Plant &lt;i&gt;n&lt;/i&gt;-alkane production from litterfall altered the diversity and community structure of alkane degrading bacteria in litter layer in lowland subtropical rainforest in Taiwan

Abstract. n-Alkane and alkane-degrading bacteria have long been used as crucial biological indicators of paleoecology, petroleum pollution, and oil and gas prospecting. However, the relationship between n-alkane and alkane-degrading bacteria in natural forests is still poorly understood. In this study, long-chain n-alkane (C14–C35) concentrations in litterfall, litter layer, and topsoil as well as the diversity and abundance of n-alkane-degrading bacterial communities in litter layers were investigated in three habitats across a lowland subtropical rainforest in southern Taiwan: ravine, windward, and leeward habitats in Nanjenshan. Our results demonstrate that the litterfall yield and productivity of long-chain n-alkane were highest in the ravine habitats. However, long-chain n-alkane concentrations in all habitats were decreased drastically to a similar low level from the litterfall to the bulk soil, suggesting a higher rate of long-chain n-alkane degradation in the ravine habitat. Operational taxonomic unit (OTU) analysis using next-generation sequencing data revealed that the relative abundances of microbial communities in the windward and leeward habitats were similar and different from that in the ravine habitat. Data mining of community amplicon sequencing using the NCBI database revealed that alkB-gene-associated bacteria (95 % DNA sequence similarity to alkB-containing bacteria) were most abundant in the ravine habitat. Empirical testing of litter layer samples using semi-quantitative polymerase chain reaction for determining alkB gene levels confirmed that the ravine habitat had higher alkB gene levels than the windward and leeward habitats. Heat map analysis revealed parallels in pattern color between the plant and microbial species compositions of the habitats, suggesting a causal relationship between the plant n-alkane production and microbial community diversity. This finding indicates that the diversity and relative abundance of microbial communities in the litter layer are affected by n-alkane plant composition in the litterfall.

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Plant n-alkane production from litterfall altered the diversity and community structure of alkane degrading bacteria in litter layer in lowland subtropical rainforest in Taiwan

10.5194/bg-2017-161 ◽

2017 ◽

Author(s):

Tung-Yi Huang ◽

Bing-Mu Hsu ◽

Wei-Chun Chao ◽

Cheng-Wei Fan

Keyword(s):

Microbial Communities ◽

Relative Abundance ◽

Metagenomic Data ◽

Next Generation Sequencing Data ◽

Litter Layer ◽

Natural Forests ◽

Sequencing Data ◽

Alkb Gene ◽

Degrading Bacteria ◽

Long Chain

Abstract. n-Alkane and alkane-degrading bacteria have long been used as important biological indicators in paleoecology, petroleum pollution and oil and gas prospecting. However, their relationships in natural forests are still poorly understood. In this study, long chain n-alkane (C14-C35) levels of plants in litterfall, litter layer and topsoil and the diversity and abundance of n-alkane-degrading bacterial community in litter layer were investigated in 3 habitats across a lowland subtropical rainforest in southern Taiwan, i.e. the ravine habitat, the windward habitat and leeward habitat in Nanjenshan. Our results demonstrated that the litterfall production and flux of long chain n-alkane in ravine area were highest among all habitats. However, long chain n-alkane concentration formed a steep gradient to a similar level from the litterfall to the bulk soil in all habitats, suggesting a higher degrading rate of long chain n-alkane in ravine habitat. The operational taxonomic unit (OTU) analysis from next generation sequencing data revealed that the relative abundance of microbial communities in windward and leeward habitats were similar to each other and different from ravine habitat. Metagenomic data mining by NCBI database revealed that alkB gene associated bacterial (95 % similarity to alkB contained bacteria in DNA sequence) were highest in ravine area compared to other habitats. Empirical testing of litter-layer samples by semi-quantitative PCR in alkB gene levels confirmed that ravine habitat had higher alkB gene levels than windward and leeward habitats. Heat map analysis revealed a parallel in the color pattern between plant vegetation and microbial species-composition of habitats, suggesting a causal relationship between the plant n-alkane production and the diversity of microbial communities. This finding indicated that the diversity and relative abundance of microbial communities in litter layer were affected by the n-alkane composition in litterfall derived by plant vegetation.

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Microbial Communities on Plastic Polymers in the Mediterranean Sea

Frontiers in Microbiology ◽

10.3389/fmicb.2021.673553 ◽

2021 ◽

Vol 12 ◽

Author(s):

Annika Vaksmaa ◽

Katrin Knittel ◽

Alejandro Abdala Asbun ◽

Maaike Goudriaan ◽

Andreas Ellrott ◽

...

Keyword(s):

Microbial Communities ◽

Mediterranean Sea ◽

Amplicon Sequencing ◽

Polymer Surfaces ◽

Rrna Gene ◽

Sequencing Data ◽

Microbial Biofilms ◽

Degrading Bacteria ◽

The Mediterranean

Plastic particles in the ocean are typically covered with microbial biofilms, but it remains unclear whether distinct microbial communities colonize different polymer types. In this study, we analyzed microbial communities forming biofilms on floating microplastics in a bay of the island of Elba in the Mediterranean Sea. Raman spectroscopy revealed that the plastic particles mainly comprised polyethylene (PE), polypropylene (PP), and polystyrene (PS) of which polyethylene and polypropylene particles were typically brittle and featured cracks. Fluorescence in situ hybridization and imaging by high-resolution microscopy revealed dense microbial biofilms on the polymer surfaces. Amplicon sequencing of the 16S rRNA gene showed that the bacterial communities on all plastic types consisted mainly of the orders Flavobacteriales, Rhodobacterales, Cytophagales, Rickettsiales, Alteromonadales, Chitinophagales, and Oceanospirillales. We found significant differences in the biofilm community composition on PE compared with PP and PS (on OTU and order level), which shows that different microbial communities colonize specific polymer types. Furthermore, the sequencing data also revealed a higher relative abundance of archaeal sequences on PS in comparison with PE or PP. We furthermore found a high occurrence, up to 17% of all sequences, of different hydrocarbon-degrading bacteria on all investigated plastic types. However, their functioning in the plastic-associated biofilm and potential role in plastic degradation needs further assessment.

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Pyrosequencing Assessment of Soil Microbial Communities in Organic and Conventional Potato Farms

Plant Disease ◽

10.1094/pdis-02-10-0090 ◽

2010 ◽

Vol 94 (11) ◽

pp. 1329-1335 ◽

Cited By ~ 67

Author(s):

Akifumi Sugiyama ◽

Jorge M. Vivanco ◽

Sastry S. Jayanty ◽

Daniel K. Manter

Keyword(s):

Microbial Community ◽

Genetic Distance ◽

Microbial Communities ◽

Relative Abundance ◽

Quantitative Polymerase Chain Reaction ◽

Soil Microbial Communities ◽

Pythium Ultimum ◽

Community Diversity ◽

Organic Farms ◽

Conventional Farms

Organic farming is frequently touted as being beneficial to soil health by increasing microbial community diversity; however, contradictory results exist in the literature. In this study, we compared several organic and conventional potato farms in Colorado for differences in soil nutrients and microbial communities using 454 pyrosequencing of the 18S ribosomal RNA gene. Organic farms showed a slightly higher diversity and evenness within the microbial community compared with conventional farms. No difference in the number of observed or estimated total operational taxonomic units (OTUs) was observed between management strategies. However, the relative abundance of 16 OTUs (3% genetic distance) differed between the organic and conventional farms, with seven increasing and nine decreasing in organic farms. A variety of known potato fungal pathogens (e.g., Alternaria spp., Ulocladium spp., and Pythium ultimum) were detected in the soil, including three different OTUs (3% genetic distance) with a high homology to the early blight pathogen Alternaria solani. Relative abundance for Alternaria spp. was higher in conventional farms (relative abundance 30.15 versus 7.8%), whereas the relative abundance for P. ultimum was higher in organic farms (relative abundance 0.25 versus 0.05%). Quantitative polymerase chain reaction, using primers specific for A. solani, Phoma foveata, and Pythium ultimum, yielded similar results to the pyrosequencing, validating the use of pyrosequencing data for the quantification of OTU relative abundances.

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SMN1 copy-number and sequence variant analysis from next generation sequencing data

10.1101/2020.03.31.014589 ◽

2020 ◽

Author(s):

Daniel Lopez-Lopez ◽

Carlos Loucera ◽

Rosario Carmona ◽

Virginia Aquino ◽

Josefa Salgado ◽

...

Keyword(s):

Next Generation Sequencing ◽

Copy Number ◽

Muscular Atrophy ◽

Sequence Similarity ◽

Homozygous Deletion ◽

Next Generation Sequencing Data ◽

Sequence Variant ◽

Next Generation ◽

Sequencing Data ◽

Generation Sequencing

AbstractSpinal Muscular Atrophy (SMA) is a severe neuromuscular autosomal recessive disorder affecting 1/10,000 live births. Most SMA patients present homozygous deletion of SMN1, while the vast majority of SMA carriers present only a single SMN1 copy. The sequence similarity between SMN1 and SMN2, and the complexity of the SMN locus makes the estimation of the SMN1 copy-number by next generation sequencing (NGS) very difficult Here, we present SMAca, the first python tool to detect SMA carriers and estimate the absolute SMN1 copy-number using NGS data. Moreover, SMAca takes advantage of the knowledge of certain variants specific to SMN1 duplication to also identify silent carriers. This tool has been validated with a cohort of 326 samples from the Navarra 1000 Genomes project (NAGEN1000). SMAca was developed with a focus on execution speed and easy installation. This combination makes it especially suitable to be integrated into production NGS pipelines. Source code and documentation are available on Github at: www.github.com/babelomics/SMAca

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PaPrBaG: A random forest approach for the detection of novel pathogens from NGS data

10.7287/peerj.preprints.2379v1 ◽

2016 ◽

Author(s):

Carlus Deneke ◽

Robert Rentzsch ◽

Bernhard Y Renard

Keyword(s):

Random Forest ◽

Sequence Similarity ◽

Next Generation Sequencing Data ◽

Reference Database ◽

Sequencing Data ◽

Bacterial Strains ◽

Bacterial Genomes ◽

Pathogenicity Prediction ◽

Ngs Data ◽

Reference Genomes

The reliable detection of novel bacterial pathogens from next generation sequencing data is a key challenge for microbial diagnostics. Current computational tools usually rely on sequence similarity and often fail to detect novel species when closely related genomes are unavailable or missing from reference database used. Here, we present the random forest based approach PaPrBaG (Pathogenicity Prediction for Bacterial Genomes). PaPrBaG overcomes genetic divergence by training on a wide set of species with known pathogenicity phenotype. To that end we generated a novel label source of pathogenic and non-pathogenic bacterial strains, using a rule-based protocol to annotate pathogenicity based on genome metadata. A detailed comparative study reveals that PaPrBaG has several advantages over sequence similarity approaches. Most importantly, it always provides a prediction whereas other approaches discard a large number of sequencing reads that are far away from currently known reference genomes. Furthermore, PaPrBaG remains reliable even at very low genomic coverages. Combining PaPrBaG with existing approaches further improves prediction results.

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Complete genome sequences of Streptomyces spp. isolated from disease-suppressive soils

10.21203/rs.2.10524/v1 ◽

2019 ◽

Author(s):

Stephen C Heinsch ◽

Suzie Hsu ◽

Lindsey Otto-Hanson ◽

Linda Kinkel ◽

Michael Smanski

Keyword(s):

Microbial Communities ◽

Natural Product ◽

De Novo ◽

Sequence Similarity ◽

Gene Clusters ◽

Sequencing Data ◽

Sample Number ◽

Genus Streptomyces ◽

Streptomyces Sp ◽

Streptomyces Spp

Abstract Background Bacteria within the genus Streptomyces remain a major source of new natural product discovery and as soil inoculants in agriculture where they promote plant growth and protect from disease. Recently, Streptomyces spp. have been implicated as important members of naturally disease-suppressive soils. To shine more light on the ecology and evolution of disease-suppressive microbial communities, we have sequenced the genome of three Streptomyces strains isolated from disease-suppressive soils and compared them to previously sequenced isolates. Strains selected for sequencing had previously showed strong phenotypes in competition or signaling assays. Results Here we present the de novo sequencing of three strains of the genus Streptomyces isolated from disease-suppressive soils to produce high-quality complete genomes. Streptomyces sp. GS93-23, Streptomyces sp. 3211-3, and Streptomyces sp. S3-4 were found to have linear chromosomes of 8.24 Mb, 8.23 Mb, and greater than 7.5 Mb, respectively. In addition, two of the strains were found to have large, linear plasmids. Each strain harbors between 26 and 38 natural product biosynthetic gene clusters, on par with previously sequenced Streptomyces spp.. We compared these newly-sequenced genomes with those of previously sequenced organisms. We see substantial natural product biosynthetic diversity between closely related strains, with the gain/loss of episomal DNA elements being a primary driver of genome evolution. Conclusions Long read sequencing data facilitates large contig assembly for high-GC Streptomyces genomes. While the sample number is too small for a definitive conclusion, we do not see evidence that disease suppressive soil isolates are particularly privileged in terms of numbers of BGCs. The strong sequence similarity between GS93-23 and previously isolated Streptomyces lydicus suggests that species recruitment may contribute to the evolution of disease-suppressive microbial communities.

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Comparison of microbiome samples: methods and computational challenges

Briefings in Bioinformatics ◽

10.1093/bib/bbaa121 ◽

2020 ◽

Author(s):

Matteo Comin ◽

Barbara Di Camillo ◽

Cinzia Pizzi ◽

Fabio Vandin

Keyword(s):

Next Generation Sequencing ◽

Microbial Communities ◽

Species Identification ◽

Disease Status ◽

Next Generation Sequencing Data ◽

Data Sets ◽

Efficient Computation ◽

Sequencing Data ◽

Reference Genomes ◽

Generation Sequencing

Abstract The study of microbial communities crucially relies on the comparison of metagenomic next-generation sequencing data sets, for which several methods have been designed in recent years. Here, we review three key challenges in the comparison of such data sets: species identification and quantification, the efficient computation of distances between metagenomic samples and the identification of metagenomic features associated with a phenotype such as disease status. We present current solutions for such challenges, considering both reference-based methods relying on a database of reference genomes and reference-free methods working directly on all sequencing reads from the samples.

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Complete genome sequences of Streptomyces spp. isolated from disease-suppressive soils

10.21203/rs.2.10524/v2 ◽

2019 ◽

Author(s):

Stephen C Heinsch ◽

Suzie Hsu ◽

Lindsey Otto-Hanson ◽

Linda Kinkel ◽

Michael Smanski

Keyword(s):

Microbial Communities ◽

Natural Product ◽

De Novo ◽

Sequence Similarity ◽

Gene Clusters ◽

Sequencing Data ◽

Sample Number ◽

Genus Streptomyces ◽

Streptomyces Sp ◽

Streptomyces Spp

Abstract Bacteria within the genus Streptomyces remain a major source of new natural product discovery and as soil inoculants in agriculture where they promote plant growth and protect from disease. Recently, Streptomyces spp. have been implicated as important members of naturally disease-suppressive soils. To shine more light on the ecology and evolution of disease-suppressive microbial communities, we have sequenced the genome of three Streptomyces strains isolated from disease-suppressive soils and compared them to previously sequenced isolates. Strains selected for sequencing had previously showed strong phenotypes in competition or signaling assays. Results Here we present the de novo sequencing of three strains of the genus Streptomyces isolated from disease-suppressive soils to produce high-quality complete genomes. Streptomyces sp. GS93-23, Streptomyces sp. 3211-3, and Streptomyces sp. S3-4 were found to have linear chromosomes of 8.24 Mb, 8.23 Mb, and greater than 7.5 Mb, respectively. In addition, two of the strains were found to have large, linear plasmids. Each strain harbors between 26 and 38 natural product biosynthetic gene clusters, on par with previously sequenced Streptomyces spp.. We compared these newly-sequenced genomes with those of previously sequenced organisms. We see substantial natural product biosynthetic diversity between closely related strains, with the gain/loss of episomal DNA elements being a primary driver of genome evolution. Conclusions Long read sequencing data facilitates large contig assembly for high-GC Streptomyces genomes. While the sample number is too small for a definitive conclusion, we do not see evidence that disease suppressive soil isolates are particularly privileged in terms of numbers of BGCs. The strong sequence similarity between GS93-23 and previously isolated Streptomyces lydicus suggests that species recruitment may contribute to the evolution of disease-suppressive microbial communities.

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