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12 result(s) for "Punčochář, Michal"
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Variability of strain engraftment and predictability of microbiome composition after fecal microbiota transplantation across different diseases
Fecal microbiota transplantation (FMT) is highly effective against recurrent Clostridioides difficile infection and is considered a promising treatment for other microbiome-related disorders, but a comprehensive understanding of microbial engraftment dynamics is lacking, which prevents informed applications of this therapeutic approach. Here, we performed an integrated shotgun metagenomic systematic meta-analysis of new and publicly available stool microbiomes collected from 226 triads of donors, pre-FMT recipients and post-FMT recipients across eight different disease types. By leveraging improved metagenomic strain-profiling to infer strain sharing, we found that recipients with higher donor strain engraftment were more likely to experience clinical success after FMT ( P = 0.017) when evaluated across studies. Considering all cohorts, increased engraftment was noted in individuals receiving FMT from multiple routes (for example, both via capsules and colonoscopy during the same treatment) as well as in antibiotic-treated recipients with infectious diseases compared with antibiotic-naïve patients with noncommunicable diseases. Bacteroidetes and Actinobacteria species (including Bifidobacteria ) displayed higher engraftment than Firmicutes except for six under-characterized Firmicutes species. Cross-dataset machine learning predicted the presence or absence of species in the post-FMT recipient at 0.77 average AUROC in leave-one-dataset-out evaluation, and highlighted the relevance of microbial abundance, prevalence and taxonomy to infer post-FMT species presence. By exploring the dynamics of microbiome engraftment after FMT and their association with clinical variables, our study uncovered species-specific engraftment patterns and presented machine learning models able to predict donors that might optimize post-FMT specific microbiome characteristics for disease-targeted FMT protocols. Coupling microbial metagenomics with machine learning enables prediction of donor strain engraftment after fecal microbiota transplantation (FMT) for a range of diseases, and may help tailor design of FMT to optimize microbial engraftment and achieve clinical outcomes.
Genomic diversity and ecology of human-associated Akkermansia species in the gut microbiome revealed by extensive metagenomic assembly
Background Akkermansia muciniphila is a human gut microbe with a key role in the physiology of the intestinal mucus layer and reported associations with decreased body mass and increased gut barrier function and health. Despite its biomedical relevance, the genomic diversity of A. muciniphila remains understudied and that of closely related species, except for A. glycaniphila , unexplored. Results We present a large-scale population genomics analysis of the Akkermansia genus using 188 isolate genomes and 2226 genomes assembled from 18,600 metagenomes from humans and other animals. While we do not detect A. glycaniphila , the Akkermansia strains in the human gut can be grouped into five distinct candidate species, including A. muciniphila , that show remarkable whole-genome divergence despite surprisingly similar 16S rRNA gene sequences. These candidate species are likely human-specific, as they are detected in mice and non-human primates almost exclusively when kept in captivity. In humans, Akkermansia candidate species display ecological co-exclusion, diversified functional capabilities, and distinct patterns of associations with host body mass. Analysis of CRISPR-Cas loci reveals new variants and spacers targeting newly discovered putative bacteriophages. Remarkably, we observe an increased relative abundance of Akkermansia when cognate predicted bacteriophages are present, suggesting ecological interactions. A. muciniphila further exhibits subspecies-level genetic stratification with associated functional differences such as a putative exo/lipopolysaccharide operon. Conclusions We uncover a large phylogenetic and functional diversity of the Akkermansia genus in humans. This variability should be considered in the ongoing experimental and metagenomic efforts to characterize the health-associated properties of A. muciniphila and related bacteria.
Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4
Metagenomic assembly enables new organism discovery from microbial communities, but it can only capture few abundant organisms from most metagenomes. Here we present MetaPhlAn 4, which integrates information from metagenome assemblies and microbial isolate genomes for more comprehensive metagenomic taxonomic profiling. From a curated collection of 1.01 M prokaryotic reference and metagenome-assembled genomes, we define unique marker genes for 26,970 species-level genome bins, 4,992 of them taxonomically unidentified at the species level. MetaPhlAn 4 explains ~20% more reads in most international human gut microbiomes and >40% in less-characterized environments such as the rumen microbiome and proves more accurate than available alternatives on synthetic evaluations while also reliably quantifying organisms with no cultured isolates. Application of the method to >24,500 metagenomes highlights previously undetected species to be strong biomarkers for host conditions and lifestyles in human and mouse microbiomes and shows that even previously uncharacterized species can be genetically profiled at the resolution of single microbial strains. Integration of metagenomic assemblies and microbial isolate genomes improves profiling of uncharacterized species.
Fecal microbiota transplantation plus anti-PD-1 immunotherapy in advanced melanoma: a phase I trial
Fecal microbiota transplantation (FMT) represents a potential strategy to overcome resistance to immune checkpoint inhibitors in patients with refractory melanoma; however, the role of FMT in first-line treatment settings has not been evaluated. We conducted a multicenter phase I trial combining healthy donor FMT with the PD-1 inhibitors nivolumab or pembrolizumab in 20 previously untreated patients with advanced melanoma. The primary end point was safety. No grade 3 adverse events were reported from FMT alone. Five patients (25%) experienced grade 3 immune-related adverse events from combination therapy. Key secondary end points were objective response rate, changes in gut microbiome composition and systemic immune and metabolomics analyses. The objective response rate was 65% (13 of 20), including four (20%) complete responses. Longitudinal microbiome profiling revealed that all patients engrafted strains from their respective donors; however, the acquired similarity between donor and patient microbiomes only increased over time in responders. Responders experienced an enrichment of immunogenic and a loss of deleterious bacteria following FMT. Avatar mouse models confirmed the role of healthy donor feces in increasing anti-PD-1 efficacy. Our results show that FMT from healthy donors is safe in the first-line setting and warrants further investigation in combination with immune checkpoint inhibitors. ClinicalTrials.gov identifier NCT03772899 . In patients with advanced melanoma, fecal microbiota transplantation from healthy donors combined with the anti-PD-1 inhibitors nivolumab or pembrolizumab was well tolerated with an encouraging objective response rate of 65% in the first-line treatment setting.
The person-to-person transmission landscape of the gut and oral microbiomes
The human microbiome is an integral component of the human body and a co-determinant of several health conditions 1 , 2 . However, the extent to which interpersonal relations shape the individual genetic makeup of the microbiome and its transmission within and across populations remains largely unknown 3 , 4 . Here, capitalizing on more than 9,700 human metagenomes and computational strain-level profiling, we detected extensive bacterial strain sharing across individuals (more than 10 million instances) with distinct mother-to-infant, intra-household and intra-population transmission patterns. Mother-to-infant gut microbiome transmission was considerable and stable during infancy (around 50% of the same strains among shared species (strain-sharing rate)) and remained detectable at older ages. By contrast, the transmission of the oral microbiome occurred largely horizontally and was enhanced by the duration of cohabitation. There was substantial strain sharing among cohabiting individuals, with 12% and 32% median strain-sharing rates for the gut and oral microbiomes, and time since cohabitation affected strain sharing more than age or genetics did. Bacterial strain sharing additionally recapitulated host population structures better than species-level profiles did. Finally, distinct taxa appeared as efficient spreaders across transmission modes and were associated with different predicted bacterial phenotypes linked with out-of-host survival capabilities. The extent of microorganism transmission that we describe underscores its relevance in human microbiome studies 5 , especially those on non-infectious, microbiome-associated diseases. Data from more than 9,700 human stool and oral metagenomes has been used to decipher the strain transmission patterns of the human microbiome from mother to infant, within households and within populations.
Influence of microbiota-associated metabolic reprogramming on clinical outcome in patients with melanoma from the randomized adjuvant dendritic cell-based MIND-DC trial
Tumor immunosurveillance plays a major role in melanoma, prompting the development of immunotherapy strategies. The gut microbiota composition, influencing peripheral and tumoral immune tonus, earned its credentials among predictors of survival in melanoma. The MIND-DC phase III trial (NCT02993315) randomized (2:1 ratio) 148 patients with stage IIIB/C melanoma to adjuvant treatment with autologous natural dendritic cell (nDC) or placebo (PL). Overall, 144 patients collected serum and stool samples before and after 2 bimonthly injections to perform metabolomics (MB) and metagenomics (MG) as prespecified exploratory analysis. Clinical outcomes are reported separately. Here we show that different microbes were associated with prognosis, with the health-related Faecalibacterium prausnitzii standing out as the main beneficial taxon for no recurrence at 2 years ( p  = 0.008 at baseline, nDC arm). Therapy coincided with major MB perturbations (acylcarnitines, carboxylic and fatty acids). Despite randomization, nDC arm exhibited MG and MB bias at baseline: relative under-representation of F. prausnitzii , and perturbations of primary biliary acids (BA). F. prausnitzii anticorrelated with BA, medium- and long-chain acylcarnitines. Combined, these MG and MB biomarkers markedly determined prognosis. Altogether, the host-microbial interaction may play a role in localized melanoma. We value systematic MG and MB profiling in randomized trials to avoid baseline differences attributed to host-microbe interactions. MIND-DC was a randomized, placebo-controlled, phase 3 trial of adjuvant blood-derived natural dendritic cell (nDC)-based therapy in patients with stage III melanoma, showing that nDC-induced immune responses did not translate into survival benefit. Here the authors report that, despite randomization, baseline differences in fecal metagenomics and serum metabolomics profiles between treatment arms might have influenced the clinical outcome of the trial.
The reasoning behind assessing push-up tests - an in depth analysis
A good exercise does not necessarily make for a good measurement tool and using such a tool may lead to wrong conclusions if used for scientific measurement and personal evaluation, yet it happens when using pushup tests which are subjective and lack reliability. This study examined the reasons behind the questionable reliability of push-up testing. Material and Methods: Fifty videorecorded 30-second push-up test performances were evaluated by 10 highly experienced raters in two separate assessment trials. The assessment involved counting the number of acceptable repetitions and identifying any technical flaws in the execution of the exercise. The collected evaluations were analyzed using quantitative and qualitative methods. Results: Statistical analysis (p < 0.05) revealed significant inter-rater differences in counting in both trials. Comparable counting was only found among raters who marked the same technique as \"perfect\" and overall concordance on perfect execution was 79.4%. Intra-rater counting reliability ranged from r = 0.57 to r = 0.92. Three main areas of technique deterioration were identified: incomplete arm extension (10.2% of denied repetitions), inadequate arm flexion (7%), and failure to keep the body straight and rigid (6.3%), which was also the most disputed between the raters. Additionally, male raters were more lenient towards the technique imperfections of female subjects. Many miscalculations were also detected, often correlated with perfect technique execution (88% of cases). The second most common cause of miscalculating was raters' willingness to count a repetition that was interrupted mid-execution due to time constraints. Conclusions: The study findings indicate that push-up assessment is highly subjective and should be avoided in scientific or personal evaluations that require a higher level of precision. The reliability of the assessment heavily depends on the individual administering the test, and the average evaluator demonstrates only moderate reliability. To mitigate gender-based bias, considering a female evaluator for female examinees is recommended. Therefore, caution is advised when relying on push-up tests when more reliable alternatives are available.
Evaluating metagenomic analyses for undercharacterized environments: what's needed to light up the microbial dark matter?
Non-human-associated microbial communities play important biological roles, but they remain less understood than human-associated communities. Here, we assess the impact of key environmental sample properties on a variety of state-of-the-art metagenomic analysis methods. In simulated datasets, all methods performed similarly at high taxonomic ranks, but newer marker-based methods incorporating metagenomic assembled genomes outperformed others at lower taxonomic levels. In real environmental data, taxonomic profiles assigned to the same sample by different methods showed little agreement at lower taxonomic levels, but the methods agreed better on community diversity estimates and estimates of the relationships between environmental parameters and microbial profiles.
Extending and improving metagenomic taxonomic profiling with uncharacterized species with MetaPhlAn 4
Metagenomic assembly enables novel organism discovery from microbial communities, but from most metagenomes it can only capture few abundant organisms. Here, we present a method - MetaPhlAn 4 - to integrate information from both metagenome assemblies and microbial isolate genomes for improved and more comprehensive metagenomic taxonomic profiling. From a curated collection of 1.01M prokaryotic reference and metagenome-assembled genomes, we defined unique marker genes for 26,970 species-level genome bins, 4,992 of them taxonomically unidentified at the species level. MetaPhlAn 4 explains ~20% more reads in most international human gut microbiomes and >40% in less-characterized environments such as the rumen microbiome, and proved more accurate than available alternatives on synthetic evaluations while also reliably quantifying organisms with no cultured isolates. Application of the method to >24,500 metagenomes highlighted previously undetected species to be strong biomarkers for host conditions and lifestyles in human and mice microbiomes, and showed that even previously uncharacterized species can be genetically profiled at the resolution of single microbial strains. MetaPhlAn 4 thus integrates the novelty of metagenomic assemblies with the sensitivity and fidelity of reference-based analyses, providing efficient metagenomic profiling of uncharacterized species and enabling deeper and more comprehensive microbiome biomarker detection. Competing Interest Statement The authors have declared no competing interest.