Biology subjects

Davis, J. H.

Publications and source records attributed to Davis, J. H..

23 records · Page 2Linked to original sources

bioRxiv2022

Uncovering structural ensembles from single particle cryo-EM data using cryoDRGN

CryoDRGN is a machine learning system for heterogeneous cryo-EM reconstruction of proteins and protein complexes from single particle cryo-EM data. Central to this approach is a deep generative model for heterogeneous cryo-EM density maps, which we empirically find effectively models both discrete and continuous forms of structural variability. Once trained, cryoDRGN is capable of generating an arbitrary number of 3D density maps, and thus interpreting the resulting ensemble is a challenge. Here, we showcase interactive and automated processing approaches for analyzing cryoDRGN results. Specifically, we detail a step-by-step protocol for analysis of the assembling 50S ribosome dataset (Davis et al., EMPIAR-10076), including preparation of inputs, network training, and visualization of the resulting ensemble of density maps. Additionally, we describe and implement methods to comprehensively analyze and interpret the distribution of volumes with the assistance of an associated atomic model. This protocol is appropriate for structural biologists familiar with processing single particle cryo-EM datasets and with moderate experience programming in Python and navigating Jupyter notebooks. It requires 3-4 days to complete.

biochemistry↗

bioRxiv2022

KsgA facilitates ribosomal small subunit maturation by proofreading a key structural lesion

Ribosome assembly is orchestrated by many assembly factors, including ribosomal RNA methyltransferases whose precise role is poorly understood. Here, we leverage the power of cryo-EM and machine learning to discover that the bacterial methyltransferase KsgA performs a novel "proofreading" function in assembly of the ribosomal small subunit by recognizing and partially disassembling particles that have matured but are not competent for translation. We propose that this activity allows inactive particles an opportunity to reassemble into an active state, thereby increasing overall assembly fidelity. Detailed structural quantifications in our datasets additionally enabled expansion of the Nomura assembly map to highlight rRNA helix and r-protein interdependencies, which newly details how binding and docking of these elements are tightly coupled. These results have wide-ranging implications in our understanding of the quality control mechanisms governing ribosome biogenesis, and showcase the power of heterogeneity analysis in cryo-EM to unveil functionally relevant information in biological systems.

biochemistry↗

bioRxiv2022

UVC Inactivation of Black Mold is Wavelength-Dependent, and its Growth in HVAC Systems is Preventable Using Periodic Dosing with commercially available UVC LEDs

Mold growth in HVAC systems poses a threat to human health, increases facility management operating costs due to decreased air flow efficiency, and damages buildings, impacting buildings attractiveness in an ever more competitive property market concerned with both carbon footprint and ventilation quality. Although UVC treatment of HVAC systems has been shown to reduce growth, efficient design requires a specified amount of UVC dose coupled with a specific dosing strategy. UVC disinfection efficacy and wavelength sensitivity of spores from the most common and notorious black mold, Cladosporium halotolerans is not known. This study investigates the sensitivity of C. halotolerans and demonstrates that growth of black mold on HVAC coils can be effectively prevented with a periodic dosing scheme using commercially available UVC LEDs. Multiple UVC LED arrays with varying wavelength peaks in the range of 252-280 nm were used to demonstrate the spectral sensitivity of C. halotolerans by keeping the wavelength specific UVC dose equal in order to avoid bias. The data obtained for doses of 25, 75, 125, 175, and 225 mJ/cm2 was used. The data obtained was used to determine a dose response curve and susceptibility patterns. Disinfection performances for the arrays were determined using log reduction value (LRV) by comparing the controls against the irradiated treatments. To study mold growth prevention on HVAC coils, the 267 nm array which had the best disinfection efficacy was utilized. The coils were placed in a chamber with a temperature set at 24 {degrees}C and relative humidity (RH) at 96%. Unlike the controls, the test coil was irradiated with a dose of 28.8 mJ/cm2 every 12 hours. The coils were monitored, and observations were recorded using time-lapse videos. The highest disinfection level of black mold observed in the range of 250-280nm occurred at 267 nm, with 225 mJ/cm2 obtaining 4.03 LRV. Linear regression analysis at 95% for 252 nm (R2 =0.9637, p=0.0030), 261 nm (R2 =0.9711, p=0.0021), 267 nm (R2 =0.9723, p=0.0020), 270 nm (R2 =0.9819, p=0.0010), 273 nm (R2 =0.9878, p=0.0006), and 280 nm (R2 =0.9914, p=0.0003) displayed significant association between arrays peak wavelengths and disinfection performances against C. halotolerans. The study revealed that a higher dose of 225 mJ/cm2 is required to disinfect C. halotolerans by 99.99% (4.03 LRV). However, using a periodic dosing strategy utilizing 28.8 mJ/cm2 prevented any mold growth, while the fungal levels in the positive control increased. The study allows for the design and implementation of mold growth prevention strategies in HVAC systems to improve health and lower operating costs.

microbiology↗

bioRxiv2020

CryoDRGN: Reconstruction of heterogeneous structures from cryo-electron micrographs using neural networks

Cryo-EM single-particle analysis has proven powerful in determining the structures of rigid macromolecules. However, many protein complexes are flexible and can change conformation and composition as a result of functionally-associated dynamics. Such dynamics are poorly captured by current analysis methods. Here, we present cryoDRGN, an algorithm that for the first time leverages the representation power of deep neural networks to efficiently reconstruct highly heterogeneous complexes and continuous trajectories of protein motion. We apply this tool to two synthetic and three publicly available cryo-EM datasets, and we show that cryoDRGN provides an interpretable representation of structural heterogeneity that can be used to identify discrete states as well as continuous conformational changes. This ability enables cryoDRGN to discover previously overlooked structural states and to visualize molecules in motion.

molecular biology↗

bioRxiv2019

Role of Era in Assembly and Homeostasis of the Ribosomal Small Subunit

To reveal the role of the essential protein Era in the assembly of the 30S ribosomal subunit, we analyzed assembly intermediates that accumulated in Era-depleted Escherichia coli cells using quantitative mass spectrometry, cryo-electron microscopy and in-cell footprinting. Our combined approach allowed for visualization of the small subunit as it assembled and revealed that with the exception of key helices in the platform domain, all other 16S rRNA domains were able to fold even in the absence of Era. Notably, the maturing particles did not stall while waiting for the platform domain to mature and instead re-routed their folding pathway to enable concerted maturation of other structural motifs spanning multiple rRNA domains. We also found that binding of Era to the mature 30S subunit destabilized helix 44 and the decoding center preventing binding of YjeQ, another assembly factor. This work establishes Eras role in ribosome assembly and suggests new roles in maintaining ribosome homeostasis.

molecular biology↗