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1 Research article 2
3
4 Mating changes the genital microbiome in both sexes of the common bedbug
5 Cimex lectularius across populations
6
7
8 Running title: Mating-induced changes in bedbug genital microbiomes
9
10
11 Sara Bellinvia1, Paul R. Johnston2, Susan Mbedi3,4, Oliver Otti1
12
13
14 1 Animal Population Ecology, Animal Ecology I, University of Bayreuth, Universitätsstraße 30, 95440
15 Bayreuth, Germany
16 2 Institute for Biology, Free University Berlin, Königin-Luise-Straße 1-3, 14195 Berlin, Germany.
17 3 Museum für Naturkunde - Leibniz-Institute for Evolution and Biodiversity Research, Invalidenstraße
18 43, 10115 Berlin.
19 4 Berlin Center for Genomics in Biodiversity Research (BeGenDiv), Königin-Luise-Straße 1-3, 14195
20 Berlin, Germany.
21
22
23 Corresponding author: Sara Bellinvia
24 Phone: +49921552646, e-mail: [email protected]
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25 ABSTRACT
26 Many bacteria live on host surfaces, in cells, and specific organ systems. Although gut microbiomes of
27 many organisms are well-documented, the bacterial communities of reproductive organs, i.e. genital
28 microbiomes, have received little attention. During mating, male and female genitalia interact and
29 copulatory wounds can occur, providing an entrance for sexually transmitted microbes. Besides being
30 potentially harmful to the host, invading microbes might interact with resident genital microbes and
31 affect immunity. While sexual transmission of individual symbiont species is relatively well-
32 understood, few studies have addressed how mating changes genital microbiomes. Here, we
33 characterize male and female genital microbiomes in four different populations of the common
34 bedbug Cimex lectularius and investigate mating-induced changes. We dissected reproductive organs
35 from virgin and mated individuals to sequence their genital microbiomes. We show that mating
36 changes genital microbiomes, suggesting bacteria are sexually transmitted. This raises the question
37 how the host’s physiological and immunological mechanisms control mating-induced changes in their
38 genital microbiomes. Also, genital microbiomes varied between populations and the sexes. This
39 provides evidence for local and sex-specific adaptation of bacteria and hosts, again suggesting that
40 bacteria might play an important role in shaping the evolution of reproductive traits. Coadaptation of
41 genital microbiomes and reproductive traits might further lead to reproductive isolation between
42 populations, giving reproductive ecology an important role in speciation. Future studies should
43 investigate the transmission dynamics between the sexes and populations to uncover potential
44 reproductive barriers.
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45 INTRODUCTION
46 Animals have intimate associations with bacteria. These bacteria are found on host surfaces, within
47 and between host cells, or are associated with specific organ systems, such as the gut1–3. Also,
48 reproductive organs of a variety of animals often harbor several different bacterial species. Microbes
49 have been found on male reproductive organs and in semen of vertebrates4–9, but also in female
50 reproductive organs of birds and mammals, both including humans5,10–13. In insects, besides
51 intracellular reproductive manipulators (reviewed in14), extracellular microbes have been found both
52 on the male copulatory organ and within the female reproductive organs (reviewed in15, also see16,17).
53 Interestingly, the microbiomes of whole body homogenates or the gut are sex-specific in a variety of
54 species18–20. Possible reasons could be differences in behaviors or feeding strategies, different
55 functions of the two sexes in the ecosystem, or different roles in reproduction. Supporting the latter,
56 pronounced differences exist between the genital microbiomes of female and male red-winged
57 blackbirds5 and bedbugs16,17, respectively. However, the role of genital microbes in reproduction and
58 the exact composition of these genital microbiomes is still unknown for most insect species.
59 Microbiomes are dynamic and react to environmental change. Diet21,22, age23, climate24, and even time
60 of day25 alter the composition of the gut microbiome of humans, mice and lizards. Some life-history
61 events affect multiple microbiomes at the same time, for instance pregnancy changes the vaginal, gut,
62 and oral microbiomes26. Genital microbiomes might be subject to similar changes. For instance,
63 women have a distinct vaginal microbiome before and after the menopause27. An obvious pattern that
64 has the potential to affect genital microbiomes is mating as the microbiomes of both sexes encounter
65 each other and potentially interact. Therefore, physiological changes in anticipation to the production
66 of offspring might occur. To date, little is known about the potential effects of mating on the
67 composition of genital microbiomes, especially in species other than humans.
68 Microbes are sexually transmitted in a large range of species (e.g.28–30). Not only typical sexually
69 transmitted microbes (STM) are transferred during mating, also opportunistic microbes (OM)
70 inhabiting the genitalia17,31,32 might be transferred. Possible entry ports are genital openings and
71 copulatory wounds, which frequently occur for example in insects, spiders, flatworms and 3 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
72 gastropods33. These OM might have a more direct effect compared to STM: Once transferred into the
73 female genital tract, sperm will be exposed to a rich microbial flora7,10. Several bacterial species, such
74 as Escherichia coli34–36, Pseudomonas aeruginosa37, and Staphylococcus aureus38 can decrease sperm
75 motility and agglutinate spermatozoa in humans. In insects, bacteria from the environment have the
76 potential to increase sperm mortality39. Therefore, male reproductive success might depend on the
77 microbe communities within the female, and males would be selected to protect their sperm. Females
78 could be invaded by STM or sexually transmitted OM, disturbing the present genital microbiome. The
79 intestinal microbiota of mice, for instance, was shown to be altered by Salmonella typhimurium40 and
80 Citrobacter rodentium41. Copulatory wounding during mating further increases the risk of
81 opportunistic infection not only in invertebrate species42,43, but also in humans44. Both males and
82 females might be subject to a considerable cost of reproduction, even if OM do not always become
83 pathogenic. Hosts should invest in reducing or regulating the number of STMs or sexually transmitted
84 OM to prevent uncontrolled growth, most likely by using their immune system. However, sexually
85 transmitted bacteria disturbing the composition of the genital microbiome might select not only for a
86 host immune response, but also for defensive responses in the resident microbiota16. Therefore, the
87 host and its endosymbionts have a mutual interest in keeping invading bacteria in check. In some
88 organisms, the resident microbiota is part of the interaction with invading microbes45–48.
89 If genital microbiomes are subject to OM, an adaptation to environmental microbes seems
90 conceivable. Indeed, the human vaginal microbiome seems to depend on ancestry: American women
91 of African, Asian, European, and Hispanic ancestry harbored distinct vaginal microbiomes11 and African
92 ancestry was related to larger alpha diversity of the vaginal microbiome compared to European
93 ancestry49, raising the question whether there are conserved differences in the community
94 composition between populations. Despite the potential relevance for speciation, not much is known
95 about the adaptation of insect genital microbiomes to different host populations which might lead to
96 reproductive isolation. Another unresolved question is how genital microbiomes are affected by
97 mating and whether induced changes differ between populations. Unlike in humans such mating-
98 induced changes can be experimentally investigated in insects with relatively little effort17. 4 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
99 Bedbugs are an interesting system to study mating-induced changes of insect genital microbiomes
100 because several organs are involved in reproduction. During mating, these organs might be invaded by
101 microbes that use the routes of ejaculate transfer as entrance to the reproductive organs. The male
102 ejaculate consists of spermatozoa that are stored in the male sperm vesicles and seminal fluid from
103 the seminal fluid vesicles. After mounting the female, the male transfers the ejaculate via its copulatory
104 organ, the paramere, into the female paragenital copulatory organ, the mesospermalege50. This female
105 immune organ is filled with immune cells (hemocytes) and has evolved to reduce the cost of mating
106 associated with bacterial infection51. After a few hours, sperm travel through the hemolymph towards
107 the ovaries50. All tissues involved could be invaded by microbes that impose a risk of infection or sperm
108 damage. We predict female tissues to be more affected by an invasion of OM compared to male tissues
109 because bacteria could be transmitted via the paramere and enter the immune organ via copulatory
110 wounds. We expect the reproductive organs to differ in their microbial composition and the microbial
111 composition itself to change due to mating. Indeed, there are potential indications of sexual
112 transmission in bedbugs17. Furthermore, microbial communities differ between reproductive organs
113 and copulation increases the similarity of female and male organs. Bacteria present in mated but not
114 virgin individuals of one sex are found in the opposite sex and resident bacteria are replaced with
115 introduced bacteria17. Our aim is to investigate whether these findings are a general pattern across
116 bedbug populations.
117 Here, we describe the genital microbiome of male and female common bedbugs Cimex lectularius. We
118 focus on a potential difference in the microbial community between populations, between the two
119 sexes, between organs, and between virgin and mated individuals to evaluate the effect of the external
120 environment on the genital microbiome and the risk of a change in composition via copulation. We
121 expect distinct microbiomes between the investigated groups. If compositional changes due to mating
122 are caused by sexual transmission, we expect to find bacterial strains that occur in virgin individuals of
123 only one sex but in mated individuals of both sexes. Mating-induced changes in the genital microbiome
124 should be caused by a loss or introduction of bacterial strains or by a replacement of resident with
125 invading bacterial strains. We predict that the mechanisms differ between females and males due to 5 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
126 the different function of the organs involved in mating. In case members of a specific bacterial strain
127 invade the genital microbiome, mating should change the abundance of the given bacterial strain. To
128 test our predictions, we use a community ecology approach based on 16S rRNA sequencing data from
129 the genital microbiomes of four bedbug populations.
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130 RESULTS AND DISCUSSION
131
132 We sequenced 643 samples from bedbug reproductive organs or cuticle to characterize the
133 composition of the genital microbiomes and investigate the effect of mating. After filtering, we
134 obtained 149 sequence variants (SVs) from 495 samples (Table 1). Average alpha diversity given by the
135 Simpson index (1-D) was 0.59 (0.56; 0.62) (mean and 95% confidence interval) (Figure S1).
136
137 Microbiomes of virgin bedbugs
138 Differences in the composition of cuticular and genital microbiomes
139 Virgin bedbugs harbored distinct cuticular and genital microbiomes. The members of microbial
140 communities and their relative abundance differed between the cuticle and the internal reproductive
2 141 organs (F1,218=5.257, R =0.024, q=0.003) but not between the cuticle and the external reproductive
2 142 organ, the paramere (F1,91=1.411, R =0.015, q=0.14) or the internal reproductive organs of both sexes
2 143 and the paramere (F1,177=2.350, R =0.013, q=0.02) (Figure S2). The groups did not differ in between-
144 individual difference (F2,243=1.521, p=0.22).
145 On the first glance, the compositional differences between microbiomes of internal reproductive
146 organs and cuticle seem to be caused by location. Environmental bacteria have been found on the
147 external reproductive organ of bedbugs32, suggesting cuticle and paramere should mostly be colonized
148 by environmental bacteria. In contrast, internal organs might be more protected from environmental
149 bacteria but at the same time they might harbor symbionts that play a role in bedbug reproduction.
150 Although we found distinct microbial communities on the cuticle and in the internal reproductive
151 organs, the microbiome of the paramere was not different from the microbiome of all other organs.
152 Hence, its microbiome could be influenced by the microbiomes of both the cuticle and the internal
153 microbiome. Alternatively, a combination of organ location and function might be responsible for this
154 finding.
155
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156 Composition of genital microbiomes
157 Genital microbiomes of virgin bedbugs harbored on average 25 (21; 28) SVs (mean and 95% confidence
158 interval) and were specific to each group of bedbugs. The members of microbial communities and their
2 159 relative abundances differed between populations (F3,170=1.885, R =0.030, p=0.004) and sexes
2 160 (F1,170=3.776, R =0.020, p=0.001) (Figure S3). Even different organs taken from the same sex harbored
2 161 distinct microbiomes (F4,170=1.578, R =0.034, p=0.008). Between-individual variation did not differ
162 between populations (F3,175=1.410, p=0.24), sexes (F1,177=2.138, p=0.15), or organs (F5,173=1.488,
163 p=0.20).
164 We did not find any SV present in all samples of a given sex, but three SVs occurred in at least half of
165 all individuals of both sexes. Males and females did not differ in the prevalence of a
166 gammaproteobacterial endosymbiont of C. lectularius (males: 67%, females: 64%) and one Rickettsia
167 strain (males: 58%, females: 59%), whereas more females than males harbored a second Rickettsia
168 strain (males: 59%, females: 69%). The relative abundance of the three most prevalent genera varied
169 tremendously from 0% to 50% (gammaproteobacterial endosymbiont) or from 0% to 100% (both
170 Rickettsia strains) in individual samples. Virgin males and females shared 69% (population A), 88%
171 (population B), 86% (population C), and 95% (population D) of all SVs found in virgin bedbugs from the
172 specific population (Figure 1).
173 Population-specific microbiomes are likely to arise if host and microbes coevolve. Sexual conflict and
174 genetic drift might play a role as well. Ultimately, differences in microbiome composition might be
175 involved in speciation processes such as reproductive isolation. We here present a system under
176 controlled lab conditions, fed with the same food source, nevertheless being held in separate
177 containers. Despite of the controlled environmental factors, we found differences in microbiome
178 composition between bedbug populations. Our findings are in accordance with the evidence for
179 ancestry-dependent vaginal microbiomes in humans11,49. In contrast to our study under controlled lab
180 conditions, it is difficult to exclude lifestyle factors, such as diet, sex partners, etc. as the cause of
181 differences in vaginal microbiomes. We are aware that this comparison with humans might be far-
182 fetched, as the taxa clearly differ in their interaction with microbes. Unfortunately, little is known 8 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
183 about genital microbiomes in insects. We could draw here parallels to gut microbiomes because they
184 are also heavily influenced by influx of environmental microbes, but this is equally hypothetical.
185 Therefore, we prefer to highlight that our study shows that insects and other arthropods are ideal
186 study systems to experimentally investigate genital microbiomes and their role in reproduction in more
187 detail.
188 Differences in microbiome composition between females and males have been found in whole body
189 homogenates or gut samples in a variety of species18–20. These differences could be explained by
190 different behaviors or feeding strategies, different functions of the two sexes in the ecosystem, or
191 different roles in reproduction. Despite a lack of studies investigating the origin of sexual dimorphism
192 in the microbiome, pronounced differences exist between the genital microbiomes of female and male
193 red-winged blackbirds5 and bedbugs16,17, respectively. Furthermore, our finding of organ-specific
194 bacterial communities within the same sex is in accordance with the varying microbiome composition
195 along the female reproductive tract in humans52. Either the different accessibility for OM or the
196 function of the organs could be responsible for such a specificity. To our knowledge, we provide
197 evidence for organ-specific genital microbiomes in female insects for the first time.
198
199 Mating-induced changes in the genital microbiomes
200 Changes in the presence and relative abundance of specific SVs
201 We found mating-induced changes in the genital microbiomes of females and males regarding the
202 presence of specific SVs and their relative abundance as virgin and mated individuals harbored distinct
2 203 genital microbiomes (F1,355=1.938, R =0.005, p=0.03) (Figure S3). We found no interaction of organ and
2 2 204 mating status (F5,317=1.003, R =0.013, p=0.49), population and mating status (F3,317=0.762, R =0.006,
2 205 p=0.83), or population, organ and mating status (F15,317=0.779, R =0.031, p=0.99). Between-individual
206 variation was similar between mating status (F1,363=0.010, p=0.92), organs (F5,359=1.462, p=0.20), and
207 populations (F3,361=0.281, p=0.84).
208 In all populations, males and mated females shared bacterial strains that were not present in virgin
209 females (Figure 1). In two out of four populations, mated males harbored bacteria that were present 9 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
210 in females but not in virgin males. This does not necessarily indicate sexual transmission of these
211 strains since their prevalence did not differ between virgin and mated individuals of the same sex
212 (q>0.05). All bacteria found in mated but not virgin individuals that were not present in the
213 reproductive organs of the opposite sex occurred on the cuticle of virgin bedbugs.
214 Changes in strain composition can be caused by direct sexual transmission of OM, via ejaculate transfer
215 or being transferred from the male paramere or the female cuticle into the mesospermalege. Genital
216 openings or copulatory wounds provide both entry and exit for bacteria. Indeed, our results indicate
217 that bacteria that occur in mated but not in virgin individuals of one sex originate from the reproductive
218 organs of the opposite sex as well as from the cuticle. However, we found no significant differences in
219 the prevalence of these strains between virgin and mated individuals. A classical transmission study
220 could show whether sexual transmission and transmission of OM from the environment is a common
221 phenomenon in bedbugs.
222
223 Potential mechanisms affecting composition
224 We partitioned beta diversity, given as the Jaccard index, into nestedness (strain loss or introduction
225 of new strains) and turnover (replacement of strains) to analyze the potential mechanism of the
226 mating-induced change found in genital microbiomes. In 16 out of 24 cases the proportion of beta
227 diversity explained by SV turnover was higher than the proportion explained by SV nestedness (Table
228 2). In male organs, turnover was the dominant mechanism in 10 out of 12 cases, while in females both
229 mechanisms accounted for the composition change in half of the cases.
230 Against our expectations, there was potential transmission to males, indicated by a replacement of
231 resident with new bacterial strains. This is surprising because it is less likely for the male to be subject
232 to copulatory wounding and the distance between the environment and the internal reproductive
233 organs is larger compared to females. Thus, we would have expected invading microbes to be flushed
234 out via ejaculate transfer rather than to invade the internal reproductive organs. However, in case
235 males do not apply pressure to transfer the ejaculate, bacteria might reach the internal organs through
236 the ejaculatory duct via a capillary effect similar to the invasion of human testicles by urethral 10 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
237 pathogens through the seminal duct or the epididymal duct53. The induced expression of antimicrobial
238 peptides in the genital tract of Drosophila males in response to bacteria deposited on the genital plate54
239 suggests bacteria can enter the reproductive organs of male insects via genital openings. Experimental
240 manipulation of bacteria on the paramere might clarify whether and how bacteria can enter the
241 paramere and move through the ejaculatory duct towards the sperm vesicles and seminal fluid
242 vesicles.
243
244 Abundance changes
245 Mating changed the abundance of several bacterial strains in almost all organs within populations
246 (Table 3). However, the proportion of differentially abundant SVs did not differ between populations
247 (F3,19=0.421, p=0.74) or between males and females (F1,19=1.554, p=0.23) and population did not
248 interact with sex (F3,16=1.181, p=0.35). No clear direction of abundance change, i.e. decrease or
249 increase in abundance, for populations, sexes, or organs was identified (Figure 2). The absolute log2-
250 fold change representing the strength of abundance change differed between populations
251 (F3,316=5.577, p<0.001) but not between sexes (F1,316=0.048, p=0.826) and population did not interact
252 with sex (F3,313=0.946, p=0.419).
253 We expected that the genital microbiomes of females would be more affected by invading bacteria,
254 but the abundance change or its strength did not depend on sex. A high stability of the genital
255 microbiome is especially important for females because bacteria can enter the body more easily
256 compared to males. Bacteria might not only decrease survival51 but also cause a trade-off between
257 immunity and mating and hence decrease fecundity. Such a reduction in fecundity after an immune
258 challenge has been found in dipterans, coleopterans, and orthopterans55 and is likely to also exist in
259 bedbugs. Moreover, bacteria harm sperm within the female directly. Escherichia coli, Pseudomonas
260 aeruginosa, and Staphylococcus aureus decrease sperm motility34–38 and incapacitate spermatozoa38
261 in humans, at least in vitro, and environmental bacteria increase sperm mortality in bedbugs39. To
262 reduce the costs of mating-associated infections, bedbugs have evolved the mesospermalege51. The
263 high number of hemocytes50 able to phagocytose bacteria56 in this organ might stabilize its microbiome 11 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
264 and protect against invading bacteria. In addition, lysozyme in the seminal fluid of males57 and in the
265 mesospermalege produced in anticipation of mating58 could help to reduce invading bacteria.
266 Furthermore, endosymbionts have been shown to interact with invading microbes45–48 and might help
267 to control non-resident bacteria in the genital microbiomes. Future studies should investigate the
268 effect of the species with the largest abundance changes in the genital microbiomes on fecundity and
269 survival and what adaptations have evolved to eliminate the possible threat to host integrity.
270 We have demonstrated that genital microbiomes of the common bedbug Cimex lectularius differ
271 between populations, sexes and organs. Our findings show that genital microbiomes are sensitive to
272 an activity that every sexually reproducing animal has to face, i.e. mating. Future studies should
273 investigate sexual transmission dynamics of OM in combination with fitness effects on both sexes.
274 Experimental manipulation of the female immune system could provide important information about
275 the importance of immunity in response to genitalia-associated bacteria. Finally, coadaptation of
276 genital microbiomes and reproductive traits might lead to reproductive isolation between populations,
277 giving reproductive ecology an important role in speciation.
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278 METHODS
279
280 Bedbug culture
281 Common bedbugs (Cimex lectularius L.) are an established model system for examining consequences
282 of sexual selection and reproductive physiology51,59. We used four large stock populations of the
283 common bedbug. Three populations were field caught from London, UK in 2006 (A), from Nairobi,
284 Kenya, in 2008 (C), and from Watamu, Kenya, in 2010 (D). The fourth population (B) was a long-term
285 lab stock originally obtained from the London School of Hygiene and Tropical Medicine over 20 years
286 ago. The populations were maintained in a climate chamber at 26±1°C, at 70% relative humidity and a
287 light cycle of 12L:12D and fed weekly using the protocol of Hase60. After eclosion, all individuals were
288 kept in sex-specific groups of 20-30 individuals in 60ml plastic pots containing filter paper. Males were
289 fed twice. Females were fed three times, with the last feeding on the day of dissection because fully
290 fed females cannot resist copulation via traumatic insemination 61.
291
292 Mating and sample preparation
293 Dissections and DNA extractions were conducted in the laboratory of the Animal Population Ecology
294 at the University Bayreuth. We dissected 643 three-week-old males and females, originating from four
295 different populations (Population A: N=163, population B: N=160, population C: N=160, population D:
296 N=160). Half of the individuals were randomly mated for 60 seconds and dissected 1-2 hours after
297 mating. That means that the sperm were still present in the mesospermalege of mated females at the
298 time of dissection. We used standard dissection techniques minimizing the potential of contamination
299 by a lab butane burner (Labogaz 206, Campingaz, Hattersheim, Germany) placed next to the dissection
300 microscope. The dissection kit was autoclaved each day and each individual forceps and surgical
301 scissors were dipped in ethanol (70%) and flame sterilized before each dissection.
302 We collected different reproductive tissues and cuticle samples from females and males (for sample
303 sizes see Table 1). Each sample was taken from a different bedbug since it is difficult to obtain all tissues
304 from the same individual. From males we collected sperm vesicles, seminal fluid vesicles and
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305 paramere. In females we investigated the mesospermalege, ovaries and hemolymph. Hemolymph was
306 collected using a sterilized glass capillary pulled to a fine point. Each tissue was transferred into an
307 Eppendorf tube containing 150µl of phosphate-buffered saline. We investigated whether invading
308 bacteria in the genital microbiomes of mated bedbugs originated from the paramere or the cuticle by
309 transferring whole females or males, whose paramere had been removed, into a tube. To evaluate
310 contamination during the dissection process, we placed an open Eppendorf tube containing only
311 phosphate-buffered saline next to the dissection microscope while processing the bedbugs. This tube
312 was then processed in the same way as all tissue samples from which we extracted DNA. All samples
313 were frozen in liquid nitrogen and stored at -80°C.
314
315 Molecular methods
316 Prior to transferring the samples to the MicroBead tubes from the MO BIO UltraClean Microbial DNA
317 Isolation Kit (dianova GmbH, Hamburg, Germany), we homogenized them using pestles made from
318 sterile pipette tips (200µl). We followed the UltraClean protocol, except that we dissolved the DNA in
319 30µl elution buffer for higher yield. DNA was stored at -20°C. To control for contamination during DNA
320 extraction we performed one extraction without adding any tissue.
321 The library preparation and sequencing was done in the laboratory of the Berlin Center for Genomics
322 in Biodiversity Research (BeGenDiv). The samples were split up into four sequencing runs, each
323 balanced in terms of population, sex, organ, and mating status, resulting in four libraries with 128±25
324 (mean±SD) samples each, including controls. Using the universal primers 515fB (5’-
325 GTGYCAGCMGCCGCGGTAA-3’, 62) and 806rB (5’-GGACTACNVGGGTWTCTAAT-3’, 63), we amplified the
326 variable V4 region from the bacterial 16S rRNA (denaturation: 94°C for 3 min; 30 cycles of
327 denaturation: 94°C for 45 s, annealing: 50°C for 1 min, extension: 72°C for 90 s; extension: 72°C for 10
328 min). After amplicons had been purified using Agencourt AMPure XP beads (Beckmann Coulter GmbH,
329 Krefeld, Germany), a unique combination of two eight nucleotide long index sequences per sample
330 were used for barcoding each sample in a second PCR (denaturation: 95°C for 2 min; 8 cycles of
331 denaturation: 95°C for 20 s, annealing: 52°C for 30 s, extension: 72°C for 30s; extension: 72°C for 3 14 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
332 min). After a second purification step with AMPure beads, the DNA concentration of the PCR products
333 was quantified with the Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, USA). Samples
334 that had a higher concentration than 5 ng/µl were diluted to this concentration, all other samples were
335 left undiluted. The quality of the pooled amplicons was verified with a microgel electrophoresis system
336 (Agilent 2100 Bioanalyzer, Agilent Technologies, Santa Clara, CA, USA). The resulting libraries were
337 sequenced by an Illumina MiSeq sequencer. For each of the two PCRs per sequencing run we had two
338 negative controls containing only purified water instead of DNA. Two additional samples for each PCR
339 per sequencing run contained the bacterial DNA from a whole homogenized bedbug to increase
340 sequencing depth. The sequences were deposited in NCBI’s Sequence Read Archive with the accession
341 number PRJNA560165.
342
343 Bioinformatical analysis
344 Data processing and check for contamination
345 All data processing and analyses were performed in R (version 5.3.164) with the packages dada2
346 (version 1.10.165), decontam (version 1.2.066), phyloseq (version 1.19.167), pairwiseAdonis (version
347 version 0.0.168), vegan (version 2.4-569), and edgeR (version 3.22.170). We used the dada265 pipeline to
348 filter and trim the sequences with the fastqPairedFilter function. The first 10 bp were removed and the
349 sequences were truncated after 260 bp (forward reads) or 200 bp (reverse reads), or at the first
350 instance of a quality score less than or equal to 2. Sequences with expected errors higher than 2 were
351 discarded. The remaining sequences were dereplicated with the default parameters of the derepFastq
352 function and denoised with the dada function (enabled selfConsist option). We constructed a sequence
353 variant (SV) table with the makeSequenceTable function. All SVs were checked for chimeras with the
354 removeBimeraDenovo function and default parameters. The taxonomy was assigned with the
355 Greengenes database71. To control for contamination, we scored the controls for dissection, DNA
356 isolation, target PCR and indexing PCR with the decontam package66 and removed the SVs that were
357 found to be contaminants based on their prevalence in controls. We further removed all SVs that
358 occurred in only one sample and that had less than 0.01% of the total number of reads, as suggested 15 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
359 by Caporaso et al.72. We verified the taxonomical assignment with Blast2Go73 and its default options.
360 We excluded uncultured or environmental samples. If Blast2Go did not find a match, we used NCBI’s
361 BLASTn with the default options, excluding uncultured and environmental sample sequences. The
362 taxonomic assignments of the different algorithms were in accordance for kingdom, phylum, class,
363 order, family and genus level in 110 out of 149 SVs. In one of the mismatches, the BLAST hit with the
364 highest e-value and coverage belonged to an endosymbiont of C. lectularius, the unclassified
365 gammaproteobacterium mentioned by Hosokawa et al.74. We therefore changed the taxonomy
366 assignment of this SV. In seven out of the mis-assigned cases, all BLAST hits agreed on one genus and
367 we therefore changed the assignment. In 38 other cases there was no clear BLAST result. Hence, we
368 kept the Greengenes assignment for the levels that were congruent with the BLAST results and
369 changed the assignment of the other levels to “Unclassified”. Information regarding sample type, read
370 numbers for samples and SVs, and assigned taxa can be found in the Supplement (Table S1-S3).
371
372 Statistical analysis of differences in the microbiomes of virgin bedbugs between populations, sexes, and
373 organs
374 We calculated the relative abundance of all genera by dividing the number of reads for the given SV
375 within one sample by the total number of reads for all SVs within the same sample. Alpha diversity was
376 estimated based on the Simpson index (1-D) with the phyloseq package67. We then analyzed the
377 differences in microbiome composition between internal reproductive organs, external reproductive
378 organs and cuticle with a multilevel pairwise comparison using PERMANOVAs (pairwiseAdonis
379 package68) based on Bray-Curtis dissimilarities. P-values were adjusted with the Benjamini-Hochberg
380 procedure. Between-individual differences between the three groups were analyzed with an ANOVA
381 of the function betadisper in the vegan package69.
382 To compare the genital microbiome composition between populations and sexes, we used a
383 PERMANOVA (999 permutations, vegan package69) with the fixed effects population, sex, and organ
384 nested within sex based on Bray-Curtis dissimilarities obtained with the phyloseq package67. Between-
385 individual variation was then compared with 3 separate ANOVAs of the betadisper function in the 16 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
386 vegan package69 for populations, sexes, and organs. The prevalence of all SVs in males and females
387 was calculated by dividing the number of samples for the given sex that contained a given SV by the
388 total number of samples of the given sex.
389
390 Statistical analysis of effects of mating on the bacterial communities
391 Differences in the composition of genital microbiomes from virgin and mated bedbugs were analysed
392 with a PERMANOVA (999 permutations, vegan package69) with the fixed effects population, organ, and
393 mating status, and their interactions based on Bray-Curtis dissimilarities obtained with the phyloseq
394 package67. Non-significant interactions were removed from the model. We then compared between-
395 individual variation with separate ANOVAs of the betadisper function in the vegan package69 for
396 population, organ and mating status.
397 To analyse the potential of sexual transmission, we extracted the SVs present in virgin individuals of
398 only one sex but in mated individuals of both sexes. We applied Fisher’s exact tests to determine
399 whether the prevalence of each of these SVs differed between virgin and mated individuals. P-values
400 were adjusted with the Benjamini-Hochberg procedure.
401 We analyzed whether the different bacterial strains hosted by virgin and mated individuals are due to
402 a loss or introduction of specific strains (nestedness) or due to a replacement of resident bacterial
403 strains with introduced bacteria (turnover). To analyze the contribution of these two mechanisms, we
404 partitioned beta diversity, in this case given by the Jaccard index, into nestedness and turnover with
405 the function nestedbetasor in the vegan package69. Before applying this function, we produced a
406 presence-absence matrix that included all SVs present in each population, organ, and mating status.
407 With the package edgeR70,75 we tested for differential abundance of SVs between the genital
408 microbiomes of virgin and mated bedbugs with the glmQLFit and glmQLFTest function. Normalization
409 factors were calculated with the relative log expression76 and applied to raw read counts. Contrasts
410 were built for every mating status within organ and population and p-values were adjusted with the
411 Benjamini-Hochberg procedure and a false discovery rate of 1%. The resulting proportion of SVs with
412 differential abundance was analyzed with a logistic regression with quasibinomial error structure and 17 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
413 the fixed effects population and sex, including their interaction. Groups were then compared with an
414 ANOVA. To analyze the effects of population and sex on the strength of abundance change given by
415 the absolute log2-fold change, we fitted a GLM with Gaussian error structure with the fixed effects sex
416 and organ nested within sex and population as the random factor. Normality of the data was restored
417 with the Box-Cox transformation (MASS package77) and checked visually before groups were compared
418 with an ANOVA. Non-significant interactions were removed from the models.
419
18 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
420 ACKNOWLEDGEMENTS
421 S.B. was supported by a grant of O.O. awarded by the German Research Foundation (OT 521/2-1). We
422 would like to thank M. Kaltenpoth for helpful comments on the manuscript.
423
424 AUTHOR CONTRIBUTIONS
425 O.O., P.R.J., and S.B. conceived the idea and designed the experiment. S.B. and S.M. carried out the
426 experiment. S.B. and P.R.J. performed the bioinformatics and statistical analysis. S.B., P.R.J., S.M. and
427 O.O. interpreted the results and S.B. and O.O. wrote the manuscript. All authors read and approved of
428 the final manuscript.
429
430 CONFLICT OF INTEREST
431 The authors have declared no conflict of interest.
432 CONFLICT OF INTEREST
433 The authors have declared no conflict of interest.
19 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
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607 TABLES
608 Table 1 Sample sizes and number of bacterial communities that were successfully sequenced for each
609 group of samples. Sampled organs were: cuticle (C), sperm vesicle (S), seminal fluid vesicle (Sf),
610 paramere (P), mesospermalege (M), hemolymph (H) and ovary (O).
Population Sex Organ Mating status N total N sequenced A Male C Virgin 10 7 A Male C Mated 10 6 A Male S Virgin 10 7 A Male S Mated 11 7 A Male Sf Virgin 10 7 A Male Sf Mated 10 6 A Male P Virgin 10 7 A Male P Mated 10 6 A Female C Virgin 11 7 A Female C Mated 11 8 A Female M Virgin 10 8 A Female M Mated 10 6 A Female H Virgin 11 8 A Female H Mated 10 6 A Female O Virgin 10 6 A Female O Mated 9 7 B Male C Virgin 10 8 B Male C Mated 10 8 B Male S Virgin 10 8 B Male S Mated 10 10 B Male Sf Virgin 10 5 B Male Sf Mated 10 7 B Male P Virgin 10 5 B Male P Mated 10 7 B Female C Virgin 10 8 B Female C Mated 10 10 B Female M Virgin 10 9 B Female M Mated 10 7 B Female H Virgin 10 9 B Female H Mated 10 10 B Female O Virgin 10 9 B Female O Mated 10 9 C Male C Virgin 10 9 C Male C Mated 10 8 C Male S Virgin 10 10 C Male S Mated 10 9 C Male Sf Virgin 10 6 C Male Sf Mated 10 10 C Male P Virgin 12 7
29 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
C Male P Mated 8 6 C Female C Virgin 10 10 C Female C Mated 10 8 C Female M Virgin 10 8 C Female M Mated 10 7 C Female H Virgin 10 6 C Female H Mated 10 7 C Female O Virgin 10 6 C Female O Mated 10 8 D Male C Virgin 10 9 D Male C Mated 10 7 D Male S Virgin 10 9 D Male S Mated 10 9 D Male Sf Virgin 10 7 D Male Sf Mated 10 8 D Male P Virgin 10 7 D Male P Mated 10 9 D Female C Virgin 10 9 D Female C Mated 10 8 D Female M Virgin 10 8 D Female M Mated 10 8 D Female H Virgin 10 9 D Female H Mated 10 9 D Female O Virgin 10 8 D Female O Mated 10 8 611
30 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
612 Table 2 Turnover (replacement of strains) and nestedness (strain loss or introduction of new strains)
613 of the microbiomes of the sperm vesicle (S), the seminal fluid vesicle (Sf), the paramere (P), the
614 mesospermalege (M), the hemolymph (H) and the ovary (O) obtained by partitioning beta diversity
615 (Jaccard index) with the vegan package69. The mechanisms explaining a higher proportion of beta
616 diversity within population and organ are indicated in bold type.
Population Sex Organ Jaccard Index Proportion Turnover Proportion Nestedness A Male S 0.15 0.22 0.78 A Male Sf 0.29 0.46 0.54 A Male P 0.38 0.60 0.40 A Female M 0.71 0.14 0.86 A Female H 0.63 0.06 0.94 A Female O 0.52 0.87 0.13 B Male S 0.39 0.96 0.04 B Male Sf 0.20 0.56 0.44 B Male P 0.21 0.72 0.28 B Female M 0.56 0.72 0.28 B Female H 0.48 0.13 0.87 B Female O 0.63 0.69 0.31 C Male S 0.40 0.91 0.09 C Male Sf 0.18 0.69 0.31 C Male P 0.72 0.97 0.03 C Female M 0.65 0.25 0.75 C Female H 0.51 0.30 0.70 C Female O 0.61 0.82 0.18 D Male S 0.11 0.65 0.35 D Male Sf 0.20 0.74 0.26 D Male P 0.41 0.70 0.30 D Female M 0.23 0.45 0.55 D Female H 0.33 0.95 0.05 D Female O 0.29 0.74 0.26 617
31 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
618 Table 3 Differential abundance of the microbiomes of the sperm vesicle (S), the seminal fluid vesicle
619 (Sf), the paramere (P), the mesospermalege (M), the hemolymph (H) and the ovary (O) from virgin vs
620 mated individuals. Values were obtained by fitting a GLM in the edgeR package70,75. Only SVs with
621 significant differential abundance (q<0.05) are reported.
Population Sex Organ Number of differentially abundant SVs Total number of SVs A Male S 8 140 A Male Sf 3 129 A Male P 5 131 A Female M 44 120 A Female H 34 131 A Female O 2 100 B Male S 31 125 B Male Sf 2 138 B Male P 12 128 B Female M 4 107 B Female H 60 120 B Female O 0 71 C Male S 0 121 C Male Sf 15 136 C Male P 0 76 C Female M 0 89 C Female H 40 133 C Female O 0 51 D Male S 3 147 D Male Sf 3 133 D Male P 40 128 D Female M 6 135 D Female H 7 132 D Female O 2 123 622
32 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
623 FIGURES
624
625 Figure 1 Occurrence of all SVs within the genital microbiomes split up by population, sex, and mating
626 status. A total of 149 SVs were detected, of which 147 were harbored by population A, 146 by
627 population B, 146 by population C, and 148 by population D.
33 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
628
629 Figure 2 Abundance change of SVs present in the microbiomes of the sperm vesicle (S), the seminal
630 fluid vesicle (Sf), the paramere (P), the mesospermalege (M), the hemolymph (H) and the ovary (O)
631 from virgin vs mated individuals as estimated by GLM fits in the edgeR package70,75. Given is the log2-
632 fold change of SVs with significant differential abundance as a measure of the direction and strength
633 of abundance change.
34 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
634 SUPPLEMENTARY INFORMATION
635
636 Figure S1 Alpha diversity of each sample in the sperm vesicle (S), the seminal fluid vesicle (Sf), on the
637 paramere (P), in the mesospermalege (M), the hemolymph (H) and the ovary (O). Depicted are means
638 and standard errors of the mean. Simpson indices were obtained with the estimate_richness function
639 in the phyloseq package67.
35 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
640
641 Figure S2 PCoA of microbiomes from cuticle in comparison to the external reproductive organ of
642 males) and internal reproductive organs of both sexes. Ordination was performed with the ordinate
643 function and plotted with the plot_ordination function in the phyloseq package67.
36 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
644
645 Figure S3 PCoA of all groups of genital microbiomes. Organs are sperm vesicle (S), seminal fluid vesicle
646 (Sf), paramere (P), mesospermalege (M), hemolymph (H) and ovary (O). Ordination was performed
647 with the ordinate function and plotted with the plot_ordination function in the phyloseq package67.
648
37 bioRxiv preprint doi: https://doi.org/10.1101/819300; this version posted October 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
649 All supplemental tables can be requested via email ([email protected]).
650
651 Table S1 Sample information regarding population, sex, organ, mating status, and dissection date.
652
653 Table S2 Raw read counts for each sample and SV.
654
655 Table S3 Assigned taxa for each SV.
38