Transient Receptor Potential Ankyrin 1 Ion Channel Is Expressed in Osteosarcoma and Its Activation Reduces Viability.

Osteosarcoma is a highly malignant, painful cancer with poor treatment opportunities and a bad prognosis. Transient receptor potential ankyrin 1 (TRPA1) and vanilloid 1 (TRPV1) receptors are non-selective cation channels that have been of great interest in cancer, as their expression is increased in some malignancies. In our study we aim to characterize the expression and functionality of the TRPA1 and TRPV1 channels in human and mouse osteosarcoma tissues and in a mouse cell line. TRPA1/Trpa1 and TRPV1/Trpv1 mRNA expressions were demonstrated by PCR gel electrophoresis and RNAscope in situ hybridization. The function of these channels was confirmed by their radioactive 45Ca2+ uptake in response to the TRPA1 agonist, Allyl-isothiocyanate (AITC), and TRPV1 agonist, capsaicin, in K7M2 cells. An ATP-based K2M7 cell viability luminescence assay was used to determine cell viability after AITC or capsaicin treatments. Both TRPA1/Trpa1 and TRPV1/Trpv1 were expressed similarly in human and mouse osteosarcoma tissues, while Trpa1 transcripts were more abundantly present in K7M2 cells. TRPA1 activation with 200 µM AITC induced a significant 45Ca2+ influx into K7M2 cells, and the antagonist attenuated this effect. In accordance with the lower Trpv1 expression, capsaicin induced a moderate 45Ca2+ uptake, which did not reach the level of statistical significance. Both AITC and capsaicin significantly reduced K7M2 cell viability, demonstrating EC50 values of 22 µM and 74 µM. The viability-decreasing effect of AITC was significantly but only partially antagonized by HC-030031, but the action of capsaicin was not affected by the TRPV1 antagonist capsazepine. We provide here the first data on the functional expression of the TRPA1 and TRPV1 ion channels in osteosarcoma, suggesting novel diagnostic and/or therapeutic perspectives.

Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation - A meta-analysis.

BACKGROUND: Although interest in the role of extracellular vesicles (EV) in oncology is growing, not all potential aspects have been investigated. In this meta-analysis, data regarding (i) the EV proteome and (ii) the invasion and proliferation capacity of the NCI-60 tumor cell lines (60 cell lines from nine different tumor types) were analyzed using machine learning methods. METHODS: On the basis of the entire proteome or the proteins shared by all EV samples, 60 cell lines were classified into the nine tumor types using multiple logistic regression. Then, utilizing the Least Absolute Shrinkage and Selection Operator, we constructed a discriminative protein panel, upon which the samples were reclassified and pathway analyses were performed. These panels were validated using clinical data (n = 4,665) from Human Protein Atlas. RESULTS: Classification models based on the entire proteome, shared proteins, and discriminative protein panel were able to distinguish the nine tumor types with 49.15%, 69.10%, and 91.68% accuracy, respectively. Invasion and proliferation capacity of the 60 cell lines were predicted with R2 = 0.68 and R2 = 0.62 (p < 0.0001). The results of the Reactome pathway analysis of the discriminative protein panel suggest that the molecular content of EVs might be indicative of tumor-specific biological processes. CONCLUSION: Integrating in vitro EV proteomic data, cell physiological characteristics, and clinical data of various tumor types illuminates the diagnostic, prognostic, and therapeutic potential of EVs. Video Abstract.

Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2.

We present a miniaturized immunofluorescence assay (mini-IFA) for measuring antibody response in patient blood samples. The method utilizes machine learning-guided image analysis and enables simultaneous measurement of immunoglobulin M (IgM), IgA, and IgG responses against different viral antigens in an automated and high-throughput manner. The assay relies on antigens expressed through transfection, enabling use at a low biosafety level and fast adaptation to emerging pathogens. Using severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as the model pathogen, we demonstrate that this method allows differentiation between vaccine-induced and infection-induced antibody responses. Additionally, we established a dedicated web page for quantitative visualization of sample-specific results and their distribution, comparing them with controls and other samples. Our results provide a proof of concept for the approach, demonstrating fast and accurate measurement of antibody responses in a research setup with prospects for clinical diagnostics.

MMP-9 as Prognostic Marker for Brain Tumours: A Comparative Study on Serum-Derived Small Extracellular Vesicles.

Matrix metalloproteinase-9 (MMP-9) degrades the extracellular matrix, contributes to tumour cell invasion and metastasis, and its elevated level in brain tumour tissues indicates poor prognosis. High-risk tissue biopsy can be replaced by liquid biopsy; however, the blood-brain barrier (BBB) prevents tumour-associated components from entering the peripheral blood, making the development of blood-based biomarkers challenging. Therefore, we examined the MMP-9 content of small extracellular vesicles (sEVs)-which can cross the BBB and are stable in body fluids-to characterise tumours with different invasion capacity. From four patient groups (glioblastoma multiforme, brain metastases of lung cancer, meningioma, and lumbar disc herniation as controls), 222 serum-derived sEV samples were evaluated. After isolating and characterising sEVs, their MMP-9 content was measured by ELISA and assessed statistically (correlation, paired t-test, Welch's test, ANOVA, ROC). We found that the MMP-9 content of sEVs is independent of gender and age, but is affected by surgical intervention, treatment, and recurrence. We found a relation between low MMP-9 level in sEVs (<28 ppm) and improved survival (8-month advantage) of glioblastoma patients, and MMP-9 levels showed a positive correlation with aggressiveness. These findings suggest that vesicular MMP-9 level might be a useful prognostic marker for brain tumours.

Impact of Experimental Conditions on Extracellular Vesicles' Proteome: A Comparative Study.

Extracellular vesicle (EV) research is a rapidly developing field, mainly due to the key role of EVs in intercellular communication and pathophysiological processes. However, the heterogeneity of EVs challenges their exploration and the establishment of gold-standard methods. Here, we aimed to reveal the influence of technical changes on EV biology and the reliability of experimental data. We used B16F1 melanoma cells as a model and applied nanoparticle tracking analysis, mass spectrometry (LC-MS/MS) and pathway enrichment analysis to analyze the quantity, size distribution, proteome and function of their small EVs (sEVs) produced in sEV-depleted fetal bovine serum (FBS)-containing medium or serum-free medium. Additionally, we investigated the effects of minor technical variances on the quality of sEV preparations. We found that storage of the isolates at -80 °C has no adverse effect on LC-MS/MS analysis, and an additional washing step after differential ultracentrifugation has a minor influence on the sEV proteome. In contrast, FBS starvation affects the production and proteome of sEVs; moreover, these vesicles may have a greater impact on protein metabolism, but a smaller impact on cell adhesion and membrane raft assembly, than the control sEVs. As we demonstrated that FBS starvation has a strong influence on sEV biology, applying serum-free conditions might be considered in in vitro sEV studies.

The role of the metabolite cargo of extracellular vesicles in tumor progression.

Metabolomic reprogramming in tumor and stroma cells is a hallmark of cancer but understanding its effects on the metabolite composition and function of tumor-derived extracellular vesicles (EVs) is still in its infancy. EVs are membrane-bound sacs with a complex molecular composition secreted by all living cells. They are key mediators of intercellular communication both in normal and pathological conditions and play a crucial role in tumor development. Although lipids are major components of EVs, most of the EV cargo studies have targeted proteins and nucleic acids. The potential of the EV metabolome as a source for biomarker discovery has gained recognition recently, but knowledge on the biological activity of tumor EV metabolites still remains limited. Therefore, we aimed (i) to compile the list of metabolites identified in tumor EVs isolated from either clinical specimens or in vitro samples and (ii) describe their role in tumor progression through literature search and pathway analysis.

MISpheroID: a knowledgebase and transparency tool for minimum information in spheroid identity.

Spheroids are three-dimensional cellular models with widespread basic and translational application across academia and industry. However, methodological transparency and guidelines for spheroid research have not yet been established. The MISpheroID Consortium developed a crowdsourcing knowledgebase that assembles the experimental parameters of 3,058 published spheroid-related experiments. Interrogation of this knowledgebase identified heterogeneity in the methodological setup of spheroids. Empirical evaluation and interlaboratory validation of selected variations in spheroid methodology revealed diverse impacts on spheroid metrics. To facilitate interpretation, stimulate transparency and increase awareness, the Consortium defines the MISpheroID string, a minimum set of experimental parameters required to report spheroid research. Thus, MISpheroID combines a valuable resource and a tool for three-dimensional cellular models to mine experimental parameters and to improve reproducibility.

SpheroidPicker for automated 3D cell culture manipulation using deep learning.

Recent statistics report that more than 3.7 million new cases of cancer occur in Europe yearly, and the disease accounts for approximately 20% of all deaths. High-throughput screening of cancer cell cultures has dominated the search for novel, effective anticancer therapies in the past decades. Recently, functional assays with patient-derived ex vivo 3D cell culture have gained importance for drug discovery and precision medicine. We recently evaluated the major advancements and needs for the 3D cell culture screening, and concluded that strictly standardized and robust sample preparation is the most desired development. Here we propose an artificial intelligence-guided low-cost 3D cell culture delivery system. It consists of a light microscope, a micromanipulator, a syringe pump, and a controller computer. The system performs morphology-based feature analysis on spheroids and can select uniform sized or shaped spheroids to transfer them between various sample holders. It can select the samples from standard sample holders, including Petri dishes and microwell plates, and then transfer them to a variety of holders up to 384 well plates. The device performs reliable semi- and fully automated spheroid transfer. This results in highly controlled experimental conditions and eliminates non-trivial side effects of sample variability that is a key aspect towards next-generation precision medicine.

Cell lines and clearing approaches: a single-cell level 3D light-sheet fluorescence microscopy dataset of multicellular spheroids.

Nowadays, three dimensional (3D) cell cultures are widely used in the biological laboratories and several optical clearing approaches have been proposed to visualize individual cells in the deepest layers of cancer multicellular spheroids. However, defining the most appropriate clearing approach for the different cell lines is an open issue due to the lack of a gold standard quantitative metric. In this article, we describe and share a single-cell resolution 3D image dataset of human carcinoma spheroids imaged using a light-sheet fluorescence microscope. The dataset contains 90 multicellular cancer spheroids derived from 3 cell lines (i.e. T-47D, 5-8F, and Huh-7D12) and cleared with 5 different protocols, precisely ClearT, ClearT2, CUBIC, ScaleA2, and Sucrose. To evaluate image quality and light penetration depth of the cleared 3D samples, all the spheroids have been imaged under the same experimental conditions, labelling the nuclei with the DRAQ5 stain and using a Leica SP8 Digital LightSheet microscope. The clearing quality of this dataset was annotated by 10 independent experts and thus allows microscopy users to qualitatively compare the effects of different optical clearing protocols on different cell lines. It is also an optimal testbed to quantitatively assess different computational metrics evaluating the image quality in the deepest layers of the spheroids.

Raman Spectral Signatures of Serum-Derived Extracellular Vesicle-Enriched Isolates May Support the Diagnosis of CNS Tumors.

Investigating the molecular composition of small extracellular vesicles (sEVs) for tumor diagnostic purposes is becoming increasingly popular, especially for diseases for which diagnosis is challenging, such as central nervous system (CNS) malignancies. Thorough examination of the molecular content of sEVs by Raman spectroscopy is a promising but hitherto barely explored approach for these tumor types. We attempt to reveal the potential role of serum-derived sEVs in diagnosing CNS tumors through Raman spectroscopic analyses using a relevant number of clinical samples. A total of 138 serum samples were obtained from four patient groups (glioblastoma multiforme, non-small-cell lung cancer brain metastasis, meningioma and lumbar disc herniation as control). After isolation, characterization and Raman spectroscopic assessment of sEVs, the Principal Component Analysis-Support Vector Machine (PCA-SVM) algorithm was performed on the Raman spectra for pairwise classifications. Classification accuracy (CA), sensitivity, specificity and the Area Under the Curve (AUC) value derived from Receiver Operating Characteristic (ROC) analyses were used to evaluate the performance of classification. The groups compared were distinguishable with 82.9-92.5% CA, 80-95% sensitivity and 80-90% specificity. AUC scores in the range of 0.82-0.9 suggest excellent and outstanding classification performance. Our results support that Raman spectroscopic analysis of sEV-enriched isolates from serum is a promising method that could be further developed in order to be applicable in the diagnosis of CNS tumors.

A quantitative metric for the comparative evaluation of optical clearing protocols for 3D multicellular spheroids.

3D multicellular spheroids quickly emerged as in vitro models because they represent the in vivo tumor environment better than standard 2D cell cultures. However, with current microscopy technologies, it is difficult to visualize individual cells in the deeper layers of 3D samples mainly because of limited light penetration and scattering. To overcome this problem several optical clearing methods have been proposed but defining the most appropriate clearing approach is an open issue due to the lack of a gold standard metric. Here, we propose a guideline for 3D light microscopy imaging to achieve single-cell resolution. The guideline includes a validation experiment focusing on five optical clearing protocols. We review and compare seven quality metrics which quantitatively characterize the imaging quality of spheroids. As a test environment, we have created and shared a large 3D dataset including approximately hundred fluorescently stained and optically cleared spheroids. Based on the results we introduce the use of a novel quality metric as a promising method to serve as a gold standard, applicable to compare optical clearing protocols, and decide on the most suitable one for a particular experiment.

Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS Tumors.

Liquid biopsy-based methods to test biomarkers (e.g., serum proteins and extracellular vesicles) may help to monitor brain tumors. In this proteomics-based study, we aimed to identify a characteristic protein fingerprint associated with central nervous system (CNS) tumors. Overall, 96 human serum samples were obtained from four patient groups, namely glioblastoma multiforme (GBM), non-small-cell lung cancer brain metastasis (BM), meningioma (M) and lumbar disc hernia patients (CTRL). After the isolation and characterization of small extracellular vesicles (sEVs) by nanoparticle tracking analysis (NTA) and atomic force microscopy (AFM), liquid chromatography -mass spectrometry (LC-MS) was performed on two different sample types (whole serum and serum sEVs). Statistical analyses (ratio, Cohen's d, receiver operating characteristic; ROC) were carried out to compare patient groups. To recognize differences between the two sample types, pairwise comparisons (Welch's test) and ingenuity pathway analysis (IPA) were performed. According to our knowledge, this is the first study that compares the proteome of whole serum and serum-derived sEVs. From the 311 proteins identified, 10 whole serum proteins and 17 sEV proteins showed the highest intergroup differences. Sixty-five proteins were significantly enriched in sEV samples, while 129 proteins were significantly depleted compared to whole serum. Based on principal component analysis (PCA) analyses, sEVs are more suitable to discriminate between the patient groups. Our results support that sEVs have greater potential to monitor CNS tumors, than whole serum.

Potent Chimeric Antimicrobial Derivatives of the Medicago truncatula NCR247 Symbiotic Peptide.

In Rhizobium-legume symbiosis, the bacteria are converted into nitrogen-fixing bacteroids. In many legume species, differentiation of the endosymbiotic bacteria is irreversible, culminating in definitive loss of their cell division ability. This terminal differentiation is mediated by plant peptides produced in the symbiotic cells. In Medicago truncatula more than ∼700 nodule-specific cysteine-rich (NCR) peptides are involved in this process. We have shown previously that NCR247 and NCR335 have strong antimicrobial activity on various pathogenic bacteria and identified interaction of NCR247 with many bacterial proteins, including FtsZ and several ribosomal proteins, which prevent bacterial cell division and protein synthesis. In this study we designed and synthetized various derivatives of NCR247, including shorter fragments and various chimeric derivatives. The antimicrobial activity of these peptides was tested on the ESKAPE bacteria; Enterococcus faecalis, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Escherichia coli as a member of Enterobacteriaceae and in addition Listeria monocytogenes and Salmonella enterica. The 12 amino acid long C-terminal half of NCR247, NCR247C partially retained the antimicrobial activity and preserved the multitarget interactions with partners of NCR247. Nevertheless NCR247C became ineffective on S. aureus, P. aeruginosa, and L. monocytogenes. The chimeric derivatives obtained by fusion of NCR247C with other peptide fragments and particularly with a truncated mastoparan sequence significantly increased bactericidal activity and altered the antimicrobial spectrum. The minimal bactericidal concentration of the most potent derivatives was 1.6 µM, which is remarkably lower than that of most classical antibiotics. The killing activity of the NCR247-based chimeric peptides was practically instant. Importantly, these peptides had no hemolytic activity or cytotoxicity on human cells. The properties of these NCR derivatives make them promising antimicrobials for clinical use.

Melanoma-Derived Exosomes Induce PD-1 Overexpression and Tumor Progression via Mesenchymal Stem Cell Oncogenic Reprogramming.

Recently, it has been described that programmed cell death protein 1 (PD-1) overexpressing melanoma cells are highly aggressive. However, until now it has not been defined which factors lead to the generation of PD-1 overexpressing subpopulations. Here, we present that melanoma-derived exosomes, conveying oncogenic molecular reprogramming, induce the formation of a melanoma-like, PD-1 overexpressing cell population (mMSCPD-1+) from naïve mesenchymal stem cells (MSCs). Exosomes and mMSCPD-1+ cells induce tumor progression and expression of oncogenic factors in vivo. Finally, we revealed a characteristic, tumorigenic signaling network combining the upregulated molecules (e.g., PD-1, MET, RAF1, BCL2, MTOR) and their upstream exosomal regulating proteins and miRNAs. Our study highlights the complexity of exosomal communication during tumor progression and contributes to the detailed understanding of metastatic processes.

Small extracellular vesicles convey the stress-induced adaptive responses of melanoma cells.

Exosomes are small extracellular vesicles (sEVs), playing a crucial role in the intercellular communication in physiological as well as pathological processes. Here, we aimed to study whether the melanoma-derived sEV-mediated communication could adapt to microenvironmental stresses. We compared B16F1 cell-derived sEVs released under normal and stress conditions, including cytostatic, heat and oxidative stress. The miRNome and proteome showed substantial differences across the sEV groups and bioinformatics analysis of the obtained data by the Ingenuity Pathway Analysis also revealed significant functional differences. The in silico predicted functional alterations of sEVs were validated by in vitro assays. For instance, melanoma-derived sEVs elicited by oxidative stress increased Ki-67 expression of mesenchymal stem cells (MSCs); cytostatic stress-resulted sEVs facilitated melanoma cell migration; all sEV groups supported microtissue generation of MSC-B16F1 co-cultures in a 3D tumour matrix model. Based on this study, we concluded that (i) molecular patterns of tumour-derived sEVs, dictated by the microenvironmental conditions, resulted in specific response patterns in the recipient cells; (ii) in silico analyses could be useful tools to predict different stress responses; (iii) alteration of the sEV-mediated communication of tumour cells might be a therapy-induced host response, with a potential influence on treatment efficacy.

SerpinB2 is involved in cellular response upon UV irradiation.

Ultraviolet light induced pyrimidine dimer is a helix distortion DNA damage type, which recruits repair complexes. However, proteins of these complexes that take part in both DNA damage recognition and repair have been well-described, the regulation of the downstream steps of nucleotide excision repair (NER) have not been clearly clarified yet. In a high-throughput screen, we identified SerpinB2 (SPB2) as one of the most dramatically upregulated gene in keratinocytes following UV irradiation. We found that both the mRNA and the protein levels of SPB2 were increased upon UV irradiation in various cell lines. Additionally, UV damage induced translocation of SPB2 from the cytoplasm to the nucleus as well as the damage induced foci formation of it. Here we show that SPB2 co-localizes with XPB involved in the NER pathway at UV-induced repair foci. Finally, we demonstrated that UV irradiation promoted the association of SPB2 with ubiquitylated proteins. In basal cell carcinoma tumour cells, we identified changes in the subcellular localization of SPB2. Based on our results, we conclude that SPB2 protein has a novel role in UV-induced NER pathway, since it regulates the removal of the repair complex from the damaged site leading to cancerous malformation.

Chicken or the Egg: Microbial Alterations in Biopsy Samples of Patients with Oral Potentially Malignant Disorders.

Oral carcinogenesis often leads to the alteration of the microbiota at the site of the tumor, but data are scarce regarding the microbial communities of oral potentially malignant disorders (OPMDs). Punch biopsies were taken from healthy and non-healthy mucosa of OPMD patients to analyze the microbiome using metagenome sequencing. In healthy oral mucosa biopsies the bacterial phyla Firmicutes, Fusobacteria, Proteobacteria, Actinobacteria and Bacteroidetes were detected by Ion Torrent sequencing. The same phyla as well as the phyla Fibrobacteres and Spirochaetes were present in the OPMD biopsies. On the species level, there were 10 bacterial species unique to the healthy tissue and 35 species unique to the OPMD lesions whereas eight species were detected in both samples. We observed that the relative abundance of Streptococcus mitis decreased in the OPMD lesions compared to the uninvolved tissue. In contrast, the relative abundance of Fusobacterium nucleatum, implicated in carcinogenesis, was elevated in OPMD. We detected markedly increased bacterial diversity in the OPMD lesions compared to the healthy oral mucosa. The ratio of S. mitis and F. nucleatum are characteristically altered in the OPMD lesions compared to the healthy mucosa.

Prevalence and genotypes of human papillomavirus in saliva and tumor samples of head and neck cancer patients in Hungary.

In addition to traditional risk factors such as smoking, alcohol consumption and betel nut use, human papillomavirus (HPV) infection also plays a role in the development of head and neck squamous cell carcinomas (HNSCCs). Although among European countries the highest incidence and mortality rates of head and neck cancer types were recorded in Hungary, data regarding HPV prevalence in HNSCCs is scarce. We collected biopsy and saliva samples from patients diagnosed with HNSCC or oral potentially malignant disorders (OPMDs) and tested them for the presence of HPV using the PCR consensus primer set MY09/11 and the GP5+/6+ primer pair. HPV genotypes were assessed by sequencing of the amplified PCR fragments. Oral mucosa and saliva samples from tumor- and OPMD-free individuals were also analysed. HPV was detected in 11 out of 60 HNSCC samples (18%). All of the HPV positive tumors carried HPV type 16. 5 out of the 57 saliva samples collected from HNSCC patients was HPV positive (8.8%); among them, in addition to HPV16, HPV13 was also detected. Tumors located to the oropharynx had the highest HPV positivity rate with 50% (7 out of 14), which was significantly higher than the HPV prevalence in oral mucosa samples collected from controls (0 out of 20; p > 0.001) or in OPMD biopsies (0 out of 21, p > 0.001). 2 out of 57 control saliva samples (3.5%, subtype HPV13 and 11) and 3 out of 39 saliva samples from OPMD patients (7.7%, subtype HPV18, 81 and 10) were HPV positive. Our data suggested that HPV16 infection may contribute, in concert with cigarette smoking, to the development of a subset of head and neck cancers in Hungary. HPV16 infection per se does not account, however, for the high HNSCC incidence rate recorded in this country.

Advanced Cell Classifier: User-Friendly Machine-Learning-Based Software for Discovering Phenotypes in High-Content Imaging Data.

High-content, imaging-based screens now routinely generate data on a scale that precludes manual verification and interrogation. Software applying machine learning has become an essential tool to automate analysis, but these methods require annotated examples to learn from. Efficiently exploring large datasets to find relevant examples remains a challenging bottleneck. Here, we present Advanced Cell Classifier (ACC), a graphical software package for phenotypic analysis that addresses these difficulties. ACC applies machine-learning and image-analysis methods to high-content data generated by large-scale, cell-based experiments. It features methods to mine microscopic image data, discover new phenotypes, and improve recognition performance. We demonstrate that these features substantially expedite the training process, successfully uncover rare phenotypes, and improve the accuracy of the analysis. ACC is extensively documented, designed to be user-friendly for researchers without machine-learning expertise, and distributed as a free open-source tool at www.cellclassifier.org.

Binary mixture of Satureja hortensis and Origanum vulgare subsp. hirtum essential oils: in vivo therapeutic efficiency against Helicobacter pylori infection.

BACKGROUND: Helicobacter pylori can cause many gastrointestinal and also extra-gastrointestinal disorders and is a major risk factor for gastric carcinoma and MALT lymphoma. Currently, numerous antibiotic-based therapies are available; however, these therapies have numerous drawbacks, mainly due to increasing prevalence of antibiotic resistant strains. Thus, there is an urgent need to develop novel therapeutic agents against H. pylori infections. MATERIALS AND METHODS: In this study, the anti-H. pylori activity of 2:1 mixture of Satureja hortensis and Origanum vulgare subsp. hirtum essential oils (2MIX) was investigated in vivo. After screening in vitro cytotoxicity of 2MIX on mammalian cell lines, the therapeutic efficiency was studied in a mouse model, where changes in H. pylori colonization were detected by PCR and histology of gastric samples. The immune reaction of mice was tested based on cytokine and chemokine production, and the in vivo toxicity of 2MIX was also investigated by measuring ALT and AST enzyme activities and Cyp3a11 and HO-1 mRNA levels in livers of mice. RESULTS: 2MIX had not shown in vitro cytotoxicity against cell lines, only the highest concentration caused significant decrease in their survival rates. In the in vivo experiments, 2MIX successfully eradicated the pathogen in 70% of the mice. We could not detect toxicity or altered cytokine and chemokine balance after in vivo treatments in mice. CONCLUSIONS: These results show that 2MIX is effective in reducing H. pylori colonization suggesting that this essential oil mixture has great potential as a new, effective, and safe therapeutic agent against H. pylori.