Fan Zhang’s research while affiliated with The University of Sydney and other places

Primary sclerosing cholangitis (PSC) is a chronic progressing cholestatic disease that often co-occurs with inflammatory bowel disease (PSC-IBD). PSC-IBD affecting the colon (PSC-UC) is likened clinically to ulcerative colitis (UC), however differences include a right colon dominance, less severe inflammatory phenotype and a greater lifetime risk of colorectal cancer. To understand the basis of clinical differences, we combine single-cell mRNA and antigen receptor sequencing, 16S ribosomal DNA analysis and spatial transcriptomics on biopsies from multiple colon regions of both PSC-UC and UC patients in remission or at the time of relapse. We discover disease-specific cell and microbial profiles between these cohorts, highlighting a distinct landscape in the right colon of PSC-UC patients and an epithelial-endothelial cell state that may contribute to intestinal permeability in UC. We show the expansion of an activated mast cell state in both diseases during flare, and demonstrate the requirement of TMEM176B in sustaining this activated state. Together this work demonstrates that PSC-UC and UC are distinct diseases with common cell mechanisms during inflammation, providing cellular and microbial insights to improve treatment of both patient cohorts.

Introduction Disruption of the gut microbiome has been widely reported in inflammatory bowel disease (IBD), particularly reduced bacterial diversity. Determining the role of this in IBD onset is hampered by a paucity of studies in newly diagnosed disease. We present outputs from a systematic review of the microbiome in pre-treatment IBD. Methods We searched MEDLINE, Embase between inception and December 2022 for any study presenting microbial analysis of patients diagnosed with IBD in the pre-treatment phase. All screening and extractions were done independently in duplicate. Data extracted included all measures of microbial diversity, the source of samples, any reported controls and clinical/patient parameters. Where appropriate, we performed random-effects meta-analysis of standardised mean difference, reporting 95% CI values and sub-grouped by type of IBD. Results 10,805 abstracts were screened and 217 full texts reviewed. Ultimately, 92 studies were included. 22 studies based on high-throughput technologies presented alpha diversity indices from IBD and controls. 86% of these offered a Shannon index. This was therefore used for synthesis and included faecal samples from 405 IBD (116 mixed, 225 Crohn’s disease [CD], 64 Ulcerative colitis [UC]) and 324 healthy controls (HC); alongside mucosal biopsies from 171 CD with 172 symptomatic controls (SC) and 42 UC with 60 SC. 68% of studies were paediatric.12 studies presented Shannon diversity from faeces vs HC cohorts. The studies were highly heterogenous. Nonetheless, alpha diversity was significantly lower in IBD, across both UC and CD. 7 studies presented Shannon diversity from mucosal biopsies vs SC cohorts. No papers presented mixed IBD, so subtypes were reviewed separately. Heterogeneity was lower across these studies but differences in diversity did not reach significance (see figure 1 ). • Download figure • Open in new tab • Download powerpoint Abstract P107 Figure 1 Alpha diversity meta-analysis (Shannon Index), split by sample type and patient group. Conclusions In IBD, faecal bacterial alpha diversity is significantly reduced compared to healthy controls, but mucosal alpha diversity is not in comparison with symptomatic patients without IBD. Factors influencing the faecal stream, such as rapid transit and malabsorption may exaggerate the difference between IBD and healthy. The similarity between mucosal diversity in IBD and symptomatic controls bolsters the view that other factors must be present alongside microbiome disruption to precipitate IBD. These signals will be further explored using secondary analysis of available inception sequencing datasets.

The pathogenesis of inflammatory bowel disease (IBD) is complex and multifactorial. Undertreated disease has substantial individual and societal consequences. Current patient classification and subsequent positioning of IBD therapy are based on crude, readily accessible clinical data. These broad parameters are unlikely to reflect underlying molecular profiles and may account for the observed heterogeneity in treatment response. Precision medicine offers identification and integration of molecular profiles into clinical decision-making. Despite several promising scientific and technological advances, the pathogenesis and targetable molecular drivers of IBD remain incompletely understood. Precision medicine therefore remains aspirational. This comprehensive narrative review describes our current understanding of IBD pathophysiology, highlights preliminary genetic, immunological and microbial predictors of treatment response and outlines the role of ‘big data’ and machine learning in the path towards precision medicine.

Background Chemoradiotherapy treatment (CRT) for head and neck cancer (HNC) is associated with toxicities such as mucositis and dysphagia. Oropharyngeal microbiota may play a role in these toxicities, however, the causative link and clinical relevance remain unclear. Aims: 1) determine if dysbiosis is present in HNC and the impact of CRT on the course of the dysbiosis during and after treatment; 2) investigate whether mucositis and associated dysbiosis after CRT are risk factors for long-term dysphagia. Methods Prospective longitudinal observational study to analyse the diversity and composition of saliva microbiome samples collected from 47 HNC patients (age 64, SD±12.2) undergoing CRT and 20 non-HNC controls (age 68, SD±10.5) using metagenomics sequencing. HNC samples were collected before CRT, immediately and 12 months after completion of CRT. Mucositis was assessed using the WHO Oral Mucositis Grading Scale. Dysphagia was assessed using Sydney Swallow Questionnaire (SSQ). Results The salivary microbiome in HNC pre-treatment was compositionally different and exhibited decreased diversity compared to controls. During treatment, α-diversity decreased significantly, and β-diversity showed a significant compositional change from pre-treatment and healthy controls (p<0.05). Twelve months post-treatment, the microbiome showed a significant recovery in diversity and a shift in composition (IDDF2023-ABS-0249 Figure 1. Alpha diversity comparison and beta diversity analysis between healthy controls and HNC patients at 3 microbiome collection points before during and 12 months post CRT).Severe mucositis during treatment was associated with a higher prevalence of long-term dysphagia (IDDF2023-ABS-0249 Figure 2 (A) Comparison of SSQ score at 12 months between HNC patients with mild moderate and severe mucositis during treatment). Microbiome analysis revealed no difference in α-diversity between severe and mild-moderate mucositis groups before treatment but marked differences immediately after CRT. At twelve months, the severe group microbiome diversity remained low, while the mild-moderate group recovered significantly (IDDF2023-ABS-0249 Figure 2 (B) Longitudinal microbiome alpha diversity based on mucos). β-diversity showed a more profound microbiome shift in the severe group at 12 months compared to the mild-moderate group. Dysphagic patients at 12 months had lower diversity (IDDF2023-ABS-0249 Figure 2C) than non-dysphagic patients, while the composition shift was not significant. Conclusions Results demonstrate the presence of dysbiosis in HNC and the impact of CRT on the oropharyngeal microbiome. Results also suggest that severe mucositis and associated dysbiosis after CRT may contribute to long-term dysphagia. These findings may help to develop strategies for microbiome-based interventions to improve treatment outcomes and reduce complications. • Download figure • Open in new tab • Download powerpoint Abstract IDDF2023-ABS-0249 Figure 1 Alpha diversity comparison and beta diversity analysis between healthy controls and HNC patients at 3 microbiome collection points before during and 12 months post CRT • Download figure • Open in new tab • Download powerpoint Abstract IDDF2023-ABS-0249 Figure 2 (A) Comparison of SSQ score at 12 months between HNC patients with mild moderate and severe mucositis during treatment (B) Longitudinal microbiome alpha diversity based on mucos

Viruses are the most abundant form of life on earth and play important roles in a broad range of ecosystems. Currently, two methods, whole genome shotgun metagenome (WGSM) and viral-like particle enriched metagenome (VLPM) sequencing, are widely applied to compare viruses in various environments. However, there is no critical assessment of their performance in recovering viruses and biological interpretation in comparative viral metagenomic studies. To fill this gap, we applied the two methods to investigate the stool virome in hepatocellular carcinoma (HCC) patients and healthy controls. Both WGSM and VLPM methods can capture the major diversity patterns of alpha and beta diversities and identify the altered viral profiles in the HCC stool samples compared with healthy controls. Viral signatures identified by both methods showed reductions of Faecalibacterium virus Taranis in HCC patients’ stool. Ultra-deep sequencing recovered more viruses in both methods, however, generally, 3 or 5 Gb were sufficient to capture the non-fragmented long viral contigs. More lytic viruses were detected than lysogenetic viruses in both methods, and the VLPM can detect the RNA viruses. Using both methods would identify shared and specific viral signatures and would capture different parts of the total virome.

Recent research suggests that dysbiosis of the oral microbial community is associated with head and neck cancer (HNC). It remains unclear whether this dysbiosis causes chemo-radiotherapy (CRT)-related complications. However, to address this question, it is essential to determine the most representative oral site for microbiome sampling. In this study, our purpose was to determine the optimal site for oral sample collection and whether the presence of HNC is associated with altered oral microbiome from this site. In 21 newly diagnosed HNC patients and 27 healthy controls, microbiome samples were collected from saliva, swabs from buccal mucosa, tongue, hard palate, faucial pillars and all mucosal sites combined. Microbial DNA was extracted and underwent 16S rRNA amplicon gene sequencing. In healthy controls, analysis of observed taxonomic units detected differences in alpha- and beta-diversity between sampling sites. Saliva was found to have the highest intra-community microbial diversity and lowest within-subject (temporal) and between-subject variance. Feature intersection showed that most species were shared between all sites, with saliva demonstrating the most unique species as well as highest overlap with other sites. In HNC patients, saliva was found to have the highest diversity but differences between sites were not statistically significant. Across all sites, HNC patients had lower alpha diversity than healthy controls. Beta-diversity analysis showed HNC patients’ microbiome to be compositionally distinct from healthy controls. This pattern was confirmed when the salivary microbiome was considered alone. HNC patients exhibited reduced diversity of the oral microbiome. Salivary samples demonstrate temporal stability, have the richest diversity and are sufficient to detect perturbation due to presence of HNC. Hence, they can be used as representative oral samples for microbiome studies in HNC patients.

Aging, medication use, and global function are associated with changes in microbiome. However, their interrelationships and changes over time require further characterisation. In a longitudinal aging mouse study, we investigated the effects of aging, chronic polypharmacy with high Drug Burden Index (DBI, measure of total anticholinergic and sedative medication exposure) and gradual cessation (deprescribing) on the microbiome, further exploring any association with global outcomes. Chronic administration of high DBI polypharmacy attenuated the aging-related reduction in alpha diversity, which was not sustained after deprescribing. Beta diversity and LEfSe (Linear discriminant analysis Effect Size) features varied with age, polypharmacy and deprescribing. Aging with and without polypharmacy shared decreases in Bifidobacteriaceae, Paraprevotellaceae, Bacteroidaceae, and Clostridiaceae, while only aging with polypharmacy showed increased LEfSe features. Microbiome diversity correlated with frailty, nesting, and open field performance. Polypharmacy deprescribing reversed changes that occurred with treatment. However, the microbiome did not recover to its pre-treatment composition at 12 months, nor develop the same aging-related changes from 12 to 24 months as the control group. Overall, aging, chronic polypharmacy, and deprescribing, differentially affected the diversity and composition of the gut microbiome, which is associated with frailty and function.