Opportunities and barriers in omics-based biomarker discovery for steatotic liver diseases.

The rising prevalence of liver diseases related to obesity and excessive use of alcohol is fuelling an increasing demand for accurate biomarkers aimed at community screening, diagnosis of steatohepatitis and significant fibrosis, monitoring, prognostication and prediction of treatment efficacy. Breakthroughs in omics methodologies and the power of bioinformatics have created an excellent opportunity to apply technological advances to clinical needs, for instance in the development of precision biomarkers for personalised medicine. Via omics technologies, biological processes from the genes to circulating protein, as well as the microbiome - including bacteria, viruses and fungi, can be investigated on an axis. However, there are important barriers to omics-based biomarker discovery and validation, including the use of semi-quantitative measurements from untargeted platforms, which may exhibit high analytical, inter- and intra-individual variance. Standardising methods and the need to validate them across diverse populations presents a challenge, partly due to disease complexity and the dynamic nature of biomarker expression at different disease stages. Lack of validity causes lost opportunities when studies fail to provide the knowledge needed for regulatory approvals, all of which contributes to a delayed translation of these discoveries into clinical practice. While no omics-based biomarkers have matured to clinical implementation, the extent of data generated has enabled the hypothesis-free discovery of a plethora of candidate biomarkers that warrant further validation. To explore the many opportunities of omics technologies, hepatologists need detailed knowledge of commonalities and differences between the various omics layers, and both the barriers to and advantages of these approaches.

Terlipressin therapy is associated with increased risk of colonisation with multidrug-resistant bacteria in patients with decompensated cirrhosis.

BACKGROUND: Patients with cirrhosis are susceptible to develop bacterial infections that trigger acute decompensation (AD) and acute-on-chronic liver failure (ACLF). Infections with multidrug-resistant organisms (MDRO) are associated with deleterious outcome. MDRO colonisation frequently proceeds MDRO infections and antibiotic therapy has been associated with MDRO colonisation. AIM: The aim of the study was to assess the influence of non-antibiotic medication contributing to MDRO colonisation. METHODS: Three hundred twenty-four patients with AD and ACLF admitted to the ICU of Frankfurt University Hospital with MDRO screening were included. Regression models were performed to identify drugs associated with MDRO colonisation. Another cohort (n = 129) from Barcelona was included to validate. A third multi-centre cohort (n = 203) with metagenomic sequencing data of stool was included to detect antibiotic resistance genes. RESULTS: A total of 97 patients (30%) were identified to have MDRO colonisation and 35 of them (11%) developed MDRO infection. Patients with MDRO colonisation had significantly higher risk of MDRO infection than those without (p = 0.0098). Apart from antibiotic therapy (odds ratio (OR) 2.91, 95%-confidence interval (CI) 1.82-4.93, p < 0.0001), terlipressin therapy in the previous 14 days was the only independent covariate associated with MDRO colonisation in both cohorts, the overall (OR 9.47, 95%-CI 2.96-30.23, p < 0.0001) and after propensity score matching (OR 5.30, 95%-CI 1.22-23.03, p = 0.011). In the second cohort, prior terlipressin therapy was a risk factor for MDRO colonisation (OR 2.49, 95% CI 0.911-6.823, p = 0.075) and associated with risk of MDRO infection during follow-up (p = 0.017). The validation cohort demonstrated that antibiotic inactivation genes were significantly associated with terlipressin administration (p = 0.001). CONCLUSIONS: Our study reports an increased risk of MDRO colonisation in patients with AD or ACLF, who recently received terlipressin therapy, while other commonly prescribed non-antibiotic co-medications had negligible influence. Future prospective trials are needed to confirm these results.

Enterotypes of the human gut mycobiome.

BACKGROUND: The fungal component of the human gut microbiome, also known as the mycobiome, plays a vital role in intestinal ecology and human health. However, the overall structure of the gut mycobiome as well as the inter-individual variations in fungal composition remains largely unknown. In this study, we collected a total of 3363 fungal sequencing samples from 16 cohorts across three continents, including 572 newly profiled samples from China. RESULTS: We identify and characterize four mycobiome enterotypes using ITS profiling of 3363 samples from 16 cohorts. These enterotypes exhibit stability across populations and geographical locations and significant correlation with bacterial enterotypes. Particularly, we notice that fungal enterotypes have a strong age preference, where the enterotype dominated by Candida (i.e., Can_type enterotype) is enriched in the elderly population and confers an increased risk of multiple diseases associated with a compromised intestinal barrier. In addition, bidirectional mediation analysis reveals that the fungi-contributed aerobic respiration pathway associated with the Can_type enterotype might mediate the association between the compromised intestinal barrier and aging. CONCLUSIONS: We show that the human gut mycobiome has stable compositional patterns across individuals and significantly correlates with multiple host factors, such as diseases and host age. Video Abstract.

Cultivation-independent genomes greatly expand taxonomic-profiling capabilities of mOTUs across various environments.

BACKGROUND: Taxonomic profiling is a fundamental task in microbiome research that aims to detect and quantify the relative abundance of microorganisms in biological samples. Available methods using shotgun metagenomic data generally depend on the deposition of sequenced and taxonomically annotated genomes, usually from cultures of isolated strains, in reference databases (reference genomes). However, the majority of microorganisms have not been cultured yet. Thus, a substantial fraction of microbial community members remains unaccounted for during taxonomic profiling, particularly in samples from underexplored environments. To address this issue, we developed the mOTU profiler, a tool that enables reference genome-independent species-level profiling of metagenomes. As such, it supports the identification and quantification of both "known" and "unknown" species based on a set of select marker genes. RESULTS: We present mOTUs3, a command line tool that enables the profiling of metagenomes for >33,000 species-level operational taxonomic units. To achieve this, we leveraged the reconstruction of >600,000 draft genomes, most of which are metagenome-assembled genomes (MAGs), from diverse microbiomes, including soil, freshwater systems, and the gastrointestinal tract of ruminants and other animals, which we found to be underrepresented by reference genomes. Overall, two thirds of all species-level taxa lacked a reference genome. The cumulative relative abundance of these newly included taxa was low in well-studied microbiomes, such as the human body sites (6-11%). By contrast, they accounted for substantial proportions (ocean, freshwater, soil: 43-63%) or even the majority (pig, fish, cattle: 60-80%) of the relative abundance across diverse non-human-associated microbiomes. Using community-developed benchmarks and datasets, we found mOTUs3 to be more accurate than other methods and to be more congruent with 16S rRNA gene-based methods for taxonomic profiling. Furthermore, we demonstrate that mOTUs3 increases the resolution of well-known microbial groups into species-level taxa and helps identify new differentially abundant taxa in comparative metagenomic studies. CONCLUSIONS: We developed mOTUs3 to enable accurate species-level profiling of metagenomes. Compared to other methods, it provides a more comprehensive view of prokaryotic community diversity, in particular for currently underexplored microbiomes. To facilitate comparative analyses by the research community, it is released with >11,000 precomputed profiles for publicly available metagenomes and is freely available at: https://github.com/motu-tool/mOTUs . Video Abstract.