Gut dysbiosis has been suggested as a major risk factor for the development of late-onset sepsis (LOS), a main cause of mortality and morbidity in preterm infants. We aimed to assess specific ...signatures of the gut microbiome, including metabolic profiles, in preterm infants <34 weeks of gestation preceding LOS.
In a single-center cohort, fecal samples from preterm infants were prospectively collected during the period of highest vulnerability for LOS (days 7, 14, and 21 of life). Following 16S rRNA gene profiling, we assessed microbial community function using microbial metabolic network modeling. Data were adjusted for gestational age and use of probiotics.
We studied stool samples from 71 preterm infants with LOS and 164 unaffected controls (no LOS/necrotizing enterocolitis). In most cases, the bacteria isolated in diagnostic blood culture corresponded to the genera in the gut microbiome. LOS cases had a decelerated development of microbial diversity. Before onset of disease, LOS cases had specific gut microbiome signatures with higher abundance of Bacilli (specifically coagulase-negative Staphylococci) and a lack of anaerobic bacteria. In silico modeling of bacterial community metabolism suggested accumulation of the fermentation products ethanol and formic acid in LOS cases before the onset of disease.
Intestinal dysbiosis preceding LOS is characterized by an accumulation of Bacilli and their fermentation products and a paucity of anaerobic bacteria. Early microbiome and metabolic patterns may become a valuable biomarker to guide individualized prevention strategies of LOS in highly vulnerable populations.
Fine-scale knowledge of the changes in composition and function of the human gut microbiome compared that of our closest relatives is critical for understanding the evolutionary processes underlying ...its developmental trajectory. To infer taxonomic and functional changes in the gut microbiome across hominids at different timescales, we perform high-resolution metagenomic-based analyzes of the fecal microbiome from over two hundred samples including diverse human populations, as well as wild-living chimpanzees, bonobos, and gorillas. We find human-associated taxa depleted within non-human apes and patterns of host-specific gut microbiota, suggesting the widespread acquisition of novel microbial clades along the evolutionary divergence of hosts. In contrast, we reveal multiple lines of evidence for a pervasive loss of diversity in human populations in correlation with a high Human Development Index, including evolutionarily conserved clades. Similarly, patterns of co-phylogeny between microbes and hosts are found to be disrupted in humans. Together with identifying individual microbial taxa and functional adaptations that correlate to host phylogeny, these findings offer insights into specific candidates playing a role in the diverging trajectories of the gut microbiome of hominids. We find that repeated horizontal gene transfer and gene loss, as well as the adaptation to transient microaerobic conditions appear to have played a role in the evolution of the human gut microbiome.
The microbial ecosystem seems to be an important player for therapeutic intervenption in inflammatory bowel disease IBD. We assessed longitudinal microbiome changes in IBD patients undergoing therapy ...with either azathioprine AZA or anti-tumour necrosis factor anti-TNF antibodies. We predicted the metabolic microbial community exchange and linked it to clinical outcome.
Faecal and blood samples were collected from 65 IBD patients at baseline and after 12 and 30 weeks on therapy. Clinical remission was defined as Crohn's Disease Activity Index CDAI < 150 in Crohn´s disease CD, partial Mayo score <2 in ulcerative colitis UC, and faecal calprotectin values <150 µg/g and C-reactive protein <5 mg/dl. 16S rRNA amplicon sequencing was performed. To predict microbial community metabolic processes, we constructed multispecies genome-scale metabolic network models.
Paired Bray-Curtis distance between baseline and follow-up time points was significantly different for UC patients treated with anti-TNF antibodies. Longitudinal changes in taxa composition at phylum level showed a significant decrease of Proteobacteria and an increase of Bacteroidetes in CD patients responding to both therapies. At family level, Lactobacilli were associated with persistent disease and Bacteroides abundance with remission in CD. In-silico simulations of microbial metabolite exchange predicted a 1.7-fold higher butyrate production capacity of patients in remission compared with patients without remission p = 0.041. In this model, the difference in butyrate production between patients in remission and patients without remission was most pronounced in the CD group treated with AZA p = 0.008.
In-silico simulation identifies microbial butyrate synthesis predictive of therapeutic efficacy in IBD.
Genome-scale metabolic models of microorganisms are powerful frameworks to predict phenotypes from an organism's genotype. While manual reconstructions are laborious, automated reconstructions often ...fail to recapitulate known metabolic processes. Here we present gapseq ( https://github.com/jotech/gapseq ), a new tool to predict metabolic pathways and automatically reconstruct microbial metabolic models using a curated reaction database and a novel gap-filling algorithm. On the basis of scientific literature and experimental data for 14,931 bacterial phenotypes, we demonstrate that gapseq outperforms state-of-the-art tools in predicting enzyme activity, carbon source utilisation, fermentation products, and metabolic interactions within microbial communities.
Imaging the distribution of metabolites is very powerful in diagnostics but it is also employed in fundamental research. Although NMR spectroscopy is well established for determining metabolic ...profiles of biological samples, its application is limited to magnetic resonance imaging that can produce images of larger structures, but the number of detectable metabolites is very low. Mass spectrometry imaging on the other hand is well established with pixel sizes in the μm range. This limits the analysis of larger structures like tissue sections and detection of metabolites depends on their ionization properties. High resolution NMR metabolomics could complement these methods. However, this is prevented due to time consuming extraction procedures. To overcome these limitations, the following protocol was established and applied to two different ham slices: sampling is directly done into the NMR tube and after extraction of polar and non-polar metabolites in the NMR tube, slice selective NMR spectra are acquired. Multivariate analysis (PCA) of the NMR-spectra and subsequent visualization of the differences correlate well with structures visible in the ham slices. The proposed protocol can be used for metabolic imaging and could complement other imaging methods.
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•Sampling and metabolite extraction in an NMR tube allows rapid sample processing.•Metabolic profiles are determined using slice-selective NMR experiments.•This approach has been applied to slices of two different ham types.•Statistical analysis identifies differences in the metabolic profiles.•Visualization of differences correlate well with structures visible in the ham slices.
Literature covered: early 2000s to late 2017Bacteria frequently exchange metabolites with other micro- and macro-organisms. In these often obligate cross-feeding interactions, primary metabolites ...such as vitamins, amino acids, nucleotides, or growth factors are exchanged. The widespread distribution of this type of metabolic interactions, however, is at odds with evolutionary theory: why should an organism invest costly resources to benefit other individuals rather than using these metabolites to maximize its own fitness? Recent empirical work has shown that bacterial genotypes can significantly benefit from trading metabolites with other bacteria relative to cells not engaging in such interactions. Here, we will provide a comprehensive overview over the ecological factors and evolutionary mechanisms that have been identified to explain the evolution and maintenance of metabolic mutualisms among microorganisms. Furthermore, we will highlight general principles that underlie the adaptive evolution of interconnected microbial metabolic networks as well as the evolutionary consequences that result for cells living in such communities.
The reconstruction and application of genome-scale metabolic network models is a central topic in the field of systems biology with numerous applications in biotechnology, ecology, and medicine. ...However, there is no agreed upon standard for the definition of the nutritional environment for these models. The objective of this article is to provide a guideline and a clear paradigm on how to translate nutritional information into an in-silico representation of the chemical environment. Step-by-step procedures explain how to characterise and categorise the nutritional input and to successfully apply it to constraint-based metabolic models. In parallel, we illustrate the proposed procedure with a case study of the growth of Escherichia coli in a complex nutritional medium and show that an accurate representation of the medium is crucial for physiological predictions. The proposed framework will assist researchers to expand their existing metabolic models of their microbial systems of interest with detailed representations of the nutritional environment, which allows more accurate and reproducible predictions of microbial metabolic processes.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Bacteria that have adapted to nutrient-rich, stable environments are typically characterized by reduced genomes. The loss of biosynthetic genes frequently renders these lineages auxotroph, hinging ...their survival on an environmental uptake of certain metabolites. The evolutionary forces that drive this genome degradation, however, remain elusive. Our analysis of 949 metabolic networks revealed auxotrophies are likely highly prevalent in both symbiotic and free-living bacteria. To unravel whether selective advantages can account for the rampant loss of anabolic genes, we systematically determined the fitness consequences that result from deleting conditionally essential biosynthetic genes from the genomes of Escherichia coli and Acinetobacter baylyi in the presence of the focal nutrient. Pairwise competition experiments with each of 20 mutants auxotrophic for different amino acids, vitamins, and nucleobases against the prototrophic wild type unveiled a pronounced, concentration-dependent growth advantage of around 13% for virtually all mutants tested. Individually deleting different genes from the same biosynthesis pathway entailed gene-specific fitness consequences and loss of the same biosynthetic genes from the genomes of E. coli and A. baylyi differentially affected the fitness of the resulting auxotrophic mutants. Taken together, our findings suggest adaptive benefits could drive the loss of conditionally essential biosynthetic genes.
In order to survive and reproduce, organisms must perform a multitude of tasks. However, trade-offs limit their ability to allocate energy and resources to all of these different processes. One ...strategy to solve this problem is to specialize in some traits and team up with other organisms that can help by providing additional, complementary functions. By reciprocally exchanging metabolites and/or services in this way, both parties benefit from the interaction. This phenomenon, which has been termed functional specialization or division of labor, is very common in nature and exists on all levels of biological organization. Also, microorganisms have evolved different types of synergistic interactions. However, very often, it remains unclear whether or not a given example represents a true case of division of labor. Here we aim at filling this gap by providing a list of criteria that clearly define division of labor in microbial communities. Furthermore, we propose a set of diagnostic experiments to verify whether a given interaction fulfills these conditions. In contrast to the common use of the term, our analysis reveals that both intraspecific and interspecific interactions meet the criteria defining division of labor. Moreover, our analysis identified non-cooperators of intraspecific public goods interactions as growth specialists that divide labor with conspecific producers, rather than being social parasites. By providing a conceptual toolkit, our work will help to unambiguously identify cases of division of labor and stimulate more detailed investigations of this important and widespread type of inter-microbial interaction.
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•The main criteria defining microbial division of labor are (1) functional complementarity, (2) a synergistic advantage, (3) negative frequency-dependent selection, and (4) positive assortment among two or more bacterial genotypes.•Division of labor results from biochemical or evolutionary trade-offs.•Division of labor can be caused by epigenetic, regulatory, or genetic mechanisms.•Division of labor is common both within and between microbial species.•Non-producers of public goods are growth specialists that divide labor with their relatives producing the public good.
The exchange of metabolites among different bacterial genotypes profoundly impacts the structure and function of microbial communities. However, the factors governing the establishment of these ...cross-feeding interactions remain poorly understood. While shared physiological features may facilitate interactions among more closely related individuals, a lower relatedness should reduce competition and thus increase the potential for synergistic interactions. Here, we investigate how the relationship between a metabolite donor and recipient affects the propensity of strains to engage in unidirectional cross-feeding interactions. For this, we performed pairwise cocultivation experiments between four auxotrophic recipients and 25 species of potential amino acid donors. Auxotrophic recipients grew in the vast majority of pairs tested (63%), suggesting metabolic cross-feeding interactions are readily established. Strikingly, both the phylogenetic distance between donor and recipient and the dissimilarity of their metabolic networks were positively associated with the growth of auxotrophic recipients. Analyzing the co-growth of species from a gut microbial community in silico also revealed that recipient genotypes benefitted more from interacting with metabolically dissimilar partners, thus corroborating the empirical results. Together, our work identifies the metabolic dissimilarity between bacterial genotypes as a key factor determining the establishment of metabolic cross-feeding interactions in microbial communities.
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•Auxotrophic and prototrophic bacteria readily engaged in metabolic cross-feeding•Recipient growth correlated with phylogenetic and metabolic distance to donors•Cross-feeding is more likely to establish between metabolically dissimilar strains
Giri et al. study the factors that determine the establishment of obligate unidirectional cross-feeding between two bacterial populations. Combining experiments with in silico simulations of a gut bacterial community, the authors show that metabolic interactions are more likely to establish between unrelated and metabolically dissimilar genotypes.
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