Biology subjects

Zheng, H.

Publications and source records attributed to Zheng, H..

17 recordsLinked to original sources

bioRxiv2026

Proteomic analysis of Stony Coral Tissue Loss Disease demonstrates coral-algal dysbiosis during disease progression

Stony Coral Tissue Loss Disease (SCTLD) has devastated Caribbean reefs, yet the host molecular response to infection is poorly understood. Previous gene expression studies of diseased corals identified shifts in the immune response, apoptosis, and coral-algal dysbiosis. Here, we characterized the proteomic response of Diploria labyrinthiformis to SCTLD by comparing protein abundance in healthy tissue from uninfected colonies and apparently healthy and neighboring diseased tissue from infected colonies. These results were compared with existing metagenomic data from the same samples that previously demonstrated significant shifts in the coral microbiome due to SCTLD. We identified 480 differentially abundant proteins when comparing diseased lesion and healthy tissues, but only 12 between apparently healthy and healthy tissues. Pathway-level analysis provides evidence of immune suppression in apparently healthy tissue, suggesting that host molecular responses precede visible disease progression. Diseased lesion tissues showed wound-healing responses combined with a decreased abundance of proteins involved in symbiosome maintenance and increased oxidative stress responses, consistent with host-algal dysbiosis. This result correlates with the previous metagenomic analysis of these samples which found that infected colonies exhibit distinct algal symbiont communities dominated by Symbiodinium necroappetens, whereas healthy colonies are dominated by Durusdinium trenchii and Breviolum spp. Comparison with existing transcriptomic studies revealed both shared and distinct molecular responses, underscoring the importance of integrating multi-omics approaches to understand coral diseases. Our results suggest that SCTLD in D. labyrinthiformis is associated with early immune suppression, coral-algal dysbiosis, oxidative stress, and subsequent wound-healing responses.

ecology↗

bioRxiv2018

Inhibition of Mycobacterium tuberculosis DosRST two-component regulatory system signaling by targeting response regulator DNA binding and sensor kinase heme

Mycobacterium tuberculosis (Mtb) possesses a two-component regulatory system, DosRST, that enables Mtb to sense host immune cues and establish a state of non-replicating persistence (NRP). NRP bacteria are tolerant to several anti-mycobacterial drugs and are thought to play a role in the long course of tuberculosis (TB) therapy. Therefore, small molecules that inhibit Mtb from establishing or maintaining NRP could reduce the reservoir of drug tolerant bacteria and function as an adjunct therapy to reduce treatment time. Previously, we reported the discovery of six novel chemical inhibitors of DosRST, named HC101A-106A, from a whole cell, reporter-based phenotypic high throughput screen. Here, we report functional and mechanism of action studies of HC104A and HC106A. RNAseq transcriptional profiling shows that the compounds downregulate genes of the DosRST regulon. Both compounds reduce hypoxia-induced triacylglycerol synthesis by ~50%. HC106A inhibits Mtb survival during hypoxia-induced NRP, however, HC104A did not inhibit survival during NRP. An electrophoretic mobility assay shows that HC104A inhibits DosR DNA binding in a dose-dependent manner, indicating that HC104A may function by directly targeting DosR. In contrast, UV-visible spectroscopy studies suggest HC106A directly targets the histidine kinase heme, via a mechanism that is distinct from the oxidation and alkylation of heme previously observed with artemisinin (HC101A). Synergistic interactions were observed when DosRST inhibitors were examined in pair-wise combinations with the strongest potentiation observed between artemisinin paired with HC102A, HC103A, or HC106A. Our data collectively show that the DosRST pathway can be inhibited by multiple distinct mechanisms.

microbiology↗

bioRxiv2018

A deep learning framework for imputing missing values in genomic data

MotivationThe presence of missing values is a frequent problem encountered in genomic data analysis. Lost data can be an obstacle to downstream analyses that require complete data matrices. State-of-the-art imputation techniques including Singular Value Decomposition (SVD) and K-Nearest Neighbors (KNN) based methods usually achieve good performances, but are computationally expensive especially for large datasets such as those involved in pan-cancer analysis.\n\nResultsThis study describes a new method: a denoising autoencoder with partial loss (DAPL) as a deep learning based alternative for data imputation. Results on pan-cancer gene expression data and DNA methylation data from over 11,000 samples demonstrate significant improvement over standard denoising autoencoder for both data missing-at-random cases with a range of missing percentages, and missing-not-at-random cases based on expression level and GC-content. We discuss the advantages of DAPL over traditional imputation methods and show that it achieves comparable or better performance with less computational burden.\n\nAvailabilityhttps://github.com/gevaertlab/DAPL\n\nContactogevaert@stanford.edu

bioinformatics↗

bioRxiv2018

Genome-wide patterns of gene expression in a wild primate indicate species-specific mechanisms associated with tolerance to natural simian immunodeficiency virus infection

Over 40 species of nonhuman primates host simian immunodeficiency viruses (SIVs). In natural hosts, infection is generally assumed to be nonpathogenic due to a long coevolutionary history between host and virus, although pathogenicity is difficult to study in wild nonhuman primates. We used whole-blood RNA-seq and SIV prevalence from 29 wild Ugandan red colobus (Piliocolobus tephrosceles) to assess the effects of SIV infection on host gene expression in wild, naturally SIV-infected primates. We found no evidence for chronic immune activation in infected individuals, suggesting that SIV is not immunocompromising in this species, in contrast to HIV in humans. Notably, an immunosuppressive gene, CD101, was upregulated in infected individuals. This gene has not been previously described in the context of nonpathogenic SIV infection. This expands the known variation associated with SIV infection in natural hosts, and may suggest a novel mechanism for tolerance of SIV infection in the Ugandan red colobus.

genomics↗

bioRxiv2018

Comparative genomic analysis revealed rapid differentiation in the pathogenicity-related gene repertoires between Pyricularia oryzae and Pyricularia penniseti isolated from a Pennisetum grass

BackgroundsPyricularia is a multispecies complex that could infect and cause severe blast disease on diverse hosts, including rice, wheat and many other grasses. Although the genome size of this fungal complex is small [~40 Mbp for Pyricularia oryzae (syn. Magnaporthe oryzae), and ~45 Mbp for P. grisea], the genome plasticity allows the fungus to jump and adapt to new hosts. Therefore, deciphering the genome basis of individual species could facilitate the evolutionary and genetic study of this fungus. However, except for the P. oryzae subgroup, many other species isolated from diverse hosts, such as the Pennisetum grasses, remain largely uncovered genetically.\n\nResultsHere, we report the genome sequence of a pyriform-shaped fungal strain P. penniseti P1609 isolated from a Pennisetum grass (JUJUNCAO) using PacBio SMRT sequencing technology. We performed a phylogenomic analysis of 28 Magnaporthales species and 5 non-Magnaporthales species and addressed P1609 into a Pyricularia subclade that is distant from P. oryzae. Comparative genomic analysis revealed that the pathogenicity-related gene repertoires were fairly different between P1609 and the P. oryzae strain 70-15, including the cloned avirulence genes, other putative secreted proteins, as well as some other predicted Pathogen-Host Interaction (PHI) genes. Genomic sequence comparison also identified many genomic rearrangements.\n\nConclusionTaken together, our results suggested that the genomic sequence of the P. penniseti P1609 could be a useful resource for the genetic study of the Pennisetum-infecting Pyricularia species.

genomics↗

bioRxiv2018

PRL-1 is required for neuroprotection against olfactory CO2 stimulation in Drosophila

The Mammalian phosphatase of regenerating liver (PRL) family is primarily recognized for its oncogenic properties. Here we found that in Drosophila, loss of prl-1 resulted in CO2-induced brain disorder presented as irreversible wing hold up with enhancement of Ca2+ responses at the neuron synaptic terminals. Overexpression of Prl-1 in the nervous system could rescue the mutant phenotype. We show that Prl-1 is particularly expressed in CO2-responsive neural circuit and the higher brain centers. Ablation of the CO2 olfactory receptor, Gr21a, suppressed the mutant phenotype, suggesting that CO2 acts as a neuropathological substrate in absence of Prl-1. Further studies found that the wing hold up is an obvious consequence upon knockdown of Uex, a magnesium transporter, which directly interacts with Prl-1. Conditional expression of Uex in the nervous system could rescue the phenotype of prl-1 mutants. We demonstrate that Uex acts genetically downstream of Prl-1. Our findings provide important insights into mechanisms of Prl-1 protection against olfactory CO2 stimulation induced brain disorder at the level of detailed neural circuits and functional molecular connections.

neuroscience↗

bioRxiv2018

Recovered and dead outcome patients caused by influenza A (H7N9) virus infection show different pro-inflammatory cytokine dynamics during disease progress and its application in real-time prognosis

The persistent circulation of influenza A(H7N9) virus within poultry markets and human society leads to sporadic epidemics of influenza infections. Severe pneumonia and acute respiratory distress syndrome (ARDS) caused by the virus lead to high morbidity and mortality rates in patients. Hyper induction of pro-inflammatory cytokines, which is known as \"cytokine storm\", is closely related to the process of viral infection. However, systemic analyses of H7N9 induced cytokine storm and its relationship with disease progress need further illuminated. In our study we collected 75 samples from 24 clinically confirmed H7N9-infected patients at different time points after hospitalization. Those samples were divided into three groups, which were mild, severe and fatal groups, according to disease severity and final outcome. Human cytokine antibody array was performed to demonstrate the dynamic profile of 80 cytokines and chemokines. By comparison among different prognosis groups and time series, we provide a more comprehensive insight into the hypercytokinemia caused by H7N9 influenza virus infection. Different dynamic changes of cytokines/chemokines were observed in H7N9 infected patients with different severity. Further, 33 cytokines or chemokines were found to be correlated with disease development and 11 of them were identified as potential therapeutic targets. Immuno-modulate the cytokine levels of IL-8, IL-10, BLC, MIP-3a, MCP-1, HGF, OPG, OPN, ENA-78, MDC and TGF-{beta} 3 are supposed to be beneficial in curing H7N9 infected patients. Apart from the identification of 35 independent predictors for H7N9 prognosis, we further established a real-time prediction model with multi-cytokine factors for the first time based on maximal relevance minimal redundancy method, and this model was proved to be powerful in predicting whether the H7N9 infection was severe or fatal. It exhibited promising application in prognosing the outcome of a H7N9 infected patients and thus help doctors take effective treatment strategies accordingly.

immunology↗

bioRxiv2018

Enterovirus 71 structural viral protein 1 promotes mouse Schwann cell autophagy via endoplasmic reticulum stress-mediated peripheral myelin protein 22 upregulation

Enterovirus 71 (EV71) accounts for the majority of hand, foot and mouth disease-related deaths due to fatal neurological complications. The clinical observations and animal models found the early invasion of nervous system, and the demyelinating phenomenon was observed. As one of the receptors of EV71 structural viral protein 1 (VP1), SCARB2 mainly exists on the myelin sheath. EV71 VP1 can promote viral replication through inducing autophagy in neuron cells. This study aims to investigate the role and mechanism of VP1 in autophagy of mouse Schwann cells (MSCs). An EV71 VP1-expressing vector (pEGFP-C3-VP1) was generated and transfected into MSCs. Transmission electron microscopy (TEM) and Western blot analysis of the autophagy marker microtubule-associated proteins 1A/1B light chain 3B (LC3B) were used to assess autophagy in the cells. Real-time PCR and immunofluorescent staining were performed to determine the expression of PMP22. Small interfering RNA against PMP22 was employed to investigate the role of PMP22 in MSCs autophagy. Selective endoplasmic reticulum (ER) stress inhibitor salubrinal (SAL) was employed to determine whether PMP22 is mediated by ER stress. Our results demonstrated that VP1 played a promotive role in MSC autophagy. Overexpression of VP1 upregulated PMP22. PMP22 deficiency downregulated LC3B and thus inhibited autophagy. Furthermore, PMP22 expression was significantly suppressed by SAL. VP1 promotes MSC autophagy through upregulating ER stress-mediated PMP22 expression. VP1/ER stress/ PMP22 axis in autophagy may be a potential therapeutic target for EV71 infection-induced fatal neuronal damage.

cell biology↗

bioRxiv2018

Novel organelle anion channels formed by chromogranin B drive normal granule maturation in endocrine cells

All endocrine cells need an anion conductance for maturation of secretory granules. Identity of this family of anion channels has been elusive for forty years. We now show that a family of granule protein, CHGB, serves the long-sought conductance. CHGB interacts with membranes through two amphipathic helices, and forms a chloride channel with large conductance and high anion selectivity. Fast kinetics and high cooperativity suggest that CHGB tetramerizes to form a functional channel. Nonfunctional mutants separate CHGBs function in granule maturation from that in granule biogenesis. In neuroendocrine cells, CHGB channel and a H+-ATPase drives normal insulin maturation inside or dopamine loading into secretory granules. CHGBs tight membrane-association after exocytotic release of secretory granules separates its intracellular function from extracellular functions of its proteolytic peptides. CHGB-null mice show consistent impairment of granule acidification in pancreatic beta-cells. These findings together support that the phylogenetically conserved CHGB proteins constitute a new family of organelle chloride channels in the regulated secretory pathway among various endocrine cells.

cell biology↗

bioRxiv2018

Multi-hierarchical Profiling the Structure-Activity Relationships of Engineered Nanomaterials at Nano-Bio Interfaces

Increasingly raised concerns (nanotoxicity, clinical translation, etc) on nanotechnology require breakthroughs in structure-activity relationship (SAR) analyses of engineered nanomaterials (ENMs) at nano-bio interfaces. However, current nano-SAR assessments failed to disclosure sufficient information to understand ENM-induced bio-effects. Here we developed a multi-hierarchical nano-SAR assessment for a representative ENM, Fe2O3 by systematically examining cellular metabolite and protein changes. This nano-SAR profile allows visualizing the contributions of 7 basal properties of Fe2O3 to their diverse bio-effects. For instance, while surface reactivity is responsible for Fe2O3-induced cell migration, the inflammatory effects of Fe2O3 nanorods and nanoplates are determined by their aspect ratio and surface reactivity, respectively. We further discovered the detailed mechanisms, including NLRP3 inflammasome pathway and monocyte chemoattractant protein-1 involved signaling. Both effects were further validated in animal lungs. Our findings provide substantial new insights at nano-bio interfaces, which may facilitate the tailored design of ENMs to endow them with desired bio-effects.

pharmacology and toxicology↗

bioRxiv2018

YAP1 Oncogene is a Context-specific Driver for Pancreatic Ductal Adenocarcinoma

AbstractTranscriptomic profiling classifies pancreatic ductal adenocarcinoma (PDAC) into several molecular subtypes with distinctive histological and clinical characteristics. However, little is known about the molecular mechanisms that define each subtype and their correlation with clinical outcome. Mutant KRAS is the most prominent driver in PDAC, present in over 90% of tumors, but the dependence of tumors on oncogenic KRAS signaling varies between subtypes. In particular, squamous subtype are relatively independent of oncogenic KRAS signaling and typically display much more aggressive clinical behavior versus progenitor subtype. Here, we identified that YAP1 activation is enriched in the squamous subtype and associated with poor prognosis. Activation of YAP1 in progenitor subtype cancer cells profoundly enhanced malignant phenotypes and transformed progenitor subtype cells into squamous subtype. Conversely, depletion of YAP1 specifically suppressed tumorigenicity of squamous subtype PDAC cells. Mechanistically, we uncovered a significant positive correlation between WNT5A expression and the YAP1 activity in human PDAC, and demonstrated that WNT5A overexpression led to YAP1 activation and recapitulated YAP1-dependent but Kras-independent phenotype of tumor progression and maintenance. Thus, our study identifies YAP1 oncogene as a major driver of squamous subtype PDAC and uncovers the role of WNT5A in driving PDAC malignancy through activation of the YAP pathway.

cancer biology↗

bioRxiv2018

Template switching causes artificial junction formation and false identification of circular RNAs

Hundreds of thousands of putative circular RNAs have been identified through deep sequencing and bioinformatic analyses. However, the circularity of these putative RNA circles has not been experimentally validated due to limited methodologies currently available. We reported here that the template-switching capability of commonly used reverse transcriptases (e.g., SuperScript II) leads to the formation of artificial junction sequences, and consequently misclassification of large linear RNAs as RNA circles. Use of reverse transcriptases without terminal transferase activity (e.g., MonsterScript) for cDNA synthesis is critical for the identification of physiological circular RNAs. We also report two methods, MonsterScript junction PCR and high-resolution melting curve analyses, which can reliably distinguish circular RNAs from their linear forms and thus, can be used to discover and validate true circular RNAs.\n\nSignificance StatementThe vast majority of circular RNAs were identified through computational detection of junction sequences in the deep sequencing reads because these unique fusion sequences represent back-splicing events. We found that artificial junction sequences could be formed through template switching (TS) when MMLV-derived reverse transcriptases, e.g., SuperScript II, are used to synthesize cDNAs. Thus, many of the reported circular RNAs may not be RNA circles, but rather experimental artifacts. Fake circular RNAs can be avoided by using reverse transcriptases without terminal transferase activity (e.g., MonsterScript) for cDNA synthesis. We developed two novel methods, MonsterScript junction PCR and high-resolution melting curve analyses, for distinguishing circular RNAs from their linear form.

molecular biology↗

bioRxiv2018

Benchmark of lncRNA Quantification for RNA-Seq of Cancer Samples

Long non-coding RNAs (lncRNAs) emerge as important regulators of various biological processes. Many lncRNAs with tumor-suppressor or oncogenic functions in cancer have been discovered. While many studies have exploited public resources such as RNA-Seq data in The Cancer Genome Atlas (TCGA) to study lncRNAs in cancer, it is crucial to choose the optimal method for accurate expression quantification of lncRNAs. In this benchmarking study, we compared the performance of pseudoalignment methods Kallisto and Salmon, and alignment-based methods HTSeq, featureCounts, and RSEM, in lncRNA quantification, by applying them to a simulated RNA-Seq dataset and a pan-cancer RNA-Seq dataset from TCGA. We observed that full transcriptome annotation, including both protein coding and noncoding RNAs, greatly improves the specificity of lncRNA expression quantification. Pseudoalignment-based methods detect more lncRNAs than alignment-based methods and correlate highly with simulated ground truth. On the contrary, alignment-based methods tend to underestimate lncRNA expression or even fail to capture lncRNA signal in the ground truth. These underestimated genes include cancer-relevant lncRNAs such as TERC and ZEB2-AS1. Overall, 10-16% of lncRNAs can be detected in the samples, with antisense and lincRNAs the two most abundant categories. A higher proportion of antisense RNAs are detected than lincRNAs. Moreover, among the expressed lncRNAs, more antisense RNAs are discordant from ground truth than lincRNAs when measured by alignment-based methods, indicating that antisense RNAs are more susceptible to mis-quantification. In addition, the lncRNAs with fewer transcripts, less than three exons, and lower sequence uniqueness tend to be more discordant. In summary, pseudoalignment methods Kallisto or Salmon in combination with the full transcriptome annotation is our recommended strategy for RNA-Seq analysis for lncRNAs.\n\nAUTHOR SUMMARYLong non-coding RNAs (lncRNAs) emerge as important regulators of various biological processes. Our benchmarking work on both simulated RNA-Seq dataset and pan-cancer dataset provides timely and useful recommendations for wide research community who are studying lncRNAs, especially for those who are exploring public resources such as TCGA RNA-Seq data. We demonstrate that using full transcriptome annotation in RNA-Seq analysis is strongly recommended as it greatly improves the specificity of lncRNA quantification. Whats more, pseudoalignment methods Kallisto and Salmon outperform alignment-based methods in lncRNA quantification. It is worth noting that the default workflow for TCGA RNA-Seq data stored in Genomic Data Commons (GDC) data portal uses HTSeq, an alignment-based method. Thus, reanalyzing the data might be considered when checking gene expression in TCGA datasets. In summary, pseudoalignment methods Kallisto or Salmon in combination with full transcriptome annotation is our recommended strategy for RNA-Seq analysis for lncRNAs.

bioinformatics↗

bioRxiv2017

The pomegranate (Punica granatum L.) genome provides insights into fruit quality and ovule developmental biology

Pomegranate (Punica granatum L.) with an uncertain taxonomic status has an ancient cultivation history, and has become an emerging fruit due to its attractive features such as the bright red appearance and the high abundance of medicinally valuable ellagitannin-based compounds in its peel and aril. However, the absence of genomic resources has restricted further elucidating genetics and evolution of these interesting traits. Here we report a 274-Mb high-quality draft pomegranate genome sequence, which covers approximately 81.5% of the estimated 336 Mb genome, consists of 2,177 scaffolds with an N50 size of 1.7 Mb, and contains 30,903 genes. Phylogenomic analysis supported that pomegranate belongs to the Lythraceae family rather than the monogeneric Punicaceae family, and comparative analyses showed that pomegranate and Eucalyptus grandis shares the paleotetraploidy event. Integrated genomic and transcriptomic analyses provided insights into the molecular mechanisms underlying the biosynthesis of ellagitannin-based compounds, the color formation in both peels and arils during pomegranate fruit development, and the unique ovule development processes that are characteristic of pomegranate. This genome sequence represents the first reference in Lythraceae, providing an important resource to expand our understanding of some unique biological processes and to facilitate both comparative biology studies and crop breeding.

genomics↗

bioRxiv2017

Assessing Inhibitors Of Mutant Isocitrate Dehydrogenase Using A Suite Of Pre-Clinical Discovery Assays

Isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) are key metabolic enzymes that are mutated in a variety of cancers to confer a gain-of-function activity resulting in the accumulation and secretion of an oncometabolite, D-2-hydroxyglutarate (2-HG). Accumulation of 2-HG can result in epigenetic dysregulation and a block in cellular differentiation, suggesting these mutations play a role in neoplasia. Based on its potential as a cancer target, a number of small molecule inhibitors have been developed to specifically inhibit mutant forms of IDH (mIDH1 and mIDH2). Here, a panel of mIDH inhibitors were systematically profiled using biochemical, cell-based, and tier-one ADME techniques. We quantified the biochemical effect of each inhibitor on mIDH1 (R132H and R132C) and mIDH2 (R172Q). The effect of these inhibitors on 2-HG concentrations in seven cell lines representing five different IDH1 mutations in both 2D and 3D cell cultures was assessed. Target engagement of these inhibitors was analyzed utilizing cellular thermal shift assays (CETSA), the effects of inhibitors on reversing 2-HG-induced block on leukemic cellular differentiation. We conclude from our mIDH1 assay panel that AG-120 and a Novartis inhibitor exhibited excellent activity in all biochemical and most cellular assays. While AG-120 has superior DMPK properties, it lacks efficacy a leukemic differentiation model. In conclusion, we present a comprehensive suite of in vitro preclinical drug development assays that can be used as a tool-box to identify lead compounds for mIDH drug discovery programs, as well as what we believe is the most comprehensive publically available dataset on the top mIDH inhibitors.

cancer biology↗

bioRxiv2017

RET Ligands Mediate Endocrine Sensitivity via a Bi-stable Feedback Loop with ERα

The RET tyrosine kinase signaling pathway is involved in the development of endocrine resistant ER+ breast cancer. However, the expression of the RET receptor itself has not been directly linked to clinical cases of resistance, suggesting that additional factors are involved. We show that both ER+ endocrine resistant and sensitive breast cancers have functional RET tyrosine kinase signaling pathway, but that endocrine sensitive breast cancer cells lack RET ligands that are necessary to drive endocrine resistance. Transcription of one RET ligand, GDNF, is necessary and sufficient to confer resistance in the ER+ MCF-7 cell line. In patients, RET ligand expression predicts responsiveness to endocrine therapies and correlates with survival. Collectively, our findings show that ER+ tumor cells are \"poised\" for RET mediated endocrine resistance, expressing all components of the RET signaling pathway, but endocrine sensitive cells lack high expression of RET ligands that are necessary to initiate the resistance phenotype.

cancer biology↗

bioRxiv2016

Acidic pH-dependent depletion of Mycobacterium tuberculosis thiol pools potentiates antibiotics and oxidizing agents

Mycobacterium tuberculosis (Mtb) must sense and adapt to immune pressures such as acidic pH and reactive oxygen species (ROS) during pathogenesis. The goal of this study was to isolate compounds that inhibit acidic pH resistance, thus defining virulence pathways that are vulnerable to chemotherapy. Here we report that the acidic pH-dependent compound AC2P36 depletes intracellular thiol pools, sensitizes Mtb to killing by acidic pH, and potentiates the bactericidal activity of isoniazid, clofazimine, and oxidizing agents. We show that the pHdependent activity of AC2P36 is associated with metabolic stress at acidic pH and a pHdependent accumulation of intracellular ROS. Mechanism of action studies show that AC2P36 directly depletes Mtb thiol pools. These data support a model where chemical depletion of Mtb thiol pools at acidic pH enhances sensitivity to oxidative damage, resulting in bacterial killing and potentiation of antibiotics.

microbiology↗