heterogeneity in brain circuits.

neuroscience↗

bioRxiv2024

Genome assembly of the southern pine beetle (Dendroctonus frontalis Zimmerman) reveal the origins of gene content reduction in Dendroctonus

Dendroctonus frontalis, also known as southern pine beetle (SPB), represents the most damaging forest pest in the southeastern United States. Strategies to predict, monitor and suppress SPB outbreaks have had limited success. Genomic data are critical to inform on pest biology and to identify molecular targets to develop improved management approaches. Here, we produced a chromosome-level genome assembly of SPB using long-read sequencing data. Synteny analyses confirmed the conservation of the core coleopteran Stevens elements and validated the bona fide SPB X chromosome. Transcriptomic data were used to obtain 39,588 transcripts corresponding to 13,354 putative protein-coding loci. Comparative analyses of gene content across 14 beetle and 3 other insects revealed several losses of conserved genes in the Dendroctonus clade and gene gains in SPB and Dendroctonus that were enriched for loci encoding membrane proteins and extracellular matrix proteins. While lineage-specific gene losses contributed to the gene content reduction observed in Dendroctonus, we also showed that widespread misannotation of transposable elements represents a major cause of the apparent gene expansion in several non-Dendroctonus species. Our findings uncovered distinctive features of the SPB gene complement and disentangled the role of biological and annotation-related factors contributing to gene content variation across beetles.

genomics↗

bioRxiv2023

MAHOMES II: A webserver for predicting if a metal binding site is enzymatic

Recent advances have enabled high-quality computationally generated structures for proteins with no solved crystal structures. However, protein function data remains largely limited to experimental methods and homology mapping. Since structure determines function, it is natural that methods capable of using computationally generated structures for functional annotations need to be advanced. Our laboratory recently developed a method to distinguish between metalloenzyme and non-enzyme sites. Here we report improvements to this method by upgrading our physicochemical features to alleviate the need for structures with sub-angstrom precision and using machine learning to reduce training data labeling error. Our improved classifier identifies protein bound metal sites as enzymatic or non-enzymatic with 94% precision and 92% recall. We demonstrate that both adjustments increased predictive performance and reliability on sites with sub-angstrom variations. We constructed a set of predicted metalloprotein structures with no solved crystal structures and no detectable homology to our training data. Our model had an accuracy of 90 - 97.5% depending on the quality of the predicted structures included in our test. Finally, we found the physicochemical trends that drove this models successful performance were local protein density, second shell ionizable residue burial, and the pockets accessibility to the site. We anticipate that our models ability to correctly identify catalytic metal sites could enable identification of new enzymatic mechanisms and improve de novo metalloenzyme design success rates. Significance statementIdentification of enzyme active sites on proteins with unsolved crystallographic structures can accelerate discovery of novel biochemical reactions, which can impact healthcare, industrial processes, and environmental remediation. Our lab has developed an ML tool for predicting sites on computationally generated protein structures as enzymatic and non-enzymatic. We have made our tool available on a webserver, allowing the scientific community to rapidly search previously unknown protein function space.

bioinformatics↗

bioRxiv2022

Is It A Barrel? General Features of Transmembrane Beta Barrels from a Large Database

Large datasets contribute new insights to subjects formerly investigated by exemplars. We used co-evolution data to create a large, high-quality database of transmembrane {beta}-barrels (TMBB). By applying simple feature detection on generated evolutionary contact maps, our method (IsItABarrel) achieves 95.88% balanced accuracy when discriminating among protein classes. Moreover, comparison with IsItABarrel revealed a high rate of false positives in previous TMBB algorithms. In addition to being more accurate than previous datasets, our database (available online) contains 1,894,206 bacterial TMBB proteins from 20 evolutionary classes, respectively 17 and 2.2 times larger than the previous sets TMBB-DB and OMPdb. We anticipate that due to its quality and size the database will serve as a useful resource where high quality TMBB sequence data is required. We found that TMBBs can be divided into 10 types, three of which have not been previously reported. We find tremendous variance in proteome percentage among TMBB-containing organisms with some using 6.79% of their proteome for TMBBs and others using as little as 0.27% of their proteome. The distribution of the lengths of the TMBBs is suggestive of previously hypothesized duplication events. In addition, we find that the C-terminal {beta}-signal varies among different classes of bacteria though it is most commonly HyGHyGY+F. However, this {beta}-signal is only characteristic of prototypical TMBBs. The nine non-prototypical barrel types have other C-terminal motifs and it remains to be determined if these alternative motifs facilitate TMBB insertion or perform any other signaling function. Significance StatementOuter membrane proteins (OMPs) control all interactions between Gram negative bacteria and their environments including uptake and efflux of antibiotics. We created an algorithm that identifies bacterial OMPs from sequence. The quality of our algorithm allows us to identify most OMPs ([~]1.8 million) from prokaryotic genomes including >240,000 unrelated to previously structurally-resolved OMPs. We identify ten types of OMPs in our database. The largest types signal sequence--used for targeting the membrane-insertion machinery--varies by phylogenetic class. All other types of OMPs do not have a related signal sequence, raising new questions of how these proteins fold. Our web-accessible database will allow for further exploration of the varieties of outer membrane proteins to uncover new targets for controlling antibiotic resistance.

bioinformatics↗

bioRxiv2019

A sparse, spatially biased subtype of mature granule cell is preferentially recruited in hippocampal-associated behaviors

Animals can store information about experiences by activating specific neuronal populations, and subsequent reactivation of these neural ensembles can lead to recall of salient experiences. In the hippocampus, granule cells of the dentate gyrus participate in such memory engrams; however, whether there is an underlying logic to granule cell participation has not been examined. Here, we found that a broad range of novel experiences preferentially activates granule cells of the suprapyramidal blade relative to the infrapyramidal blade. Motivated by this, we identified a suprapyramidal-blade-enriched population of granule cells with distinct spatial, morphological, physiological, and developmental properties. Via transcriptomics, we mapped these traits onto a sparse and discrete granule cell subtype that was recruited at a ten-fold greater frequency than expected by subtype prevalence, constituting the majority of all recruited granule cells. Thus, a rare and spatially localized granule cell subtype is intrinsically predisposed to activation during hippocampal memory formation.

neuroscience↗