Wild bees and their nests host Paenibacillus bacteria with functional potential of avail

Background

In previous studies, the gram-positive firmicute genus Paenibacillus was found with significant abundances in nests of wild solitary bees. Paenibacillus larvae is well-known for beekeepers as a severe pathogen causing the fatal honey bee disease American foulbrood, and other members of the genus are either secondary invaders of European foulbrood or considered a threat to honey bees. We thus investigated whether Paenibacillus is a common bacterium associated with various wild bees and hence poses a latent threat to honey bees visiting the same flowers.

Results

We collected 202 samples from 82 individuals or nests of 13 bee species at the same location and screened each for Paenibacillus using high-throughput sequencing-based 16S metabarcoding. We then isolated the identified strain Paenibacillus MBD-MB06 from a solitary bee nest and sequenced its genome. We did find conserved toxin genes and such encoding for chitin-binding proteins, yet none specifically related to foulbrood virulence or chitinases. Phylogenomic analysis revealed a closer relationship to strains of root-associated Paenibacillus rather than strains causing foulbrood or other accompanying diseases. We found anti-microbial evidence within the genome, confirmed by experimental bioassays with strong growth inhibition of selected fungi as well as gram-positive and gram-negative bacteria.

Conclusions

The isolated wild bee associate Paenibacillus MBD-MB06 is a common, but irregularly occurring part of wild bee microbiomes, present on adult body surfaces and guts and within nests especially in megachilids. It was phylogenetically and functionally distinct from harmful members causing honey bee colony diseases, although it shared few conserved proteins putatively toxic to insects that might indicate ancestral predisposition for the evolution of insect pathogens within the group. By contrast, our strain showed anti-microbial capabilities and the genome further indicates abilities for chitin-binding and biofilm-forming, suggesting it is likely a useful associate to avoid fungal penetration of the bee cuticula and a beneficial inhabitant of nests to repress fungal threats in humid and nutrient-rich environments of wild bee nests.

Full Text: https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-018-0614-1
by: Alexander Keller, Annette Brandel, Mira C. Becker, Rebecca Balles, Usama Ramadan Abdelmohsen, Markus J. Ankenbrand and Wiebke Sickel

Bacterial community structure and succession in nests of two megachilid bee genera

Studies on honeybees have revealed bacterial taxa which adopt key functions in the hive, in terms of nutrient uptake and immune responses. Despite solitary bees providing invaluable ecological services, the contribution of their microbial communities to larval health and the development and fitness of adults is mainly unknown. To address this gap, we conducted a 16S rDNA meta-barcoding study including larvae and stored pollen in nest chambers from two different megachilid solitary bee genera. We tested how host taxonomy, environmental context and the developmental stage of larvae determined richness and composition of associated bacterial communities. A total of 198 specimens from Osmia bicornis, Osmia caerulescens, Megachile rotundataandMegachile versicolor nests were investigated. Solitary bee bacterial microbiota in the nesting environment were mostly homogeneous within species, and not significantly affected by landscape. For each bee species, we identified bacterial taxa that showed consistent occurrence in the larvae and stored pollen. For the pollen provision, we also described a community shift with progressing larval development, suggesting a reduction of imported floral bacteria.

by: Anna Voulgari-Kokota, Gudrun Grimmer, Ingolf Steffan-Dewenter, Alexander Keller

FENNEC: Functional Exploration of Natural Networks and Ecological Communities

Assessment of species composition in ecological communities and networks is an important aspect of biodiversity research. Yet, for many ecological questions the ecological properties (traits) of organisms in a community are more informative than their scientific names. Furthermore, other properties like threat status, invasiveness, or human usage are relevant for many studies, but they can not be directly evaluated from taxonomic names alone. Despite the fact that various public databases collect such trait information, it is still a tedious manual task to enrich existing community tables with those traits, especially for large data sets. For example, nowadays, meta-barcoding or automatic image processing approaches are designed for high-throughput analyses, yielding thousands of taxa for hundreds of samples in very short time frames.

We developed the FENNEC, a web-based workbench that eases this process by mapping publicly available trait data to the user’s community tables in an automated process. We run a public instance holding traits that cover a range of topics includeing specialization, invasiveness, vulnerability, and agricultural relevance. Scientists are free to use the FENNEC as a resource for their ecological research.

Website: https://fennec.molecular.eco

Freely available at GitHub:  https://github.com/molbiodiv/fennec

Preprint: https://www.biorxiv.org/content/early/2017/09/27/194308

meta-barcoding marker demultiplexing

A single script! What it does: demultiplexing of metabarcoding data which consists of multiple markers.

  • Data must have followed a library preparation/sequencing strategy which includes sequencing of the forward primers.
  • Data must be demultiplexed for samples already.
  • Sequence data must be in forward orientation.

The categorization is based on Hidden Markov Model (HHMs) hits of the forward primer within the first 20 bp. This is very fast, and allows high throughput of the data.

GitHub: https://github.com/molbiodiv/meta-barcoding-marker-demultiplex

AliTV – Alignment Toolbox and Visualization

The comparison of genome structures of organisms can yield interesting insights into evolutionary processes. In order to do the comparison, whole genome alignments are required. However, the interpretation of whole genome alignments is difficult without proper visualization. AliTV utilizes d3.js to create interactive visualizations of whole genome alignments.

Example visualizations including the alignment of seven chloroplast genomes are available online.

Freely available at GitHub:  https://github.com/AliTVTeam/AliTV

Publication: https://peerj.com/articles/cs-116/

TBro: visualization and management of de novo transcriptomes

A web based transcriptome browser suitable for de novo transcriptomics. It has been used to analyze the Venus Flytrap transcriptome.

TBro is a web application that allows biologists to browse the vast amount of data generated by RNA-seq experiments. Powerful search options exist to find transcripts of interest. All information for each transcript is aggregated on a single page. Transcripts of interest can be organized in carts and analyzed together.

Freely available at GitHub:  https://github.com/TBroTeam/TBro

Publication: https://academic.oup.com/database/article/doi/10.1093/database/baw146/2742073

biojs-io-biom: A JavaScript library for handling data in Biological Observation Matrix (BIOM) format.

This library provides an easy to use interface to interact with data in BIOM format. The library itself is written using ES6 and is tested with Mocha. In order to provide compatibility with both versions 1.0 and 2.1 of the BIOM format a lightweight conversion server has been developed. You can find a public instance of the conversion server here.

Freely available at GitHub:  https://github.com/molbiodiv/biojs-io-biom

Publication: https://f1000research.com/articles/5-2348/v2

bcgTree: automatized phylogenetic tree building from bacterial core genomes

The need for multi-gene analyses in scientific fields such as phylogenetics and DNA barcoding has increased in recent years. In particular, these approaches are increasingly important for differentiating bacterial species, where reliance on the standard 16S rDNA marker can result in poor resolution. Additionally, the assembly of bacterial genomes has become a standard task due to advances in next-generation sequencing technologies. We created a bioinformatic pipeline, bcgTree, which uses assembled bacterial genomes either from databases or own sequencing results from the user to reconstruct their phylogenetic history. The pipeline automatically extracts 107 essential single-copy core genes, found in a majority of bacteria, using hidden Markov models and performs a partitioned maximum-likelihood analysis.

Freely available at GitHub:  https://github.com/molbiodiv/bcgTree

Publication: http://www.nrcresearchpress.com/doi/abs/10.1139/gen-2015-0175

 

Pollen/Plant ITS2 reference set for the RDP/UTAX classifier (2015)

Meta-barcoding of mixed pollen samples constitutes a suitable alternative to conventional pollen identification via light microscopy. Current approaches however have limitations in practicability due to low sample throughput and/or inefficient processing methods, e.g. separate steps for amplification and sample indexing.

We thus developed a new primer-adapter design for high throughput sequencing with the Illumina technology that remedies these issues. It uses a dual-indexing strategy, where sample-specific combinations of forward and reverse identifiers attached to the barcode marker allow high sample throughput with a single sequencing run. It does not require further adapter ligation steps after amplification. We applied this protocol to 384 pollen samples collected by solitary bees and sequenced all samples together on a single Illumina MiSeq v2 flow cell. According to rarefaction curves, 2,000–3,000 high quality reads per sample were sufficient to assess the complete diversity of 95% of the samples. We were able to detect 650 different plant taxa in total, of which 95% were classified at the species level. Together with the laboratory protocol, we also present an update of the reference database used by the classifier software, which increases the total number of covered global plant species included in the database from 37,403 to 72,325 (93% increase).

This study thus offers improvements for the laboratory and bioinformatical workflow to existing approaches regarding data quantity and quality as well as processing effort and cost-effectiveness. Although only tested for pollen samples, it is furthermore applicable to other research questions requiring plant identification in mixed and challenging samples.

Reference: Sickel W, M Ankenbrand, G Grimmer, A Holzschuh,S Härtel, J Lanzen, I Steffan-Dewenter, A Keller (2015) Increased efficiency in identifying mixed pollen samples by meta-barcoding with a dual-indexing approach. BMC Ecology 15: 20

Github: https://github.com/molbiodiv/meta-barcoding-dual-indexing