- Volume 73, Issue 11, 2024

Background. The growing interest in microbiota–epigenetics–immune system research stems from the understanding that microbiota, a group of micro-organisms colonized in the human body, can influence the gene expression through epigenetic mechanisms and interaction with the immune system. Epigenetics refers to changes in gene activity that are not caused by the alteration in the DNA sequence itself.

Discussion. The clinical significance of this research lies in the potential to develop new therapies for diseases linked to the imbalance of these microbial species (dysbiosis), such as cancer and neurodegenerative diseases. The intricate interaction between microbiota and epigenetics involves the production of metabolites and signalling molecules that can impact our health by influencing immune responses, metabolism and inflammation. Understanding these interactions could lead to novel therapeutic strategies targeting microbiota–epigenetic pathways to improve health outcomes.

Conclusion. In this context, we aim to review and emphasize the current knowledge and key concepts that link the microbiota to epigenetics and immune system function, exploring their relevance to the development and maintenance of homeostasis and susceptibility to different diseases later in life. We aim to elucidate key concepts concerning the interactions and potential effects among the human gut microbiota, epigenetics, the immune system and ageing diseases linked to dysbiosis.

Introduction. Antibiotic tolerance corresponds to the bacterial ability to survive a transient exposure to antibiotics and is often associated with treatment failure. Current methods of identifying tolerance based on bacterial growth are time-consuming. This study explores the use of a growth-independent method utilizing nanomotion technology to detect antibiotic-tolerant bacteria.

Hypothesis. The nanomotion signal obtained from a nanomechanical sensor measures real-time metabolic activity and cellular processes and could provide valuable information about the tolerance of bacteria to antibiotics that cannot be detected by standard antibiotic susceptibility tests.

Aim. The aim of this study is to investigate the potential of nanomotion technology to record antibiotic-tolerant bacteria.

Methodology. We generated a slow-growing Escherichia coli strain by manipulating mazF expression levels and confirmed its viability by several standard methods. We subsequently measured its nanomotion and the nanomotion of the WT E. coli in the presence or absence of antibiotics. Supervised machine learning was employed to distinguish slow-growing from exponentially growing bacteria. Observations for bacterial nanomotions were confirmed by standard kill curves.

Results. We distinguished slow-growing from exponentially growing bacteria using specific features from the nanomotion signal. Furthermore, the exposition of both growth phenotypes to polymyxin decreased the nanomotion signal indicating cell death. Similarly, when exponentially growing cells were exposed to ampicillin, an antibiotic whose efficacy depends on the growth rate, the nanomotion signal also decreased. In contrast, the nanomotion signal remained unchanged for slow-growing bacteria upon exposure to ampicillin. In addition, antibiotic exposure can cause bacterial elongation, in which the biomass of a cell increases without cell division. By overexpressing sulA, we mimicked antibiotic-induced elongation. Differences in the nanomotion signal were observed when comparing elongating and non-elongating phenotypes.

Conclusion. This work shows that nanomotion signals entail information about the reaction to antibiotics that standard MIC-based antibiotic susceptibility tests cannot detect. In the future, nanomotion-based antibiotic tolerance tests could be developed for clinical use in chronic or relapsing infections.

Introduction. Alcohol dependence (AD) and sleep disturbance (SD) independently affect gut microbiota, potentially disrupting the circadian rhythm of the microbiota and the host. However, the impact of SD on the composition and rhythmicity of gut flora in AD patients remains poorly understood.

Gap Statement. Characteristics of gut flora and diurnal oscillations in AD patients experiencing SD are unknown.

Aim. This study aims to explore alterations in gut flora and diurnal oscillations in AD patients experiencing SD.

Methodology. Thirty-two AD patients and 20 healthy subjects participated, providing faecal samples at 7 : 00 AM, 11 : 00 AM, 3 : 00 PM and 7 : 00 PM for gut microbiota analysis using 16S rDNA sequencing. AD patients were further categorized into those with poor sleep (ADwPS) and those with good sleep (ADwGS) for further analyses.

Results. The ADwPS group demonstrated elevated levels of anxiety, depression and withdrawal severity compared to the ADwGS group (all P<0.05). The β-diversity of gut microbiota in the ADwPS group differed from that in the ADwGS group (P<0.05). Bacterial abundances at various taxonomic levels, including Cyanobacteria and Pseudomonadales, differed between the ADwPS and ADwGS groups (all P<0.05). Utilizing unweighted UniFrac analysis, the β-diversity of gut microbiota in the ADwPS group demonstrated robust diurnal oscillation (P<0.05), whereas this pattern was statistically insignificant in the ADwGS group. Notably, the abundance of pathogenic bacteria like Pseudomonadales and Pseudomonadaceae exhibited marked diurnal fluctuation in the ADwPS group (all P<0.05).

Conclusion. SD in AD patients extends beyond alcohol-induced alterations, impacting gut microbiota composition, function and diurnal oscillation patterns. This highlights its add-on influence, supplementing AD-related changes.

Introduction. Cytomegalovirus (CMV) is a widely disseminated betaherpesvirus that typically induces latant infections. In immunocompromised populations, especially transplant and HIV-infected patients, CMV infection increases in-hospital mortality.

Gap statement. Although machine learning models have been widely used in clinical diagnosis and prognosis prediction, reports on machine learning model predictions for the in-hospital mortality of HIV/AIDS patients with CMV infection have not been reported.

Aim. Analyze the general gemographic and clinical characteristics of HIV/AIDS patients with CMV infection and identify the factors affecting the prognosis of this population, which will help to reduce their in-hospital mortality.

Methods. Hospitalized HIV/AIDS patients with CMV infection were recruited from the Fourth People’s Hospital of Nanning, Guangxi, from 2012 to 2019. After dividing them into survival and death groups based on their in-hospital survival status, their general and clinical profiles were described. Following 1 : 3 propensity score matching to equalize baseline characteristics, three machine-learning models (Random Forest, Support Vector Machine and eXtreme Gradient Boosting) were deployed to forecast factors influencing prognosis. The SHapley Additive exPlanations tool explained the models.

Results. A total of 1102 HIV/AIDS patients with CMV infection were analysed. There was no statistical difference in the general condition of the study subjects (P＞0.05). Prevalent complications/coinfections included pneumonia (63.6%), tuberculosis (47.2%) and oral fungal infections (44.6%). There were significant differences between the groups in pneumonia, cryptococcosis and hypoproteinaemia (P<0.05). The differences in laboratory indicators between patients were also statistically significant (P<0.05). The three machine learning models demonstrated good performance, identifying primary predictors of mortality. Pneumonia, urea, indirect bilirubin and platelet distribution width exhibited positive associations with death, with higher levels correlating with an increased mortality risk. Conversely, CD4 T-cell count, CD8 T-cell count and platelet displayed negative correlations with mortality.

Conclusions. HIV/AIDS patients with CMV infection exhibit distinctive clinical features impacting survival outcomes. Machine learning models accurately identify key influencing factors and predict mortality risk in this population, which appears to be essential to reducing in-hospital mortality.

Introduction. The existence of a mutual relationship between gut microbiota and immune homeostasis highlights its importance in the context of kidney transplantation.

Gap statement. The translational utility of gut microbiota as a biomarker for allograft injury has not been assessed before.

Aim. In this study, we aimed to characterize the gut microbial diversity in kidney transplant recipients and investigate the alterations in the gut microbial composition in association with allograft injury such as histopathological graft rejection and calcineurin inhibitor toxicity. In addition, we compared the gut microbial quantitation using 16S metagenomics and quantitative PCR (qPCR) to assess its translational utility.

Methodology. In this prospective longitudinal cohort study, we enrolled 38 kidney transplant recipients and collected serial faecal specimens (n=114), once before the induction therapy, and twice after transplant, during the first and third month. We characterized the gut microbial composition through 16S rRNA sequencing and qPCR from the DNA isolates of the samples. The recipients were clinically followed up for a median of 600 days post-transplant. Histopathological evidence of allograft rejection and calcineurin inhibitor toxicity were used for the correlational analysis with gut microbial diversity.

Results. Significant differences in the gut microbial diversity were observed between the pre- and post-transplant samples. Pre-transplant gut microbiota revealed a higher relative abundance of phylum Bacteroidetes in the allograft rejection group, and a higher relative abundance of phylum Firmicutes was observed in the histopathological features of calcineurin inhibitor toxicity (hCNI toxicity) group. We found a high concordance between 16S metagenomics and qPCR outputs for assessing the gut microbial diversity. Furthermore, the receiver operating characteristic curve analysis has also proven that the pre-transplant levels of gut microbial dysbiosis, as a potential predictive biomarker for allograft injury.

Conclusion. Our pilot study found a strong statistical association of gut microbial dysbiosis with kidney allograft injury, highlighting the potential of gut microbiota as a predictive biomarker and that qPCR serves as a more reliable and economic tool for assessing dysbiosis paving the way for its translational utility.

Introduction. Strongyloides stercoralis, the human threadworm, is a parasitic nematode with global distribution, estimated to infect over 600 million people. Chronic infection is often asymptomatic, but hyperinfection and dissemination syndromes can occur in the immunosuppressed with high case fatality rates. Whilst strongyloidiasis is endemic in Fiji, its prevalence in Fijian migrant groups in the UK is unknown.

Gap Statement. No previous studies have been conducted on the prevalence of Strongyloides and other gastrointestinal parasites (GIPs) in Fijian migrants to the UK.

Aim. We conducted a cross-sectional study of the prevalence of GIPs in a Fijian migrant population.

Methodology. Participants completed a questionnaire on residence, travel and clinical symptoms and were asked to provide a serum sample for S. stercoralis IgG ELISA, venous blood samples for eosinophil count and a faecal sample for charcoal culture, multiplex real-time PCR (rtPCR) and microscopy after formalin-ethyl acetate concentration. Sequencing was performed on pooled Strongyloides larvae for nuclear 18S rRNA hyper-variable regions (HVRs) I and IV.

Results. A total of 250 participants (94% male) with median (range) age 37 (20–51) years entered the study, 15 (1–24) years since leaving Fiji. S. stercoralis IgG ELISA was positive in 87/248 (35.1 %) and 14/74 (18.9 %) had a GIP detected in faeces. This included 7/74 (9.5 %) with Strongyloides and 5/74 (6.8 %) with hookworms. Dermatological symptoms were more common in those with Strongyloides, and eosinophilia (>0.5×109 cells per litre) was present in 55.6% of those with positive S. stercoralis IgG. rtPCR was the most sensitive faecal diagnostic test for Strongyloides and hookworms in faeces. Sequences of nuclear 18S rRNA for HVRs I and IV confirmed the presence of S. stercoralis.

Conclusion. This first cross-sectional study in Fijian migrants found a high rate of chronic infection with GIPs, particularly S. stercoralis. Faecal microscopy was insensitive compared to charcoal culture, rtPCR or serology, demonstrating the importance of specialist parasitological tests when investigating people with a suspected chronic infection. Our study highlights an overlooked burden of strongyloidiasis in the UK and has implications for screening and treatment programmes in Fiji and for migrants from Fiji.

Introduction. Enterococcus faecalis is a common pathogen associated with many oral diseases and is often isolated from oral cancer patients. However, limited information is available on its key virulence gene expression in oral cancer cell microenvironment and cancer cell behaviour in co-culture studies.

Hypothesis. E. faecalis overexpresses virulence genes when co-cultured with oral cancer cells and possibly alters the tumour microenvironment, promoting oral cancer proliferation and survival.

Aim. To investigate altered virulence gene expression in E. faecalis and oral cancer cell behaviour using in vitro co-culture experiments.

Methodology. Cal27 cells were co-cultured with E. faecalis and assessed for their cell proliferation, apoptosis, migration and clonogenicity using standard cell culture assays. The levels of reactive oxygen species (ROS) and inflammatory cytokines, along with proliferative, angiogenic and apoptotic biomarker expressions, were also assessed. E. faecalis adherence to cancer cells was demonstrated by the gentamicin protection assay. Real time-PCR was used to analyse the expression of virulence genes.

Results. Co-culture of Cal27 cells with E. faecalis showed significantly higher cell proliferation, migration and clonogenicity compared to the control (P<0.01). A significant increase in the levels of ROS and inflammatory cytokines and overexpression of Ki67, vascular endothelial growth factor, extracellular signal-regulated kinase 1/2, phosphoinositide 3 kinase and Akt was observed in the co-culture group. E. faecalis also downregulated p53 and Bax genes while upregulated Bcl-2. The virulence genes GelE, Asa and Ace were overexpressed in E. faecalis co-cultured with Cal27 cells.

Conclusion. The results from this study indicate the possible risks of E. faecalis infection in oral cancer. An effective antibiotic strategy against E. faecalis to prevent complications associated with oral diseases, including cancer, is needed.

Introduction. Mucormycosis is an aggressive, angioinvasive infection associated with high morbidity and mortality. The disease remains difficult to treat, with limited available antifungal drugs. Consequently, there is an urgent need to develop alternate therapeutics against mucormycosis. In an earlier study, we demonstrated that the non-steroidal anti-inflammatory drug diflunisal impacted the actin cytoskeleton and quorum sensing and inhibited the formation of filopodia-/cytoneme-like extensions in Rhizopus arrhizus.

Hypothesis. The non-steroidal anti-inflammatory drug diflunisal could exhibit potential antifungal activity.

Aim. This study aimed to investigate the plausible antifungal activity of diflunisal against a range of medically important Mucorales and its combination effect with antifungal drugs.

Methodology. The antifungal activity of diflunisal against Rhizopus arrhizus, Lichtheimia corymbifera, Rhizomucor pusillus, Cunninghamella bertholletiae, Mucor indicus, Mucor irregularis and Apophysomyces elegans was evaluated by broth microdilution assay. Allied salicylates were also screened. A combination assay with amphotericin B deoxycholate and posaconazole was performed by fractional inhibitory concentration test.

Results. Exposure to diflunisal inhibited Rhizopus arrhizus spore germination in a dose-dependent manner. MICs of diflunisal against different Mucorales ranged from 64 to 2048 µg ml−1. Remarkably low levels of diflunisal (0.03–2 µg ml−1), depending on the strain/species tested, improved the antifungal activity of amphotericin B against mucoralean fungi by twofold (ΣFIC ≈ 0.5–0.508; P<0.01). Field-emission scanning electron micrographs further confirmed these observations. MICs of posaconazole were unchanged by this compound.

Conclusion. Considering that amphotericin B remains the first-line drug against mucormycosis and exhibits dose-dependent side effects in clinical practice, especially nephrotoxicity, the observed additive interaction at remarkably low, clinically achievable levels of diflunisal demonstrates its potential utility as an adjunct therapy against mucoralean fungi.