Leaf-shelters facilitate the colonization of arthropods and enhance microbial diversity on plants
Data files
Aug 08, 2024 version files 1.88 MB
-
Arthropods_Microbiome_GLMM_PERMANOVA.csv
-
Arthropods_T1_Permanova.csv
-
Arthropods_T2_Permanova.csv
-
insect.body.length.csv
-
metadata.T1.csv
-
metadata.T2.csv
-
Microbiome_T1.csv
-
Microbiome_T2.csv
-
otu_counts_T1.csv
-
otu_table_T2.txt
-
otu.count.T1.txt
-
otu.count.T2.txt
-
README.md
-
taxonomy.lefse.T1.tsv
-
taxonomy.lefse.T2.tsv
Abstract
Shelter-building insects are important ecosystem engineers, playing critical roles in structuring arthropod communities. Nonetheless, the influence of leaf shelters and arthropods on plant-associated microbiota remains largely unexplored. Arthropods that visit or inhabit plants can contribute to the leaf microbial community, resulting in significant changes in plant-microbe interactions. By artificially constructing leaf shelters, we provide evidence that shelter-building insects influence not only the arthropod community structure but also impact the phyllosphere microbiota. Leaf shelters exhibited higher abundance and richness of arthropods, changing the associated arthropod community composition. These shelters also altered the composition and community structure of phyllosphere microbiota, promoting greater richness and diversity of bacteria at the phyllosphere. In leaf shelters, microbial diversity positively correlated with the richness and diversity of herbivores. These findings demonstrate the critical role of leaf shelters in structuring both arthropod and microbial communities through altered microhabitats and species interactions.
README: Leaf-shelters facilitate the colonization of arthropods and enhance microbial diversity on plants
Journal: Ecology Letters
Authors:
M.S. Danilo F. B. dos Santos
M.S. Jacob E. Herschberger
M.S. Bijay Subedi
Dr. Victoria M. PociusWesley
Dr. J. Neely
Dr. Sasha E. Greenspan
Dr. C. Guilherme Becker
Dr. Gustavo Q. Romero
Dr. Mônica F. Kersch-Becker
Data collection:
Trial 1 - June 2018
Trial 2 - August 2021
Contact information:
M.S. Danilo F. B. dos Santos: dxf5343@psu.edu
Dr. Dr. Mônica F. Kersch-Becker: mfkb@psu.edu
Keywords: ecosystem engineering, plant-insect interactions, plant microbiome, leaf shelters, phyllosphere
Funding:
- Department of Entomology at the Pennsylvania State University and the USDA National Institute of Food and Agriculture and Hatch Appropriations under Project #PEN04923 and Accession #7006440.
- FAPESP (Grants 2019/08474-8,2022/10765-3 and 2023/01589-0), by a CNPq-Brazil productivity grant, and funding from the Royal Society, Newton Advanced Fellowship (Grant No. NAF/R2/180791).
- Distinguished Huck Fellowship from the Huck Institute of Life Sciences at Pennsylvania State University.
Dataset description
This dataset contains records of plant-insect-bacteria interactions through artificial leaf shelters in oak trees in North America. The study aimed to investigate the impacts of leaf shelters on the arthropod community and on the bacterial community inside the shelters. The study also aimed to investigate correlations between arthropod visits and the bacterial community in shelters.
File information
Dataset files:
- “Arthropods_Microbiome_GLMM_PERMANOVA.csv” - This is the main dataset containing records of arthropods visits and the bacterial community present in the treatments. For each treatment, control or leaf shelter, we recorded the number of arthropods and identified the arthropods in laboratory. Additionally, all leaves were swabbed for bacterial analyses. From the number of arthropods visits and the number of observed features of bacteria, community metrics such as richness, Shannon diversity, evenness, and Phylogenetic diversity were calculated. These records and metrics were use to compare the effects of shelters in arthropods and bacterial taxa. This dataset also provides the data used for the correlation analyses.
- “Arthropod_T1_Permanova.csv” and “Arthropod_T2_Permanova.csv” - These files contain the records of arthropod frequency per samples, which provide the matrix to perform the PERMANOVA test for both trials. This file provides the comparison between the community composition for arthropods between control leaves and leaf shelters.
- “Microbiome_T1.csv” and Microbiome_T2.csv” - These files contain the records of observed features of the Operational Taxonomic Units (OTUs) per samples, which provide the matrix to performa the PERMANOVA test for both trials. This file provides the comparison between the community composition for bacteria taxa between control leaves and leaf shelters.
- “insect.body.lenght.csv” - This dataset contains the measurements taken from the insects recorded in Trial 1 and the bacterial community metrics also from trial 1 to make the correlation between body size and bacterial richness.
- “metadata.T1.csv” and “metadata.T2.csv” - These are the dataset that contains the samples identity and the OTUs that were recorded in each leaf sample. These metadata will help to create the LEfSE plots.
- “otu.count.T1” and “otu.count.T2” - These dataset provide a matrix of the number of observed OTUs for each single sample. This matrix is used to calculate the relative abundance that is depicted in the LEfSE plots.
- “taxonomy.lefse.T1” and “taxonomy.lefse.T2 - These dataset contains the taxonomic information for the OTUs that were significant according to the LEfSE analyses.
File Formats:
• CSV (Comma-Separated Values) for data files.
• .R for the scripts used in R - version 4.4.1 (2024-06-14)
Variables descriptions
- File: “Arthropods_Microbiome_GLMM_PERMANOVA.csv” “plant_id” - the unique plant identity “block” - the subset of experimental unit “treatment” - the groups of leaves assigned as control or leaf shelter “trial” - the data point collection, in this case we had two datapoint collections “Omnivore_count” and all other variables that ends in “_count” represents the guild name and the frequency of arthropods for that specific guild “Omnivore_rich” and all other variables that ends in “_rich” represents the guild name and the richness of arthropods for that specific guild “Omnivore_shann” and all other variables that ends in “_shann” represents the guild name and the Shannon diversity index of arthropods for that specific guild “micro_rich” - represents the richness for the bacterial taxa “micro_phylo_div” - represents the Phylogenetic diversity index (Faith) for the bacterial taxa “micro_pielou” - represents the evenness for the bacterial taxa “micro_shann” - represents the Shannon diversity index for the bacterial taxa
- File: “Arthropod_T1_Permanova.csv” and “Arthropod_T2_Permanova.csv” “Plant-id” - the unique plant identity “treatment” - the groups of leaves assigned as control or leaf shelter “trial” - the data point collection, in this case we had two datapoint collections All other columns are arthropods identification to the lower taxonomic level possible
- File: “Microbiome_T1.csv” “Sample_Type” - represents the treatments “lf” for leaf shelter and “c” for control “ID” - represents the plant number All other columns are bacterial taxons
3.1 File: Microbiome_T2.csv”
“plant_number” - the number assigned for each plant
“treatment” - the groups of leaves assigned as control or leaf shelter
All other columns are bacterial taxons
- File: “insect.body.lenght.csv” “plant_id” - the number assigned for each plant “treatment” - the groups of leaves assigned as control or leaf shelter “mean_body_length_mm” - is the insect body length measured in millimiters “otu_richness” - represents the richness for the bacterial taxa “otu_diversity” - represents the Shannon diversity index for the bacterial taxa
- File: “metadata.T1.csv” OBS: only the two first columns are important for this file. “plant_id” - plant identity “treatment” - the groups of leaves assigned as control or leaf shelter
5.1 File: “metadata.T2.csv”
Same as in item (5)
- File: “otu.count.T1” “otu” - represents the OTUs coded as OTU1….OTUx for all OTUs found in trial 1 All the remaining columns represents the leaf treatment “lf1a…lf10a” for control and “lf1b…lf15b” for leaf shelter
6.1 File: “otu.count.T2”
Same as in item (6)
- File: “taxonomy.lefse.T1” “otu” - represents the OTUs codename “taxon” - represents the name for the bacterial species
7.1 File: “taxonomy.lefse.T2
Same as in item (7)
In all datasets “NA” represents data not available.
#LEfSE analyses on Galaxy website (http://galaxy.biobakery.org/)
Methods
Study area and system
We conducted the experiment in the southeastern plains of the United States at the J. Nicholene Bishop Biological Field Station (32°51’11” N, 87°40’22” W, Akron, AL). The experiment was conducted in June 2018 (15 pairs of trees) and in August 2021 (30 pairs of trees), and plants were 5-15 meters apart. The average minimum and maximum temperatures recorded during the experiment were 19-32°C in 2018 and 22-32°C in 2021. Throughout the experimental period of the trial conducted in June, precipitation averaged 127 mm, whereas in August 2021, it averaged 25.4 mm. The study area consisted of an oak-hickory-pine forest. We selected the white oak, Quercus alba, as a model system for constructing artificial leaf shelters. Q. alba plays an important role in providing food and shelter for numerous arthropod species (Lill & Marquis 2003; Baer & Marquis 2014). This system is ideal for studying the role of ecosystem engineers, considering the rich diversity of shelter-building insects on oaks (Quercus spp.), which are dominant canopy species in eastern North American forests (Lill & Marquis 2003; Baer & Marquis 2014). Shelter-building caterpillars occur in at least 17 Lepidoptera families including Hesperiidae, Nymphalidae, Gelechiidae, Oecophoridae, Lasiocampidae, Pyralidae, Gracillariidae, Tortricidae, Geometridae, and Erebidae (Fitzgerald et al. 1991; Fukui 2001; Lill et al. 2007). Even when present at low densities, the shelters constructed by these insects can have disproportionately large effects on the diversity and structure of arthropod communities at both local (tree-level) and regional (habitat-level) scales due to their high densities and broad distributions (Jones et al. 1994; Lill et al. 2007; Vieira & Romero 2013; Wetzel et al. 2016). The decline of this specialized group could have unprecedented consequences for their host plants and the numerous macro- and microorganisms associated with them.
Experimental design and data collection
We created artificial leaf shelters on white oak to investigate whether these structures facilitate arthropod colonization and promote phyllosphere microbial diversity. We constructed cylindrical leaf rolls with a diameter of 0.6 cm - a common size found in natural leaf shelters - using a sterilized pencil. We rolled damage-free oak leaves from adaxial to abaxial and secured them with sterilized stainless steel hair pins (7cm long and 2mm thick, U shape) (Vieira & Romero 2013). We standardized our sampling effort by conducting the experiment only on leaves between 1 and 2 meters above the ground. Control leaves received a hair pin and were left unrolled. We selected 45 oak tree pairs (90 trees in total), with each pair spaced at least two meters apart. Trees were randomly assigned to either control or leaf shelter treatment. Different pairs (blocks) were separated by at least 6 meters. For each tree, we randomly selected and marked five undamaged leaves and inspected for the presence of arthropods. To prevent cross contamination, we handled leaves and constructed the leaf shelters using disposable nitrile gloves. A new pair of gloves was used for each individual leaf. After a ten-day period, we collected all experimental leaves by encasing each leaf in a sterile plastic bag and cutting the leaf at the petiole. Before collecting the control leaves, we carefully inspected them, and if necessary, we collected all arthropods present before removing the leaves. For leaf shelters, the arthropods were consistently found inside the shelters, allowing us to collect the leaf with the arthropods inside. The leaves were kept on ice until they could be stored in a -20°C freezer. At the laboratory, we recorded the number of arthropods, identified them to the lowest taxonomic level possible, and categorized them in trophic guilds.
Phyllosphere microbiome analysis
To investigate whether leaf shelters promote microbial diversity in the phyllosphere, we swabbed all leaves with sterile cotton swabs to sample the bacterial community (Medical Wire MW113). We swabbed the surface of each leaf 30 times. In 2018 (trial 1), we used one cotton swab for all five leaves per plant. In 2021 (trial 2), we used a different cotton swab for each of the five leaves per plant. After swabbing the leaves, each swab was placed inside a 2 mL screw cap tube and dry stored at -80 °C. We extracted DNA from the swabs using the DNeasy kit (Qiagen) with slight modifications to the manufacture’s protocol to increase DNA yield (Kueneman et al. 2014). We then PCR-amplified the V4 region of the bacterial 16S rRNA gene using dual-indexed 515F and 806R barcoded-primers (Kozich et al. 2013). Pooled PCR amplicons of all the samples were purified using a QlAquick Gel Extraction Kit (Qiagen) and sent for sequencing on an Illumina MiSeq sequencer at TUFTs Genomic core facility in Boston, Massachusetts, United States. We received bacterial sequences demultiplexed by sample. Subsequently, we imported forward reads into Quantitative Insights into Microbial Ecology (QIIME2) to extract alpha and beta diversity metrics for bacterial microbiomes. Prior to analyzing sequence data, we trimmed sequences to 150 bp, filtered by quality scores, and used the Deblur pipeline to cluster sequences into operational taxonomic units (OTUs) based on 97% similarity. We assigned taxonomy to OTUs using the Greengenes 13.8 reference sequence database. We then removed chloroplast and mitochondrial sequences and removed reads from any OTU contributing less than 0.005% of total reads (Bokulich et al. 2013). We rarefied the OTU table to 1000 reads for 2018, and 1580 reads for 2021 based on rarefaction curves. The bacterial community extracted from each of the five swabs per tree in 2021 were summed to provide a single data point, except for the phylogenetic diversity, which was averaged across the swabs. The raw DNA sequences can be found on NCBI under the ID project: PRJNA1116723.
Statistical analyses
We used multivariate analysis of variance (MANOVA, Roy’s greatest root) to assess the effects of leaf shelters and year on arthropod community diversity metrics (abundance, richness, and Shannon diversity) and the main feeding guilds recorded (herbivores and predators), followed by univariate analyses. To test whether leaf shelters influence arthropod and microbial communities, we conducted a generalized linear mixed models (GLMM) with a Gaussian distribution for continuous and Poisson for count data. We modelled treatment as a fixed effect, year as a random effect, and the following variables as response variables: abundance, richness, and Shannon diversity of arthropods and richness, diversity, evenness (Pielou), and phylogenetic diversity of bacteria. To test whether leaf shelters alter arthropod and bacterial community composition, we conducted permutational multivariate analysis of variance (PERMANOVA) using the “adonis2” function and Bray-Curtis dissimilarity coefficient; we used Monte Carlo permutation (999) to test the significance of these results (Oksanen 2008). The PERMANOVA was performed using quantitative (relative abundance) data. We visualized the community composition similarity with nonmetric multidimensional scaling (NMDS). We used the “envfit” function to identify the most important species contributing to the composition of bacterial and arthropod community structures. Additionally, to investigate the relationship between bacterial diversity and arthropod abundance, richness, and diversity, we used Pearson correlation analysis using the base R function “cor.test”. This analysis was performed separately for each year due to variations in the arthropod community composition between years. We then investigated the contribution of specific arthropod guilds (herbivores and predators) to bacterial diversity. In 2021, the abundance of herbivores, omnivores and detritivores was low. Therefore, we only analyzed the relationship between predators and bacterial diversity for that year. We also conducted a Pearson correlation analysis to examine the relationship between arthropod body size and bacterial richness. To identify specific association between bacterial taxa and either of the two treatments we conducted a Linear Discriminant Analyzes Effect Size (LEfSe) to estimate the effect size of each treatment and characterize the differences between the two microbial communities. All analyses, except LefSe, were conducted in R version 4.4.1 (2024-06-14), using the “vegan”, “glmmTMB”, and “metaMDS” packages. LefSe was performed on the Huttenhower Lab Galaxy Server 2.0 website for LefSe.