Tax4Fun2: prediction of habitat-specific functional profiles and functional redundancy based on 16S rRNA gene sequences

Environmental Microbiome, Journal Year: 2020, Volume and Issue: 15(1)

Published: May 18, 2020

Sequencing of 16S rRNA genes has become a powerful technique to study microbial communities and their responses towards changing environmental conditions in various ecosystems. Several tools have been developed for the prediction functional profiles from gene sequencing data, because numerous questions ecosystem ecology require knowledge community functions addition taxonomic composition. However, accuracy these relies on information derived genomes available public databases, which are often not representative microorganisms present studied ecosystem. In addition, there is also lack predict redundancy communities.To address challenges, we Tax4Fun2, an R package redundancies prokaryotic sequences. We demonstrate that predicted by Tax4Fun2 highly correlated metagenomes same samples. further show higher accuracies than PICRUSt Tax4Fun. By incorporating user-defined, habitat-specific genomic information, robustness substantially enhanced. with determined simulated communities.Tax4Fun2 provides researchers unique tool investigate based data. It easy-to-use, platform-independent memory-efficient, thus enabling without extensive bioinformatics or access high-performance clusters profiles. Another feature it allows calculate specific functions, potentially important measure how resilient will be perturbation. implemented freely at https://github.com/bwemheu/Tax4Fun2.

Language: Английский

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PICRUSt2: An improved and customizable approach for metagenome inference

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2019, Volume and Issue: unknown

Published: June 15, 2019

One major limitation of microbial community marker gene sequencing is that it does not provide direct information on the functional composition sampled communities. Here, we present PICRUSt2 ( https://github.com/picrust/picrust2 ), which expands capabilities original PICRUSt method 1 to predict potential a based profiles. This updated and implementation includes several improvements over previous algorithm: an expanded database families reference genomes, new approach now compatible with any OTU-picking or denoising algorithm, novel phenotype predictions. Upon evaluation, was more accurate than PICRUSt1 other current approaches overall. also flexible allows addition custom databases. We highlight these important caveats regarding use predicted metagenomes, are related inherent challenges analyzing metagenome data in general.

Language: Английский

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Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future

Frontiers in Microbiology, Journal Year: 2018, Volume and Issue: 9

Published: Sept. 25, 2018

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that inedible for humans, whilst providing metabolic energy the host producing methane. Consequently, ruminants produce meat milk, which are rich in high quality protein, vitamins minerals therefore contribute food security. As world population predicted reach approximately 9.7 billion by 2050, ruminant production has increase satisfy global protein demand, despite limited land availability, ensuring environmental impact minimised. goals can be met deepening our understanding microbiome. Attempts manipulate microbiome benefit agricultural challenges have been ongoing decades with success, mostly due lack detailed this ability culture most these outside rumen. potential meet livestock through animal breeding introduction dietary interventions during early life recently emerged as promising new technologies. Our inability phenotype high-throughput manner also hampered progress, although recent 'omic' data may allow further development mathematical models microbial gene biomarkers proxies. Advances computational tools, sequencing technologies cultivation-independent 'omics' approaches continue revolutionise This will ultimately provide knowledge framework needed solve current future challenges.

Language: Английский

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Inference-based accuracy of metagenome prediction tools varies across sample types and functional categories

Microbiome, Journal Year: 2020, Volume and Issue: 8(1)

Published: April 2, 2020

Despite recent decreases in the cost of sequencing, shotgun metagenome sequencing remains more expensive compared with 16S rRNA amplicon sequencing. Methods have been developed to predict functional profiles microbial communities based on their taxonomic composition. In this study, we evaluated performance three commonly used prediction tools (PICRUSt, PICRUSt2, and Tax4Fun) by comparing significance differential abundance predicted gene those from across different environments.We selected 7 datasets human, non-human animal, environmental (soil) samples that publicly available sequences. As would expect previous literature, strong Spearman correlations were observed between compositions relative measured However, these preserved even when genes permuted samples. This suggests simple correlation coefficient is a highly unreliable measure for tools. an alternative, PICRUSt, Tax4Fun sequenced inference models associated metadata within each dataset. With approach, found reasonable human datasets, performing better related "housekeeping" functions. degraded sharply outside inference.We conclude utility default database likely limited development specific warranted. Video abstract.

Language: Английский

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A microbial sea of possibilities: current knowledge and prospects for an improved understanding of the fish microbiome

Reviews in Aquaculture, Journal Year: 2019, Volume and Issue: 12(2), P. 1101 - 1134

Published: Aug. 13, 2019

Abstract The mucosal surfaces of fish represent an important barrier that supports and regulates a diverse array microbial assemblages contributes to the overall health fitness host. For farmed species, knowledge how these host–microbial systems adapt respond various stressors is pivotal for managing health, nutrition optimizing productivity in aquaculture. While our understanding communities factors shape them now suggest balanced microbiota critical healthy functioning fish, mechanisms behind interactions are still poorly understood. Much existing research has focused on characterizing taxonomic diversity different across body (e.g. skin, gills gastrointestinal tract), response changing nutrition, environmental conditions. However, specific functional contributions (or members) remain elusive, especially or diseased fish. Here, we review current their interplay likely involvement with We also seek address identify gaps explore future prospects improving

Language: Английский

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The Role of the Gut Microbiome in Cattle Production and Health: Driver or Passenger?

Annual Review of Animal Biosciences, Journal Year: 2020, Volume and Issue: 8(1), P. 199 - 220

Published: Feb. 15, 2020

Ruminant production systems face significant challenges currently, driven by heightened awareness of their negative environmental impact and the rapidly rising global population. Recent findings have underscored how composition function rumen microbiome are associated with economically valuable traits, including feed efficiency methane emission. Although omics-based technological advances in last decade revolutionized our understanding host-associated microbial communities, there remains incongruence over correct approach for analysis large omic data sets. A that examines host/microbiome interactions both lower digestive tract is required to harness full potential gastrointestinal sustainable ruminant production. This review highlights animal community may identify exploit causal relationships between gut host traits interest a practical application health

Language: Английский

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Review: Ruminal microbiome and microbial metabolome: effects of diet and ruminant host

animal, Journal Year: 2020, Volume and Issue: 14, P. s78 - s86

Published: Jan. 1, 2020

The rumen contains a great diversity of prokaryotic and eukaryotic microorganisms that allow the ruminant to utilize ligno-cellulose material convert non-protein nitrogen into microbial protein obtain energy amino acids. However, fermentation also has potential deleterious consequences associated with emissions greenhouse gases, excessive excreted in manure may adversely influence nutritional value products. While several strategies for optimizing use by ruminants have been suggested, better understanding key involved their activities is essential manipulate processes successfully. Diet most obvious factor influencing microbiome fermentation. Among dietary interventions, ban antimicrobial growth promoters animal production systems led an increasing interest plant extracts rumen. Plant (e.g. saponins, polyphenol compounds, oils) shown decrease methane improve efficiency utilization; however, there are limitations such as inconsistency, transient adverse effects feed additives ruminants. It proved host population both heritable trait through effect early-life nutrition on structure function adult Recent developments allowed phylogenetic information be upscaled metabolic information; research effort cultivation in-depth study characterization needed. introduction integration metagenomic, transcriptomic, proteomic metabolomic techniques offering greatest reaching truly systems-level rumen; studies focused broader approach needs considered.

Language: Английский

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On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Microbial Genomics, Journal Year: 2024, Volume and Issue: 10(2)

Published: Feb. 29, 2024

Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation function. To mitigate this, tools PICRUSt2, Tax4Fun2, PanFP MetGEM infer profiles from sequencing data using different algorithms. Prior studies have cast doubts on quality these predictions, motivating us systematically evaluate matched metagenomic datasets, simulated data. Our contribution is threefold: (i) data, we investigate if technical biases could explain discordance between inferred expected results; (ii) considering human cohorts type two diabetes, colorectal cancer obesity, test health-related differential abundance measures categories are concordant gene-inferred metagenome-derived and; (iii) since copy number an confounder in inference, customised normalisation with rrnDB database improve results. results show that gene-based inference generally do not necessary sensitivity delineate changes microbiome should thus be used care. Furthermore, outline differences individual tested recommendations tool selection.

Language: Английский

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Microbiome diversity and dysbiosis in aquaculture

Reviews in Aquaculture, Journal Year: 2020, Volume and Issue: 13(2), P. 1077 - 1096

Published: Oct. 27, 2020

Abstract With the continuous growth of human population and associated need for high‐quality protein, aquaculture sector will be required to increase significantly in productivity. This productivity achieved through more efficient use resources like feeds, genetic improvement limiting impacts disease. One key links between animal disease is that microbial diversity, with high‐throughput sequencing technologies increasing our understanding role microorganisms play health, development physiology vertebrate invertebrate hosts alike. Increasing microbial–host interactions help avoid or manage dysbiosis systems final aim improving We review current literature, which indicates there an association diversity systems, as changes bacterial microbiomes are implicated performance, both viral origin, triggered by environmental stressors diet choice. Dysbiosis, whether form loss beneficial bacteria, expansion pathogens potentially harmful microorganisms, can used indicator tool monitoring purposes. Development management strategies towards preserving balance, including maintaining host, critical health cultured aquatic animals likely aquaculture.

Language: Английский

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Rumen Microbiome Composition Is Altered in Sheep Divergent in Feed Efficiency

Frontiers in Microbiology, Journal Year: 2020, Volume and Issue: 11

Published: Aug. 25, 2020

Rumen microbiome composition and functioning is linked to animal feed efficiency, particularly for bovine ruminants. To investigate this in sheep, we compared rumen bacterial archaeal populations (and predicted metabolic processes) of sheep divergent the efficiency trait conversion ratio (FCR). In our study 50 Texel cross Scottish Blackface (TXSB) ram lambs were selected from an original cohort 200 lambs. From these, 26 further experimentation based on their extreme (High Feed Efficiency, HFE=13; Low LFE=13). Animals fed a 95% concentrate diet ad libitum over 36 days. 16S rRNA amplicon sequencing was used communities liquid solid fractions FCR. Weighted UniFrac distances separated HFE LFE archaea fraction (Permanova, P0.1) diversity (P>0.1) not affected by FCR phenotype. Only genus Prevotella 1 differentially abundant between cohorts. Although no major compositional shifts identified amongst efficient cohorts (FDR>0.05), correlation analysis putative drivers with Ruminococcaceae UCG-014 (liquid, rho=-0.53; solid, rho=-0.56) Olsenella (solid, rho=-0.40) exhibiting significant negative association (P<0.05). Bifidobacterium Megasphera showed positive correlations ADG. Major cellulolytic bacteria Fibrobacter rho=0.43) Ruminococcus rho=0.41; rho=41) correlated positively Our provides evidence that likely influenced changes community, abundance specific bacteria, rather than overall within microbiome.

Language: Английский

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