Alejandro Artacho

Gut microbiota disturbance during antibiotic therapy: a multi-omic approach

Objective Antibiotic (AB) usage strongly affects microbial intestinal metabolism and thereby impacts human health. Understanding this process and the underlying mechanisms remains a major research goal. Accordingly, we conducted the first comparative omic investigation of gut microbial communities in faecal samples taken at multiple time points from an individual subjected to β-lactam therapy. Methods The total (16S rDNA) and active (16S rRNA) microbiota, metagenome, metatranscriptome (mRNAs), metametabolome (high-performance liquid chromatography coupled to electrospray ionisation and quadrupole time-of-flight mass spectrometry) and metaproteome (ultra high performing liquid chromatography coupled to an Orbitrap MS2 instrument [UPLC-LTQ Orbitrap-MS/MS]) of a patient undergoing AB therapy for 14 days were evaluated. Results Apparently oscillatory population dynamics were observed, with an early reduction in Gram-negative organisms (day 6) and an overall collapse in diversity and possible further colonisation by ‘presumptive’ naturally resistant bacteria (day 11), followed by the re-growth of Gram-positive species (day 14). During this process, the maximum imbalance in the active microbial fraction occurred later (day 14) than the greatest change in the total microbial fraction, which reached a minimum biodiversity and richness on day 11; additionally, major metabolic changes occurred at day 6. Gut bacteria respond to ABs early by activating systems to avoid the antimicrobial effects of the drugs, while ‘presumptively’ attenuating their overall energetic metabolic status and the capacity to transport and metabolise bile acid, cholesterol, hormones and vitamins; host–microbial interactions significantly improved after treatment cessation. Conclusions This proof-of-concept study provides an extensive description of gut microbiota responses to follow-up β-lactam therapy. The results demonstrate that ABs targeting specific pathogenic infections and diseases may alter gut microbial ecology and interactions with host metabolism at a much higher level than previously assumed.

Altered metabolism of gut microbiota contributes to chronic immune activation in HIV-infected individuals.

Altered interplay between gut mucosa and microbiota during treated HIV infection may possibly contribute to increased bacterial translocation and chronic immune activation, both of which are predictors of morbidity and mortality. Although a dysbiotic gut microbiota has recently been reported in HIV+ individuals, the metagenome gene pool associated with HIV infection remains unknown. The aim of this study is to characterize the functional gene content of gut microbiota in HIV+ patients and to define the metabolic pathways of this bacterial community, which is potentially associated with immune dysfunction. We determined systemic markers of innate and adaptive immunity in a cohort of HIV-infected individuals on successful antiretroviral therapy without comorbidities and in healthy non-HIV-infected subjects. Metagenome sequencing revealed an altered functional profile, with enrichment of the genes involved in various pathogenic processes, lipopolysaccharide biosynthesis, bacterial translocation, and other inflammatory pathways. In contrast, we observed depletion of genes involved in amino acid metabolism and energy processes. Bayesian networks showed significant interactions between the bacterial community, their altered metabolic pathways, and systemic markers of immune dysfunction. This study reveals altered metabolic activity of microbiota and provides novel insight into the potential host–microbiota interactions driving the sustained inflammatory state in successfully treated HIV-infected patients.

Differential Effects of Antibiotic Therapy on the Structure and Function of Human Gut Microbiota

The human intestinal microbiota performs many essential functions for the host. Antimicrobial agents, such as antibiotics (AB), are also known to disturb microbial community equilibrium, thereby having an impact on human physiology. While an increasing number of studies investigate the effects of AB usage on changes in human gut microbiota biodiversity, its functional effects are still poorly understood. We performed a follow-up study to explore the effect of ABs with different modes of action on human gut microbiota composition and function. Four individuals were treated with different antibiotics and samples were taken before, during and after the AB course for all of them. Changes in the total and in the active (growing) microbiota as well as the functional changes were addressed by 16S rRNA gene and metagenomic 454-based pyrosequencing approaches. We have found that the class of antibiotic, particularly its antimicrobial effect and mode of action, played an important role in modulating the gut microbiota composition and function. Furthermore, analysis of the resistome suggested that oscillatory dynamics are not only due to antibiotic-target resistance, but also to fluctuations in the surviving bacterial community. Our results indicated that the effect of AB on the human gut microbiota relates to the interaction of several factors, principally the properties of the antimicrobial agent, and the structure, functions and resistance genes of the microbial community.

The active human gut microbiota differs from the total microbiota.

The human gut microbiota is considered one of the most fascinating reservoirs of microbial diversity hosting between 400 to 1000 bacterial species distributed among nine phyla with Firmicutes, Bacteroidetes and Actinobacteria representing around of the diversity. One of the most intriguing issues relates to understanding which microbial groups are active players in the maintenance of the microbiota homeostasis. Here, we describe the diversity of active microbial fractions compared with the whole community from raw human fecal samples. We studied four healthy volunteers by 16S rDNA gene pyrosequencing. The fractions were obtained by cell sorting based on bacterial RNA concentration. Bacterial families were observed to appear or disappear on applying a cell sorting method in which flow cytometry was used to evaluate the active cells by pyronin-Y staining of RNA. This method was able to detect active bacteria, indicating that the active players differed from that observed in raw fecal material. Generally, observations showed that in the active fractions, the number of reads related to Bacteroidetes decreased whereas several families from Clostridiales (Firmicutes) were more highly represented. Moreover, a huge number of families appeared as part of the active fraction when cell sorting was applied, indicating reads that are simply statistically hidden by the total reads.

Microbial Succession in the Gut: Directional Trends of Taxonomic and Functional Change in a Birth Cohort of Spanish Infants

In spite of its major impact on life-long health, the process of microbial succession in the gut of infants remains poorly understood. Here, we analyze the patterns of taxonomic and functional change in the gut microbiota during the first year of life for a birth cohort of 13 infants. We detect that individual instances of gut colonization vary in the temporal dynamics of microbiota richness, diversity, and composition at both functional and taxonomic levels. Nevertheless, trends discernible in a majority of infants indicate that gut colonization occurs in two distinct phases of succession, separated by the introduction of solid foods to the diet. This change in resource availability causes a sharp decrease in the taxonomic richness of the microbiota due to the loss of rare taxa (p = 2.06e-9), although the number of core genera shared by all infants increases substantially. Moreover, although the gut microbial succession is not strictly deterministic, we detect an overarching directionality of change through time towards the taxonomic and functional composition of the maternal microbiota. Succession is however not complete by the one year mark, as significant differences remain between one-year-olds and their mothers in terms of taxonomic (p = 0.009) and functional (p = 0.004) microbiota composition, and in taxonomic richness (p = 2.76e-37) and diversity (p = 0.016). Our results also indicate that the taxonomic composition of the microbiota shapes its functional capacities. Therefore, the observed inter-individual variability in taxonomic composition during succession is not fully compensated by functional equivalence among bacterial genera and may have important physiological consequences. Finally, network analyses suggest that positive interactions among core genera during community assembly contribute to ensure their permanence within the gut, and highlight an expansion of complexity in the interactions network as the core of taxa shared by all infants grows following the introduction of solid foods.

Functional consequences of microbial shifts in the human gastrointestinal tract linked to antibiotic treatment and obesity.

The microbiomes in the gastrointestinal tract (GIT) of individuals receiving antibiotics and those in obese subjects undergo compositional shifts, the metabolic effects and linkages of which are not clearly understood. Herein, we set to gain insight into these effects, particularly with regard to carbohydrate metabolism, and to contribute to unravel the underlying mechanisms and consequences for health conditions. We measured the activity level of GIT carbohydrate-active enzymes toward 23 distinct sugars in adults patients (n = 2) receiving 14-d β-lactam therapy and in obese (n = 7) and lean (n = 5) adolescents. We observed that both 14 d antibiotic-treated and obese subjects showed higher and less balanced sugar anabolic capacities, with 40% carbohydrates being preferentially processed as compared with non-treated and lean patients. Metaproteome-wide metabolic reconstructions confirmed that the impaired utilization of sugars propagated throughout the pentose phosphate metabolism, which had adverse consequences for the metabolic status of the GIT microbiota. The results point to an age-independent positive association between GIT glycosidase activity and the body mass index, fasting blood glucose and insulin resistance (r2 ≥ 0.95). Moreover, antibiotics altered the active fraction of enzymes controlling the thickness, composition and consistency of the mucin glycans. Our data and analyses provide biochemical insights into the effects of antibiotic usage on the dynamics of the GIT microbiota and pin-point presumptive links to obesity. The knowledge and the hypotheses generated herein lay a foundation for subsequent, systematic research that will be paramount for the design of “smart” dietary and therapeutic interventions to modulate host-microbe metabolic co-regulation in intestinal homeostasis.

Structural and functional changes in the gut microbiota associated to Clostridium difficile infection

Antibiotic therapy is a causative agent of severe disturbances in microbial communities. In healthy individuals, the gut microbiota prevents infection by harmful microorganisms through direct inhibition (releasing antimicrobial compounds), competition, or stimulation of the hosts immune defenses. However, widespread antibiotic use has resulted in short- and long-term shifts in the gut microbiota structure, leading to a loss in colonization resistance in some cases. Consequently, some patients develop Clostridium difficile infection (CDI) after taking an antibiotic (AB) and, at present, this opportunistic pathogen is one of the main causes of antibiotic-associated diarrhea in hospitalized patients. Here, we analyze the composition and functional differences in the gut microbiota of C. difficile infected (CDI) vs. non-infected patients, both patient groups having been treated with AB therapy. To do so we used 16S rRNA gene and metagenomic 454-based pyrosequencing approaches. Samples were taken before, during and after AB treatment and were checked for the presence of the pathogen. We performed different analyses and comparisons between infected (CD+) vs. non-infected (CD−) samples, allowing proposing putative candidate taxa and functions that might protect against C. difficile colonization. Most of these potentially protective taxa belonged to the Firmicutes phylum, mainly to the order Clostridiales, while some candidate protective functions were related to aromatic amino acid biosynthesis and stress response mechanisms. We also found that CDI patients showed, in general, lower diversity and richness than non-infected, as well as an overrepresentation of members of the families Bacteroidaceae, Enterococcaceae, Lactobacillaceae and Clostridium clusters XI and XIVa. Regarding metabolic functions, we detected higher abundance of genes involved in the transport and binding of carbohydrates, ions, and others compounds as a response to an antibiotic environment.

A probabilistic expert system for predicting the risk of Legionella in evaporative installations

Research highlights? The bacterium Legionella usually lives in water sources such as cooling towers. ? We discuss a probabilistic expert system for predicting the risk of Legionella. ? The expert system has a master-slave architecture. ? The inference engine is implemented through Bayesian reasoning. ? Bayesian networks model and connect relationships for chemical and physical variables. Early detection in water evaporative installations is one of the keys to fighting against the bacterium Legionella, the main cause of Legionnaires disease. This paper discusses the general structure, elements and operation of a probabilistic expert system capable of predicting the risk of Legionella in real time from remote information relating to the quality of the water in evaporative installations.The expert system has a master-slave architecture. The slave is a control panel in the installation at risk containing multi-sensors which continuously provide measurements of chemical and physical variables continuously. The master is a net server which is responsible for communicating with the control panel and is in charge of storing the information received, processing the data through the environment R and publishing the results in a web server.The inference engine of the expert system is constructed through Bayesian networks, which are very useful and powerful models that put together probabilistic reasoning and graphical modelling. Bayesian reasoning and Markov Chain Monte Carlo algorithms are applied in order to study the relevant unknown quantities involved in the parametric learning and propagation of evidence phases.

Impact of probiotic Saccharomyces boulardii on the gut microbiome composition in HIV-treated patients: a double-blind, randomised, placebo-controlled trial

Dysbalance in gut microbiota has been linked to increased microbial translocation, leading to chronic inflammation in HIV-patients, even under effective HAART. Moreover, microbial translocation is associated with insufficient reconstitution of CD4+T cells, and contributes to the pathogenesis of immunologic non-response. In a double-blind, randomised, placebo-controlled trial, we recently showed that, compared to placebo, 12 weeks treatment with probiotic Saccharomyces boulardii significantly reduced plasma levels of bacterial translocation (Lipopolysaccharide-binding protein or LBP) and systemic inflammation (IL-6) in 44 HIV virologically suppressed patients, half of whom (n = 22) had immunologic non-response to antiretroviral therapy (<270 CD4+Tcells/μL despite long-term suppressed viral load). The aim of the present study was to investigate if this beneficial effect of the probiotic Saccharomyces boulardii is due to modified gut microbiome composition, with a decrease of some species associated with higher systemic levels of microbial translocation and inflammation. In this study, we used 16S rDNA gene amplification and parallel sequencing to analyze the probiotic impact on the composition of the gut microbiome (faecal samples) in these 44 patients randomized to receive oral supplementation with probiotic or placebo for 12 weeks. Compared to the placebo group, in individuals treated with probiotic we observed lower concentrations of some gut species, such as those of the Clostridiaceae family, which were correlated with systemic levels of bacterial translocation and inflammation markers. In a sub-study of these patients, we observed significantly higher parameters of microbial translocation (LBP, soluble CD14) and systemic inflammation in immunologic non-responders than in immunologic responders, which was correlated with a relative abundance of specific gut bacterial groups (Lachnospiraceae genus and Proteobacteria). Thus, in this work, we propose a new therapeutic strategy using the probiotic yeast S. boulardii to modify gut microbiome composition. Identifying pro-inflammatory species in the gut microbiome could also be a useful new marker of poor immune response and a new therapeutic target.

Metagenomics of Bacterial Diversity in Villa Luz Caves with Sulfur Water Springs

New biotechnology applications require in-depth preliminary studies of biodiversity. The methods of massive sequencing using metagenomics and bioinformatics tools offer us sufficient and reliable knowledge to understand environmental diversity, to know new microorganisms, and to take advantage of their functional genes. Villa Luz caves, in the southern Mexican state of Tabasco, are fed by at least 26 groundwater inlets, containing 300–500 mg L−1 H2S and <0.1 mg L−1 O2. We extracted environmental DNA for metagenomic analysis of collected samples in five selected Villa Luz caves sites, with pH values from 2.5 to 7. Foreign organisms found in this underground ecosystem can oxidize H2S to H2SO4. These include: biovermiculites, a bacterial association that can grow on the rock walls; snottites, that are whitish, viscous biofilms hanging from the rock walls, and sacks or bags of phlegm, which live within the aquatic environment of the springs. Through the emergency food assistance program (TEFAP) pyrosequencing, a total of 20,901 readings of amplification products from hypervariable regions V1 and V3 of 16S rRNA bacterial gene in whole and pure metagenomic DNA samples were generated. Seven bacterial phyla were identified. As a result, Proteobacteria was more frequent than Acidobacteria. Finally, acidophilic Proteobacteria was detected in UJAT5 sample.