DOI: 10.5061/dryad.3tx95x6s3
title: Development of xanthone derivatives as effective broad-spectrum antimicrobials: Disrupting cell wall and inhibiting DNA synthesis

description: Discovering potent antibiotics is of critical importance due to the
 substantial increases of microbial resistance. Xanthones are intriguing
 sources of antimicrobials, despite a scarcity of extensive investigations
 into their mechanisms of action. Here, we reported the development of a
 series of xanthone derivatives, among which compound XT17 displayed strong
 broad-spectrum antibacterial activity, weak hemolytic activity and low
 cytotoxicity against mammalian cell lines, low frequencies of drug
 resistance, and potent in vivo efficacy in Staphylococcu aureus or
 Pseudomonas aeruginosa induced murine corneal infection models. Compound
 XT17 presented a multifaceted mode of actions, involving the disruption of
 cell wall by interacting with lipoteichoic acid or lipopolysaccharides and
 the suppression of DNA synthesis. A further docking study confirmed the
 capability of compound XT17 to form a stable complex with the bacterial
 gyrase enzyme. This work could offer an innovative design strategy for
 developing broad-spectrum therapeutic agents against drug-resistant
 bacteria.
description: A series of xanthone derived antimicrobial agents were designed
 and synthesized. The xanthone scaffold serves as the core precursor for a
 further chemically modification at its phenolic hydroxyl positions to
 improve the pharmacological properties of xanthone derivatives against
 both Gram-positive and Gram-negative bacteria. The candidate compound
 XT17, identified through a structure-activity relationship (SAR) study of
 these synthesized compounds, showed strong bactericidal properties and
 potent in vitro efficacy. A comprehensive transcriptomic analysis of the
 candidate compound XT17 was assessed using the high-throughput RNA-seq
 technique to gain insight into the antibacterial mechanisms. This efficacy
 stems from a dual-action mechanism: cell wall destruction and DNA gyrase
 inhibition. <strong>Growth condition and total
 RNA extraction</strong> For the challenge
 experiments, 5 ml of <em>E. coli</em> ATCC 25922 at an
 OD<sub>600</sub> of 0.5, representing the mid-log phase, was
 exposed to compound XT17 (4× MIC) for 2 h in a biological duplicate.
 Cultures treated with 4× MIC ciprofloxacin and without antibiotics served
 as positive and negative controls, respectively. After exposure, 1 ml
 aliquots of cells were immediately pelleted at 4 °C by centrifugation for
 2 min at 2000 rpm. The supernatants were removed and immediately frozen in
 liquid nitrogen. The samples were stored at −80 °C for later total RNA
 isolation. Total RNA was extracted using the bacterial RNA kit (Omega
 Bio-Tek, USA) according to the manufacturer’s instructions. The RNA
 Integrity Number (RIN) values were obtained to assess RNA quality using an
 Agilent Genomics 2200 Tape Station instrument.
 <strong>Transcriptome sequencing </strong>
 A total amount of 2–5 ng of the RNA per sample was executed as
 the input material to construct each cDNA library for RNA sequencing using
 the NEBNext Ultra Directional RNA Library prep kit from Illumina. The
 quality of the resulting libraries was checked using Agilent High
 Sensitivity DNA chips to ensure proper library size distribution and the
 absence of small adapters. Libraries were quantified and normalized by
 qPCR before being sequenced at 150 cycles with the NextSeq 500 High Output
 Kit, yielding approximately 9 million, 75 bp, and paired-end reads for
 each library. <strong>Bioinformatics
 analysis</strong> Read mapping was aligned using
 Bowtie2. HTSeq v0.6.1 was used for quantification of expression levels.
 DESeq2 on the R package (v1.12.4) was used to calculate differentially
 expressed genes. Differential expression was computed using edgeR:
 exactTest for each treatment versus the untreated control. The
 <em>E. coli</em> database used for mapping was
 GCF_017357505.1_ASM1735750v1_genomic.fna. Both the Gene Ontology (GO), and
 Kyoto Encyclopedia of Genes and Genomes (KEGG Ortholog database)
 enrichment analyses were done with Fisher’s exact test. All
 <em>P</em> values were adjusted with the Benjamini-Hochberg
 procedure to generate false-discovery rates (FDRs; adjusted
 <em>P</em> values). GO enrichment analysis was carried out
 using the clusterProfiler package on the R platform. KEGG pathway mapping
 and figure generation were performed with the PathView website. Clusters
 of Orthologous Groups (COG) of protein databases with an E-value of 1
 e<sup>-5</sup>. For hierarchal clustering analysis of gene
 expression, the gene expression levels were normalized to z-scores of
 log<sub>10 </sub>(FPKM + 1), where FPKM is fragments per
 kilobase per million. For hierarchal clustering analysis of the regulation
 of transcription factors, the UMPGA method was used as the clustering
 method. Transcription of genes that were not notably regulated was
 considered unchanged. Volcano plots were generated by plot_volcano from
 soothsayer (https://github.com/jolespin/soothsayer) in Python v.3.6.6.
 Directed networks (DiNetwork) were constructed and plotted using NetworkX
 and Matplotlib Python packages, respectively. Hierarchical clustering
 analysis and heatmap calculation were performed with the pheatmap package
 on R platform. The umap package on the R platform was used for UMAP
 analysis of FPKM vectors of each transcriptome. The figures were created
 via ggplot2 package.
description: # Development of xanthone derivatives as effective broad-spectrum
 antimicrobials: Disrupting cell wall and inhibiting DNA synthesis
 [https://doi.org/10.5061/dryad.3tx95x6s3
 ](https://doi.org/10.5061/dryad.3tx95x6s3) ## Description of the data and
 file structure ### Files and variables #### File:
 CPF\_vs\_CONTROL.gene\_DE.signi.addAnno.xlsx **Description:**  The
 transcriptome changes on Ciprofloxacin (CPF)-treated *E. coli* ATCC 25922
 via RNA sequencing (RNA-seq) technology. ##### Variables * Mean
 TPM, log2FoldChange, p Value, q Value  #### File:
 XT17\_vs\_CONTROL.gene\_DE.signi.addAnno.xlsx **Description:** The
 transcriptome changes on compound **XT17**-treated *E. coli* ATCC 25922
 via RNA sequencing (RNA-seq) technology. ##### Variables Mean
 TPM, log2FoldChange, p Value, q Value  | **abbreviation** |
 **description** | | :--------------- |
 :---------------------------------------------------------------------------------------------------------------------- | | Gene id | Gene Identifier | | down | down regulated genes | | up | up regulated genes | | MeanTPM | Mean Transcripts Per Million | | log2FoldChange | Representing the ratio of expression levels between two samples | | pValue | Used to evaluate whether the differences between samples are significant | | qValue | Statistical measure for controlling false positive rate | | GO | Gene Ontology | | KEGG | ‌Kyoto Encyclopedia of Genes and Genomes | | COG | Cluster of Orthologous Groups | | - | Indicating that there is no relevant annotation information for this gene or protein under a specific GO/KEGG/COG term. | ## Code/software Read mapping was aligned using Bowtie2. HTSeq v0.6.1 was used for quantification of expression levels. DESeq2 on the R package (v1.12.4) was used to calculate differentially expressed genes. Differential expression was computed using edgeR: exactTest for each treatment versus the untreated control. Volcano plots were generated by plot_volcano from soothsayer ([https://github.com/jolespin/soothsayer](https://github.com/jolespin/soothsayer)) in Python v.3.6.6. Directed networks (DiNetwork) were constructed and plotted using NetworkX and Matplotlib Python packages, respectively. Hierarchical clustering analysis and heatmap calculation were performed with the pheatmap package on R platform. The umap package on the R platform was used for UMAP analysis of FPKM vectors of each transcriptome. The figures were created via ggplot2 package.