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Article ; Online: Classifying liganded states in heterogeneous single-particle cryo-EM datasets.

Arnold, William R / Asarnow, Daniel / Cheng, Yifan

2022 Volume 71, Issue Supplement_1, Page(s) i23–i29

Abstract: A powerful aspect of single-particle cryogenic electron microscopy is its ability to determine high-resolution structures from samples containing heterogeneous mixtures of the same macromolecule in different conformational or compositional states. Beyond ...

Abstract	A powerful aspect of single-particle cryogenic electron microscopy is its ability to determine high-resolution structures from samples containing heterogeneous mixtures of the same macromolecule in different conformational or compositional states. Beyond determining structures at higher resolutions, one outstanding question is if macromolecules with only subtle conformation differences, such as the same protein bound with different ligands in the same binding pocket, can be separated reliably, and if information concerning binding kinetics can be derived from the particle distributions of different conformations obtained in classification. In this study, we address these questions by assessing the classification of synthetic heterogeneous datasets of Transient Receptor Potential Vanilloid 1 generated by combining different homogeneous experimental datasets. Our results indicate that classification can isolate highly homogeneous subsets of particle for calculating high-resolution structures containing individual ligands, but with limitations.
Language	English
Publishing date	2022-03-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2707496-1
ISSN	2050-5701 ; 2050-5698
ISSN (online)	2050-5701
ISSN	2050-5698
DOI	10.1093/jmicro/dfab044
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Article: Recent advances in infectious disease research using cryo-electron tomography.

Asarnow, Daniel / Becker, Vada A / Bobe, Daija / Dubbledam, Charlie / Johnston, Jake D / Kopylov, Mykhailo / Lavoie, Nathalie R / Li, Qiuye / Mattingly, Jacob M / Mendez, Joshua H / Paraan, Mohammadreza / Turner, Jack / Upadhye, Viraj / Walsh, Richard M / Gupta, Meghna / Eng, Edward T

Frontiers in molecular biosciences

2024 Volume 10, Page(s) 1296941

Abstract: With the increasing spread of infectious diseases worldwide, there is an urgent need for novel strategies to combat them. Cryogenic sample electron microscopy (cryo-EM) techniques, particularly electron tomography (cryo-ET), have revolutionized the field ...

Abstract	With the increasing spread of infectious diseases worldwide, there is an urgent need for novel strategies to combat them. Cryogenic sample electron microscopy (cryo-EM) techniques, particularly electron tomography (cryo-ET), have revolutionized the field of infectious disease research by enabling multiscale observation of biological structures in a near-native state. This review highlights the recent advances in infectious disease research using cryo-ET and discusses the potential of this structural biology technique to help discover mechanisms of infection in native environments and guiding in the right direction for future drug discovery.
Language	English
Publishing date	2024-01-15
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2814330-9
ISSN	2296-889X
ISSN	2296-889X
DOI	10.3389/fmolb.2023.1296941
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Article: A broadly generalizable stabilization strategy for sarbecovirus fusion machinery vaccines.

Lee, Jimin / Stewart, Cameron / Schaefer, Alexandra / Leaf, Elizabeth M / Park, Young-Jun / Asarnow, Daniel / Powers, John M / Treichel, Catherine / Corti, Davide / Baric, Ralph / King, Neil P / Veesler, David

bioRxiv : the preprint server for biology

2023

Abstract: Continuous evolution of SARS-CoV-2 alters the antigenicity of the immunodominant spike (S) receptor-binding domain and N-terminal domain, undermining the efficacy of vaccines and monoclonal antibody therapies. To overcome this challenge, we set out to ... ...

Abstract	Continuous evolution of SARS-CoV-2 alters the antigenicity of the immunodominant spike (S) receptor-binding domain and N-terminal domain, undermining the efficacy of vaccines and monoclonal antibody therapies. To overcome this challenge, we set out to develop a vaccine focusing antibody responses on the highly conserved but metastable S
Language	English
Publishing date	2023-12-20
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.12.12.571160
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Article: Full-spike deep mutational scanning helps predict the evolutionary success of SARS-CoV-2 clades.

Dadonaite, Bernadeta / Brown, Jack / McMahon, Teagan E / Farrell, Ariana G / Asarnow, Daniel / Stewart, Cameron / Logue, Jenni / Murrell, Ben / Chu, Helen Y / Veesler, David / Bloom, Jesse D

bioRxiv : the preprint server for biology

2023

Abstract: SARS-CoV-2 variants acquire mutations in spike that promote immune evasion and impact other properties that contribute to viral fitness such as ACE2 receptor binding and cell entry. Knowledge of how mutations affect these spike phenotypes can provide ... ...

Abstract	SARS-CoV-2 variants acquire mutations in spike that promote immune evasion and impact other properties that contribute to viral fitness such as ACE2 receptor binding and cell entry. Knowledge of how mutations affect these spike phenotypes can provide insight into the current and potential future evolution of the virus. Here we use pseudovirus deep mutational scanning to measure how >9,000 mutations across the full XBB.1.5 and BA.2 spikes affect ACE2 binding, cell entry, or escape from human sera. We find that mutations outside the receptor-binding domain (RBD) have meaningfully impacted ACE2 binding during SARS-CoV-2 evolution. We also measure how mutations to the XBB.1.5 spike affect neutralization by serum from individuals who recently had SARS-CoV-2 infections. The strongest serum escape mutations are in the RBD at sites 357, 420, 440, 456, and 473-however, the antigenic impacts of these mutations vary across individuals. We also identify strong escape mutations outside the RBD; however many of them decrease ACE2 binding, suggesting they act by modulating RBD conformation. Notably, the growth rates of human SARS-CoV-2 clades can be explained in substantial part by the measured effects of mutations on spike phenotypes, suggesting our data could enable better prediction of viral evolution.
Language	English
Publishing date	2023-11-14
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.11.13.566961
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Article: Enhancing the signal-to-noise ratio and generating contrast for cryo-EM images with convolutional neural networks.

Palovcak, Eugene / Asarnow, Daniel / Campbell, Melody G / Yu, Zanlin / Cheng, Yifan

IUCrJ

2020 Volume 7, Issue Pt 6, Page(s) 1142–1150

Abstract: In cryogenic electron microscopy (cryo-EM) of radiation-sensitive biological samples, both the signal-to-noise ratio (SNR) and the contrast of images are critically important in the image-processing pipeline. Classic methods improve low-frequency image ... ...

Abstract	In cryogenic electron microscopy (cryo-EM) of radiation-sensitive biological samples, both the signal-to-noise ratio (SNR) and the contrast of images are critically important in the image-processing pipeline. Classic methods improve low-frequency image contrast experimentally, by imaging with high defocus, or computationally, by applying various types of low-pass filter. These contrast improvements typically come at the expense of the high-frequency SNR, which is suppressed by high-defocus imaging and removed by low-pass filtration. Recently, convolutional neural networks (CNNs) trained to denoise cryo-EM images have produced impressive gains in image contrast, but it is not clear how these algorithms affect the information content of the image. Here, a denoising CNN for cryo-EM images was implemented and a quantitative evaluation of SNR enhancement, induced bias and the effects of denoising on image processing and three-dimensional reconstructions was performed. The study suggests that besides improving the visual contrast of cryo-EM images, the enhanced SNR of denoised images may be used in other parts of the image-processing pipeline, such as classification and 3D alignment. These results lay the groundwork for the use of denoising CNNs in the cryo-EM image-processing pipeline beyond particle picking.
Language	English
Publishing date	2020-10-24
Publishing country	England
Document type	Journal Article
ZDB-ID	2754953-7
ISSN	2052-2525
ISSN	2052-2525
DOI	10.1107/S2052252520013184
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Article ; Online: Dispatched uses Na

Wang, Qianqian / Asarnow, Daniel E / Ding, Ke / Mann, Randall K / Hatakeyama, Jason / Zhang, Yunxiao / Ma, Yong / Cheng, Yifan / Beachy, Philip A

Nature

2021 Volume 599, Issue 7884, Page(s) 320–324

Abstract: The Dispatched protein, which is related to the NPC1 and PTCH1 cholesterol ... ...

Abstract	The Dispatched protein, which is related to the NPC1 and PTCH1 cholesterol transporters
MeSH term(s)	Animals ; Binding Sites ; Cell Membrane/chemistry ; Cell Membrane/metabolism ; Cryoelectron Microscopy ; Hedgehog Proteins/chemistry ; Hedgehog Proteins/metabolism ; Hedgehog Proteins/ultrastructure ; Lipid Metabolism ; Membrane Lipids/chemistry ; Membrane Lipids/isolation & purification ; Membrane Proteins/chemistry ; Membrane Proteins/genetics ; Membrane Proteins/metabolism ; Membrane Proteins/ultrastructure ; Mice ; Models, Molecular ; Mutation ; Sodium/metabolism
Chemical Substances	Hedgehog Proteins ; Membrane Lipids ; Membrane Proteins ; Shh protein, mouse ; dispatched-1 protein, mouse ; Sodium (9NEZ333N27)
Language	English
Publishing date	2021-10-27
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	120714-3
ISSN	1476-4687 ; 0028-0836
ISSN (online)	1476-4687
ISSN	0028-0836
DOI	10.1038/s41586-021-03996-0
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Article ; Online: Automatic classification of protein structures using low-dimensional structure space mappings.

Asarnow, Daniel / Singh, Rahul

BMC bioinformatics

2014 Volume 15 Suppl 2, Page(s) S1

Abstract: Background: Protein function is closely intertwined with protein structure. Discovery of meaningful structure-function relationships is of utmost importance in protein biochemistry and has led to creation of high-quality, manually curated classification ...

Abstract	Background: Protein function is closely intertwined with protein structure. Discovery of meaningful structure-function relationships is of utmost importance in protein biochemistry and has led to creation of high-quality, manually curated classification databases, such as the gold-standard SCOP (Structural Classification of Proteins) database. The SCOP database and its counterparts such as CATH provide a detailed and comprehensive description of the structural and evolutionary relationships of the proteins of known structure and are widely employed in structural and computational biology. Since manual classification is both subjective and highly laborious, automated classification of novel structures is increasingly an active area of research. The design of methods for automated structure classification has been rendered even more important since the recent past, due to the explosion in number of solved structures arising out of various structural biology initiatives. In this paper we propose an approach to the problem of structure classification based on creating and tessellating low dimensional maps of the protein structure space (MPSS). Given a set of protein structures, an MPSS is a low dimensional embedding of structural similarity-based distances between the molecules. In an MPSS, a group of proteins (such as all the proteins in the PDB or sub-samplings thereof) under consideration are represented as point clouds and structural relatedness maps to spatial adjacency of the points. In this paper we present methods and results that show that MPSS can be used to create tessellations of the protein space comparable to the clade systems within SCOP. Though we have used SCOP as the gold standard, the proposed approach is equally applicable for other structural classifications. Methods: In the proposed approach, we first construct MPSS using pairwise alignment distances obtained from four established structure alignment algorithms (CE, Dali, FATCAT and MATT). The low dimensional embeddings are next computed using an embedding technique called multidimensional scaling (MDS). Next, by using the remotely homologous Superfamily and Fold levels of the hierarchical SCOP database, a distance threshold is determined to relate adjacency in the low dimensional map to functional relationships. In our approach, the optimal threshold is determined as the value that maximizes the total true classification rate vis-a-vis the SCOP classification. We also show that determining such a threshold is often straightforward, once the structural relationships are represented using MPSS. Results and conclusion: We demonstrate that MPSS constitute highly accurate representations of protein fold space and enable automatic classification of SCOP Superfamily and Fold-level relationships. The results from our automatic classification approach are remarkably similar to those found in the distantly homologous Superfamily level and the quite remotely homologous Fold levels of SCOP. The significance of our results are underlined by the fact that most automated methods developed thus far have only managed to match the closest-homology Family level of the SCOP hierarchy and tend to differ considerably at the Superfamily and Fold levels. Furthermore, our research demonstrates that projection into a low-dimensional space using MDS constitutes a superior noisereducing transformation of pairwise distances than do the variety of probability- and alignment-length-based transformations currently used by structure alignment algorithms.
MeSH term(s)	Algorithms ; Cluster Analysis ; Computational Biology/methods ; Databases, Protein ; Protein Conformation ; Proteins/chemistry ; Proteins/classification
Chemical Substances	Proteins
Language	English
Publishing date	2014-01-24
Publishing country	England
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/1471-2105-15-S2-S1
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Article: Broadly neutralizing antibodies against emerging delta-coronaviruses.

bioRxiv : the preprint server for biology

2024

Abstract: Porcine deltacoronavirus (PDCoV) spillovers were recently detected in children with acute undifferentiated febrile illness, underscoring recurrent zoonoses of divergent coronaviruses. To date, no vaccines or specific therapeutics are approved for use in ... ...

Abstract	Porcine deltacoronavirus (PDCoV) spillovers were recently detected in children with acute undifferentiated febrile illness, underscoring recurrent zoonoses of divergent coronaviruses. To date, no vaccines or specific therapeutics are approved for use in humans against PDCoV. To prepare for possible future PDCoV epidemics, we isolated human spike (S)-directed monoclonal antibodies from transgenic mice and found that two of them, designated PD33 and PD41, broadly neutralized a panel of PDCoV variants. Cryo-electron microscopy structures of PD33 and PD41 in complex with the PDCoV receptor-binding domain and S ectodomain trimer provide a blueprint of the epitopes recognized by these mAbs, rationalizing their broad inhibitory activity. We show that both mAbs inhibit PDCoV by competitively interfering with host APN binding to the PDCoV receptor-binding loops, explaining the mechanism of viral neutralization. PD33 and PD41 are candidates for clinical advancement, which could be stockpiled to prepare for possible future PDCoV outbreaks.
Language	English
Publishing date	2024-04-01
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.03.27.586411
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Article ; Online: Recent advances in infectious disease research using cryo-electron tomography

Daniel Asarnow / Vada A. Becker / Daija Bobe / Charlie Dubbledam / Jake D. Johnston / Mykhailo Kopylov / Nathalie R. Lavoie / Qiuye Li / Jacob M. Mattingly / Joshua H. Mendez / Mohammadreza Paraan / Jack Turner / Viraj Upadhye / Richard M. Walsh / Meghna Gupta / Edward T. Eng

Frontiers in Molecular Biosciences, Vol

2024 Volume 10

Abstract	With the increasing spread of infectious diseases worldwide, there is an urgent need for novel strategies to combat them. Cryogenic sample electron microscopy (cryo-EM) techniques, particularly electron tomography (cryo-ET), have revolutionized the field of infectious disease research by enabling multiscale observation of biological structures in a near-native state. This review highlights the recent advances in infectious disease research using cryo-ET and discusses the potential of this structural biology technique to help discover mechanisms of infection in native environments and guiding in the right direction for future drug discovery.
Keywords	cryo-ET ; pathogen ; infectious diseases ; viruses ; bacteria ; host-pathogen interaction ; Biology (General) ; QH301-705.5
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Segmenting the etiological agent of schistosomiasis for high-content screening.

Asarnow, Daniel E / Singh, Rahul

IEEE transactions on medical imaging

2013 Volume 32, Issue 6, Page(s) 1007–1018

Abstract: Schistosomiasis is a parasitic disease with a global health impact second only to malaria. The World Health Organization has classified schistosomiasis as an illness for which new therapies are urgently needed. However, the causative parasite is ... ...

Abstract	Schistosomiasis is a parasitic disease with a global health impact second only to malaria. The World Health Organization has classified schistosomiasis as an illness for which new therapies are urgently needed. However, the causative parasite is refractory to current high-throughput drug screening due to the diversity and complexity of shape, appearance and movement-based phenotypes exhibited in response to putative drugs. Currently, there is no automated image-based approach capable of relieving this deficiency. We propose and validate an image segmentation algorithm designed to overcome the distinct challenges posed by schistosomes and macroparasites in general, including irregular shapes and sizes, dense groups of touching parasites and the unpredictable effects of drug exposure. Our approach combines a region-based distributing function with a novel edge detector derived from phase congruency and grayscale thinning by threshold superposition. The method is sufficiently rapid, robust and accurate to be used for quantitative analysis of diverse parasite phenotypes in high-throughput and high-content screening.
MeSH term(s)	Algorithms ; Animals ; Drug Discovery ; High-Throughput Screening Assays/methods ; Humans ; Image Processing, Computer-Assisted/methods ; Microscopy/methods ; Reproducibility of Results ; Schistosoma/chemistry ; Schistosoma/drug effects ; Schistosoma/isolation & purification ; Schistosomiasis/parasitology ; Schistosomicides/pharmacology
Chemical Substances	Schistosomicides
Language	English
Publishing date	2013-06
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	622531-7
ISSN	1558-254X ; 0278-0062
ISSN (online)	1558-254X
ISSN	0278-0062
DOI	10.1109/TMI.2013.2247412
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