Microbiome characterization
We used both a culture-based
microbial analysis followed by Sanger sequencing and DNA metabarcoding
to quantify the microbial communities associated with household
arthropods captured by the citizen scientists (Fig. 1). For samples
collected between August 2018 and July 2019, we characterized the
composite microbiota associated with the arthropods’ morphospecies,
including exogenous (exoskeleton) and the endogenous (gut) microbiota
together. For a subset of the samples (July to October 2019), we
analysed the exogenous and the endogenous microbiota separately. This
allowed us to study whether the exogenous microbiota composition varied
seasonally and co-varied with environmental variables (e.g., temperature
and humidity).
The endogenous and
exogenous microbiota were collected from pools of up to 5 arthropods
from the same morphospecies to capture the bacterial communities’
diversity. The exogenous microbiota was collected by washing and
vortexing the arthropod pools (2850 rpm for 30 seconds) in sterile
distilled water (SDW) and pelleting the bacterial community through
centrifugation at 13000g for two minutes in an Eppendorf centrifuge
(Hamburg, Germany). Following the collection of the exogenous
microbiota, the pools were washed in 70% ethanol for 2 minutes, rinsed
with SDW, and homogenised by grinding in 1 ml of SDW using a sterile
micro pestle (Eppendorf, Hamburg, Germany), to collect the endogenous
(gut) microbiota. Both the total microbiota extracted from samples
collected between August 2018 and July 2019 and the microbiota collected
separately from endogenous and exogenous microbiota (July to October
2019), were split into two aliquots; the first aliquot was serially
diluted down to 10-4 of the initial concentration and
plated on Nutrient Agar, Mannitol Salt Agar, Violet Red Bile Glucose
Agar and Blood Agar N° 2 (Thermo Fisher Scientific Oxoid Ltd,
Basingstoke, UK); the second aliquot was used for DNA metabarcoding
(Fig. 1).
All the inoculated bacteria on agar media were incubated at 37°C for 48h
in aerobic conditions, whereas Blood agar plates were incubated both in
aerobic and anaerobic conditions. Following incubation, bacterial
colonies were counted, corrected for the number of arthropods in each
pool and the serial dilution factor and expressed as the number of
Colony Forming Units (CFU/ml/arthropod). A total of 166 colonies across
the collected samples was sequenced using Sanger sequencing technology,
following gDNA extraction with QIAamp DNA mini kit (Qiagen, Hilden,
Germany), and amplification of the 16S rRNA Vi-V2 region [27F
(5’-AGAGTTTGATCATGGCTCA-3’) and 1492R (5’-TACGGTTACCTTGTTACGACTT-3’)].
The PCR conditions were as follows: 95°C for 15 minutes, followed by 35
cycles at 95°C for 1 minute, 50°C for 1 minute, and 72°C for 1 minute. A
final extension at 72°C for 10 minutes was used. The PCR products were
purified using QIAquick PCR Purification Kit (Qiagen, Hilden, Germany)
and quantified on a 1.2% agarose gel stained with ethidium bromide
(Bio-Rad Laboratories, Hercules, California, USA). The Sanger sequencing
was completed by Eurofins Genomics, Ebersberg, Germany.
Genomic DNA for the
metabarcoding analysis was extracted from the microbiota community of
each arthropod pool using the DNeasy PowerWater kit (Qiagen, Venlo,
Netherlands) following filtration on 0.2 μm filter funnels (Thermo
Fisher Scientific, Waltham, USA). Extracted DNA was then prepared in
paired end 250bp amplicon libraries obtained with the 16S RNA V1-V2
region, using a 2 step PCR protocol with 96x96 dual tag barcoding to
facilitate multiplexing and to reduce crosstalk between samples in
downstream analyses (MacConaill et al. 2018). Negative controls
were used for PCR biases and contamination. They consisted of genomic
libraries constructed using the SDW used to wash the arthropods and of
libraries without target DNA. PCR1 and PCR2 primers, as well as
annealing temperatures per primer pair in PCR1 are in Table S1. QCs were
performed at each PCR step. Excess primer dimers and dinucleotides from
PCR1 were removed using Thermostable alkaline phosphatase (Promega) and
Exonuclease I (New England Biolabs). PCR2 amplicons were purified using
High Prep PCR magnetic beads (Auto Q Biosciences) and quantitated using
a 200 pro plate reader (TECAN) using qubit dsDNA HS solution
(Invitrogen). A standard curve was created by running standards of known
concentration on each plate against which sample concentration was
determined. PCR2 amplicons were mixed in equimolar quantities at a final
concentration of 12 pmol using a Biomek FXp liquid handling robot
(Beckman Coulter). Pooled libraries molarity was confirmed using a HS
D1000 tapestation screentape (Agilent) prior to 250bp paired end
sequencing on an Illumina MiSeq platform to obtain 100,000 reads per
sample and amplicon. The genomic libraries were prepared and sequenced
by EnviSion, Environmental BioSequencign and BioComputing at the
University of Birmingham
(https://www.envision-service.com/).
Data analysis
The sequences obtained
with Sanger technology were analysed using the software FinchTv (version
1.4.0) and taxonomically assigned using Blast V 2.12.0+ using default
parameters, following the removal of PCR primer sequences.
Metabarcoding sequences
were analysed using qiime2 (Caporaso et al. 2010). Amplicon
sequence variants (ASVs) were obtained by removing adapter primers with
the cutadapt plug-in (Martin 2011), denoising with DADA2, trimming low
quality reads, merging forward and reverse reads, dereplicating and
filtering out chimaeras (Callahan et al. 2016). Taxonomic
assignment of the 16S sequences was done using the DAIRY database (Meolaet al. 2019) , following the removal of unassigned reads with the
microDecon R package (McKnight et al. 2019).
The R-package Vegan
(Oksanen 2020) was used for statistical analysis of both the
culture-based and the metabarcoding sequences. We applied a permutation
analysis of variance (PERMANOVA) on the weighted Bray-Curtis distance
for both metabarcoding and culture-based sequences, using the Adonis
function in R (Team 2020) to quantify the effect of Arthropod family,
season (month of sampling) and environment (urban/suburban), and their
combined effects on the microbiota diversity.
We studied correlations
between environmental variables and the compositional changes of the
exogenous and endogenous microbiota. The environmental variables studied
were average air temperature, precipitation, humidity, and wind speed
obtained from the Stourbridge weather station (UK), located within a 20
Km range from the 20 households used in this study (metnet.co.uk).
Significant associations between beta diversity (weighted diversity
between samples) and environmental variables were established using a
Spearman’s rank correlation test (P < 0.05).
The bacterial families
identified through the culture-based and high throughput DNA
metabarcoding were mapped onto the approved list of biological agents
published by the Health and Safety Executive Advisory Committee on
Dangerous Pathogens ((ACDP) 2020) to identify pathogens with potential
adverse effect on human health.