Biology subjects

Barker, B.

Publications and source records attributed to Barker, B..

5 recordsLinked to original sources

bioRxiv2025

D614G reshapes allosteric networks and opening mechanisms of SARS-CoV-2 spikes

The SARS-CoV-2 spike glycoprotein binds human epithelial cells and enables infection through a key conformational transition that exposes its receptor binding domain (RBD). Experimental evidence indicates that spike mutations, particularly the early D614G variant, alter the rate of this conformational shift, potentially increasing viral infectivity. To investigate how mutations reshape the conformational landscape, we conducted extensive weighted ensemble simulations of the Ancestral, Delta, and Omicron BA.1 spike strains along the RBD opening pathway. We observe that Ancestral, Delta, and Omicron BA.1 spike RBDs open differently, with Omicron BA.1 following a more direct opening profile until it reaches a "super-open" state wherein it begins to "peel", suggesting increased S1 flexibility. Via dynamical network analysis, we identified two allosteric communication networks uniting all S1 domains: the established N2R linker and a newly discovered anti-parallel R2N linker. In Delta and Omicron BA.1 variant spikes, RBD opening is facilitated by both linkers, while the Ancestral strain relies predominantly on the N2R linker. In the ancestral spike, the D614-K854 salt bridge impedes allosteric communication through the R2N linker, whereas the loss of this salt bridge in all subsequent VOCs alleviates local frustration and, we believe, accelerates RBD opening. Hydrogen-deuterium mass spectrometry experiments validate these altered dynamics in the D614 region across Ancestral, D614G, and Omicron BA.1 spikes. This study unveils a hidden allosteric network, connecting the NTD to the RBD via the 614-proximal region, and the D614G mutation reshapes the fitness landscape of these critical viral glycoproteins. Significance StatementOur work reveals how the D614G mutation in the SARS-CoV-2 spike protein reshapes its internal communication pathways and speeds up receptor binding domain (RBD) opening, providing mechanistic insight into the evolution and enhanced infectivity of SARS-CoV-2 variants of concern. We also describe differences in opening pathways and relative rates of opening for Delta and Omicron BA.1 spike RBDs relative to the original (Ancestral) coronavirus strain from Wuhan, China.

biophysics↗

bioRxiv2024

Inferring the composition of a mixed culture of natural microbial isolates by deep sequencing

Next generation sequencing has unlocked a wealth of genotype information for microbial populations, but phenotyping remains a bottleneck for exploiting this information, particularly for pathogens that are difficult to manipulate. Here, we establish a method for high-throughput phenotyping of mixed cultures, in which the pattern of naturally occurring single-nucleotide polymorphisms in each isolate is used as intrinsic barcodes which can be read out by sequencing. We demonstrate that our method can correctly deconvolute strain proportions in simulated mixed-strain pools. As an experimental test of our method, we perform whole genome sequencing of 66 natural isolates of the thermally dimorphic pathogenic fungus Coccidioides posadasii and infer the strain compositions for large mixed pools of these strains after competition at 37{degrees}C and room temperature. We validate the results of these selection experiments by recapitulating the temperature-specific enrichment results in smaller pools. Additionally, we demonstrate that strain fitness estimated by our method can be used as a quantitative trait for genome-wide association studies. We anticipate that our method will be broadly applicable to natural populations of microbes and allow high-throughput phenotyping to match the rate of genomic data acquisition. Author summaryThe diversity of the gene pool in natural populations encodes a wealth of information about its molecular biology. This is an especially valuable resource for non-model organisms, from humans to many microbial pathogens, lacking traditional genetic approaches. An effective method for reading out this population genetic information is a genome wide association study (GWAS) which searches for genotypes correlated with a phenotype of interest. With the advent of cheap genotyping, high throughput phenotyping is the primary bottleneck for GWAS, particularly for microbes that are difficult to manipulate. Here, we take advantage of the fact that the naturally occurring genetic variation within each individual strain can be used as an intrinsic barcode, which can be used to read out relative abundance of each strain as a quantitative phenotype from a mixed culture. Coccidioides posadasii, the causative agent of Valley Fever, is a fungal pathogen that must be manipulated under biosafety level 3 conditions, precluding many high-throughput phenotyping approaches. We apply our method to pooled competitions of C. posadasii strains at environmental and host temperatures. We identify robustly growing and temperature-sensitive strains, confirm these inferences in validation pooled growth experiments, and successfully demonstrate their use in GWAS.

genetics↗

bioRxiv2021

#COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol

We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus ob-scure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized. ACM Reference FormatAbigail Dommer1{dagger}, Lorenzo Casalino1{dagger}, Fiona Kearns1{dagger}, Mia Rosenfeld1, Nicholas Wauer1, Surl-Hee Ahn1, John Russo,2 Sofia Oliveira3, Clare Morris1, AnthonyBogetti4, AndaTrifan5,6, Alexander Brace5,7, TerraSztain1,8, Austin Clyde5,7, Heng Ma5, Chakra Chennubhotla4, Hyungro Lee9, Matteo Turilli9, Syma Khalid10, Teresa Tamayo-Mendoza11, Matthew Welborn11, Anders Christensen11, Daniel G. A. Smith11, Zhuoran Qiao12, Sai Krishna Sirumalla11, Michael OConnor11, Frederick Manby11, Anima Anandkumar12,13, David Hardy6, James Phillips6, Abraham Stern13, Josh Romero13, David Clark13, Mitchell Dorrell14, Tom Maiden14, Lei Huang15, John McCalpin15, Christo- pherWoods3, Alan Gray13, MattWilliams3, Bryan Barker16, HarindaRajapaksha16, Richard Pitts16, Tom Gibbs13, John Stone6, Daniel Zuckerman2*, Adrian Mulholland3*, Thomas MillerIII11,12*, ShantenuJha9*, Arvind Ramanathan5*, Lillian Chong4*, Rommie Amaro1*. 2021. #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy ofDeltaSARS-CoV-2 in a Respiratory Aerosol. In Supercomputing 21: International Conference for High Perfor-mance Computing, Networking, Storage, and Analysis. ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI

biophysics↗

bioRxiv2021

The Predicted Metabolic Function of the Gut Microbiota of Drosophila melanogaster

An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and its impact on host physiology. This research can be confounded by poorly-understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multi-way interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle including 2-oxoglutarate and succinate are produced at high flux and cross-fed between bacterial taxa suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host. IMPORTANCEDrosophila is an important model for microbiome research partly because of the low complexity of its mostly culturable gut microbiota. Our current understanding of how Drosophila interacts with its gut microbes and how these interactions influence host traits derives almost entirely from empirical studies that focus on individual microbial taxa or classes of metabolites. These studies have failed to capture fully the complexity of metabolic interactions that occur between host and microbe. To overcome this limitation, we reconstructed and analyzed 31 metabolic models for every combination of the five principal bacterial taxa in the gut microbiome of Drosophila. This revealed that metabolic interactions between between Drosophila gut bacterial taxa are highly dynamic and influenced by co-occurring bacteria and nutrient availability. Our results generate testable hypothesis about among-microbe ecological interactions in the Drosophila gut and the diversity of metabolites available to influence host traits.

microbiology↗

bioRxiv2020

Optogenetic activation of CA1 pyramidal neurons in vivo induces hypersynchronous and low voltage fast seizures

Increasing evidence supports the idea that the CA1 of the hippocampus plays an important role in the pathogenesis of temporal lobe epilepsy (TLE). There is however a lack of proof that the over-excitation of CA1 alone is sufficient in inducing seizures in vivo. Furthermore, the relevance of the seizures induced from the over-excitation of CA1 to the pathophysiology of TLE is undetermined. Here, we employed optogenetics to activate pyramidal neurons (PNs) in CA1, which reliably induced generalized seizures in freely moving non-epileptic mice. We showed that repeated photostimulations had a kindling effect. In addition, seizures induced by over-active CA1 PNs were dominated by two distinctive onset patterns, i.e. hypersynchronous (HYP) and low voltage fast (LVF) activities, which are widely recorded in patients with and animal models of TLE. In our study, HYP seizures were predominantly associated with the first photostimulation and were entirely replaced by the LVF type afterwards. This phenomenon suggests that the activation of CA1 PNs, when occurring after the first seizure, could lead to the recruitment of GABAergic interneurons to participate in the seizure generation. These findings suggest that seizures induced from the over-excitation of CA1 PNs likely involved the same hippocampal networks and cellular mechanisms underlying TLE.

neuroscience↗