1,721,170 research outputs found
The Potential of Microbiome Big Data in Precision Medicine: Predicting Outcomes Through Machine Learning
No full textMassive sequencing techniques for compositional and functional profiling of the gut microbiome, a key modifier of human health, are generating thousands of data that are well suited to machine learning approaches. In particular, there is now full awareness that such microbiome data, if properly exploited, can improve the prediction of a range of clinical outcomes in disparate contexts. Here, we first discuss the importance of the gut microbiome in human physiology and pathophysiology and then provide some practical examples of machine learning applied to microbiome research in the context of specific disorders, such as obesity and cancer (with a particular focus on colorectal cancer [CRC]), in the field of personalized nutrition, and within the meta-community framework for inter-microbiome predictions. While there is still a long way to go to integrate machine learning into the clinical decision-making scheme, its potential in microbiome-based precision medicine is emerging more than ever
From whole-genome shotgun sequencing to viral community profiling: The viromescan tool
No full textViromeScan is an innovative metagenomic analysis tool that allows the viral community characterization in terms of taxonomy from raw data of metagenomics sequencing. It efficiently denoises samples from reads of other microorganisms. Users can adopt the same shotgun metagenomic sequencing data to fully characterize complex microbial ecosystems, including bacteria and viruses. Here we apply ViromeScan pipeline to some examples, thus illustrating the processes computed from raw data to the final output
The Human Gut Microbiome and Its Relationship with Osteoarthritis Pain
No full textThe gut microbiome constitutes the largest reservoir of the human microbiome and probably the one most capable of influencing the health of the whole body through multiple system-level interactions. Composed mainly of bacteria but also fungi and viruses, this microbial ecosystem is highly diverse and complex, functionally redundant, individual specific, plastic, and resilient. An alteration of its structure, i.e., dysbiosis, has been shown to participate in the onset and progression of various metabolic and inflammatory diseases. This is mainly due to the increase of opportunistic pathogens or pathobionts and/or the depletion of health-associated taxa, such as short-chain fatty acid producers, with impaired intestinal permeability (i.e., leaky gut) and altered immune signaling [1]. It is therefore not surprising that the gut microbiome can also be a crucial factor in the management of osteoarthritis (OA). Exposure to stress and pain may lead to alterations in the interactions between the brain and the intestine (i.e., the gut–brain axis) by changing gastrointestinal secretion, gut motility and permeability, and microbial gene expression and quorum-sensing signals, thus contributing to dysbiosis and increasing the rate of translocation of bacterial products or even bacteria, thereby eliciting systemic inflammation [2] (Figure 1). It has been hypothesized that patients with OA-related pain will exhibit an imbalance of the gut microbiota associated with pain intensity [3]
Editorial: Nutritional modulation of central nervous system development, maintenance, plasticity, and recovery
Full text linkAgeing and Human Gut Microbiome: The Taxonomic and Functional Transition Towards an Elderly-Type Microbiome
No full textThe gut microbiome is recognized as an important component in determining the health status of ageing individuals due to its role in modulating digestive functions, immunity and resistance to pathogen infections, and cognitive functions. Microbial data from long-lived individuals showed the progressive transition to a peculiar elderly-type microbiome, often related to immunosenescence, inflammageing, and frailty, along with the emergence of some possibly ageing-supportive features. Here, we extensively describe the characteristics of such a microbiome configuration, with a focus on the concomitant ageing-associated unavoidable physiological modifications, in order to bring out the close connections between the human host and its microbial counterpart
Simultaneous HS-SPME GC-MS determination of short chain fatty acids, trimethylamine and trimethylamine N-oxide for gut microbiota metabolic profile
No full textTrimethylamine (TMA), trimethylamine-N-oxide (TMAO) and short chain fatty acids (SCFAs), as acetic, propionic, butyric and valeric acids are among the most important products of the gut microbiota (GM) metabolism. The present study is aimed at the determination of TMA, TMAO and SCFAs by a double step headspace-solid phase microextraction (HS-SPME) and gas chromatography-mass spectrometry (GC-MS) analysis, allowing the simultaneous quantitation of both the acidic and basic metabolites in faecal samples. TMAO amount was evaluated after its reduction to TMA by using Fe(II)-EDTA complex as a reagent. Under the fully validated experimental conditions, adequate sensitivity (LOQ 0.011–0.23 μmol g−1), good accuracy (79 – 110%) and precision (CV% < 11%) were achieved for all the target analytes. The presented method is successfully applied to the quantitation of the considered gut metabolites in faecal samples from Italian healthy volunteers
Connect the dots: sketching out microbiome interactions through networking approaches
Full text linkMicrobiome networking analysis has emerged as a powerful tool for studying the complex interactions among microorganisms in various ecological niches, including the human body and several environments. This analysis has been used extensively in both human and environmental studies, revealing key taxa and functional units peculiar to the ecosystem considered. In particular, it has been mainly used to investigate the effects of environmental stressors, such as pollution, climate change or therapies, on host-associated microbial communities and ecosystem function. In this review, we discuss the latest advances in microbiome networking analysis, including methods for constructing and analyzing microbiome networks, and provide a case study on how to use these tools. These analyses typically involve constructing a network that represents interactions among microbial taxa or functional units, such as genes or metabolic pathways. Such networks can be based on a variety of data sources, including 16S rRNA sequencing, metagenomic sequencing, and metabolomics data. Once constructed, these networks can be analyzed to identify key nodes or modules important for the stability and function of the microbiome. By providing insights into essential ecological features of microbial communities, microbiome networking analysis has the potential to transform our understanding of the microbial world and its impact on human health and the environment
Microbiota-Host Transgenomic Metabolism, Bioactive Molecules from the Inside
No full textMolecular factors from the gut microbiota provide the host with the right metabolic, immunological, and neurological components to support health and well-being. However, certain circumstances can rupture the mutualistic pact with our intestinal counterpart, pushing the gut microbiome toward a dysbiotic layout, where microbiome-derived molecules may contribute to a disease state. We are now beginning to understand the microbiota-host co-regulated pathways underlying these processes, paving the way for a new era of rational piloting of the gut microbiome functions, through the design of a new generation of microbiome-targeting drugs. Microbiota-derived metabolites are emerging as promising starting hit compounds to modulate human targets, hence triggering certain pharmacological responses. In conclusion, drug discovery targeting the gut microbiota as well as the characterization of microbiota-derived metabolites can represent innovative medicinal chemistry possibilities toward the identification of novel drug candidates, targets, and more in general innovative ways for the treatment of unmet medical needs
Bile acids and oxo-metabolites as markers of human faecal input in the ancient Pompeii ruins
Full text linkSmall organic molecules, lipids, proteins, and DNA fragments can remain stable over centuries. Powerful and sensitive chemical analysis can therefore be used to characterize ancient remains for classical archaeological studies. This bio-ecological dimension of archaeology can contribute knowledge about several aspects of ancient life, including social organization, daily habits, nutrition, and food storage. Faecal remains (i.e. coprolites) are particularly interesting in this regard, with scientists seeking to identify new faecal markers. Here, we report the analysis of faecal samples from modern-day humans and faecal samples from a discharge pit on the site of the ruins of ancient Pompeii. We propose that bile acids and their gut microbiota oxo-metabolites are the most specific steroid markers for detecting faecal inputs. This is due to their extreme chemical stability and their exclusive occurrence in vertebrate faeces, compared to other ubiquitous sterols and steroids
Gut Microbiome as a Potential Marker of Hematologic Recovery Following Induction Therapy in Acute Myeloid Leukemia Patients
Full text linkBackground: The management of acute myeloid leukemia (AML) is hindered by treatment-related toxicities and complications, particularly cytopenia, which remains a leading cause of mortality. Given the pivotal role of the gut microbiota (GM) in hemopoiesis and immune regulation, we investigated its impact on hematologic recovery during AML induction therapy. Methods: We profiled the GM of 27 newly diagnosed adult AML patients using 16S rRNA amplicon sequencing and correlated it with key clinical parameters before and after induction therapy. Results: Our investigation revealed intriguing associations between the GM composition and crucial recovery indicators, including platelet, lymphocyte, and neutrophil counts, and identified early GM signatures predictive of improved hematologic recovery. Remarkably, patients demonstrating superior recovery had higher alpha diversity and enrichment in health-associated taxa belonging to the genera Faecalibacterium, Ruminococcus, Blautia, and Butyricimonas at diagnosis. Conclusions: Despite certain study limitations, our findings suggest that evaluating GM features could serve as a potential marker for hematologic recovery. This preliminary work opens avenues for personalized risk assessment and interventions, possibly involving GM modulation tools, to optimize recovery in AML patients undergoing induction therapy and potentially enhancing overall outcomes in individuals with hematologic diseases
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