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1.
Nat Commun ; 11(1): 5773, 2020 11 13.
Article in English | MEDLINE | ID: mdl-33188211

ABSTRACT

Beneficial modulation of the gut microbiome has high-impact implications not only in humans, but also in livestock that sustain our current societal needs. In this context, we have tailored an acetylated galactoglucomannan (AcGGM) fibre to match unique enzymatic capabilities of Roseburia and Faecalibacterium species, both renowned butyrate-producing gut commensals. Here, we test the accuracy of AcGGM within the complex endogenous gut microbiome of pigs, wherein we resolve 355 metagenome-assembled genomes together with quantitative metaproteomes. In AcGGM-fed pigs, both target populations differentially express AcGGM-specific polysaccharide utilization loci, including novel, mannan-specific esterases that are critical to its deconstruction. However, AcGGM-inclusion also manifests a "butterfly effect", whereby numerous metabolic changes and interdependent cross-feeding pathways occur in neighboring non-mannanolytic populations that produce short-chain fatty acids. Our findings show how intricate structural features and acetylation patterns of dietary fibre can be customized to specific bacterial populations, with potential to create greater modulatory effects at large.


Subject(s)
Dietary Fiber/pharmacology , Gastrointestinal Microbiome , Gastrointestinal Tract/metabolism , Gastrointestinal Tract/microbiology , Secondary Metabolism , Acetylation/drug effects , Animals , Butyrates/metabolism , Cecum/metabolism , Diet , Feeding Behavior/drug effects , Female , Gastrointestinal Microbiome/drug effects , Gastrointestinal Tract/drug effects , Genome , Male , Mannans/pharmacology , Metabolic Networks and Pathways/drug effects , Metagenomics , Principal Component Analysis , Proteome/metabolism , RNA, Ribosomal, 16S/genetics , Secondary Metabolism/drug effects , Swine , Wood/chemistry
2.
Microbiome ; 7(1): 97, 2019 06 27.
Article in English | MEDLINE | ID: mdl-31248462

ABSTRACT

BACKGROUND: Hospital wastewaters contain fecal material from a large number of individuals, of which many are undergoing antibiotic therapy. It is, thus, plausible that hospital wastewaters could provide opportunities to find novel carbapenemases and other resistance genes not yet described in clinical strains. Our aim was therefore to investigate the microbiota and antibiotic resistome of hospital effluent collected from the city of Mumbai, India, with a special focus on identifying novel carbapenemases. RESULTS: Shotgun metagenomics revealed a total of 112 different mobile antibiotic resistance gene types, conferring resistance against almost all classes of antibiotics. Beta-lactamase genes, including encoding clinically important carbapenemases, such as NDM, VIM, IMP, KPC, and OXA-48, were abundant. NDM (0.9% relative abundance to 16S rRNA genes) was the most common carbapenemase gene, followed by OXA-58 (0.84% relative abundance to 16S rRNA genes). Among the investigated mobile genetic elements, class 1 integrons (11% relative abundance to 16S rRNA genes) were the most abundant. The genus Acinetobacter accounted for as many as 30% of the total 16S rRNA reads, with A. baumannii accounting for an estimated 2.5%. High throughput sequencing of amplified integron gene cassettes identified a novel functional variant of an IMP-type (proposed IMP-81) carbapenemase gene (eight aa substitutions) along with recently described novel resistance genes like sul4 and blaRSA1. Using a computational hidden Markov model, we detected 27 unique metallo-beta-lactamase (MBL) genes in the shotgun data, of which nine were novel subclass B1 genes, one novel subclass B2, and 10 novel subclass B3 genes. Six of the seven novel MBL genes were functional when expressed in Escherichia coli. CONCLUSION: By exploring hospital wastewater from India, our understanding of the diversity of carbapenemases has been extended. The study also demonstrates that the microbiota of hospital wastewater can serve as a reservoir of novel resistance genes, including previously uncharacterized carbapenemases with the potential to spread further.


Subject(s)
Bacterial Proteins/genetics , Drug Resistance, Microbial/genetics , Genes, Bacterial , Hospitals , Integrons/genetics , Microbiota/genetics , Sewage/microbiology , beta-Lactamases/genetics , Anti-Bacterial Agents/pharmacology , Bacteria/drug effects , Bacteria/genetics , Humans , India , Metagenomics , Microbial Sensitivity Tests , RNA, Ribosomal, 16S/genetics , Sequence Analysis, DNA
3.
Microbiome ; 7(1): 17, 2019 02 08.
Article in English | MEDLINE | ID: mdl-30736849

ABSTRACT

BACKGROUND: Shotgun metagenome data sets of microbial communities are highly diverse, not only due to the natural variation of the underlying biological systems, but also due to differences in laboratory protocols, replicate numbers, and sequencing technologies. Accordingly, to effectively assess the performance of metagenomic analysis software, a wide range of benchmark data sets are required. RESULTS: We describe the CAMISIM microbial community and metagenome simulator. The software can model different microbial abundance profiles, multi-sample time series, and differential abundance studies, includes real and simulated strain-level diversity, and generates second- and third-generation sequencing data from taxonomic profiles or de novo. Gold standards are created for sequence assembly, genome binning, taxonomic binning, and taxonomic profiling. CAMSIM generated the benchmark data sets of the first CAMI challenge. For two simulated multi-sample data sets of the human and mouse gut microbiomes, we observed high functional congruence to the real data. As further applications, we investigated the effect of varying evolutionary genome divergence, sequencing depth, and read error profiles on two popular metagenome assemblers, MEGAHIT, and metaSPAdes, on several thousand small data sets generated with CAMISIM. CONCLUSIONS: CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with standards of truth for method evaluation. All data sets and the software are freely available at https://github.com/CAMI-challenge/CAMISIM.


Subject(s)
Computer Simulation , Gastrointestinal Microbiome/genetics , Metagenome/genetics , Metagenomics/methods , Algorithms , Animals , Humans , Mice , Models, Biological , Sequence Analysis, DNA/methods , Software
4.
Nat Methods ; 14(11): 1063-1071, 2017 Nov.
Article in English | MEDLINE | ID: mdl-28967888

ABSTRACT

Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.


Subject(s)
Metagenomics , Software , Algorithms , Benchmarking , Sequence Analysis, DNA
5.
FEMS Microbiol Ecol ; 93(3)2017 03 01.
Article in English | MEDLINE | ID: mdl-28011598

ABSTRACT

The enrichment culture BPL is able to degrade benzene with sulfate as electron acceptor and is dominated by an organism of the genus Pelotomaculum. Members of Pelotomaculum are usually known to be fermenters, undergoing syntrophy with anaerobic respiring microorganisms or methanogens. By using a metagenomic approach, we reconstructed a high-quality genome (∼2.97 Mbp, 99% completeness) for Pelotomaculum candidate BPL. The proteogenomic data suggested that (1) anaerobic benzene degradation was activated by a yet unknown mechanism for conversion of benzene to benzoyl-CoA; (2) the central benzoyl-CoA degradation pathway involved reductive dearomatization by a class II benzoyl-CoA reductase followed by hydrolytic ring cleavage and modified ß-oxidation; (3) the oxidative acetyl-CoA pathway was utilized for complete oxidation to CO2. Interestingly, the genome of Pelotomaculum candidate BPL has all the genes for a complete sulfate reduction pathway including a similar electron transfer mechanism for dissimilatory sulfate reduction as in other Gram-positive sulfate-reducing bacteria. The proteome analysis revealed that the essential enzymes for sulfate reduction were all formed during growth with benzene. Thus, our data indicated that, besides its potential to anaerobically degrade benzene, Pelotomaculum candidate BPL is the first member of the genus that can perform sulfate reduction.


Subject(s)
Benzene/metabolism , Carbon Dioxide/metabolism , Peptococcaceae/metabolism , Sulfates/metabolism , Acyl Coenzyme A/metabolism , Anaerobiosis , Metabolic Networks and Pathways , Oxidation-Reduction , Oxidoreductases Acting on CH-CH Group Donors , Proteome/metabolism
6.
PeerJ ; 4: e1603, 2016.
Article in English | MEDLINE | ID: mdl-26870609

ABSTRACT

Background. Metagenomics is an approach for characterizing environmental microbial communities in situ, it allows their functional and taxonomic characterization and to recover sequences from uncultured taxa. This is often achieved by a combination of sequence assembly and binning, where sequences are grouped into 'bins' representing taxa of the underlying microbial community. Assignment to low-ranking taxonomic bins is an important challenge for binning methods as is scalability to Gb-sized datasets generated with deep sequencing techniques. One of the best available methods for species bins recovery from deep-branching phyla is the expert-trained PhyloPythiaS package, where a human expert decides on the taxa to incorporate in the model and identifies 'training' sequences based on marker genes directly from the sample. Due to the manual effort involved, this approach does not scale to multiple metagenome samples and requires substantial expertise, which researchers who are new to the area do not have. Results. We have developed PhyloPythiaS+, a successor to our PhyloPythia(S) software. The new (+) component performs the work previously done by the human expert. PhyloPythiaS+ also includes a new k-mer counting algorithm, which accelerated the simultaneous counting of 4-6-mers used for taxonomic binning 100-fold and reduced the overall execution time of the software by a factor of three. Our software allows to analyze Gb-sized metagenomes with inexpensive hardware, and to recover species or genera-level bins with low error rates in a fully automated fashion. PhyloPythiaS+ was compared to MEGAN, taxator-tk, Kraken and the generic PhyloPythiaS model. The results showed that PhyloPythiaS+ performs especially well for samples originating from novel environments in comparison to the other methods. Availability. PhyloPythiaS+ in a virtual machine is available for installation under Windows, Unix systems or OS X on: https://github.com/algbioi/ppsp/wiki.

7.
Gigascience ; 4: 47, 2015.
Article in English | MEDLINE | ID: mdl-26473029

ABSTRACT

Software is now both central and essential to modern biology, yet lack of availability, difficult installations, and complex user interfaces make software hard to obtain and use. Containerisation, as exemplified by the Docker platform, has the potential to solve the problems associated with sharing software. We propose bioboxes: containers with standardised interfaces to make bioinformatics software interchangeable.


Subject(s)
Computational Biology , Software
8.
Cell Host Microbe ; 17(3): 392-403, 2015 Mar 11.
Article in English | MEDLINE | ID: mdl-25732064

ABSTRACT

The microbial communities inhabiting the root interior of healthy plants, as well as the rhizosphere, which consists of soil particles firmly attached to roots, engage in symbiotic associations with their host. To investigate the structural and functional diversification among these communities, we employed a combination of 16S rRNA gene profiling and shotgun metagenome analysis of the microbiota associated with wild and domesticated accessions of barley (Hordeum vulgare). Bacterial families Comamonadaceae, Flavobacteriaceae, and Rhizobiaceae dominate the barley root-enriched microbiota. Host genotype has a small, but significant, effect on the diversity of root-associated bacterial communities, possibly representing a footprint of barley domestication. Traits related to pathogenesis, secretion, phage interactions, and nutrient mobilization are enriched in the barley root-associated microbiota. Strikingly, protein families assigned to these same traits showed evidence of positive selection. Our results indicate that the combined action of microbe-microbe and host-microbe interactions drives microbiota differentiation at the root-soil interface.


Subject(s)
Bacteria/classification , Bacteria/genetics , Hordeum/microbiology , Microbiota , Plant Roots/microbiology , Cluster Analysis , DNA, Bacterial/chemistry , DNA, Bacterial/genetics , DNA, Ribosomal/chemistry , DNA, Ribosomal/genetics , Metagenomics , Molecular Sequence Data , Phylogeny , RNA, Ribosomal, 16S/genetics , Sequence Analysis, DNA
9.
Brief Bioinform ; 13(6): 646-55, 2012 Nov.
Article in English | MEDLINE | ID: mdl-22851513

ABSTRACT

Metagenome research uses random shotgun sequencing of microbial community DNA to study the genetic sequences of its members without cultivation. This development has been strongly supported by improvements in sequencing technologies, which have rendered sequencing cheaper than before. As a consequence, downstream computational analysis of metagenome sequence samples is now faced with large amounts of complex data. One of the essential steps in metagenome analysis is reconstruction of draft genomes for populations of a community or of draft 'pan-genomes' for higher level clades. 'Taxonomic binning' corresponds to the process of assigning a taxonomic identifier to sequence fragments, based on information such as sequence similarity, sequence composition or read coverage. This is used for draft genome reconstruction, if sequencing coverage is insufficient for reconstruction based on assembly information alone. Subsequent functional and metabolic annotation of draft genomes allows a genome-level analysis of novel uncultured microbial species and even inference of their cultivation requirements.


Subject(s)
Metagenome , Sequence Analysis, DNA/methods , Binding Sites , Cluster Analysis , Metagenomics
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