Biology subjects

Wang, X. H.

Publications and source records attributed to Wang, X. H..

8 recordsLinked to original sources

bioRxiv2026

Modulation of rob expression accelerates development of antibiotic resistance in Yersinia enterocolitica

Multidrug-resistant bacteria pose a severe threat to global health. Mutations in transcriptional regulators accelerate the emergence of multidrug resistance and may have a crucial impact on pathogen evolvability under antibiotic exposure. Here, we investigate these dynamics in the bacterial pathogen Yersinia enterocolitica. In this organism, we identified a high-frequency de novo mutation in the promoter of an AraC/XylS-family transcriptional regulator, Rob. This mutation arose independently during resistance evolution against three of six antibiotic classes. Sequence and structure alignments indicate that Rob is a previously uncharacterized, lineage-specific regulator in Y. enterocolitica, featuring a conserved promoter architecture. This promoter mutation resulted in robust rob overexpression, leading to the activation of multiple downstream efflux- and membrane-associated pathways. This regulatory mutation emerges early and shapes the acquisition of tetracycline resistance, while also enhancing high-level enrofloxacin resistance in combination with canonical mutations in gyrA and parC. Despite being favored under antibiotic selection, rob overexpression is costly, resulting in counter-selection of the -57 G>A rob allele in the absence of antibiotics. Together, these findings identify Rob as a Yersinia-specific efflux regulator and demonstrate how regulatory mutations can transiently accelerate antibiotic resistance. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/707304v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@107aa88org.highwire.dtl.DTLVardef@4ccd66org.highwire.dtl.DTLVardef@411e2aorg.highwire.dtl.DTLVardef@1235fbc_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Driving factors for beta-lactam resistance gene amplification during de novo resistance evolution in E. coli

Long-term exposure of E. coli to non-lethal step-wise increasing concentrations of beta-lactam antibiotics induces high levels of resistance that can be accompanied by amplification of a chromosomal fragment around the ampC gene. We compared the amplification of the ampC fragment in the wildtype, an ampC knockout mutant, a mutant in which the ampC gene was replaced by a tetracycline resistance gene tet(B)and a strain in which the ampC has been translocated. When ampC was removed, no amplification occurred at the original ampC location, but DNA fragments were amplified around the genes coding for efflux pump AcrAB and the multiple antibiotic resistance operon MarRAB. When tet(B) replaced ampC, exposure to tetracycline induced amplification of comparable fragments, while exposure to amoxicillin induced duplication of a larger fragment elsewhere. When ampC was translocated, a fragment around it at the new location was amplified. The importance of the presence but not of the location within the chromosome of the resistance genes for the amplification process indicates that the mechanisms are neither gene nor location specific. Without the relatively efficient resistance gene ampC, duplication and amplification occur around acrAB and marRAB that code for amoxicillin and tetracycline resistance factors. These duplications and amplifications are prevented by ampC amplification.

microbiology↗

bioRxiv2024

Collateral sensitivity and cross resistance in six species of bacteria exposed to six classes of antibiotics

De novo resistance can be developed in bacteria because of exposure to sublethal concentrations of antibiotics. Once the strain has become resistant to an initial antibiotic, this can cause cross-resistance or collateral sensitivity to a second antimicrobial. Specific collateral sensitivity is rarely conserved across species because the mechanisms triggered in different microorganisms to resist antibiotics are often different. In this study, we explored which collateral sensitivity or cross resistance networks are present in six species of bacteria with induced de novo-resistance. These six species were induced to become resistant to amoxicillin/cefepime, enrofloxacin, kanamycin, tetracycline, erythromycin and chloramphenicol(1). After that, the collateral sensitivity and the cross-resistance networks were evaluated by measuring increase or decrease of MIC of thirteen antibiotics that are often used in the clinic. Collateral sensitivity for kanamycin occurred in five species of strains resistant to chloramphenicol and tetracycline and for {beta}-lactam in strains of five species resistant to kanamycin. Further genetic analysis clarified that fusA consistently mutated in five species of bacteria made de novo resistant against kanamycin, suggesting that fusA operates in parallel with the other mechanisms related to antimicrobial resistance Based on considerations of resistance, a treatment protocol starting with chloramphenicol/tetracycline, followed by kanamycin and ending with amoxicillin may eliminate bacteria that have developed resistance against the initial treatment.

microbiology↗

bioRxiv2024

De novo acquisition of antibiotic resistance in six species of bacteria

Bacteria can become resistant to antibiotics in two ways, by acquiring resistance genes through horizontal gene transfer and by de novo development of resistance upon exposure to non-lethal concentrations. The importance of the second process, de novo build-up, has not been investigated systematically over a range of species and may be underestimated as a result. To investigate the DNA mutation patterns accompanying the de novo antibiotic resistance acquisition process, six bacterial species encountered in the food chain were exposed to step-wise increasing sublethal concentrations of six antibiotics to develop high levels of resistance. Phenotypic and mutational landscapes were constructed based on whole genome sequencing (WGS) sequencing at two time points of the evolutionary trajectory. In this study, we found: 1) all of the six strains can develop high levels of resistance against most antibiotics. 2) increased resistance is accompanied by different mutations for each bacterium-antibiotic combination. 3) the number of mutations varies widely, with Y. enterocolitica having by far the most. 4) in the case of fluoroquinolone resistance, a mutational pattern of gyrA combined with parC is conserved in five of six species. 5) mutations in genes coding for efflux pumps are widely encountered in gram-negative species. The overall conclusion is that very similar phenotypic outcomes are instigated by very different genetic changes. IMPORTANCEThe significance of this study lies in the comparison of how six species of distinct genomic background under uniform conditions develop high levels of antibiotic resistance against six antibiotics. The mutational patterns in these six species of bacteria identify common target mutations and reveal how they acquire mutations from various pathways to survive and grow when exposed to sub-lethal levels of antibiotics. In addition to providing insights in microbial genetics, outcome of this study will assist policymakers when formulating practical strategies to prevent development of antimicrobial resistance in human and veterinary health care.

microbiology↗

bioRxiv2023

Brain tissue cerebrospinal fluid fraction increases quadratically in normal aging

Background and PurposeOur objective was to apply multi-compartment T2 relaxometry in cognitively normal individuals aged 20-80 years to study the effect of aging on the parenchymal cerebrospinal fluid fraction (CSFF), a measure of the microscopic-scale CSF space. Materials and MethodsA total of 66 volunteers (age range, 22-80 years) were enrolled. Voxel-wise maps of short-T2 myelin water fraction (MWF), intermediate-T2 intra/extra-cellular water fraction (IEWF), and long-T2 CSFF were obtained using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) sequence and three-pool non-linear least squares fitting. Multiple linear regression analysis with correction for multiple comparisons was performed to study the association between age and regional MWF, IEWF, and CSFF measurements, adjusting for sex and region of interest (ROI) volume. The cerebral white matter (WM), cerebral cortex, and subcortical deep gray matter (GM) were considered as ROIs. In each model, a quadratic term for age was tested using an ANOVA test. A Spearmans correlation between the normalized lateral ventricle volume, a measure of organ-level CSF space, and the regional CSFF, a measure of tissue-level CSF space, was computed. ResultsIn the multiple regression analysis, we found a statistically significant quadratic relationship between age and regional CSFF for all three ROIs (all p-values < 0.001). A statistically significant quadratic relationship with age was also found for MWF in the deep GM (p = 0.004) and IEWF in the cortex (p = 0.012). There was a statistically significant linear relationship between age and regional IEWF in the cerebral WM (p = 0.006) and deep GM (p = 0.002). In the univariate correlation analysis, the normalized lateral ventricle volume was found to correlate moderately with the regional CSFF measurement in the cerebral WM ({rho} = 0.43, p < 0.001), cortex ({rho} = 0.43, p < 0.001), and deep GM ({rho} = 0.49, p < 0.001). ConclusionBrain tissue water residing in different water compartments shows complex changing patterns with age. Parenchymal CSFF, a biomarker of microscopic-scale CSF-like water, shows a quadratic increase in both GM and WM, starting approximately at the age of 50.

neuroscience↗

bioRxiv2021

Increasing age is independently associated with higher free water in non-active MS brain - A multi-compartment analysis using FAST-T2

PurposeTo explore the relationship between the cerebral cortical perivascular space (PVS) and aging in non-active MS subjects by using the multi-echo T2 relaxometry based cerebrospinal fluid fraction (CSFF) map. MethodsMulti-echo spiral T2 data from 111 subjects with non-active multiple sclerosis (MS) were retrospectively investigated by fitting the T2 data into a three-compartment model, the three water compartments including myelin water, intra-extracellular water, and cerebrospinal fluid. Segmentation of T1w image was performed to get the region of interest (ROI) in cerebral cortical regions. The white matter lesion segmentation was conducted using a convolutional neural network (CNN) based segmentation tool. The CSFF in the ROIs were correlated with age by controlling the gender, white matter hyperintensity lesion burden, and MS disease duration. Multiple linear models were created for the analysis of aging effect on the CSFF. ResultsThe ROI analysis shows that the CSFF in the cerebral cortical regions (temporal, occipital, parietal, front, hippo, and mtl) are significantly linear increasing with age (p<0.01). The intra-extracellular water fraction (IEWF) in the ROIs are significantly linear decreasing (p<0.01). ConclusionThe multi-echo T2 based three-compartment model can be used to quantify the CSFF. The linear increase of CSF water contents in the cerebral cortical regions indicates increased perivascular space load in cortex with aging. The quantification of CSFF may provide a way to understand the glymphatic clearance function in aging and neurodegenerations. HighlightsO_LIMR T2 relaxometry is a valid method to quantify the cerebrospinal fluid fraction (CSFF) in cerebral cortical regions C_LIO_LIThe CSFF in the cerebral cortical regions are positively correlated with age by controlling the white matter lesion load in non-active MS subjects. C_LIO_LIQuantification of cerebral CSFF may reflect the perivascular space load in cortex and better interpret the disease progression in neurodegenerative disease, such as MS. C_LI

neuroscience↗

bioRxiv2020

Genome-wide characterization and expression profiling of B3 superfamily during flower induction stage in pineapple (Ananas comosus L.)

The B3 superfamily is a plant-specific family, which involves in growth and development process. By now, the identification of B3 superfamily in pineapple (Ananas comosus) has not reported. In this study, 57 B3 genes were identified and further phylogenetically classified into five subfamilies, all genes contained B3 domain. Chromosomal localization analysis revealed that 54 of 57 AcB3 genes were located on 21 chromosomes.Collinearity analysis indicated that the segmental duplication was the main event in the evolution of B3 gene superfamily and most of them were under purifying selection. Moreover, there were 7 and 39 pairs of orthologous B3s were identified between pineapple and Arabidopsis or rice, respectively, which indicated the closer genetic relationship between pineapple and rice. Most genes had cis-element of abscisic acid, ethylene, MeJA, light, and abiotic stress. qRT-PCR showed that the expression level of most AcB3 genes were up-regulated within 1 d after ethephon treatment and expressed high level in flower bud differentiation period in stem apex. This study provide a comprehensive understanding of AcB3s and a basis for future molecular studies of ethephon induced pineapple flowering.

plant biology↗

bioRxiv2019

ImmuCellAI: a unique method for comprehensive T-cell subsets abundance prediction and its application in cancer immunotherapy

The distribution and abundance of immune cells, particularly T-cell subsets, play pivotal roles in cancer immunology and therapy. There are many T-cell subsets with specific function, however current methods are limited in estimating them, thus, a method for predicting comprehensive T-cell subsets is urgently needed in cancer immunology research. Here we introduce Immune Cell Abundance Identifier (ImmuCellAI), a novel gene set signature-based method, for precisely estimating the abundance of 24 immune cell types including 18 T-cell subsets, from gene expression data. Performance evaluation on both our sequencing data with flow cytometry results and public expression data indicated that ImmuCellAI can estimate immune cells with superior accuracy than other methods especially on many T-cell subsets. Application of ImmuCellAI to immunotherapy datasets revealed that the abundance of dendritic cells (DC), cytotoxic T, and gamma delta T cells was significantly higher both in comparisons of on-treatment vs. pre-treatment and responders vs. non-responders. Meanwhile, we built an ImmuCellAI result-based model for predicting the immunotherapy response with high accuracy (AUC 0.80~0.91). These results demonstrated the powerful and unique function of ImmuCellAI in tumor immune infiltration estimation and immunotherapy response prediction. The ImmuCellAI online server is freely available at http://bioinfo.life.hust.edu.cn/web/ImmuCellAI/.

bioinformatics↗