Tripartite Symbiotic Digestion of Lignocellulose in the Digestive System of a Fungus-Growing Termite

Ahmad, Farhan; Yang, Guiying; Zhu, Yanxia; Poulsen, Michael; Li, Wuhan; Yu, Ting; Mo, Jianchu

doi:10.1128/spectrum.01234-22

Cited by 10 publications

(6 citation statements)

References 85 publications

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“…More importantly our results showed that SnakeMAGs was able to recover MAGs encompassing the major bacterial phyla found in termite guts, 32 , 33 and that some of these phyla were not recovered by ATLAS. Indeed, taxa belonging to Verrucomicrobiota, 34 Planctomycetota, 33 , 35 Synergistota, 36 Elusimicrobiota 37 and Acidobacteriota 38 , 39 have been repeatedly found in the gut of various termite species. As such, they would represent relevant targets for genome-centric analyses of the termite gut microbiota.…”

Section: Discussionmentioning

confidence: 99%

SnakeMAGs: a simple, efficient, flexible and scalable workflow to reconstruct prokaryotic genomes from metagenomes

Tadrent

Dedeine²

2023

F1000Res

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Background: Over the last decade, we have observed in microbial ecology a transition from gene-centric to genome-centric analyses. Indeed, the advent of metagenomics combined with binning methods, single-cell genome sequencing as well as high-throughput cultivation methods have contributed to the continuing and exponential increase of available prokaryotic genomes, which in turn has favored the exploration of microbial metabolisms. In the case of metagenomics, data processing, from raw reads to genome reconstruction, involves various steps and software which can represent a major technical obstacle. Methods: To overcome this challenge, we developed SnakeMAGs, a simple workflow that can process Illumina data, from raw reads to metagenome-assembled genomes (MAGs) classification and relative abundance estimate. It integrates state-of-the-art bioinformatic tools to sequentially perform: quality control of the reads (illumina-utils, Trimmomatic), host sequence removal (optional step, using Bowtie2), assembly (MEGAHIT), binning (MetaBAT2), quality filtering of the bins (CheckM, GUNC), classification of the MAGs (GTDB-Tk) and estimate of their relative abundance (CoverM). Developed with the popular Snakemake workflow management system, it can be deployed on various architectures, from single to multicore and from workstation to computer clusters and grids. It is also flexible since users can easily change parameters and/or add new rules. Results: Using termite gut metagenomic datasets, we showed that SnakeMAGs is slower but allowed the recovery of more MAGs encompassing more diverse phyla compared to another similar workflow named ATLAS. Importantly, these additional MAGs showed no significant difference compared to the other ones in terms of completeness, contamination, genome size nor relative abundance. Conclusions: Overall, it should make the reconstruction of MAGs more accessible to microbiologists. SnakeMAGs as well as test files and an extended tutorial are available at https://github.com/Nachida08/SnakeMAGs.

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Section: Discussionmentioning

confidence: 99%

SnakeMAGs: a simple, efficient, flexible and scalable workflow to reconstruct prokaryotic genomes from metagenomes

Tadrent

Dedeine²

2023

F1000Res

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“…Faith’s phylogenetic diversity ( 81 ) was calculated to determine phylogenetic diversity in the microbial communities, and Pielou’s evenness ( 82 ) was used for community evenness evaluation. For beta diversity, Jaccard similarity ( 83 ), Bray-Curtis dissimilarity ( 84 ), and weighted and unweighted UniFrac distances ( 85 ) were calculated,and were visualized by PCoA plots using ggplot2 ( 86 ).…”

Section: Methodsmentioning

confidence: 99%

Meta-analysis reveals the predictable dynamic development of the gut microbiota in commercial pigs

Dong,

Ricker,

Holman

et al. 2023

Microbiol Spectr

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Understanding the mechanisms of microbiome assembly during host development is crucial for successful modulation of the gut microbiome to improve host health and growth. However, results from previous microbial intervention studies to improve swine growth have largely been inconsistent due to the constantly changing nature of the gut microbiota and limited longitudinal sampling. Detailed characterization of the swine gut microbiota through meta-analysis allows us to understand the dynamics of microbial community succession, as well as the transient and natural variations between time points and animals. A total of 3,313 fecal microbial communities from over 349 pigs covering 60 time points (from birth to market age) from 14 publications were included in this meta-analysis. Despite differences in animal breeds and management, generalizable patterns of community assembly were identified. Alpha diversity continuously increased during early stages of animal growth and more slowly in the later stages. Beta regression analysis revealed that more microbial taxa were enriched, while fewer were excluded by the gut microbiota. The microbial community structure also changed significantly between days at early ages and became more similar as pigs aged, as revealed by dissimilarity and distance metrics. Dirichlet multinomial mixtures analysis supported gradient microbial clustering in longitudinal pig fecal samples, and we found that the early samples spread to more clusters than those from older pigs. Random forest regression identified 30 operational taxonomic units as potential microbial biomarkers for modeling swine gut microbiota development. External validation showed this model could be generalized to future microbiome studies conducted in suckling and weaning pigs and adds to the toolkit to quantify community succession. IMPORTANCE The swine gut microbiome undergoes an age-dependent assembly pattern with a developmental phase at early ages and a stabilization phase at later ages. Shorter time intervals and a wider range of data sources provided a clearer understanding of the gut microbiota colonization and succession and their associations with pig growth and development. The rapidly changing microbiota of suckling and weaning pigs implies potential time targets for growth and health regulation through gut microbiota manipulation. Since swine gut microbiota development is predictable, swine microbiota age can be calculated and compared between animal treatment groups rather than relying only on static time-matched comparisons.

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“…To date, the proposed mechanisms for retaining Termitomyces monocultures and suppressing the growth of pathogenic fungi within termites’ nests include social behavior, favorable nest microclimate condition maintenance, chemical secretions such as antimicrobial peptides, and the exploitation of symbiotic bacteria [ 56 , 60 ]. Apart from termites and fungi , diverse bacteria (such as Bacteroidetes, Proteobacteria, Firmicutes, Spirochaetes, Synergistota, and Actinobacteria) have been described in the guts and fungus combs of termites [ 60 , 61 ]. It is well documented that the symbiotic bacteria of termites have crucial functions in carbohydrate metabolism, cello-oligomer or lignin degradation, fungal cell wall degradation, atmospheric nitrogen fixation, reductive acetogenesis, and production of antimicrobial metabolites [ 7 , 55 , 56 , 60 , 61 ].…”

Section: Typical Examples Of Mutualisms Regarding Insects With Symbio...mentioning

confidence: 99%

“…Apart from termites and fungi , diverse bacteria (such as Bacteroidetes, Proteobacteria, Firmicutes, Spirochaetes, Synergistota, and Actinobacteria) have been described in the guts and fungus combs of termites [ 60 , 61 ]. It is well documented that the symbiotic bacteria of termites have crucial functions in carbohydrate metabolism, cello-oligomer or lignin degradation, fungal cell wall degradation, atmospheric nitrogen fixation, reductive acetogenesis, and production of antimicrobial metabolites [ 7 , 55 , 56 , 60 , 61 ]. The multipartite symbiotic system (fungus–termite–bacterium) in fungus-growing termite nests is sophisticated.…”

Section: Typical Examples Of Mutualisms Regarding Insects With Symbio...mentioning

confidence: 99%

Symbiotic Bacteria Regulating Insect–Insect/Fungus/Virus Mutualism

Chen,

Zhou,

2023

Insects

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Bacteria associated with insects potentially provide many beneficial services and have been well documented. Mutualism that relates to insects is widespread in ecosystems. However, the interrelation between “symbiotic bacteria” and “mutualism” has rarely been studied. We introduce three systems of mutualism that relate to insects (ants and honeydew-producing Hemiptera, fungus-growing insects and fungi, and plant persistent viruses and vector insects) and review the species of symbiotic bacteria in host insects, as well as their functions in host insects and the mechanisms underlying mutualism regulation. A deeper understanding of the molecular mechanisms and role of symbiotic bacteria, based on metagenomics, transcriptomics, proteomics, metabolomics, and microbiology, will be required for describing the entire interaction network.

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Tripartite Symbiotic Digestion of Lignocellulose in the Digestive System of a Fungus-Growing Termite

Cited by 10 publications

References 85 publications

SnakeMAGs: a simple, efficient, flexible and scalable workflow to reconstruct prokaryotic genomes from metagenomes

SnakeMAGs: a simple, efficient, flexible and scalable workflow to reconstruct prokaryotic genomes from metagenomes

Meta-analysis reveals the predictable dynamic development of the gut microbiota in commercial pigs

Symbiotic Bacteria Regulating Insect–Insect/Fungus/Virus Mutualism

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