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Biology subjects

Bao, B.

Publications and source records attributed to Bao, B..

23 records · Page 2Linked to original sources

A Single Dose of Self-Transcribing and Replicating RNA Based SARS-CoV-2 Vaccine Produces Protective Adaptive Immunity In Mice

A self-transcribing and replicating RNA (STARR) based vaccine (LUNAR(R)-COV19) has been developed to prevent SARS-CoV-2 infection. The vaccine encodes an alphavirus-based replicon and the SARS-CoV-2 full length spike glycoprotein. Translation of the replicon produces a replicase complex that amplifies and prolong SARS-CoV-2 spike glycoprotein expression. A single prime vaccination in mice led to robust antibody responses, with neutralizing antibody titers increasing up to day 60. Activation of cell mediated immunity produced a strong viral antigen specific CD8+ T lymphocyte response. Assaying for intracellular cytokine staining for IFN-{gamma} and IL-4 positive CD4+ T helper lymphocytes as well as anti-spike glycoprotein IgG2a/IgG1 ratios supported a strong Th1 dominant immune response. Finally, single LUNAR-COV19 vaccination at both 2 g and 10 g doses completely protected human ACE2 transgenic mice from both mortality and even measurable infection following wild-type SARS-CoV-2 challenge. Our findings collectively suggest the potential of Lunar-COV19 as a single dose vaccine.

immunology↗

A consensus-based and readable extension of Linear Code for Reaction Rules (LiCoRR)

Systems glycobiology aims to provide models and analysis tools that account for the biosynthesis, regulation, and interactions with glycoconjugates. To facilitate these methods, there is a need for a clear glycan representation accessible to both computers and humans. Linear Code, a linearized and readily parsable glycan structure representation, is such a language. For this reason, Linear Code was adapted to represent reaction rules, but the syntax has drifted from its original description to accommodate new and originally unforeseen challenges. Here, we delineate the consensuses and inconsistencies that have arisen through this adaptation. We recommend options for a consensus-based extension of Linear Code that can be used for reaction rule specification going forward. Through this extension and specification of Linear Code to reaction rules, we aim to minimize inconsistent symbology thereby making glycan database queries easier. With a clear guide for generating reaction rule descriptions, glycan synthesis models will be more interoperable and reproducible thereby moving glycoinformatics closer to compliance with FAIR standards. Reaction rule-extended Linear Code is an unambiguous representation for describing glycosylation reactions in both literature and code.

systems biology↗

Correcting for sparsity and non-independence in glycomic data through a system biology framework

Glycans are fundamental cellular building blocks, involved in many organismal functions. Advances in glycomics are elucidating the roles of glycans, but it remains challenging to properly analyze large glycomics datasets, since the data are sparse (each sample often has only a few measured glycans) and detected glycans are non-independent (sharing many intermediate biosynthetic steps). We address these challenges with GlyCompare, a glycomic data analysis approach that leverages shared biosynthetic pathway intermediates to correct for sparsity and non-independence in glycomics. Specifically, quantities of measured glycans are propagated to intermediate glycan substructures, which enables direct comparison of different glycoprofiles and increases statistical power. Using GlyCompare, we studied diverse N-glycan profiles from glycoengineered erythropoietin. We obtained biologically meaningful clustering of mutant cell glycoprofiles and identified knockout-specific effects of fucosyltransferase mutants on tetra-antennary structures. We further analyzed human milk oligosaccharide profiles and identified novel impacts that the mothers secretor-status on fucosylation and sialylation. Our substructure-oriented approach will enable researchers to take full advantage of the growing power and size of glycomics data.

systems biology↗

HiCluster: A Robust Single-Cell Hi-C Clustering Method Based on Convolution and Random Walk

3D genome structure plays a pivotal role in gene regulation and cellular function. Single-cell analysis of genome architecture has been achieved using imaging and chromatin conformation capture methods such as Hi-C. To study variation in chromosome structure between different cell types, computational approaches are needed that can utilize sparse and heterogeneous single-cell Hi-C data. However, few methods exist that are able to accurately and efficiently cluster such data into constituent cell types. Here, we describe HiCluster, a single-cell clustering algorithm for Hi-C contact matrices that is based on imputations using linear convolution and random walk. Using both simulated and real data as benchmarks, HiCluster significantly improves clustering accuracy when applied to low coverage Hi-C datasets compared to existing methods. After imputation by HiCluster, structures similar to topologically associating domains (TADs) could be identified within single cells, and their consensus boundaries among cells were enriched at the TAD boundaries observed in bulk samples. In summary, HiCluster facilitates visualization and comparison of single-cell 3D genomes.\n\nAvailabilityhttps://github.com/zhoujt1994/HiCluster.git

bioinformatics↗

Intersection of phosphate transport, oxidative stress and TOR signalling in Candida albicans virulence

Phosphate is an essential macronutrient required for cell growth and division. Pho84 is the major high-affinity cell-surface phosphate importer of Saccharomyces cerevisiae and a crucial element in the phosphate homeostatic system of this model yeast. We found that loss of Candida albicans Pho84 attenuated virulence in Drosophila and murine oropharyngeal and disseminated models of invasive infection, and conferred hypersensitivity to neutrophil killing. Susceptibility of cells lacking Pho84 to neutrophil attack depended on reactive oxygen species (ROS): pho84-/- cells were no more susceptible than wild type C. albicans to neutrophils from a patient with chronic granulomatous disease, or to those whose oxidative burst was pharmacologically inhibited or neutralized. pho84-/- mutants hyperactivated oxidative stress signalling. They accumulated intracellular ROS in the absence of extrinsic oxidative stress, in high as well as low ambient phosphate conditions. ROS accumulation correlated with diminished levels of the unique superoxide dismutase Sod3 in pho84-/- cells, while SOD3 overexpression from a conditional promoter substantially restored these cells oxidative stress resistance in vitro. Repression of SOD3 expression sharply increased their oxidative stress hypersensitivity. Neither of these oxidative stress management effects of manipulating SOD3 transcription was observed in PHO84 wild type cells. Sod3 levels were not the only factor driving oxidative stress effects on pho84-/- cells, though, because overexpressing SOD3 did not ameliorate these cells hypersensitivity to neutrophil killing ex vivo, indicating Pho84 has further roles in oxidative stress resistance and virulence. Measurement of cellular metal concentrations demonstrated that diminished Sod3 expression was not due to decreased import of its metal cofactor manganese, as predicted from the function of S. cerevisiae Pho84 as a low-affinity manganese transporter. Instead of a role of Pho84 in metal transport, we found its role in TORC1 activation to impact oxidative stress management: overexpression of the TORC1-activating GTPase Gtr1 relieved the Sod3 deficit and ROS excess in pho84-/- null mutant cells, though it did not suppress their hypersensitivity to neutrophil killing or hyphal growth defect. Pharmacologic inhibition of Pho84 by small molecules including the FDA-approved drug foscarnet also induced ROS accumulation. Inhibiting Pho84 could hence support host defenses by sensitizing C. albicans to oxidative stress.

microbiology↗