Differing Dietary Nutrients and Diet-associated Bacteria has Limited Impact on Spider Gut Microbiota Composition

doi:10.21203/rs.3.rs-732177/v1

Download PDF

Research Article

Differing Dietary Nutrients and Diet-associated Bacteria has Limited Impact on Spider Gut Microbiota Composition

https://doi.org/10.21203/rs.3.rs-732177/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 15 Nov, 2021

Read the published version in Microorganisms →

Version 1

posted

You are reading this latest preprint version

Spiders are a key predator of insects across ecosystems and possess great potential as pest control agents. Unfortunately, it is difficult to artificially cultivate multiple generations of most spider species. Since gut bacterial flora has been shown to significantly alter nutrient availability, it is plausible that the spiders’ microbial community play a key role in their unsuccessful breeding. However, both the gut microbial composition and its influencing factors in many spiders remain a mystery. In this study, the gut microbiota of Campanicola campanulata, specialist prey on ants and are widely distributed across China, was characterized. After, the impact of diet and diet-associated bacteria on gut bacterial composition was evaluated. First, two species of prey ants (Lasius niger and Tetramorium caespitum) were collected from different locations and fed to C. campanulata. For each diet, we then profiled the nutritional content of the ants, as well as the bacterial communities of both the ants and spiders. Results showed that the protein and carbohydrate content varied between the two prey ant species, and that the bacterial communities of the ants were clearly delineated by collection site. However, no significant differences were found in the gut microbiota of spiders that were fed the differing ants. Together, these results indicate that nutritional variation and diet-associated bacterial differences have a limited impact on the microbial composition of spider guts, suggesting that spiders have a mechanism keeping their gut bacterial community stable to ensure normal physiological function and development.

Behavioral Ecology

General Microbiology

gut microbiota

spider

diet regime

ants

nutrient

diet-associated microbes

Spiders are some of the most successful animals that use venom for their survival, and arguably consume the most diverse range of prey [1]. They are abundant and inhabit a wide range of habitats, from household crevices to rocks and vegetation reaching up to 22,000 ft. of altitude [2]. Spiders play a crucial role in biological pest control in paddy fields, orchards, cotton fields, and tea gardens [3–5]. Consequently, the artificial protection and breeding of spiders in both agricultural and forest systems can provide an alternative pest management strategy to chemical insecticides, while also facilitating ecological restoration. However, artificially breeding most spiders has proven challenging, either due to external environmental controls (temperature, humidity etc.) or inner factors resulting from environment determining the female sexual maturity, inducing the low spider survival rates in the laboratory [6]. Previous studies have shown that while spiders can digest a variety of foods, several spider taxon are specialized to prey on ants [7–9], which are also difficult to breed artificially. According to previous studies, bacteria associated with spider diets could be involved in the unsuccessful breeding of host animals (e.g., Pollock et al demonstrated that diet is linked to breeding success in blue tits (Cyanistes caeruleus)). Our previous study suggests a similar phenomenon in bugs [10, 11]. Thus, we speculate that the specialized monodietary regimes contribute to the low survival rates of spiders. Whether the unsuccessful spider breeding attempts are linked to a nutrient deficiency, and how these dietary regimens impact spiders, remains unknown.

Some evidence has suggested that gut bacterial community has a significant impact on host’s digestion, nutritional acquisition, and juvenile development [7], which are often linked to the overall community structure [12–14]. Previous studies have examined both gut bacterial diversity and biological functions in a wide range of arthropods [15–18], demonstrating the critical role of the bacterial community found in arthropod guts [19–21]. Previous studies have also illustrated that the composition of the gut microbiota is easily influenced by numerous biotic and abiotic factors, including gut structure, the physiological environment, pH, oxygen levels, intestinal immune system, and the developmental stage. Of these, diet and dietary microbiota are the most important factors [22, 23]. Considering their complicated dietary regimens and diverse gut microbiota, spiders provide a good model to explore the degree to which diet or diet-acquired microbes impact the gut bacterial community. A lot of studies on microorganisms within spiders have focused on endosymbionts and their reproductive effects on their hosts [24–26], while other studies have identified the gut microbiomes in three spider species [27]; analyzed the heritability of microbial communities within spiders [28]; and demonstrated that the gut microbiota of the Ariamnes spider, which is found in the Hawaiian islands, to be fairly conserved for over 2 million years [29]. However, considering both the abundance and variety of spiders, there is a lack of knowledge about their gut microbiota and how this bacterial composition is influenced or maintained [30].

Campanicola campanulata [31] is widely distributed across China and plays an important role in the soil arthropod community [32]. While most spiders are euryphagous, it is one of the few spiders to predate ants, making it a unique case study. C. campanulata lives in a bell-shaped nest that opens downward. It is made up of small, dry branches and fallen leaves, and is normally found in sand or clay near the soil layer. This can effectively deceive predators and increase their chances of survival [33]. In this study, two ants preyed upon by C. campanulata (Lasiu niger and Tetramorium caespitum) were collected from different geographic sites and fed to the spiders. The nutritional content in both ants was then quantified, as were the 16S rRNA V3-V4 high variable regions of the feed ants and the gut bacterial community of C. campanulata. Despite huge dietary variation at both the nutritional and microbial levels, our study highlighted a potentially novel gut regulatory mechanism in spiders and lay the foundation for future investigations into spider gut microbiota.

2.1 Sample collection and rearing

C. campanulata were collected from a field in Yingshan, Hubei, China (31°5'33"N, 115°48'26"E). All samples were collected during the same season from April to June 2019, transported to the laboratory, and starved for at least 7 days before the feed experiments. The ants selected as the food source for this study were divided into three groups according to their species and collection sites: Lasius niger (LN_WH) and Tetramorium caespitum (TC_WH) were collected from Hubei University, Wuhan, China (30°24'39.09"N, 114°19'56.88"E), and another group of Tetramorium caespitum (TC_LY) was collected from the Shuanglong mountain forest park, Luoyang, Henan, China (34°31'4.32"N, 112°43'53.06"E). The spiders were then randomly divided into the three groups and fed on one ant type (CC-LN_WH, CC-TC_WH, CC-TC_LY); 3–5 ants were put into the container at a time, and the ant carcasses were checked to confirm that spiders had fed. Spiders were dissected 48 h after feeding. The spiders and ants used in this study were all identified as non-endangered and nonprotected species.

Before dissection, spiders were surface sterilized with 70% ethanol and rinsed three times with sterile water to remove surface contaminants[34, 27, 35, 30]. While this wash will not entirely remove surface contamination, it should not enable a high signal in gut microbiota analysis. The oral cavity and stomach were separated and the entire abdomen excised for testing. The midguts were not removed due to their small sizes. Gut samples were stored in 1.5 mL microcentrifuge tubes at − 80°C for further analysis. Ant analysis was performed directly on the whole body. Ants were washed with 70% ethanol and sterile water and kept at − 80°C until DNA extraction. Six spiders and 10 ants were pooled into each group. Five replicates were performed in each biological analysis. All operations were performed in an aseptic environment.

2.2 Measurements of dietary nutrients in ants

Proteins, carbohydrates, and lipids are primary structural units in ants and the main nutritional constituents in the diet of Arthropoda. Four nutritional indices were quantified in the feed ants, including protein, glucose, triglyceride (TG), and trehalose concentrations. Before quantification, each ant sample was weighted with a precision electronic microbalance (METTLER TOLEDO). Considering that each individual ant was very small, fifteen ants were combined into one sample for analyzed concurrently. The protein content of each sample was analyzed with the Easy II protein quantitative kit (Tran). Glucose was measured using a glucose assay kit (Oxidase method). TG content was determined with TG assay kit (Nanjing Jiancheng Bioengineering Institute). The concentration of trehalose was quantified with a trehalose assay kit (Nanjing Jiancheng Bioengineering Institute), following the manufacturer’s instructions.

2.3 DNA extraction and PCR amplification

Microbial community genomic DNA of each pooled sample was extracted using a DNeasy Blood & Tissue Kit (Qiagen) following the manufacturer's instructions. The DNA extract was checked on 1% agarose gel, and DNA concentration and purity were determined with NanoDrop 2000 UV-vis spectrophotometer (Thermo Scientific, Wilmington, USA). The hypervariable region V3-V4 of the bacterial 16S rRNA gene were amplified with primer pairs (338F: 5'-ACTCCTACGGGAGGCAGCAG-3' and 806R: 5'-GGACTACHVGGGTWTCTAAT-3') by an ABI GeneAmp® 9700 PCR thermocycler (ABI, CA, USA), with an eight-base sequence barcode unique to each sample at the 5′ end of 338F and 806R, respectively. The PCR amplification was carried out in a total volume of 20 µL containing 0.8 µL of each primer, 10 ng of template DNA, 4 µL of 5 × FastPfu Buffer, 2 µL of 2.5 mM dNTPs, 0.4 µL of FastPfu Polymerase, 0.2 µL of BSA, and Supplement ddH₂O to 20 µL. The following parameters were used in the PCRs: denaturation for 3 min at 95°C and 30 cycles of denaturation for 30 s at 95°C, annealing for 30 s at 53°C, and elongation at 72°C for 45 s. For the last cycle, the elongation time was extended to 10 min at 72°C. The PCR product was extracted from 2% agarose gel and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) according to manufacturer’s instructions and quantified using QuantiFluor™ -ST (Promega, USA).

2.4 Illumina MiSeq sequencing and bioinformatic processing

Total community DNA was used for amplification and sequencing of the 16S rRNA, targeting the variable V3–V4 regions. Purified amplicons were pooled in equimolar and paired-end sequenced on an Illumina MiSeq platform (Illumina, San Diego, USA) according to the standard protocols by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). The raw 16S rRNA gene sequencing reads were demultiplexed, quality-filtered by Trimmomatic and merged by FLASH with the following criteria: (i) the 300 bp reads were truncated at any site receiving an average quality score of < 20 over a 50 bp sliding window, and the truncated reads shorter than 50 bp were discarded; (ii) exact barcode matching, 2 nucleotides mismatch in primer matching, and reads containing ambiguous characters were removed; and (iii) only overlapping sequences longer than 10 bp were assembled according to their overlapped sequence. Reads that could not be assembled were discarded. Operational taxonomic units (OTUs) with 97%, that often used in QIIME (1.9.1) similarity cutoff were clustered using UPARSE (version 7.1, http://drive5.com/uparse/), and chimeric sequences were identified and removed using UCHIME. The taxonomy of each OTU representative sequence was analyzed by RDP Classifier (http://rdp.cme.msu.edu/) against the 16S rRNA database using confidence threshold of 0.7. All steps were implemented in a Snakemake workflow. The raw pyrosequencing data was obtained and deposited in the NCBI Sequence Read Archive under the BioProjects ID: PRJNA742878.

2.5 Statistical analyses

The experimental design consisted of six groups, including three kinds of ants (LN_WH, TC_WH, TC_LY) and the spiders (CC-LN_WH, CC-TC_WH, CC-TC_LY) eating different ants. For downstream analysis, we took the obtained OTUs table and prepared a “filtered table” (v.2.5) using QIIME (1.9.1) custom scripts. First, we extracted from the OTUs table the bacteria domain using the command split_otu_table_by_taxonomy.py. OTUs tables were rarefied to a minimum sample depth, while rarefaction curves were produced with the vegan package in R, and evaluated whether the sequencing depth was saturated. To calculate the diversity indexes, we used the alpha_diversity.py and alpha_rarefaction.py commands to obtain Shannon, Simpson, ACE and Chao1, observed OTU. A Venn diagram was visualized using the R package software to show unique and shared microbial compositions. We compared the diversity indices between spider or ant groups using a one-way analysis of variance (ANOVA). ANOVA was also used to assess the statistical differences between in genus abundance between the spider or ant groups. Results with P < 0.05 between groups were considered statistically significant. Principal coordinate analysis (PCoA) of the Bray-Curtis dissimilarity distances were conducted at the genus level, and a Permutational Multivariate Analysis of Variance, based on the weighted UniFrac distance (PERMANOVA), was used to identify differences in genus abundance between the sample groups using the QIIME software package. A heatmap was generated based on the relative abundance of the genera. Data were analyzed using SPSS 19.0 and figures were drawn using GraphPad Prism 6.

3.1 Analysis of nutritional composition

We quantified the nutritional composition of three different varieties of ants, revealing significant differences between L. niger and T. caespitum species regardless of their collection sites (Fig. 1), while no difference was found for the same species of ants collected from two different sites (Figure S1). The concentration of TG in L. niger (0.0055 mmol/mg organism) was markedly lower than in T. caespitum (0.0314 mmol/mg, P < 0.05; Fig. 1c). Similarly, trehalose levels in L. niger (6.322 mg/100 mg organism) were significantly lower than in T. caespitum (9.284 mg/100 mg organism, P < 0.001; Fig. 1b). Conversely, the protein concentration in L. niger (0.093 mg/100 mg organism) was distinctly higher than T. caespitum (0.071 mg/100 mg organism, P < 0.05; Fig. 1a). Lastly, there were no significant differences in glucose content between the two ant species (0.319–0.411 mmol/mg for both; Fig. 1d), or between ants of the same species from different locations. These data highlighted the substantial nutritional difference between the two prey ant species.

3.2 The diversity analysis of the bacterial community

In total, 1,677,627 usable sequences were obtained from 29 samples. Among which, 1,116,358 high-quality sequences were selected, with an average of 38,495 sequences per sample. Table S1 lists genera with an abundance of at least 1% of the total number of OTUs found in the sample. The rarefaction curves were constructed based on S_obs to verify the adequacy of the sampling depth and were generated from randomly subsampled datasets with the same number of 16S sequences. The rarefaction curve reached saturation for each sequencing sample (Supplementary Fig. 2). The rank-abundance curve showed that the OTUs of all samples increased gradually and then held at stable values with increasing numbers of measured sequences, indicating that most bacterial sequences obtained by the MiSeq sequencing system reflect the abundance and diversity of the microbiota (Figure S3). The CC-LN_WH curve had a large range on the horizontal axis, meaning that the richness of this group was higher than the other two groups. The bacterial species in the CC-TC_LN group was more evenly distributed because its curve was flatter than in the other two groups (Figure S3).

3.3 Composition of bacterial community

To facilitate the analysis of which microbial species were common or unique among the samples, while Venn diagrams of the different groups were drawn based on their source: spiders or ants (Fig. 2). The gut microbial composition among spiders showed a little difference, however, the quantity of microbial OTUs in spiders fed with T. caespitum from Wuhan was significantly lower than the other groups, even though there were not fewer T. caespitum species than in other ants. The alpha diversity was estimated using the ACE, Chao1, Shannon, and Simpson indices (Table 1), while there were no significant differences between the gut samples of C. campanulata for the OTU numbers or the ACE, Chao1, Shannon, and Simpson indices. However, the Shannon index of the TC_LY group was significantly higher value and the Simpson’s index was significantly lower than the other two groups of ants (Table 1, Duncan’s new multiple range test, P < 0.01).

PCoA resulted in a 2-dimensional solution of ants in which, PC1 accounted for 61.49% of the variation and PC2 for 25.34% (Fig. 3a, PERMANOVAR, P = 0.002). PCoA based on the spiders revealed that the first two principal component scores accounted for 67.87% and 21.88% of the variation, respectively (Fig. 3b, PERMANOVAR, P = 0.776). These graphs demonstrate that all three spider groups were clustered together, indicating that their communities have a similar composition. The ant groups differed significantly (Supplementary Table 2). Bar graphs exhibiting the differences in the six dominant species of microbiota further validate the findings of PCoA (Fig. 4). While there was significant variation among ants (Fig. 4a), the dominant microbiota species in spiders were of the same genus (Fig. 4b). The genus with the highest relative abundance was Pseudomonas.

Quantified comparison of the five most abundant genera revealed no significant differences in the relative abundances of microbiota, at the genus level, among the three spider groups (Fig. 5b). The composition of ant microbiotas distinguished T. caespitum from Luoyang, as significantly less abundant than ants from Wuhan in both Pseudomonas and Enterobacteriaceae (Fig. 5a). A heat map, in which the difference in the abundance distribution of species between samples could be quantified by distance graphically, showed that at genus, microbial community in the six groups of spiders or ants. And also revealed that there were differences in the abundance of the microbial community phyla in some different groups (Fig. 5c). Pseudomonas had the highest abundance among the six groups and had different relative abundances in both spiders and ants. T. caespitum from Luoyang also differed from the other two ant-feed groups (Fig. 5c). Overall, these results indicate that there was no clear division among the three groups of spiders, but that the ants could not be clustered into a single region.

It is becoming increasingly understood that the gut microbiota can influence body development, physiology, and ecological inter- or intraspecific interactions [36–39]. The microbial community, however, is also plastic. Several factors can alter the composition of the gut microbial community [22, 23] and thus have the potential to shape the community function [40, 22]. According to prior studies, the influence of many factors on the microbiota is context dependent and might only be observed above a certain threshold; for instance, the composition of the predominant termite gut microbiota remained largely constant despite variations in diet [41]. In contrast, dietary differences markedly altered the gut bacterial community in gypsy moths [42]. However, studies on whether and/or which factors shape the gut microbiota of widespread predators—such as spiders—that play a key role in ecosystem stability have rarely been reported. We fed spiders with three groups of ants, which all had different nutritional contents and microbiota. We then profiled the gut bacterial communities of the spiders under different dietary conditions and identified how variations in nutrients or diet-associated bacteria affected spiders’ gut microbiota. Considering the relatively slow digestion and the strikingly endurance of starvation of the spider, the spiders were dissected 48 hours after feeding with ants. Furthermore, a pilot experiment showed that the starvation for at least 7 days had no obvious effect on total abundance of the spider’s gut microbiota. Our results demonstrated that the gut bacterial communities were similar across diets, despite differences in nutritional content or ingested microbes. Discrepancies between the two studies indicate that further research is needed to better understand the relationship between spider food and the stability of their gut microbiota.

Variations in both nutritional level and the microbial community associated with their prey can both influence predator’s gut microbiota [43], we collected two species of ants from different geographic sites to research food induced gut bacterial community changes. Previous studies suggested that feeding fish with certain species improve muscle function [37]. The protein content in diets varies considerably even in the same species [44]. To achieve a more comprehensive measurement of dietary differences, we evaluated compositional variations in protein, GT, trehalose, and glucose levels, three of which varied significantly between the L. niger and T. caespitum ant diets. In a previous study of ants, the authors found similarities in the bacterial communities between species of the same trophic level [45]. Conversely, some studies have provided evidence that the bacteria community is significantly varied across species rather than biogeography [46, 37]. To determine whether the microorganisms in spiders’ food impact their gut microbiota, we analyzed the microbial diversity of feed ants, examining both different species and the same species from different locations. We found that the microbiota composition of the feed ants varied significantly, despite all belonging to Formicidae. In our results, both geographic location and species impacted gut microbiota to varying degrees. Accordingly, spiders were divided into three groups and fed on one diverse ant subset, to assess if variations in feed created variations in spider gut microbiota.

We used Illumina MiSeq sequencing of 16S rRNA genes to test whether spiders that ate different ants would also exhibit a difference in microbial composition. Our results demonstrated that the gut microbiota in all spiders maintained a consistent composition, with Pseudomonas as the dominant genus, which is known for its metabolic diversity and its ability to colonize many niches, including the gut [47]. To ensure the abundance of Pseudomonas did not result from contamination, we performed negative extraction and PCR control, which was visualized using a 2% agarose gel. Our results found no band for the negative extraction and PCR control and an obvious band for the positive control. The presence of this OTU makes it likely to be unintentionally sequenced, however, this OTU accounted for more than 90% of total sequences in our experimental samples. Our results indicate that the high percentage of Pseudomonas in our study was not due to contamination. Compared with common spiders living in cotton fields (where 237 genera were detected at the genus level [27]), C. campanulata could maintain a relatively simple gut environment. This could be due to its limited diet. Intriguingly, Badumna Longinqua, whose diet includes crickets and fruit flies, showed the opposite result [48]. And its gut microbiome experiences pronounced temporal fluctuations and slowly approaches its initial state after more than 658 h. The difference between the results obtained by our study and that of previous research could be due to several factors, including the different spider species used and their rearing conditions. Their prey typically contains a rich microbiome, and the spiders sometimes ingest and maintain certain microbes from prey in their gut. This mimics a pattern of stability in the spider’s gut microbiota. Additionally, spider habitat and taxonomy could influence their gut microbiota [49], however, without knowing the natural state of the spider microbiomes obtained from the field, we can only conclude that the gut bacterial communities in groups fed different diets were similar, despite differences in their nutrients or ingested microbes.

Comparing the composition of the microbial community between predators and prey at the intraspecific level, we found that C. campanulata could maintain a relatively high level of Pseudomonas, which has been reported to produce tannase to detoxify or tolerate tannis in food [50, 51]. Interestingly, we detected no Acinetobacter in the spiders, despite its prevalence in the feed ants. This implies that not all microorganisms obtained from food can successfully colonize a spider gut, suggesting the host can prevent the colonization of new bacteria, possibly as a way to defend against pathogens [52]. In most cases, the intestinal bacterial community is short-lived and opportunistic, with widely diverse bacteria stemming from a constantly changing environment [53–55]. This stabilization of gut microbial diversity could be due to microbial competition or interference following the introduction of exogenous bacteria [56], however, further investigation is required to confirm either of these hypotheses.

The life history of spiders has rarely been studied due to a lack of reliable rearing methods and the difficulty of providing an artificial diet. Since spiders are primarily carnivorous, they require specific kinds of prey. Divina M. Analin et al. found that the survival rate of sac spiders was influenced by different artificial diets [57]. Several studies have demonstrated that the animal gut microbiome is important for nutritional absorption [58], while the diet-altered gut microbiota of spiders can influence its development and survival rate under artificial rearing conditions. Future work assessing whether or how gut microbiomes affect spider survival should be the focus of future studies.

In conclusion, when we analyzed the microbial composition in three spider groups with different diets, we observed no dynamic changes in gut microbiota. This indicates that diet has minimal effect on gut microbiota of C. campanulata, despite variations in feed microbial community and nutrients, ensuring normal physiological function and development. It is worth noting that identifying a mechanism by which this action takes place was beyond the scope of this study. Future studies should include additional types of prey and spiders to analyze these results on a larger scale and outline a potential mechanism for host regulation in gut microbial homeostasis. The analysis of spiders’ intestinal microbiota in conjunction with soil layer microorganisms analysis is also worthwhile endeavor, to determine if the dominant microorganisms in the spiders’ gut microbiota are a result of their environment. This work provides a blueprint for future investigation into the gut microorganisms of spiders and highlights the potential existence of a unique gut modulatory mechanism.

Acknowledgements We thank the members of the Center for Behavioural Ecology and Evolution, School of Life Sciences, Hubei University (CBEE) for samples collection. This study was financially supported by National Natural Sciences Foundation of China (NSFC-31970406/31772420/31573236).

Author’s Contributions JL and LX conceived and designed the experiments; WZ and FL performed the experiments and analyzed the data; WZ prepared the manuscript; RH and LX edited the manuscript.

Conflict of Interest The authors declare that they have no conflict of interest.

Data Availability Statement All data used in this study are available from the NCBI SRA under the BioProjects ID: PRJNA742878 (https://www.ncbi.nlm.nih.gov/sra/PRJNA742878).

Saez NJ, Senff S, Jensen JE, Er SY, Herzig V, Rash LD, King GF (2010) Spider-venom peptides as therapeutics. Toxins (Basel) 2(12):2851–2871
Masram SC, Sonarghare PC, Khaparde KP, Sahare CP, Sonparote R U (2015) Spider Diversity of Visvesvaraya National Institute of Technology Campus, Nagpur. International Journal of Researches In Biosciences, Agriculture & Technology (3)
Michalko R, Pekár S (2015) The biocontrol potential of Philodromus (Araneae, Philodromidae) spiders for the suppression of pome fruit orchard pests. Biol Control 82:13–20
Nyffeler M, Sunderland KD (2003) Composition, abundance and pest control potential of spider communities in agroecosystems: a comparison of European and US studies. Agr Ecosyst Environ 95(2–3):579–612
Marc P, Canard A, Ysnel F (1999) Spiders (Araneae) useful for pest limitation and bioindication. Agriculture Ecosystems Environment 74:229–273
Moura RR, Vasconcellos-Neto J, Gonzaga MO (2020) Female sexual maturity as a determining factor of size-assortative pairing in the protandrous spider Manogea porracea (Araneae, Araneidae). Zoologischer Anzeiger 284:1–6
Zheng Y, Xiao G, Zhou W, Gao Y, Li Z, Du G, Chen B (2020) Midgut microbiota diversity of potato tuber moth associated with potato tissue consumed. BMC Microbiol 20(1):58
Dippenaar-Schoeman AS, Md J, Avd B (1996) Ammoxenus species (Araneae: Ammoxenidae) - specialist predators of harvester termites in South Africa. African Plant Protection 2:103–109
Jackson RR, Whitehous MEA (1986) The biology of New Zealand and Queens– land pirate spiders (Araneae, Mimetidae) aggressive mimicry, araneoph– agy and prey specialization. The Zoological Society of London 210:279–303
Luo J, Cheng Y, Guo L, Wang A, Lu M, Xu L (2021) Variation of gut microbiota caused by an imbalance diet is detrimental to bugs' survival. Sci Total Environ 771:144880
Pollock CJ, Capilla-Lasheras P, McGill RAR, Helm B, Dominoni DM (2017) Integrated behavioural and stable isotope data reveal altered diet linked to low breeding success in urban-dwelling blue tits (Cyanistes caeruleus). Sci Rep 7(1):5014
Stevick RJ, Post AF, Gomez-Chiarri M (2021) Functional plasticity in oyster gut microbiomes along a eutrophication gradient in an urbanized estuary. Anim Microbiome 3(1):5
Li J, Li C, Wang M, Wang L, Liu X, Gao C, Ren L, Luo Y (2021) Gut Structure and Microbial Communities in Sirex noctilio (Hymenoptera: Siricidae) and Their Predicted Contribution to Larval Nutrition. Front Microbiol 12:641141
Jahnes BC, Poudel K, Staats A, Nicholas S, Sabree ZL (2021) Microbial Colonization Promotes Model Invertebrate Gut Tissue Growth and Development. Research Square
Anjum SI, Shah AH, Aurongzeb M, Kori J, Azim MK, Ansari MJ, Bin L (2018) Characterization of gut bacterial flora of Apis mellifera from north-west Pakistan. Saudi Journal of Biological Sciences 25(2):388–392
Muturi EJ, Ramirez JL, Rooney AP, Kim C-H (2017) Comparative analysis of gut microbiota of mosquito communities in central Illinois. PLoS Neglected Tropical Diseases 11(2):e0005377
Snyman M, Gupta AK, Bezuidenhout CC, Claassens S, van den Berg J (2016) Gut microbiota of Busseola fusca (Lepidoptera: Noctuidae). World J Microbiol Biotechnol 32(7):115
Waite DW, Dsouza M, Biswas K, Ward DF, Deines P, Taylor MW (2015) Microbial community structure in the gut of the New Zealand insect Auckland tree weta (Hemideina thoracica). Arch Microbiol 197:603–612
Thong-On A, Suzuki K, Noda S, Inoue J, Kajiwara S, Ohkuma M (2012) Isolation and characterization of anaerobic bacteria for symbiotic recycling of uric acid nitrogen in the gut of various termites. Microbes Environments 27(2):186–192
Engel P, Martinson VG, Moran NA (2012) Functional diversity within the simple gut microbiota of the honey bee. Proc Natl Acad Sci USA 109(27):11002–11007
Hongoh Y (2011) Toward the functional analysis of uncultivable, symbiotic microorganisms in the termite gut. Cell Mol Life Sci 68(8):1311–1325
Engel P, Moran NA (2013) The gut microbiota of insects - diversity in structure and function. Federation of European Microbiological Societies Microbiology Reviews 37(5):699–735
Domingo-Salvany A, Hartnoll RL, Maguire A, Brugal MT, Albertin P, Cayla JA, Casabona J, Suelves JM (1998) Analytical considerations in the use of capture-recapture to estimate prevalence: Case studies of the estimation of opiate use in the metropolitan area of barcelona, Spain. Am J Epidemiol 148(8):732–740
Duron O, Hurst GD, Hornett EA, Josling JA, Engelstadter J (2008) High incidence of the maternally inherited bacterium Cardinium in spiders. Mol Ecol 17(6):1427–1437
Goodacre SL, Martin OY, Thomas CF, Hewitt GM (2006) Wolbachia and other endosymbiont infections in spiders. Mol Ecol 15(2):517–527
Rowley SM, Raven RJ, McGraw EA (2004) Wolbachia pipientis in Australian spiders. Curr Microbiol 49(3):208–214
Hu G, Zhang L, Yun Y, Peng Y (2019) Taking insight into the gut microbiota of three spider species: No characteristic symbiont was found corresponding to the special feeding style of spiders. Ecology Evolution 9(14):8146–8156
Dunaj SJ, Bettencourt BR, Garb JE, Brucker RM (2020) Spider phylosymbiosis: divergence of widow spider species and their tissues' microbiomes. BMC Evol Biol 20(1):104
Armstrong EE, Perez-Lamarque B, Bi K, Chen C, Becking LE, Lim JY, Linderoth T, Krehenwinkel H, Gillespie R (2020) A holobiont view of island biogeography: unraveling patterns driving the nascent 2 diversification of a Hawaiian spider and its microbial associates. BioRxiv. (preprint doi: https://doi.org/10.1101/2020.12.07.414961)
Eksc K, Wolters V, Michalczechen-Lacerda VA (1997) Spiders, carabids, and staphylinids the ecological potential of predatory macroarthropods. G Benckiser:307–362
Zhangfu C (1993) A new species of the genus Achaearanea from Zhejiang Province (Araneae: Theridiidae). Acta Zootaxonomica Sinica 18:36–38
Li Z, Agnarsson I, Peng Yu, Liu J (2021) Eight cobweb spider species from China building detritus-based bell-shaped retreats (Araneae, Theridiidae). Zookeys. (submitted)
Ma N, Yu L, Gong D, Hua Z, Zeng H, Chen L, Mao A, Chen Z, Cai R, Ma Y, Zhang Z, Li D, Luo J, Zhang S, Grindstaff J (2020) Detritus decorations as the extended phenotype deflect avian predator attack in an orb-web spider. Funct Ecol 34(10):2110–2119
Catalog WS (2020) World Spider Catalog. Natural History Museum Bern
Hammer TJ, Dickerson JC, Fierer N (2015) Evidence-based recommendations on storing and handling specimens for analyses of insect microbiota. PeerJ 3:e1190
Ceja-Navarro JA, Vega FE, Karaoz U, Hao Z, Jenkins S, Lim HC, Kosina P, Infante F, Northen TR, Brodie EL (2015) Gut microbiota mediate caffeine detoxification in the primary insect pest of coffee. Nat Commun 6:7618
Linnenbrink M, Wang J, Hardouin EA, Kunzel S, Metzler D, Baines JF (2013) The role of biogeography in shaping diversity of the intestinal microbiota in house mice. Mol Ecol 22(7):1904–1916
Douglas AE (2013) Microbial brokers of insect-plant interactions revisited. J Chem Ecol 39(7):952–961
Visotto LE, Oliveira MG, Guedes RN, Ribon AO, Good-God PI (2009) Contribution of gut bacteria to digestion and development of the velvetbean caterpillar, Anticarsia gemmatalis. J Insect Physiol 55(3):185–191
Bost A, Franzenburg S, Adair KL, Martinson VG, Loeb G, Douglas AE (2018) How gut transcriptional function of Drosophila melanogaster varies with the presence and composition of the gut microbiota. Mol Ecol 27(8):1848–1859
Wang Y, Su L, Huang S, Bo C, Yang S, Li Y, Wang F, Xie H, Xu J, Song A (2016) Diversity and resilience of the wood-feeding higher termite Mironasutitermes shangchengensis gut microbiota in response to temporal and diet variations. Ecology Evolution 6(22):8235–8242
Broderick NA, Raffa KF, Goodman RM, Handelsman J (2004) Census of the bacterial community of the gypsy moth larval midgut by using culturing and culture-independent methods. Appl Environ Microbiol 70(1):293–300
Zudaire E, Simpson SJ, Montuenga LM (1998) Effects of food nutrient content, insect age and stage in the feeding cycle on the FMRFamide immunoreactivity of diffuse endocrine cells in the locust gut. The Journal of Experimental Biology (201):2971–2979
Józefiak D, Józefiak A, Kierończyk B, Rawski M, Świątkiewicz S, Długosz J, Engberg RM (2016) Insects – A natural nutrient source for poultry – A review. Annals of Animal Science 16(2):297–313
Anderson KE, Russell JA, Moreau CS, Kautz S, Sullam KE, Hu Y, Basinger U, Mott BM, Buck N, Wheeler DE (2012) Highly similar microbial communities are shared among related and trophically similar ant species. Mol Ecol 21(9):2282–2296
Ramalho MO, Bueno OC, Moreau CS (2017) Microbial composition of spiny ants (Hymenoptera: Formicidae: Polyrhachis) across their geographic range. BMC Evol Biol 17(1):96
Negroni MA, Segers F, Vogelweith F, Foitzik S (2020) Immune challenge reduces gut microbial diversity and triggers fertility-dependent gene expression changes in a social insect. BMC Genom 21(1):816
Kennedy SR, Tsau S, Gillespie R, Krehenwinkel H (2020) Are you what you eat? A highly transient and prey-influenced gut microbiome in the grey house spider Badumna longinqua. Mol Ecol 29(5):1001–1015
Colman DR, Toolson EC, Takacs-Vesbach CD (2012) Do diet and taxonomy influence insect gut bacterial communities? Mol Ecol 21(20):5124–5137
Kohl KD, Dearing MD (2012) Experience matters: prior exposure to plant toxins enhances diversity of gut microbes in herbivores. Ecology Letter 15(9):1008–1015
Xue W, Zhi-Shu X, Zhi-Bin Z, Hong-Chun P (2008) Insect seed predation and its relationships with seed crop and seed size of Quercus mongolica. Acta Entomologica Sinica 51:161–165
Dillon RJ, Dillon VM (2004) The gut bacteria of insects: nonpathogenic interactions. Annu Rev Entomol 49:71–92
Hammer TJ, Janzen DH, Hallwachs W, Jaffe SP, Fierer N (2017) Caterpillars lack a resident gut microbiome. Proc Natl Acad Sci U S A 114(36):9641–9646
Whitaker MR, Salzman S, Sanders J, Kaltenpoth M, Pierce NE (2016) Microbial communities of lycaenid butterflies do not correlate with larval diet. Front Microbiol 7:1920
Staudacher H, Kaltenpoth M, Breeuwer JA, Menken SB, Heckel DG, Groot AT (2016) Variability of bacterial communities in the moth Heliothis virescens indicates transient association with the host. PLoS One 11(5):e0154514
Kohl KD, Stengel A, Dearing MD (2016) Inoculation of tannin-degrading bacteria into novel hosts increases performance on tannin-rich diets. Environ Microbiol 18(6):1720–1729
Amalin DM, Peña JE, Reiskind J, McSorley R (2001) Comparison of the Survival of Three Species of Sac Spiders on Natural and Artificial Diets. Journal of Arachnology 29(2):253–262
Holtof M, Lenaerts C, Cullen D, Vanden Broeck J (2019) Extracellular nutrient digestion and absorption in the insect gut. Cell Tissue Res 377(3):397–414

Table 1 Richness and diversity estimation (Mean ± SEM) of the bacterial community in the gut of six groups.

Sample	Species richness indices		Species diversity indices
Sample	ACE	Chao1	Shannon diversity	Simpson diversity
LN_WH	275.37±60.72	238.20±37.70	0.45±0.08^b	0.84±0.02^a
TC_WH	195.98±78.32	198.23±78.20	0.80±0.24^b	0.77±0.06^a
TC_LY	280.55±97.26	278.61±39.20	2.10±0.72^a	0.41±0.13^b
CC-LN_WH	331.10±62.28^a	206.76±30.74	0.39±0.07	0.87±0.02
CC-TC_WH	152.03±31.98^b	114.44±23.18	0.55±0.28	0.80±0.10
CC-TC_LY	268.50±53.62^ab	233.65±60.98	0.48±0.06	0.84±0.01

Letters indicate significant differences across regimens (P<0.05).

SupplementaryFigure1.tif
The content of protein (a), trehalose (b), TG (c), and glucose (d) in Tetramorium caespitum of different locations. TC_LY, T. caespitum Luoyang; TC_WH, T. caespitum Wuhan; Asterisks indicate statistically significant differences (* P < 0.05; *** P < 0.001); NS, not significant.
SupplementaryFigure2.tif
Rarefaction curves of OTUs for the bacterial communities from ants and spiders. The rarefaction curves of determined tags tend to approach the saturation plateau. TC_LY, T. caespitum Luoyang; TC_WH, T. caespitum Wuhan; LN_WH, L. niger Wuhan; CC-, spiders fed different diets.
SupplementaryFigure3.tif
Rank-Abundance curves to evaluate species diversity at the OTU level in ants (a) and spiders (b). The abscissa represents the ordinal of the OTU, and the ordinate represents the abundance of the OTU. TC_LY, T. caespitum Luoyang; TC_WH, T. caespitum Wuhan; LN_WH, L. niger Wuhan; CC-, spiders fed different diets.
SupplementaryTable1.xlsx
Taxonomic composition of bacterial community at the genus level in each sample ( > 1%).The abundance is presented in terms of percentages of the total sequences in a sample. Enterobacteriaceae (family) was used for the unclassified group at the genus. TC_LY, T. caespitum Luoyang; TC_WH, T. caespitum Wuhan; LN_WH, L. niger Wuhan; CC-, spiders fed different diets.
SupplementaryTable2.xlsx
Principal coordinate analysis (PCoA) of unweighted UniFrac analysis demonstrated that there was significant variation among ants (PERMANOVAR, P < 0.05). TC_LY, T. caespitum Luoyang; TC_WH, T. caespitum Wuhan; LN_WH, L. niger Wuhan; CC-, spiders fed different diets.

Download PDF

Journal Publication

published 15 Nov, 2021

Read the published version in Microorganisms →

Version 1

posted

You are reading this latest preprint version

Differing Dietary Nutrients and Diet-associated Bacteria has Limited Impact on Spider Gut Microbiota Composition

Status:

Journal Publication

Version 1

Abstract

Figures

1 Introduction

2 Materials And Methods

2.1 Sample collection and rearing

2.2 Measurements of dietary nutrients in ants

2.3 DNA extraction and PCR amplification

2.4 Illumina MiSeq sequencing and bioinformatic processing

2.5 Statistical analyses

3 Results

3.1 Analysis of nutritional composition

3.2 The diversity analysis of the bacterial community

3.3 Composition of bacterial community

4 Discussion

Declarations

References

Tables

Supplementary Files

Status:

Journal Publication

Version 1