Hi-C metagenomics facilitate comparative genome analysis of bacteria and yeast from spontaneous beer and cider.

Sequence-based analysis of fermented foods and beverages' microbiomes offers insights into their impact on taste and consumer health. High-throughput metagenomics provide detailed taxonomic and functional community profiling, but bacterial and yeast genome reconstruction and mobile genetic elements tracking are to be improved. We established a pipeline for exploring fermented foods microbiomes using metagenomics coupled with chromosome conformation capture (Hi-C metagenomics). The approach was applied to analyze a collection of spontaneously fermented beers and ciders (n = 12). The Hi-C reads were used to reconstruct the metagenome-assembled genomes (MAGs) of bacteria and yeasts facilitating subsequent comparative genomic analysis, assembly scaffolding and exploration of "plasmid-bacteria" links. For a subset of beverages, yeasts were isolated and characterized phenotypically. The reconstructed Hi-C MAGs primarily belonged to the Lactobacillaceae family in beers, along with Acetobacteraceae and Enterobacteriaceae in ciders, exhibiting improved quality compared to conventional metagenomic MAGs. Comparative genomic analysis of Lactobacillaceae Hi-C MAGs revealed clustering by niche and suggested genetic determinants of survival and probiotic potential. For Pediococcus damnosus, Hi-C-based networks of contigs enabled linking bacteria with plasmids. Analyzing phylogeny and accessory genes in the context of known reference genomes offered insights into the niche specialization of beer lactobacilli. The subspecies-level diversity of cider Tatumella spp. was disentangled using a Hi-C-based graph. We obtained highly complete yeast Hi-C MAGs primarily represented by Brettanomyces and Saccharomyces, with Hi-C-facilitated chromosome-level genome assembly for the former. Utilizing Hi-C metagenomics to unravel the genomic content of individual species can provide a deeper understanding of the ecological interactions within the food microbiome, aid in bioprospecting beneficial microorganisms, improving quality control and improving innovative fermented products.

Medication Use is Associated with Distinct Microbial Features in Anxiety and Depression.

This study investigated the relationship between gut microbiota and neuropsychiatric disorders (NPDs), specifically anxiety disorder (ANXD) and/or major depressive disorder (MDD), as defined by DSM-IV or V criteria. The study also examined the influence of medication use, particularly antidepressants and/or anxiolytics, classified through the Anatomical Therapeutic Chemical (ATC) Classification System, on the gut microbiota. Both 16S rRNA gene amplicon sequencing and shallow shotgun sequencing were performed on DNA extracted from 666 fecal samples from the Tulsa-1000 and NeuroMAP CoBRE cohorts. The results highlight the significant influence of medication use; antidepressant use is associated with significant differences in gut microbiota beta diversity and has a larger effect size than NPD diagnosis. Next, specific microbes were associated with ANXD and MDD, highlighting their potential for non-pharmacological intervention. Finally, the study demonstrated the capability of Random Forest classifiers to predict diagnoses of NPD and medication use from microbial profiles, suggesting a promising direction for the use of gut microbiota as biomarkers for NPD. The findings suggest that future research on the gut microbiota's role in NPD and its interactions with pharmacological treatments are needed.

Unraveling the Polysaccharide Biosynthesis Potential of Ganoderma lucidum: A Chromosome-Level Assembly Using Hi-C Sequencing.

Ganoderma lucidum exhibits the ability to synthesize a diverse range of biologically active molecules with significant pharmaceutical potential, including xylomannan and fucogalactan, which have demonstrated antitumor activity. However, there exists considerable intra-species variability in the capacity to produce these metabolites at high concentrations, likely reflecting the high genomic diversity observed from a limited number of strains sequenced to date. We employed high-throughput shotgun sequencing to obtain the complete genome sequence of G. lucidum strain 5.1, which is distinguished by its remarkable xylomannan synthesis capabilities. Through the utilization of semi-automatic reordering based on conformation capture (Hi-C) data, we substantially enhanced the assembly process, resulting in the generation of 12 chromosome-level scaffolds with a cumulative length of 39 Mbp. By employing both de novo and homology-based approaches, we performed comprehensive annotation of the genome, thereby identifying a diverse repertoire of genes likely involved in polysaccharide biosynthesis. The genome sequence generated in this study serves as a valuable resource for elucidating the molecular mechanisms underlying the medicinal potential of Ganoderma species, discovering novel pharmaceutically valuable compounds, and elucidating the ecological mechanisms of the species. Furthermore, the chromosome contact map obtained for the first time for this species extends our understanding of 3D fungal genomics and provides insights into the functional and structural organization within the fungal kingdom.

Stability of human gut microbiome: Comparison of ecological modelling and observational approaches.

The gut microbiome plays a pivotal role in the human body, and perturbations in its composition have been linked to various disorders. Stability is an essential property of a healthy human gut microbiome, which allows it to maintain its functional richness under the external influences. This property has been explored through two distinct methodologies - mathematical modelling based on ecological principles and statistical analysis drawn from observations in interventional studies. Here we conducted a meta-analysis aimed to compare the two approaches utilising the data from 9 interventional and time series studies encompassing 3512 gut microbiome profiles obtained via 16S rRNA gene sequencing. By employing the previously published compositional Lotka-Volterra method, we modelled the dynamics of the microbial community and evaluated ecological stability measures. These measures were compared to those based on observed microbiome changes. There was a substantial correlation between the outcomes of the two approaches. Particularly, local stability assessed within the ecological paradigm was positively correlated with observational stability measures accounting for the compositional nature of microbiome data. Additionally, we were able to reproduce the previously reported inverse relationship between the community's robustness to microorganism loss and local stability, attributed to the distinct impacts of coefficient characterising the network decomposition on these two stability assessments. Our findings demonstrate harmonisation between the ecological and observational approaches to microbiome analysis, advancing the understanding of healthy gut microbiome concept. This paves the way to develop efficient microbiome-targeting interventions for disease prevention and treatment.

Trajectory of hiPSCs derived neural progenitor cells differentiation into dermal papilla-like cells and their characteristics.

Dermal papilla cells (DPCs) play roles in key functions of the epidermis such as hair generation. The use of human induced pluripotent cells (hiPSCs) makes it possible to obtain DP-like cells and study the molecular mechanisms of DPC development during embryogenesis. In this work, we studied the phenotypic trajectory of hiPSCs during their differentiation into DP-like cells and evaluated the epithelial-mesenchymal interaction potential of the resulting cell line. Specifically, we differentiated hiPSCs into neural progenitor cells (NPCs) and subsequently into DP-like cells. Analysis of bulk RNA-seq data during this process enabled us to observe gene expression dynamics during five stages of dermal differentiation. Furthermore, functional assays (organoids in both collagen gels and hanging drop cultures and tubulogenesis assays) revealed that the dermal cell lines we generated could interact with epidermal cells.

Gut Microbiome in Post-COVID-19 Patients Is Linked to Immune and Cardiovascular Health Status but Not COVID-19 Severity.

The composition of the gut microbiome stores the imprints of prior infections and other impacts. COVID-19 can cause changes in inflammatory status that persist for a considerable time after infection ends. As the gut microbiome is closely associated with immunity and inflammation, the infection severity might be linked to its community structure dynamics. Using 16S rRNA sequencing of stool samples, we investigated the microbiome three months after the end of the disease/infection or SARS-CoV-2 contact in 178 post-COVID-19 patients and those who contacted SARS-CoV-2 but were not infected. The cohort included 3 groups: asymptomatic subjects (n = 48), subjects who contacted COVID-19 patients with no further infection (n = 46), and severe patients (n = 86). Using a novel compositional statistical algorithm (nearest balance) and the concept of bacterial co-occurrence clusters (coops), we compared microbiome compositions between the groups as well as with multiple categories of clinical parameters including: immunity, cardiovascular parameters and markers of endothelial dysfunction, and blood metabolites. Although a number of clinical indicators varied drastically across the three groups, no differences in microbiome features were identified between them at this follow-up point. However, there were multiple associations between the microbiome features and clinical data. Among the immunity parameters, the relative lymphocyte number was linked to a balance including 14 genera. Cardiovascular parameters were associated with up to four bacterial cooperatives. Intercellular adhesion molecule 1 was linked to a balance including ten genera and one cooperative. Among the blood biochemistry parameters, calcium was the only parameter associated with the microbiome via a balance of 16 genera. Our results suggest comparable recovery of the gut community structure in the post-COVID-19 period, independently of severity or infection status. The multiple identified associations of clinical analysis data with the microbiome provide hypotheses about the participation of specific taxa in regulating immunity and homeostasis of cardiovascular and other body systems in health, as well as their disruption in SARS-CoV-2 infections and other diseases.

RNA-DNA interactomes of three prokaryotes uncovered by proximity ligation.

Proximity ligation approaches, which are widely used to study the spatial organization of the genome, also make it possible to reveal patterns of RNA-DNA interactions. Here, we use RedC, an RNA-DNA proximity ligation approach, to assess the distribution of major RNA types along the genomes of E. coli, B. subtilis, and thermophilic archaeon T. adornatum. We find that (i) messenger RNAs preferentially interact with their cognate genes and the genes located downstream in the same operon, which is consistent with polycistronic transcription; (ii) ribosomal RNAs preferentially interact with active protein-coding genes in both bacteria and archaea, indicating co-transcriptional translation; and (iii) 6S noncoding RNA, a negative regulator of bacterial transcription, is depleted from active genes in E. coli and B. subtilis. We conclude that the RedC data provide a rich resource for studying both transcription dynamics and the function of noncoding RNAs in microbial organisms.

Luminal and Tumor-Associated Gut Microbiome Features Linked to Precancerous Lesions Malignancy Risk: A Compositional Approach.

Colorectal cancer is the third most commonly diagnosed cancer worldwide. Human gut microbiome plays important roles in protecting against it, as well as contributing to its onset and progression. Identification of specific bacterial taxa associated with early stages of colorectal cancer may help develop effective microbiome-based diagnostics. For precancerous lesions, links of their characteristics to luminal and tumor-associated microbiome composition are to be elucidated. Paired stool and tumor brush biopsy samples were collected from 50 patients with precancerous lesions and early forms of colon cancer; their microbial communities were profiled using high-throughput 16S rRNA sequencing. We showed that the microbiome differences between stool and biopsy samples can be to a high extent computationally corrected. Compositionality-aware statistical analysis of microbiome composition revealed its associations with the number of lesions, lesion type, location and malignization pathway. A major determinant of precancerous lesions malignancy risk-the number of lesions-was positively associated with the abundance of H2S-producing taxa. Our results contribute to the basis for developing early non-invasive colorectal cancer diagnostics via identifying microorganisms likely participating in early stages of cancer pathogenesis.

The hallmarks of dietary intervention-resilient gut microbiome.

Maintaining equilibrium of the gut microbiome is crucial for human health. Diet represents an important and generally accessible natural channel of controlling the nutrients supply to the intestinal microorganisms. Although many studies showed that dietary interventions can specifically modulate gut microbiome composition, further progress of the approach is complicated by interindividual variability of the microbial community response. The reported causes of this variability include the baseline microbiome composition features, but it is unclear whether any of them are intervention-specific. Here, we applied a unified computational framework to investigate the variability of microbiome response measured as beta diversity in eight various dietary interventions using previously published 16S rRNA sequencing datasets. We revealed a number of baseline microbiome features which determine the microbiome response in an intervention-independent manner. One of the most stable associations, reproducible for different interventions and enterotypes, was a negative dependence of the response on the average number of genes per microorganism in the community-an indicator of the community functional redundancy. Meanwhile, many revealed microbiome response determinants were enterotype-specific. In Bact1 and Rum enterotypes, the response was negatively correlated with the baseline abundance of their main drivers. Additionally, we proposed a method for preliminary assessment of the microbiome response. Our study delineats the universal features determining microbiome response to diverse interventions. The proposed approach is promising for understanding the mechanisms of gut microbiome stability and improving the efficacy of personalised microbiome-tailored interventions.

Approximation of a Microbiome Composition Shift by a Change in a Single Balance Between Two Groups of Taxa.

Linking microbiome composition obtained from metagenomic or 16S rRNA sequencing to various factors poses a real challenge. The compositional approach to such data is well described: a so-called isometric log-ratio (ILR) transform provides correct treatment of relative abundances. Most existing compositional methods differ in the particular choice of the transform. Although this choice does not influence the prediction of a model, it determines the subset of balances between groups of microbial taxa subsequently used for interpreting the composition shifts. We propose a method to interpret these shifts independently of the initial choice of ILR coordinates by the nearest single-balance shift. We describe here application of the method to regression, classification, and principal balance analysis of compositional data. Analytical treatment and cross-validation show that the approach provides the least-squares estimate of a single-balance shift associated with a factor with possible adjustment for covariates. As for classification and principal balance analysis, the nearest balance method provides results comparable to other compositional tools. Its advantages are the absence of assumptions about the number of taxa included in the balance and its low computational cost. The method is implemented in the R package NearestBalance. IMPORTANCE The method proposed here extends the range of compositional methods providing interpretation of classical statistical tools applied to data converted to the ILR coordinates. It provides a strictly optimal solution in several special cases. The approach is universally applicable to compositional data of any nature, including microbiome data sets.

Pentad: a tool for distance-dependent analysis of Hi-C interactions within and between chromatin compartments.

BACKGROUND: Understanding the role of various factors in 3D genome organization is essential to determine their impact on shaping large-scale chromatin units such as euchromatin (A) and heterochromatin (B) compartments. At this level, chromatin compaction is extensively modulated when transcription and epigenetic profiles change upon cell differentiation and response to various external impacts. However, detailed analysis of chromatin contact patterns within and between compartments is complicated because of a lack of suitable computational methods. RESULTS: We developed a tool, Pentad, to perform calculation, visualisation and quantitative analysis of the average chromatin compartment from the Hi-C matrices in cis, trans, and specified genomic distances. As we demonstrated by applying Pentad to publicly available Hi-C datasets, it helps to reliably detect redistribution of contact frequency in the chromatin compartments and assess alterations in the compartment strength. CONCLUSIONS: Pentad is a simple tool for the analysis of changes in chromatin compartmentalization in various biological conditions. Pentad is freely available at https://github.com/magnitov/pentad .

Self-Organization Provides Cell Fate Commitment in MSC Sheet Condensed Areas via ROCK-Dependent Mechanism.

Multipotent mesenchymal stem/stromal cells (MSC) are one of the crucial regulators of regeneration and tissue repair and possess an intrinsic program from self-organization mediated by condensation, migration and self-patterning. The ability to self-organize has been successfully exploited in tissue engineering approaches using cell sheets (CS) and their modifications. In this study, we used CS as a model of human MSC spontaneous self-organization to demonstrate its structural, transcriptomic impact and multipotent stromal cell commitment. We used CS formation to visualize MSC self-organization and evaluated the role of the Rho-GTPase pathway in spontaneous condensation, resulting in a significant anisotropy of the cell density within the construct. Differentiation assays were carried out using conventional protocols, and microdissection and RNA-sequencing were applied to establish putative targets behind the observed phenomena. The differentiation of MSC to bone and cartilage, but not to adipocytes in CS, occurred more effectively than in the monolayer. RNA-sequencing indicated transcriptional shifts involving the activation of the Rho-GTPase pathway and repression of SREBP, which was concordant with the lack of adipogenesis in CS. Eventually, we used an inhibitory analysis to validate our findings and suggested a model where the self-organization of MSC defined their commitment and cell fate via ROCK1/2 and SREBP as major effectors under the putative switching control of AMP kinase.

Suppression of liquid-liquid phase separation by 1,6-hexanediol partially compromises the 3D genome organization in living cells.

Liquid-liquid phase separation (LLPS) contributes to the spatial and functional segregation of molecular processes within the cell nucleus. However, the role played by LLPS in chromatin folding in living cells remains unclear. Here, using stochastic optical reconstruction microscopy (STORM) and Hi-C techniques, we studied the effects of 1,6-hexanediol (1,6-HD)-mediated LLPS disruption/modulation on higher-order chromatin organization in living cells. We found that 1,6-HD treatment caused the enlargement of nucleosome clutches and their more uniform distribution in the nuclear space. At a megabase-scale, chromatin underwent moderate but irreversible perturbations that resulted in the partial mixing of A and B compartments. The removal of 1,6-HD from the culture medium did not allow chromatin to acquire initial configurations, and resulted in more compact repressed chromatin than in untreated cells. 1,6-HD treatment also weakened enhancer-promoter interactions and TAD insulation but did not considerably affect CTCF-dependent loops. Our results suggest that 1,6-HD-sensitive LLPS plays a limited role in chromatin spatial organization by constraining its folding patterns and facilitating compartmentalization at different levels.

Host-Microbiome Interactions Mediated by Phenolic Metabolites in Chronically Critically Ill Patients.

The community structure and metabolic potential of gut microbiome is not well investigated, especially in chronically critically ill patients with prolonged dependence on support systems after severe brain disorders. Microbial phenolic metabolites can target the brain function by the direct and indirect modulation of inflammation. The aim of this study was to investigate the features of the gut microbiota and profile of certain metabolites in the progression and reversibility of neurological disorders in chronically critically ill patients. Fecal samples were collected in dynamics from such patients (n = 44) and analyzed using 16S rRNA sequencing. Serum microbial and mitochondrial metabolites were measured by GC-MS and compared with the biomarkers and clinical neurological scores. The identified associations between specific bacterial taxa in fecal samples, neurological status and serum levels of metabolites suggest that impacts on specific members of the gut microbiota and their metabolism might be a promising tool for regulating brain function in future.

The impact of Opisthorchis felineus infection and praziquantel treatment on the intestinal microbiota in children.

The presence of some species of helminths is associated with changes in host microbiota composition and diversity, which varies widely depending on the infecting helminth species and other factors. We conducted a prospective case-control study to evaluate the gut microbiota in children with Opisthorchis felineus infection (n=50) before and after anthelmintic treatment and in uninfected children (n=49) in the endemic region. A total of 99 children and adolescents aged between 7 and 18 years were enrolled to the study. Helminth infection was assessed before and at 3 months after treatment with praziquantel. A complex examination for each participant was performed in the study, including an assessment of the clinical symptoms and an intestinal microbiota survey by 16S rRNA gene sequencing of stool samples. There was no change in alpha diversity between O. felineus-infected and control groups. We found significant changes in the abundances of bacterial taxa at different taxonomic levels between the infected and uninfected individuals. Enterobacteriaceae family was more abundant in infected participants compared to uninfected children. On the genus level, O. felineus-infected participants' microbiota showed higher levels of Lachnospira, Escherichia-Shigella, Bacteroides, Eubacterium eligens group, Ruminiclostridium 6, Barnesiella, Oscillibacter, Faecalitalea and Anaerosporobacter and reduction of Blautia, Lachnospiraceae FCS020 and Eubacterium hallii group in comparison with the uninfected individuals. Following praziquantel therapy, there were significant differences in abundances of some microorganisms, including an increase of Faecalibacterium and decrease of Megasphaera, Roseburia. Enterobacteriaceae and Escherichia abundances were decreased up to the control group values. Our results highlight the importance of the host-parasite-microbiota interactions for the community health in the endemic regions.

Hi-C Metagenomics in the ICU: Exploring Clinically Relevant Features of Gut Microbiome in Chronically Critically Ill Patients.

Gut microbiome in critically ill patients shows profound dysbiosis. The most vulnerable is the subgroup of chronically critically ill (CCI) patients - those suffering from long-term dependence on support systems in intensive care units. It is important to investigate their microbiome as a potential reservoir of opportunistic taxa causing co-infections and a morbidity factor. We explored dynamics of microbiome composition in the CCI patients by combining "shotgun" metagenomics with chromosome conformation capture (Hi-C). Stool samples were collected at 2 time points from 2 patients with severe brain injury with different outcomes within a 1-2-week interval. The metagenome-assembled genomes (MAGs) were reconstructed based on the Hi-C data using a novel hicSPAdes method (along with the bin3c method for comparison), as well as independently of the Hi-C using MetaBAT2. The resistomes of the samples were derived using a novel assembly graph-based approach. Links of bacteria to antibiotic resistance genes, plasmids and viruses were analyzed using Hi-C-based networks. The gut community structure was enriched in opportunistic microorganisms. The binning using hicSPAdes was superior to the conventional WGS-based binning as well as to the bin3c in terms of the number, completeness and contamination of the reconstructed MAGs. Using Klebsiella pneumoniae as an example, we showed how chromosome conformation capture can aid comparative genomic analysis of clinically important pathogens. Diverse associations of resistome with antimicrobial therapy from the level of assembly graphs to gene content were discovered. Analysis of Hi-C networks suggested multiple "host-plasmid" and "host-phage" links. Hi-C metagenomics is a promising technique for investigating clinical microbiome samples. It provides a community composition profile with increased details on bacterial gene content and mobile genetic elements compared to conventional metagenomics. The ability of Hi-C binning to encompass the MAG's plasmid content facilitates metagenomic evaluation of virulence and drug resistance dynamics in clinically relevant opportunistic pathogens. These findings will help to identify the targets for developing cost-effective and rapid tests for assessing microbiome-related health risks.

Characteristics of bacterial and yeast microbiomes in spontaneous and mixed-fermentation beer and cider.

The production of experimental beer and cider products has increased, worldwide. The complex microbiomes found in these beverages affect their organoleptic qualities and chemical compositions and can have diverse impacts on human health. The total diversity of a microbiome can be elucidated through the use of high-throughput sequencing and comprehensive data analysis tools. We analysed the bacterial and yeast microbiomes found in mixed and spontaneously fermented beers (n = 14) and unpasteurised apple ciders (n = 6), using high-throughput 16S rRNA and internal transcribed spacer (ITS) sequencing. The ratio of bacteria to yeast was measured using quantitative polymerase chain reaction (qPCR), and short-chain organic acids were analysed using high-performance liquid chromatography (HPLC). An upgraded version of the Knomics-Biota system was used to analyse the data. The microbiomes included both starter microorganisms and those that originate from the production environment and the raw materials. In addition to the common Saccharomyces and Brettanomyces, the yeast diversity included many non-conventional species. The bacterial community in beer was dominated by Lactobacillus species, whereas these communities were more diverse in cider. Lactobacillus acetotolerans was prevalent in wild ales, whereas Candida ethanolica was prevalent in cask-matured beverages. We observed complex patterns of subspecies-level yeast diversity across beer styles, breweries, and countries. Our study represents an exploratory analysis of non-conventional beer and cider microbiomes and metabolomes, which contributes information necessary to develop improved quality control processes and may drive innovative product development in experimental and artisanal brewing.

Gut microbiome signature of Viliuisk encephalomyelitis in Yakuts includes an increase in microbes linked to lean body mass and eating behaviour.

BACKGROUND: Viliuisk encephalomyelitis (VE) is a rare endemic neurodegenerative disease occurring in the Yakut population of Northeastern Siberia. The main clinical features of VE are spasticity, dysarthria, dementia, central paresis and paralysis, and cortical atrophy observed via MRI. Many hypotheses have been proposed regarding its etiology, including infectious agents, genetics, environmental factors, and immunopathology. Each of these hypotheses has been supported to some extent by epidemiological and experimental data. Nevertheless, none of them has been decisively proven. Gut microbiome is one of the factors that might be involved in VE pathogenesis. RESULTS: Here we performed a pilot survey of the stool microbiomes of Yakut subjects with VE (n = 6) and without VE (n = 11). 16S rRNA sequencing showed that in comparison with the control group, the Yakuts with VE had increased proportions of Methanobrevibacter and Christensenella, which are reported to be linked to body mass index, metabolism, dietary habits and potentially to neurodegenerative disorders. The identified associations suggest that the microbiome may be involved in VE. Overall, the Yakut microbiome was quite specific in comparison with other populations, such as metropolitan Russians and native inhabitants of the Canadian Arctic. CONCLUSIONS: Describing the gut microbiome of indigenous human populations will help to elucidate the impact of dietary and environmental factors on microbial community structure and identify risks linked to the lifestyles of such groups as well as endemic diseases.

Serum and fecal profiles of aromatic microbial metabolites reflect gut microbiota disruption in critically ill patients: a prospective observational pilot study.

BACKGROUND: High serum levels of certain aromatic microbial metabolites (AMM) are associated with severity and mortality in critically ill patients. Omics-based studies suggest gut dysbiosis and reduced microbiome diversity in critical conditions. However, the landscape of gut microbial metabolites is still to be outlined, not to mention the interplay correlation between the metabolome and gut microbiome in critically ill patients. The aim of this study was to analyze the association between serum and fecal levels of AMM and compare them with the composition of gut microbiota in critically ill patients in the acute and chronic stages. METHODS: In this prospective observational pilot study, we analyzed the temporal dynamics of the gut microbiome and the AMM spectrum across two distinct subgroups-acute critical ill (ACI) patients with nosocomial pneumonia and chronically critically ill (CCI) patients (9 subjects each group)-as well as performed comparison with 23 healthy volunteers. The AMM levels for each patient were measured using GC-MS in simultaneously taken serum and fecal samples (SFS). These parameters were compared with 16S rRNA fecal microbiome profiles. RESULTS: The observed proportions of bacterial taxa suggest a significant gut dysbiosis in the ACI and the CCI patients. Stronger imbalance in microbiome composition and dynamics observed in the ACI patients compared to the CCI ones resonates with a higher severity in the former group. The total levels of AMM in serum samples were higher for the ACI patients than for the CCI patients (3.7 (1.4-6.3) and 1.1 (1.0-1.6) µM, respectively; p = 0.0003). The qualitative composition of the SFS was also altered. We discovered significant associations between gut microbial taxa levels and metabolite concentrations in blood serum as well as in feces in each of the ACI and the CCI patients. CONCLUSIONS: Aromatic microbial metabolite profiles in the gut and the serum are interlinked and reflect a disruption of the gut microbial community in critically ill patients.