Biology subjects

Peck, A.

Publications and source records attributed to Peck, A..

13 recordsLinked to original sources

bioRxiv2025

Lessons learned from a Kaggle challenge for particle picking in cryo-electron tomography

The difficulty of particle picking in cryo-electron tomography remains a barrier to routine in situ structure determination. Machine learning is well-suited to overcome this bottleneck with efficient algorithms that generalize across molecular species. To spur new algorithm development, we held a three-month Kaggle challenge that tasked contestants with annotating five molecular species across hundreds of experimental tomograms. This competition successfully engaged >1000 participants from diverse fields and delivered particle pickers that outperformed existing state-of-the-art. Systematic comparisons of the contestants submissions revealed the tolerance of subtomogram averaging to moderate but not severe over-picking and underscored the need for more robust measures of annotation quality. The winning models also highlighted the importance of data augmentation to overcome limited training data. All competition tomograms along with the ground truth and winning teams annotations have been released on the CryoET Data Portal as a resource to benchmark current and future tools for particle picking.

cell biology↗

bioRxiv2025

Unsupervised learning of structural variability in cryo-EM data using normal mode analysis of deformable atomic models

Cryogenic electron microscopy (cryo-EM) has emerged as the method of choice to characterize the structural variability of biomolecules at near-atomic resolution. We present a reconstruction approach that eliminates the need for post-hoc atomic model fitting in 3D maps by deforming a given atomic model along its normal modes directly against the 2D data. This end-to-end approach inherently reduces the risk of error propagation while increasing interpretability of resulting structural ensembles.

biophysics↗

bioRxiv2025

22q11 deletion selectively alters progenitor states and projection neuron identities in the developing cerebral cortex

The developmental origin of Layer 2/3 projection neuron (PN) pathology in the frontal association cortex due to heterozygous 22q11 gene deletion--the genetic foundation of elevated risk for schizophrenia and related psychiatric disorders in 22q11.2 Deletion Syndrome (22q11DS)--reflects cell state-dependent, temporally restricted vulnerability of transcriptionally diverse subsets of intermediate progenitors and neuroblasts. The molecular and cell biological consequences of these evanescent state-dependent changes include divergent proliferative capacity of the most highly proliferative progenitors, enhanced neurogenic gene expression, altered DNA methylation, and increased numbers of immediate neuroblast progeny at peak neurogenesis in fetal frontal cortex of the LgDel 22q11DS mouse model. These altered cell states prefigure a post-natal cohort of upper layer PNs generated at the peak of Layer 2/3 PN genesis--not before or after--whose frequencies are significantly diminished and molecular identities are substantially divergent in medial frontal association, but not primary somatosensory or visual cortices. Thus, frontal association cortices in 22q11DS and schizophrenia more broadly may be pathogenic targets due to vulnerabilities of expanded, highly proliferative, transcriptionally dynamic populations of intermediate progenitors that increase L2/3 PN frequency to enhance cortico-cortical connectivity.

neuroscience↗

bioRxiv2025

AreTomoLive: Automated reconstruction of comprehensively-corrected and denoised cryo-electron tomograms in real-time and at high throughput

A high throughput processing pipeline that performs comprehensive corrections is needed to realize the full potential of cryo-electron tomography and subtomogram averaging. The fields fragmented software landscape remains a significant hurdle to this end. Here we present AreTomoLive, an automated real-time pipeline composed of two GPU-accelerated packages. The first, AreTomo3, streamlines tomographic alignment and reconstruction, with new features to fully account for sample geometry, locally correct the contrast transfer function, and curate data for downstream tasks. The second package, DenoisET, is a new implementation of the machine learning algorithm Noise2Noise and runs in parallel with AreTomo3 to perform contrast enhancement. To reduce barriers to routine use, AreTomoLive prioritizes automation: AreTomo3 autonomously pauses and reactivates processing depending on the status of data collection, while DenoisET algorithmically determines when to transition from training to inference. AreTomoLive endeavors to advance cryoET for in situ structural analysis with its comprehensive corrections and full automation.

cell biology↗

bioRxiv2024

Annotating CryoET Volumes: A Machine Learning Challenge

Cryo-electron tomography (cryoET) has emerged as a powerful structural biology tool for understanding protein complexes in their native cellular environments. Presently, 3D volumes of cellular environments can be acquired in the thousands in a few days where each volume provides a rich and complex cellular landscape. Despite numerous innovations, localizing and identifying the vast majority of protein species in these volumes remains prohibitively difficult. Machine learning based methods provide an opportunity to automate the process of labeling and annotating cryoET volumes. Due to current bottlenecks in the annotation process, and a lack of large standardized datasets, training datasets for machine learning algorithms have been scarce. Here, we present a defined "phantom" sample, along with "ground truth" annotations, that will be the basis of a machine learning challenge to bring cryoET and ML experts together and spur creativity to address this annotation problem. We have also set up a cryoET data portal that provides additional diverse sets of annotated 3D volumes from cryoET experts across the world for the machine learning challenge.

cell biology↗

bioRxiv2023

Structural basis for functional properties of cytochrome c oxidase

Cytochrome c oxidase (CcO) is an essential enzyme in mitochondrial and bacterial respiration. It catalyzes the four-electron reduction of molecular oxygen to water and harnesses the chemical energy to translocate four protons across biological membranes, thereby establishing the proton gradient required for ATP synthesis1. The full turnover of the CcO reaction involves an oxidative phase, in which the reduced enzyme (R) is oxidized by molecular oxygen to the metastable oxidized OH state, and a reductive phase, in which OH is reduced back to the R state. During each of the two phases, two protons are translocated across the membranes2. However, if OH is allowed to relax to the resting oxidized state (O), a redox equivalent to OH, its subsequent reduction to R is incapable of driving proton translocation2,3. How the O state structurally differs from OH remains an enigma in modern bioenergetics. Here, with resonance Raman spectroscopy and serial femtosecond X-ray crystallography (SFX)4, we show that the heme a3 iron and CuB in the active site of the O state, like those in the OH state5,6, are coordinated by a hydroxide ion and a water molecule, respectively. However, Y244, a residue covalently linked to one of the three CuB ligands and critical for the oxygen reduction chemistry, is in the neutral protonated form, which distinguishes O from OH, where Y244 is in the deprotonated tyrosinate form. These structural characteristics of O provide new insights into the proton translocation mechanism of CcO.

biophysics↗

bioRxiv2023

Automatic Abdominal Multi Organ Segmentationusing Residual UNet

Automated segmentation of abdominal organs plays an important role in supporting computer-assisted diagnosis, radiotherapy, biomarker extraction, surgery navigation, and treatment planning. Segmenting multiple abdominal organs using a single algorithm would improve model development efficiency and accelerate model deployment into clinical workflows. To achieve broadly generalized performance, we trained a residual UNet using 500 CT/MRI scans collected from multi-center, multi-vendor, multi-phase, multi-disease patients, each with voxel-level annotation of 15 abdominal organs. Using the model trained on multimodality (CT/MRI), we achieved an average dice of 0.8990 in the held-out test dataset with only CT scans (N=100). An average dice of 0.8948 was achieved in the held-out test dataset with both CT and MRI scans (N=120. Our results demonstrate broad generalization of the model.

bioengineering↗

bioRxiv2021

Skopi: a simulation package for diffractive imaging of noncrystalline biomolecules

X-ray free electron lasers (XFEL) have the ability to produce ultra-bright femtosecond X-ray pulses for coherent diffraction imaging of biomolecules. While the development of methods and algorithms for macromolecular crystallography is now mature, XFEL experiments involving aerosolized or solvated biomolecular samples offer new challenges both in terms of experimental design and data processing. Skopi is a simulation package that can generate single-hit diffraction images for reconstruction algorithms, multi-hit diffraction images of aggregated particles for training machine learning classification tasks using labeled data, diffraction images of randomly distributed particles for fluctuation X-ray scattering (FXS) algorithms, and diffraction images of reference and target particles for holographic reconstruction algorithms. We envision skopi as a resource to aid the development of on-the-fly feedback during non-crystalline experiments at XFEL facilities, which will provide critical insights into biomolecular structure and function.

biophysics↗

bioRxiv2021

Montage electron tomography of vitrified specimens

Cryo-electron tomography provides detailed views of macromolecules in situ. However, imaging a large field of view to provide more cellular context requires reducing magnification during data collection, which in turn restricts the resolution. To circumvent this trade-off between field of view and resolution, we have developed a montage data collection scheme that uniformly distributes the dose throughout the specimen. In this approach, sets of slightly overlapping circular tiles are collected at high magnification and stitched to form a composite projection image at each tilt angle. These montage tilt-series are then reconstructed into massive tomograms with a small pixel size but a large field of view. For proof-of-principle, we applied this method to the thin edge of HeLa cells. Thon rings to better than 15 [A] were observed in the montaged tilt-series, and diverse cellular features were evident in the resulting tomograms. These results indicate that the additional dose required by this technique is not prohibitive to performing structural analysis to intermediate resolution across a large field of view. We anticipate that montage tomography will prove particularly useful for lamellae, increase the likelihood of imaging rare cellular events, and facilitate visual proteomics.

biophysics↗

bioRxiv2021

Amyloid β oligomer selective antibodies for Alzheimers therapeutics and diagnostics

Improvements have been made in the diagnosis of Alzheimers disease (AD), manifesting mostly in the development of in vivo imaging methods that allow for the detection of pathological changes in AD by MRI and PET scans. Many of these imaging methods, however, use agents that probe amyloid fibrils and plaques - species that do not correlate well with disease progression and are not present at the earliest stages of the disease. Amyloid {beta} oligomers (A{beta}Os), rather, are now widely accepted as the A{beta} species most germane to AD onset and progression. Here we report evidence further supporting the role of A{beta}Os as pathological instigators of AD and introduce promising anti-A{beta}O diagnostic probes capable of distinguishing the 5xFAD mouse model from wild type mice by PET and MRI. In a developmental study, A{beta} oligomers in 5xFAD mice were found to appear at 3 months of age, just prior to the onset of memory dysfunction, and spread as memory worsened. The increase of A{beta}Os is prominent in the subiculum and correlates with concomitant development of reactive astrocytosis. The impact of these A{beta}Os on memory is in harmony with findings that intraventricular injection of synthetic A{beta}Os into wild type mice induced hippocampal dependent memory dysfunction within 24 hours. Compelling support for the conclusion that endogenous A{beta}Os cause memory loss was found in experiments showing that intranasal inoculation of A{beta}O-selective antibodies into 5xFAD mice completely restored memory function, measured 30-40 days post-inoculation. These antibodies, which were modified to give MRI and PET imaging probes, were able to distinguish 5xFAD mice from wild type littermates. These results provide strong support for the role of A{beta}Os in instigating memory loss and salient AD neuropathology, and they demonstrate that A{beta}O selective antibodies have potential both for therapeutics and for diagnostics.

neuroscience↗

bioRxiv2020

Massive X-ray screening reveals two allosteric drug binding sites of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous health problems and economical challenges for mankind. To date, no effective drug is available to directly treat the disease and prevent virus spreading. In a search for a drug against COVID-19, we have performed a massive X-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (Mpro), which is essential for the virus replication and, thus, a potent drug target. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds binding to Mpro. In subsequent cell-based viral reduction assays, one peptidomimetic and five non-peptidic compounds showed antiviral activity at non-toxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2.

biophysics↗

bioRxiv2020

Challenges in solving structures from radiation-damaged tomograms of protein nanocrystals assessed by simulation

Structure determination methods are needed to resolve the atomic details that underlie protein function. X-ray crystallography has provided most of our knowledge of protein structure but is constrained by the need for large, well-ordered crystals and the loss of phase information. The rapidly developing methods of serial femtosecond crystallography, micro-electron diffraction, and single-particle reconstruction circumvent the first of these limitations by enabling data collection from nanocrystals or purified proteins. However, the first two methods also suffer from the phase problem, while many proteins fall below the molecular weight threshold required by single-particle reconstruction. Cryo-electron tomography of protein nanocrystals has the potential to overcome these obstacles of mainstream structure determination methods. Here we present a data processing scheme that combines routines from X-ray crystallography and new algorithms we developed to solve structures from tomograms of nanocrystals. This pipeline handles image processing challenges specific to tomographic sampling of periodic specimens and is validated using simulated crystals. We also assess the tolerance of this workflow to the effects of radiation damage. Our simulations indicate a trade-off between a wider tilt-range to facilitate merging data from multiple tomograms and a smaller tilt increment to improve phase accuracy. Since phase errors but not merging errors can be overcome with additional datasets, these results recommend distributing the dose over a wide angular range rather than using a finer sampling interval to solve the protein structure.

biophysics↗

bioRxiv2020

Catalytic cleavage of HEAT and subsequent covalent binding of the tetralone moiety by the SARS-CoV-2 main protease

Here we present the crystal structure of SARS-CoV-2 main protease (Mpro) covalently bound to 2-methyl-1-tetralone. This complex was obtained by co-crystallization of Mpro with HEAT (2-(((4-hydroxyphenethyl)amino)methyl)-3,4-dihydronaphthalen-1(2H)-one) in the framework of a large X-ray crystallographic screening project of Mpro against a drug repurposing library, consisting of 5632 approved drugs or compounds in clinical phase trials. Further investigations showed that HEAT is cleaved by Mpro in an E1cB-like reaction mechanism into 2-methylene-1-tetralone and tyramine. The catalytic Cys145 subsequently binds covalently in a Michael addition to the methylene carbon atom of 2-methylene-1-tetralone. According to this postulated model HEAT is acting in a pro-drug-like fashion. It is metabolized by Mpro, followed by covalent binding of one metabolite to the active site. The structure of the covalent adduct elucidated in this study opens up a new path for developing non-peptidic inhibitors.

biophysics↗