Abstract Eukaryotes have established symbiotic relationship with microorganisms, which enables them to accomplish functions that they cannot perform alone. In the German cockroach, Blattella germanica, the obligate endosymbiont Blattabacterium coexists with a rich gut microbiota. The transmission of Blattabacterium is vertical, but little is known about how the gut microbiota colonizes newborn individuals. In this study, we treated B. germanica populations with rifampicin, a broad-spectrum antibiotic, during two generations and analyzed gut bacterial composition and the Blattabacterium load in control and rifampicin-treated populations. Rifampicin exerted a drastic effect on gut microbiota composition, which recovered in the second generation in the case where the antibiotic was not added to the diet. Furthermore, we observed that bacterial species present in the diet, and particularly in the feces, contribute significantly to establishing the gut microbiota. Finally, the Blattabacterium population remained unaffected by the antibiotic treatment of adults during the first generation but was strongly reduced in the second generation, suggesting that this intracellular symbiont is sensitive to rifampicin only during the infection of the mature oocytes, when it is in an extracellular stage. insect symbiosis, gut microbiota, endosymbiont, antibiotic treatment, microbiota transmission INTRODUCTION When studying the widespread distribution of arthropods throughout our terrestrial environment, we must also consider their mutualistic relationship with microorganisms. It has been estimated that about 15% of insects maintain a mutualistic endosymbiotic association with bacteria (Douglas 1998; Moran, McCutcheon and Nakabachi 2008; Moya et al.2009). Moreover, most insects harbor intestinal symbionts, which contribute to their normal physiology and survival (Engel and Moran 2013; Yun et al.2014). Cockroaches and the lower termite Mastotermes darwiniensis (henceforth Mastotermes) harbor the endosymbiont Blattabacterium cuenoti (henceforth Blattabacterium), which belongs to Flavobacteria, located inside specialized cells (bacteriocytes) in the fat body, and they also have a rich and diverse gut microbiota. Hence, these arthropods are paradigmatic because they harbor both types of symbiotic system, providing a unique opportunity to study the dialog between two spatially separated symbionts (Bandi et al.1995; Tokuda et al.2013; Sabree and Moran 2014). Phylogenetically speaking, cockroaches (Dictyoptera: Blattaria) and termites (Dictyoptera: Isoptera) are closely related. In fact, termites form a monophyletic clade that evolved from wood-feeding cockroaches 150–170 Mya (Lo et al.2000; Bourguignon et al.2015; Nalepa 2015). The evolutionary history of Blattabacterium and their corresponding hosts is coherent, indicating that the acquisition of Blattabacterium took place in a common ancestor of cockroaches and termites (Patiño-Navarrete et al.2013). Thus, the endosymbiont was lost in all termite lineages with the exception of Mastotermes (Bandi et al.1995). The genome sequencing of Blattabacterium from several cockroach hosts, together with studies of comparative genomics, metabolic modeling and metatranscriptomics of the fat body, has led researchers to postulate that the role of Blattabacterium is to supply essential amino acids to the host, and to participate in the host's nitrogen recycling (López-Sánchez et al.2009; Sabree, Kambhampati and Moran 2009; González-Domenech et al.2012; Patiño-Navarrete et al.2014). However, Blattabacterium from the wood-feeding cockroach Cryptocercus punctulatus (henceforth Cryptocercus) and Mastotermes have lost the pathways required to synthesize five and four essential amino acids, respectively. The phylogenetic proximity of both lineages, which forms the basal branch in termite phylogeny, indicates that most gene losses took place before both lineages split (Lo et al.2003; Neef et al.2011; Sabree et al.2012; Sabree and Moran 2014). As both insects are xylophagous, the lost pathways could be compensated by similar functions undertaken by the gut microbiota (or other microorganisms) acquired by ancestral hosts. Tokuda et al. (2013) sequenced the Blattabacterium genome of a wood-feeding, non-social cockroach, Panesthia angustipennis, which is phylogenetically distant from Mastotermes and Cryptocercus. They found that the pathways for essential amino-acids synthesis are complete in this new genome, which is more similar to the genome of other non-social, omnivorous cockroaches. The authors concluded that the pathway losses of the endosymbiont are associated with the social behavior of Mastotermes and Cryptocercus, which guarantee a high-fidelity transfer of the gut microbes replacing the lost Blattabacterium metabolic functions, or even the loss of the endosymbiont in higher termites (Tokuda et al.2013). The shift from an omnivorous to a wood-based diet in the ancestor of termites and the Cryptocercus lineage was accompanied by the acquisition of cellulolytic flagellates, a specialized gut microbiota and the development of proctodeal trophallaxis (Brune and Dietrich 2015; Nalepa 2015). The function of microbes in Cryptocercus and wood-feeding termites is to metabolize and upgrade their cellulose-based nitrogen-poor diet. Lately, the loss of flagellates and the endosymbiont in the higher termites resulted in an entirely prokaryotic gut microbiota and sophisticated social behavior (Brune 2014; Brune and Dietrich 2015; Nalepa 2015). Cockroaches of the genus Cryptocercus and termites have the most complex gut community found in insects so far (Engel and Moran 2013). In Cryptocercus and Mastotermes, the most predominant phyla are Spirochaetes, Proteobacteria, Firmicutes and Bacteroidetes, with reperesentations of Actinobacteria, Synergistetes, Verrucomicrobia, candidate phylum TG1 and candidate phylum TG2 (Berlanga, Paster and Guerrero 2009; Dietrich, Köhler and Brune 2014; Berlanga 2015). In higher temites the predominant phyla are Spirochaetes, Firmicutes, Bacteroidetes (similar to those found in Cryptocercus and Mastotermes), candidate phylum TG3, Proteobacteria and Fibrobacteres (Hongoh 2010; Dietrich, Köhler and Brune 2014; Brune and Dietrich 2015). Most cockroaches are omnivorous and non-social insects, and harbor Blattabacterium that ensures nitrogen recycling and upgrading in addition to a rich complex gut microbiota, whose role is not well understood. This gut microbiota is mainly located in the hindgut, i.e. the last portion of the digestive tract (Schauer, Thompson and Brune 2012; Brune and Dietrich 2015; Gontang et al.2017). Studies into their composition seem to indicate the existence of a core microbial community based on the relative abundance of the main phyla. As in mammals, the most dominant are Firmicutes (mainly Clostridiales) and Bacteroidetes, which could be related with the omnivorous nature of both cockroaches and mammals; Proteobacteria (as in wood-feeding termites) and Fusobacteria are also abundant (Schauer, Thompson and Brune 2012; Sabree and Moran 2014; Pérez-Cobas et al.2015; Gontang et al.2017; Zhang et al.2017). Symbiont transmission is essential to ensure the maintenance of the symbiotic systems through host generations. Two fundamental transmission modes can be distinguised: horizontal and vertical, notwithstanding mixed transmission (Bright and Bulgheresi 2010). Cockroaches are hemimetabolous insects, which pass through several nymphal stages from egg to adult (six in females of Blattella germanica). In cockroaches, Blattabacterium, as other insect endosymbionts, is transmitted vertically from mother to offspring. During transmission, after the ootheca hatch, bacteriocytes containing Blattabacterium migrate from the fat body to the ovarioles in nymphs, where they adhere to the follicle cells surrounding the oocyte. After several days, the endosymbionts are expelled by exocytosis as free cells and migrate up to the intercellular space located between the oocyte and the follicle cells, where they are engulfed via endocytosis by the mature oocyte, once vitellogenesis ends and just before ovulation takes place in the adult (around 7 days after adult ecdysis), recovering the host-derived symbiosomal membrane that surrounds each endosymbiont (Tanaka 1973; Sacchi et al.1988, 1996; Giorgi and Nordin 1994). Despite our knowledge of the above mechanisms, information is still lacking as to how the gut microbiota is acquired by cockroaches. The neonatal digestive tract is microbe-free and the microbiota becomes fully established by the third instar, at which point the nymphs acquire nutritional independence (Carrasco et al.2014; Berlanga 2015). Our study aims to shed light on how gut bacteria are acquired and later colonize the hindgut of B. germanica. The absence of vertical transmission would indicate that the gut microbiota must be horizontally acquired from the environment. As B. germanica is a non-social insect, the lack of proctodeal feeding leaves the offspring with only two possible gut microbiota acquisition: a deterministic transfer by contact with colony members or their feces, or a stochastic inoculation via environmental factors. To investigate this question, we have designed an experiment to study and compare the composition of the gut microbiota during antibiotic treatment with rifampicin, and during the microbiota recovery in the next generation after antibiotic removal. The study also evaluated the acquisition of new bacteria, either from the diet, from feces, or from any other environmental source. Rifampicin was used because it is one of the most potent and broad-spectrum antibiotics due to its high-affinity binding to the RNAP β subunit (encoded rpoB gene), causing the inhibition of the bacterial DNA-dependent RNA polymerase RNAP by directly blocking the RNA elongation path (Campbell et al.2001; Goldstein 2014). Simultaneously, we have monitored the effect of rifampicin treatment on the endosymbiotic population by qPCR during the treatments. MATERIALS AND METHODS Blattella germanica population in this experiment Blattella germanica originated from a stable laboratory population housed by Dr. X. Bellés’ group at the Institute of Evolutionary Biology (CSIC-UPF, Barcelona). It was reared in culture chambers at the Cavanilles Institute of Biodiversity and Evolutionary Biology (University of Valencia) in aerated containers at 25 °C, 65% humidity and a photoperiod of 12L:12D. Cockroaches were fed dog-food pellets (Teklad Envigo, Madison, USA; global 21% protein dog diet, 2021C) and water was supplied ad libitum. When required (see below), the antibiotic rifampicin (Alfa Aesar, Karlsruhe, Germany) was supplied with the water at 0.02% (w/v). In addition, feces from control population were added to the diet when required. The dose of rifampicin was chosen because in a preliminary study higher doses beginning in nymphs seriously affected the B. germanica development (data not shown). Experimental design Newly hatched cockroaches in nymphal (n) stage (first generation, G1) (time 0n at G1 in experimental graphic design at Fig. 1) were grown until reaching adult (a) stage (identified by emergence of wings, on day 38n approximately) after the final adult ecdysis (time 0a at G1). At that point, a synchronized adult population (consisting of a set of male and female individuals collected between 0 and 48 h after adult hatching) was initiated (adult time 0a). Before any treatment, four female adult cockroaches were dissected (C0). Then, the remaining synchronized adult population was divided into two new populations. One was treated with rifampicin (+R, R population), remaining the other as control (–R, C population). Females of the rifampicin-treated and untreated populations (R and C, respectively) were dissected at the following adult G1 times (days): 10a (three females, C10 and four females, R10), 20a (three females, C20 and three females, R20), and 30a (three females C30 and four females R30). Figure 1. View largeDownload slide Experimental design to evaluate the effect of rifampicin treatment on B. germanica endosymbiont and hindgut microbiota during two generations. Timeline shows nymphal (n) and adult (a) stages for each generation, and the day on which adult females were analyzed. The experiment was initiated with a synchronized adult population (0a) of cockroaches in G1. Before any treatment, the indicated number of female was dissected at this point (C0). The population was divided and individuals were treated with rifampicin (R, R population) or untreated remaining as control (–R, C population). In G1, female cockroaches were dissected at each time point (days) for C and R populations: C10, C20, C30, R10, R20 and R30 (in C10 point, three individuals were analyzed but later reduced to 2, see text for details). Nymphs from R population were used to initiate G2, which was treated with rifampicin (+R, population RR), not treated with antibiotic (–R, population RC) or not treated with antibiotic but supplied with feces from a C population (−R+F, population RF). Ten-day-old female cockroaches from these three populations were dissected. At the indicated time points, hindgut and fat body were collected from the individuals and analyzed, as described in Materials and Methods. Figure 1. View largeDownload slide Experimental design to evaluate the effect of rifampicin treatment on B. germanica endosymbiont and hindgut microbiota during two generations. Timeline shows nymphal (n) and adult (a) stages for each generation, and the day on which adult females were analyzed. The experiment was initiated with a synchronized adult population (0a) of cockroaches in G1. Before any treatment, the indicated number of female was dissected at this point (C0). The population was divided and individuals were treated with rifampicin (R, R population) or untreated remaining as control (–R, C population). In G1, female cockroaches were dissected at each time point (days) for C and R populations: C10, C20, C30, R10, R20 and R30 (in C10 point, three individuals were analyzed but later reduced to 2, see text for details). Nymphs from R population were used to initiate G2, which was treated with rifampicin (+R, population RR), not treated with antibiotic (–R, population RC) or not treated with antibiotic but supplied with feces from a C population (−R+F, population RF). Ten-day-old female cockroaches from these three populations were dissected. At the indicated time points, hindgut and fat body were collected from the individuals and analyzed, as described in Materials and Methods. After 30 days of rifampicin treatment, some female adult cockroaches from the R population with fully developed egg case (ootheca) were isolated in individual plastic containers suspending the rifampicin treatment until the emergence of the nymphs (just a few days later). Then, newly hatched nymphs (second generation, G2) were divided in two populations that were maintained without rifampicin (–R, RC population), or without rifampicin but supplied with feces from a control population, (–R + F, RF population). A third population was established with nymphs hatched from females always treated with rifampicin (+R, RR population). Ten days after reaching the adult stage, time 10a at G2, female cockroaches were dissected from each treatment (6, 3 and 10 females from RR, RC and RF populations, respectively). Thus, a total of 10 time points and 43 females were analyzed, 24 and 19 at G1 and G2, respectively (Fig. 1). All the analyzed cockroaches were anesthetized under a stream of CO2 and freshly dissected on a paraffin plate. Then, hindguts and fat body tissue were extracted. Both tissues were collected independently using Ringer's solution, frozen in liquid nitrogen and stored at –80°C until use. The hindgut was used to analyze microbiota composition, whereas the fat body was used to monitor the Blattabacterium population. DNA extraction, bacterial 16S rRNA gene amplification and sequencing Hindgut and fat body tissue were ground with sterile plastic pestle in cell lysis buffer (CLB). Food and feces samples were ground to a fine powder in liquid nitrogen by mortar and pestle, and then CLB was added. To break the cell wall of Gram-positive bacteria, 1 μl of lysozyme (20 mg/mL) was added during lysis in CLB for all the samples. Total DNA was obtained using the JetFlex Genomic DNA Extraction kit (Genomed Löhne, Germany) and quantified using the Qubit method (Thermo Fisher). DNA obtained from the hindgut, food and feces was used as template for amplification of the V3-V4 region of the bacterial 16S rRNA genes and sequenced using the Illumina MySeq technology at the Sequencing Facility Service (SCSIE) at the University of Valencia (hindgut), and the FISABIO Foundation (food and feces). DNA obtained from the fat body was used for qPCR analyses. Processing, biodiversity and statistical analyses of the 16S rRNA reads Illumina reads were cleaned and quality-filtered using the Prinseq-lite program (Schmieder and Edwards 2011). Sequences shorter than 100 bp and with a mean Phred quality score less than 20 were removed. We used the QIIME pipeline for the operational taxonomic units (OTU) clusterization (Caporaso et al.2010b), taxonomic assignments and estimation of alpha and beta diversities. Sequences were clustered at 97% pairwise identity using the UCLUST de novo OTU picking method. A representative sequence from each OTU was aligned to the SILVA_119 dataset using PyNAST (Caporaso et al.2010a). Taxonomic assignments were carried out with UCLUST using the SILVA_119_majority taxonomy dataset as training. In the analysis, we used annotations at genus or family levels, but also considered other relevant sequences that only reached higher well-identified classification levels (named as uc). The Shannon diversity index (Shannon 1948), the species richness estimators Chao1 (Chao 1984) and the observed OTUs were calculated for all the individuals analyzed, normalized by the number of sequences to avoid bias by differences in sequencing depth between individuals. These estimators are implemented in Vegan package (Oksanen et al.2016) under R software (http://cran.r-project.org) (Development Core Team 2011). The script compare_alpha_diversity.py was used to apply a t-test to statistically compare the alpha diversity metrics between treatments. Significant differences were reported when the p-value is < 0.05 (adjusted P-values by false discovery rate [FDR] method). To test for differences between microbial communities of the different samples, Bray–Curtis dissimilarities were estimated using the Vegan package (Oksanen et al.2016). This measurement quantifies the compositional dissimilarity between two different samples, based on counts at each sample. Its value is bound between 0 and 1, where 0 means the two samples have the same composition (that is, they share all species), and 1 means the two samples do not share any species (Bray and Curtis 1957). The Bray–Curtis dissimilarities were used to perform a hierarchical clustering of the samples and a principal coordinates analysis (PCoA) to study the differences in the microbial communities associated to the different treatments (ter Braak 1986). To test the effect of the treatment on the variation in microbial composition, we also applied a permutational multivariate analysis of variance (implemented in the Adonis function of Vegan package) with 1000 permutations. Quantitative PCR For the quantification of Blattabacterium population in the fat body, an absolute quantitative real-time PCR approach, was developed. Urease gene ureC (accession number NC_013454.1) was used as specific of the endosymbiont population (López-Sánchez et al.2009), whereas actin5C gene (accession number AJ861721.1) was used for the host control (Maestro et al.2005). Primer pair used for amplifying ureC fragment was described in (Patiño-Navarrete et al.2014) (UC1F: 5΄-GTCCAGCAACTGGAACTATAGCCA-3΄ and UC1R: 5΄-CCTCCTGCACCTGCTTCTATTTGT-3΄), and specific primers for the actin5C gene were designed for this experiment: ActinF: 5΄-CACATACAACTCCATTATGAAGTGCGA-3΄ and ActinR: 5΄-TGTCGGCAATTCCGGTACATG-3΄. PCR reactions were carried out on an ArialMx Real-Time PCR System (Agilent Technologies, Düren, Germany). The qPCRs were performed using SYBR Green as fluorescent reporter in a volume of 20 μl, which contained 10 μl of Brilliant III Ultra—Fast SYBR Green QPCR Master Mix (Agilent Technologies), 5.7 μl of H2O, 0.5 μl of 10 μM of each primer, 0.3 μl of 1:50 dilution of 1 mM Reference Dye Brilliant III Ultra—Fast SYBR Green QPCR (Agilent Technologies) and 3 μl of genomic DNA. Purified PCR-amplified products were quantified using the Qubit method (Thermo Fisher). PCR products from urease gene and actin gene obtained with primer pair UC1F/UC1R and ActinF/ActinR, respectively, were purified using the NucleoSpin Gel and PCR Clean-up kit (Macherey-Nagel, Düren, Germany) and products were serially diluted 10-fold, to generate a standard curve for each gene by a 10-fold serial dilution, one for each gene. Cycling conditions were as follows: 3 min at 95 °C, 45 cycles of 5 s at 95 °C, 10 s at 60 °C and 10 s at 72 °C. The fluorescence measurement was performed at 72 °C to minimize the fluorescence that could arise from primer-dimer unspecific annealing. At the end of each reaction, a melting curve was performed to check the specificity of amplification and to confirm the absence of primer dimer formation. All reactions, including negative controls (containing water instead of DNA), were run in triplicate in 96-wells plates. Statistical differences among samples of the quantitative PCR results were tested by the Tukey multiple comparisons test (adjusted P-values by FDR method). Deposition of sequence data All the sequences in this study have been submitted to the European Bioinformatics Institute (EBI), EMBL Nucleotide Archive under accession number PRJEB23464. RESULTS Microbial diversity of the gut microbiota in B. germanica We analyzed the 16S rRNA gene (regions V3-V4) to estimate the gut bacterial composition in 43 female cockroaches belonging to 10 different time points and different treatments (see Fig. 1; Fig. S1, Supporting Information). The total number of reads amounted to 26 346 434 with an average number of 612 707 sequences per sample (maximum: 3 112 990, minimum: 56 901). After eliminating singletons, a total of 48 076 OTUs (at 97% level of homology) were observed, which were classified into 674 taxa belonging to 24 phyla, 21 in the case of G1 and 17 in G2 (see Table S1, Supporting Information). In this work, we used genus level (or the closer to genus as possible) for the classification of taxa. To work only with the most predominant taxa, we considered only those with an abundance of above 0.1% in at least one of the samples. Then, 47 taxa fulfilled this requirement and were the only ones considered in most of the analyses. These 47 predominant taxa belonged to the following eight phyla Bacteroidetes, Deferribacteres, Firmicutes, Fusobacteria, Actinobacteria, Planctomycetes, Proteobacteria and TM7. Of them, 20 could be assigned to genera, 16 reached a family level of classification, whereas the 11 remaining were named with the lowest taxonomic level possible as uc (Fig. S1 and Table S2, Supporting Information). At G1 (samples C0, C and R), the microbiota of the rifampicin-treated cockroaches (R) had a very different composition compared to the control (untreated) individuals (C0 and C). The shift already occurs at 10 days of rifampicin treatment while only small changes occurred after days 20 and 30 of treatment. Very interesting results were obtained for the only time point sampled at generation G2 in the three different treatments. The population continuing the treatment with rifampicin (RR) showed an even greater reduction in diversity than the treated (R) population in G1. On the other hand, a clear recovery in taxa diversity occurred in G2 when no rifampicin was supplied to the food, both in individuals fed normal diet (RC) and in those with a feces-supplemented diet (RF). We carried out PCoA on the bacterial communities derived from the 43 individuals analyzed (Fig. 2). As it can be observed, there is a clear difference between rifampicin-treated and non-treated samples (first axis), and to a lower extent a difference between rifampicin treatment at G1 and G2 (second axis) and between the original control samples (C0 and C) and the control samples after microbiota restoration (RC and RF) in G2 (third axis). The Adonis test showed that the grouping of the samples according to the treatment is statistically significant (P-value = 0.001). As expected, the non–antibiotic-treated samples are more similar to each other. The RC and RF samples look mixed, but the Adonis test using only these two groups indicated that there are significant differences (P-value = 0.006), deserving further study (see below). Figure 2. View largeDownload slide PCoA plot showing microbiotas similarity between the individuals analyzed under the six different treatments. Figure 2. View largeDownload slide PCoA plot showing microbiotas similarity between the individuals analyzed under the six different treatments. To test whether the samples in the different time points at G1 were homogeneous, we applied an Adonis analysis to the non–rifampicin-treated samples (C10, C20 and C30) on one hand, and to the rifampicin-treated ones on the other hand (R10, R20 and R30). In the former, we analyzed if there were differences due to time of development (female age), and in the second if there were differences mainly due to the time of rifampicin treatment. In the latter case, there was not a significant effect of sampling time (P-value = 0.3), whereas in the case of the C population, the time effect was significant (P-value = 0.012). Then, to determine the number of subgroups of samples inside the population C (presumably there should be three, one for each time point), we used the LOF (local outlier factor) algorithm to identifying density-based local outliers (Breunig et al.2000). Two subgroups were identified, one formed by the majority of the samples and the other formed by possible outliers. Sample C10.1 obtained the highest outlier score (data not shown). Again, we applied the Adonis analysis on the C samples after removing the outlier and now the time effect was not significant (P-value = 0.055). Thus, we determined that R and C (without the outlier) populations behaved like two homogeneous groups regardless of the day females were analyzed. Henceforth, in the subsequent analyses we used the following six groups (marked in red capital letters in Fig. 1): C0 (G1 population at day 0), C (formed by the combination of time points of eight adult controls during G1, at days 10 (2 samples), 20 (3 samples) and 30 (3 samples)), R (formed by the combination of the three time points of 11 G1 adults under rifampicin treatment at days 10 (four samples), 20 (three samples) and 30 (four samples), RR (adult population at G2 with rifampicin treatment), RC (adult control population at G2 with no rifampicin supply) and RF (adult population at G2 with no rifampicin supply but supplemented with feces). All the analyses were then carried out in 23 and 19 individuals from G1 and G2, respectively. The distribution of the 47 taxa and the relative abundance of the eight phyla for each treatment are shown at Fig. 3 and Table S2, Supporting Information, respectively. Bacteroidetes, Firmicutes and Proteobacteria are the predominant phyla in all the treatments, with the exception of Fusobacterium that is predominant in R samples. Again, we observed the powerful effect of rifampicin treatment at G1 (R) and G2 (RR) in the microbiota composition with respect to control populations. Furthermore, there are striking differences between the two rifampicin-treated groups in the two generations, as shown previously by PCoA (Fig. 2). Also evident is the closeness of taxa and abundances in control populations (C0 and C) at G1 with RC and RF at G2, meaning that the microbiota has been recovered (at least in the main taxa) after rifampicin treatment. Interestingly, we detected a shared microbiome composed of 10 taxa present in 100% of the individuals regardless of generation, sampling time, abundance or treatments. Its composition was Desulfovibrio (Proteobacteria phylum), Tannerella, Bacteroides, Dysgonomonas (Bacteroidetes phylum), uc_Planctomycetaceae, uc_Planctomycetes, uc_Planctomycetes;vadinHA49 (Planctomycetes phylum), uc_Erysipelotrichaceae, Erysipelotrichaceae;Incertae Sedis (Firmicutes phylum) and Fusobacterium (Fusobacteria phylum) (marked in bold in Table S3, Supporting Information). Figure 3. View largeDownload slide Bacterial composition of the gut microbiota per treatment. Relative abundance of major taxa based on the taxonomic classification of 16S rRNA sequences at genus level. C0, control population at 0–2 days; C, control, non–rifampicin-treated population at G1; R, rifampicin-treated population at G1; RR, rifampicin-treated population at G2; RC, non–rifampicin-treated population at G2; RF, non–rifampicin-treated population supplemented with feces at G2. See Fig. 1 for details. Figure 3. View largeDownload slide Bacterial composition of the gut microbiota per treatment. Relative abundance of major taxa based on the taxonomic classification of 16S rRNA sequences at genus level. C0, control population at 0–2 days; C, control, non–rifampicin-treated population at G1; R, rifampicin-treated population at G1; RR, rifampicin-treated population at G2; RC, non–rifampicin-treated population at G2; RF, non–rifampicin-treated population supplemented with feces at G2. See Fig. 1 for details. Inter-treatment variation was statistically tested (t-test) by comparing the alpha-diversity metrics (Table 1). Regarding the Shannon index, the diversity in rifampicin-treated populations R and RR is significantly lower (P-value < 0.05) compared to the other non–rifampicin-treated populations. On the other hand, the diversity among C0, C, RC and RF are not significantly different. These results confirm that the loss in diversity after the antibiotic treatment is recovered after discontinuing rifampicin in G2. On the other hand, when comparing the Chao1 and Observed OTUS values between treatments, we observed that richness in rifampicin treatments (R and RR) is significantly lower (P-value < 0.05) than in controls (C0 and C) and in RC and RF at G2. Nevertheless, richness in RC and RF is significantly lower than in control populations, indicating that although the richness increases after removing the antibiotic, it is not completely recovered after 10 days. In summary, bacterial diversity and richness were severely affected by rifampicin treatment and, despite recovered diversity after discontinuing antibiotic, recovery in terms of species richness is incomplete. Table 1. Alpha diversity. Shannon Chao1 Observed OTUs Mean SD Mean SD Mean SD C0 7.39 0.32 10 091 2237 2388 649 C 7.03 0.46 10,455 1741 2521 408 R 3.86 0.44 5346 929 1453 206 RR 3.10 0.15 785 50 337 27 RC 6.57 0.17 3583 986 1267 191 RF 6.76 0.22 3182 708 1184 175 Shannon Chao1 Observed OTUs Mean SD Mean SD Mean SD C0 7.39 0.32 10 091 2237 2388 649 C 7.03 0.46 10,455 1741 2521 408 R 3.86 0.44 5346 929 1453 206 RR 3.10 0.15 785 50 337 27 RC 6.57 0.17 3583 986 1267 191 RF 6.76 0.22 3182 708 1184 175 Shannon index and richness estimators, Chao1 (expected OTUs) and observed OTUs, for the different treatments calculated on rarefied samples with equal number of sequences per sample. C0, C, R, RR, RC and RF as in Fig. 3. SD, standard deviation. View Large To measure the differences in the bacterial community under the different conditions, we performed multiple comparisons of the Bray–Curtis distances between samples corresponding to different treatments and between replicates (Fig. 4). All the comparisons between pairs of treatments gave a distance value significantly higher (P-value < 0.01) than that expected between replicates (within the same treatment), indicating that a different community can be distinguished for each treatment. Regarding each pair of comparisons between the six groups (15 in total), we observed that the greatest differences (distance greater than 0.7) were between rifampicin-treated and non-treated samples, both in G1 (R and RR vs. C0 and C) and in G2 (R and RR vs. RC and RF), indicating, again, the clear effects of rifampicin treatment. Figure 4. View largeDownload slide Boxplots representing the comparison of Bray–Curtis distances between samples of the same treatment (replicates comparison) and between samples of two different treatments (treatments comparison). The greater the distance, the larger the difference in microbial communities. Code as in Fig. 3. Figure 4. View largeDownload slide Boxplots representing the comparison of Bray–Curtis distances between samples of the same treatment (replicates comparison) and between samples of two different treatments (treatments comparison). The greater the distance, the larger the difference in microbial communities. Code as in Fig. 3. We performed a heat map and cluster analysis based on taxon abundance for the six conditions, considering the 47 taxa under study (Fig. 5). As we can see, there are two main clusters, one formed by the rifampicin-treated females at G1 and G2 (R and RR), and the other by the untreated ones. However, in the latter cluster, two subclusters are formed, one with the samples never treated with rifampicin in G1 (C0 and C), and those without the antibiotic after one generation of rifampicin treatment RC and RF (supplemented with feces). Overall, we see that only Desulfovibrio is highly abundant in all groups (between 11.23 and 23.00%, see Table S2, Supporting Information), and is not negatively affected by rifampicin. We also found some taxa became more abundant after rifampicin treatments in R and RR (Erysipelotrichaceae and Tannerella). Other were more abundant in R but not in RR (i.e. Fusobacterium, which is the most predominant in R, and practically disappear in RR). Finally, some increased only in RR (i.e. Planctomycetes). Figure 5. View largeDownload slide Heat map and hierarchical clustering analysis representing the differences in bacterial families’ abundance for the different treatments. The different colors indicate the relative abundance of each family. Figure 5. View largeDownload slide Heat map and hierarchical clustering analysis representing the differences in bacterial families’ abundance for the different treatments. The different colors indicate the relative abundance of each family. We have further examined which particular taxa showed significant differences (Wilcoxon-test) in abundance among the 15 possible pair of treatments (Table S3, Supporting Information). From the 47 taxa with an abundance of above 0.1%, we selected 44 that were present in at least three samples. Thus, uc_Clostridiales, uc_Coriobacteriaceae and Undibacterium were not considered. Only three comparisons involving RC (RC vs. C, C0, or RF) showed no significant differences in taxa abundance. The two controls (C vs. C0) showed only four taxa with different abundances, whereas RF compared with the two controls showed differences in 14 (RF vs. C0) and 19 (RF vs. C) taxa. Two genera, ‘Ca. Saccharimonas’ and Thalassospira were lost in RC, and Pseudomonas and Blattabacterium (the latter is the endosymbiont and its presence must be a contamination during gut dissection) drastically decreased in abundance both in RC and RF. In R population, only seven taxa maintained a similar relative abundance as in C, while 28 taxa significantly decreased in abundance in favor of nine resistant ones. In RR, only two taxa had similar relative abundance as in C, 34 taxa significantly decreased in abundance and eight taxa were resistant (Table S3, Supporting Information). Finally, in the comparison between the rifampicin treatments in the two generations (R vs. RR), 15 taxa maintained a similar abundance, whereas a shift in the predominant taxa occurred in the RR population, with the complete loss of ‘Ca. Saccharimonas’ and a drastic reduction in the abundance of 23 taxa. Only five ‘super-resistant’ taxa were observed in RR, which significantly increased their abundance: Desulfovibrio, Tannerella, uc_Planctomycetes;vadinHA49, uc_Planctomycetes;Other and uc_Planctomycetaceae (see also Fig. 5; Table S2, Supporting Information). Microbiota composition in food and feces To address the gut microbiota acquisition process, we studied the bacteria present in the food (dog food pellets) and in the feces from control adults never treated with rifampicin. Two replicates of food and feces were sequenced, and the percentages of the combined reads were compared with the percentage of the combined reads of the control samples C, as representative of the total gut microbiota (Table S4, Supporting Information). For the analysis, we took into account extremely low levels of abundance (equal or lower than 0.0002%) to be able to detect most of the bacteria present that could be the source for the acquisition of the microbiota. In total 69 taxa were detected, 67 of which were in feces and 29 in food. The most interesting result is that 61 taxa detected in feces were also detected in control samples, of which 26 were also present in food and feces. Two taxa (Pantoea and Enterobacteraceae;Ambiguous_taxa) were detected only in food samples, whereas five taxa were unique for feces samples (uc_Bacteroidales;CR-115, Fusobacteriales;boneC3G7, Acetobacter, uc_Acetobacteraceae and Acetobacteraceae;Other). Finally, we identified one taxa (Weissella) found in food and feces. Remarkably, the most abundant taxa in food samples (Enterobacter, Lactobacillus and Pantoea) are in very low abundance in feces and in controls, reflecting a bacterial selection by the gut environmental conditions. It is worth mentioning that there are five predominant taxa in control populations that were not detected in either food or in feces (uc_Bacteroidales;gir-aah93h0; uc_Selenomonadales; uc_Peptococcaceae; uc_Planctomycetes;Other and the endosymbiont Blattabacterium). In summary, we observed that while food and feces contribute to the gut microbiota acquisition in the cockroach, feces are the main contributor. Is Blattabacterium affected by rifampicin treatment? Monitoring the abundance by qPCR As results show (Fig. 6; Table S3, Supporting Information), the urease gene from Blattabacterium varies significantly, about five orders of magnitude, between G1 and G2 samples, whereas no changes are found in the average copy number of the host actin gen. It is also noteworthy that, independently of whether the samples were treated with rifampicin or not, we find a significant reduction in the Blattabacterium abundance at 10, 20 and 30 days in G1 when compared with abundance at C0, whereas there are no significant differences for sampling time (10, 20 or 30 days). Figure 6. View largeDownload slide Absolute quantification of Blattabacterium population in the fat body of cockroaches. (A) The copy number of gene urease (ureC) per ng DNA fat body in samples of generation 1 (G1) untreated (C0, C10, C20 and C30) and treated with rifampicin (R10, R20 and R30). (B) The copy number of gene urease in samples of generation 2 (G2). (C) Gene actin (Actin5C) copy number per ng DNA fat body in samples of G1 and G2. Figure 6. View largeDownload slide Absolute quantification of Blattabacterium population in the fat body of cockroaches. (A) The copy number of gene urease (ureC) per ng DNA fat body in samples of generation 1 (G1) untreated (C0, C10, C20 and C30) and treated with rifampicin (R10, R20 and R30). (B) The copy number of gene urease in samples of generation 2 (G2). (C) Gene actin (Actin5C) copy number per ng DNA fat body in samples of G1 and G2. DISCUSSION This work represents the beginning of a series of experiments to systematically analyze the effect of different antibiotics, diets or any other treatments on the intestinal microbiota of the omnivorous cockroach B. germanica. In this particular study, the main goal was to ascertain the microbiota acquisition route, and also to expand on studies into its composition in adult populations. To modify the composition of the gut microbiota, we chose rifampicin, a broad-spectrum antibiotic that affects both Gram-negative and Gram-positive bacteria (Campbell et al.2001). Based on preliminary results (data not shown), the dose employed was expected to reduce the bacterial diversity present in the hindgut microbiota. Furthermore, we qPCR monitored fat-body samples to assess whether rifampicin treatment had effects on two generations of the endosymbiotic Gram-negative Blattabacterium population. The experiment was designed using synchronized adult individuals between 0 and 2 days old, which had, thus, already established a normal hindgut microbiota during the antibiotic-free nymph phase. Then, we fed rifampicin to a subpopulation until the ootheca emerged, expecting the treatment to have important effects on the microbiota. At G2, three subpopulations were established in the nymphal stage: the first population continued the antibiotic treatment until adult-stage day 10 and was, therefore, expected not to recover the microbiota; the other two populations were not treated with rifampicin but one was supplemented with feces from the control population. Comparing the gut microbiota in these two rifampicin-free populations at G2 with that of the control population indicated whether microbiota composition had recovered, thus providing a way to test the two hypotheses regarding microbiota acquisition in the absence of trophallaxis (Nalepa 2015). Sequencing the 16S rRNA gene from the bacteria present in the hindgut of rifampicin-treated and rifampicin-free females revealed the drastic changes that the microbiota underwent in the antibiotic-treated group. Studies carried out in the fish Gambusia affinis have shown how rifampicin therapy significantly changes their gut microbiota (Carlson et al.2015, 2017). An alteration in microbial diversity was also found in the gut of the Lepidoptera Spodoptera litura larvae fed on a diet supplemented with streptomycin compared to those without treatment (Thakur et al.2016). Although similar studies in B. germanica are lacking, there are some in termites. For instance, in Zootermopsis angusticollis studies into the effect of rifampicin treatment on its gut microbiota revealed a permanent reduction in bacterial diversity after treatment (Rosengaus et al.2011). The analysis of the B. germanica control population at three different adult stages (10, 20 and 30 days old) indicates that the predominant phyla in the gut microbiota of B. germanica are Bacteroidetes (49.99%), Firmicutes (18.22%), Proteobacteria (15.31%) and Fusobacteria (6.65%). Our results agree with those obtained previously in 5- and 10 day-old B. germanica adult cockroaches (Pérez-Cobas et al.2015), and in different developmental instars (Carrasco et al.2014), as well as with other studies into the composition of gut microbiota in different cockroaches, confirming the predominance of these phyla in this insect (Schauer, Thompson and Brune 2012; Sabree and Moran 2014; Gontang et al.2017; Zhang et al.2017). Additionally, relatively abundant families present in B. germanica, such as Lachnospiraceae, Ruminococcaceae, Rikenellaceae, Porphyromonadaceae or Desulfovibrionaceae, are also present in the gut microbiota of the omnivorous cockroach Shelfordella lateralis (Schauer, Thompson and Brune, 2012, 2014). Bacteroidetes and Firmicutes are also the most predominant phyla in other omnivorous animals, including mammals, revealing their importance in the adaptation to a complex diet, whereas Proteobacteria and Fusobacteria are shared with wood-feeding termites and Cryptocercus, which could indicate the importance of phylogenetically shared common bacteria. The results also confirm that Spirochaetes, a common phylum in termites and Cryptocercus, does not form part of the cockroaches’ microbiota, as it has not been found in either B. germanica or in other cockroaches (Berlanga, Paster and Guerrero 2009; Schauer, Thompson and Brune 2012; Bertino-Grimaldi et al.2013; Bauer et al.2015). To detect the presence and distribution of common bacterial lineages among termites and cockroaches, Dietrich, Köhler and Brune (2014) compared the core bacterial gut microbiota in 37 species. They found that although there are shared lineages among cockroaches and termites, the community structure differed greatly between the major host groups. Interestingly, they found that the changes in community structure coincided with major events in termite evolution. A drastic shift in the microbiota has been observed after only 10 days of rifampicin treatment (our first sampling time), indicating that the antibiotic rapidly affects rifampicin-sensitive bacteria, with the resistant bacteria soon becoming a majority. Globally, the rifampicin-treated populations in the two generations (R and RR) proved less diverse than all the other samples. Only five taxa called ‘super-resistant’ remained unaffected after two generations of rifampicin treatment (RR population): Desulfovibrio, Tannerella, uc_Planctomycetes;vadinHA49, uc_Planctomycetes;Other and uc_Planctomycetaceae. Desulfovibrio was highly abundant in all groups in spite of the treatment, showing an important presence in the gut microbiota. A similar pattern was found in a study of the effect of rifampin in the termite's gut, as Desulfovibrio abundance did not vary (Rosengaus et al.2011); furthermore, some Desulfovibrio species are resistant to rifampicin (Dzierzewicz et al.2001). In many bacterial species, rifampicin resistance has mainly been associated with mutations in the rpoB gene, which codes for DNA-dependent RNA polymerase β subunit (Goldstein 2014). However, inactivation of rifampicin by different mechanisms (glycosylation, ribosylation, phosphorylation and degradation by a monooxygenase) has been associated with low-level resistance. Additionally, modifications of cell permeability can transform antibiotic-susceptible bacteria into resistant (reviewed in Tupin et al. (2010) and Goldstein (2014)). The metagenomic study we are carrying out will tell us whether the rpoB gene is also mutated in this taxon, or other mechanisms need to be invoked. Regarding the last three super-resistant taxa, a previous work, analyzing the antibiotic resistance of Planctomycetes organisms, found that many species are naturally resistant to rifampicin (Cayrou, Raoult and Drancourt 2010). Finally, as far as we know, this is the first time Tannerella is associated to rifampicin resistance. The case of Fusobacterium is difficult to interpret. It became the most abundant genus in R population at G1 indicating it is resistant to rifampicin; however, it almost disappeared in RR at G2. It could be argued that Fusobacterium do not resist rifampicin for more than one B. germanica generation. However, in a previous work it was found that the colonization success of the obligatory anaerobic Fusobacterium strain FuSL in gnotobiotic S. lateralis cockroach was strongly affected by the presence of competitors (Tegtmeier et al.2016). A general disturbance of the gut microbiota by a prior antibiotic treatment could cause similar effects avoiding Fusubacterium to colonize the gut. An important finding is that microbiota composition almost fully recovered when antibiotic treatment was discontinued in the next generation (G2). Moreover, a quite similar recovery rate was obtained with and without supplying feces (RC and RF populations), and thus we could postulate that diet is key in hindgut colonization as previously reported (Engel and Moran 2013; Yun et al.2014). However, previous works indicated that coprophagy is an important behavior in B. germanica and it has been demonstrated that nymphs consume conspecific feces (Silverman, Vitale and Shapas 1991; Kopanic and Schal 1999; Kopanic et al.2001). Moreover, second-instar nymphs consumed less fecal material than their first-instar counterparts (Kopanic and Schal 1999). In addition, Kopanic et al. (2001) found that newly ecdysed first-instars nymphs fed only on conspecific feces survived longer than those deprived of feces, concluding that adult feces served as an important nutritional buffer for first-instar nymphs. Recently, it has also been demonstrated that aggregation of B. germanica is regulated by fecal agents produced (at least partly) by the gut microbial community present in the feces (Wada-Katsumata et al.2015). In our study, the 16S rRNA analysis of DNA extracted from the diet (dog food) and from feces of a control population revealed that diet only contained a minor part of the bacteria detected in the microbiota, whereas the bacterial composition present in feces was much more similar to that present in the microbiota. This would corroborate that contact with feces during the first stages of development could be key to establishing the gut microbiota, as previously postulated, albeit undemonstrated (Kopanic et al.2001). The results would be in agreement with a recent finding on the deterministic assembly of the bacterial communities in guts of germ-free S. lateralis (Mikaelyan et al.2016), where it has been demonstrated that the cockroach gut environment elects bacteria related to the autochthonous lineages, even from a foreign inoculum, and the normal gut microbiota is rescued after exposure to conspecifics. Thus, due to the fact that all the nymphs selected to initiate the G2 populations were in contact with maternal feces for some 24 h after hatching, the microbial content could have been available, independently of the presence or absence of feces in the diet (RF or RC) during G2. In agreement with this hypothesis, rifampicin-sensitive taxa could remain in the gut or in feces at very low abundance (even at undetectable levels) until antibiotic pressure was removed, and then these bacteria were able to colonize their gut niche once more. If this is the case, as we carried out the analysis after adult stage day 10, these would correspond to previously assembled populations. In this context, we can postulate that the five taxa present in control populations and absent from feces samples could be due to a sampling effect, as only two fecal samples were analyzed, as compared to eight gut control samples. The slightly higher diversity recovered when feces from control individuals were incorporated in G2 could indicate that recovery was higher due to the addition of feces with microbiota from the control population. Thus, new experiments are required with more sampling time points in G2, including the nymphal stages, as done previously (Carrasco et al.2014). Regarding the effect of rifampicin on the Blattabacterium population, we found that there was no significant reduction throughout G1. However, at G2, all the individuals showed a drastic reduction in the Blattabacterium population (five orders of magnitude), regardless of the treatment received, which suggests that rifampicin negatively affects the vertical transmission of the endosymbiont. Previously, the effect of rifampicin treatment on endosymbionts was studied in a population of the whitefly Bemisia tabaci (Shan et al.2016). The authors found that neither the primary nor the secondary endosymbionts were fully depleted in the adults fed on a diet with rifampicin for 48 h. However, the incidence of both endosymbionts was extremely low in the offspring of the rifampicin-treated adults, indicating that the antibiotic exerted its effect largely via females, due to the vertical transmission of endosymbionts. On the other hand, Koga, Tsuchida and Fukatsu (2003) found that when treating the pea aphid Acyrthosiphon pisum with rifampicin, the primary endosymbiont Buchnera aphidicola was eliminated, but no the facultative Serratia symbiotica. They speculated that the fragile membrane of the primary endosymbiont might increase rifampicin permeability. The results obtained in this work indicated that at least two cockroach generations of rifampicin treatment are necessary to decrease endosymbiont abundance similar to the results obtained in B. tabaci (Shan et al.2016). Due to the fact that rifampicin treatment was initiated in adults of 0–48 h, and that the infection of oocytes by free endosymbionts is temporally located after oocyte maturation by vitellogenesis and before chorionation and ovulation (around day 7 after adult ecdysis) (Tanaka 1973; Sacchi et al.1988, 1996), it is possible that rifampicin can only affect Blattabacterium when it is freely located in the extracellular space outside the oocyte, waiting to be incorporated by endocytosis. In this case, the number of embryonic bacteriocytes formed during the embryo development and in consequence, the Blattabacterium load in G2 could also be affected. Nevertheless, it is surprising that rifampicin cannot negatively affect Blattabacterium when it is inside the bacteriocytes, as can be deduced by the absence of effect on G1 and null difference between RR, RC and RF populations. Rifampicin has been described as a lipid-soluble antibiotic with intracellular antimicrobial potential in macrophages because it can easily penetrate membranes and concentrate inside the cells (Dhillon and Mitchison 1989), but in some cases rifampicin has failed to concentrate inside some macrophages showing reduced antimicrobial activity (Hartkoorn et al.2007). A possible explanation for this observation is that macrophage-mediated rifampicin metabolism reduces the intracellular antibiotic concentration. A similar mechanism has been described in some bacteria that show resistance to rifampicin (Tupin et al.2010; Goldstein 2014) In agreement with that, our results could be compatible with a reduced effective concentration of rifampicin inside the bacteriocyte due to the action of the cell metabolism that pumps the antibiotic outside the cell, or transforms it into an inactive compound. Alternatively, it is possible that rifampicin cannot enter the fat body bacteriocytes at the concentration used in this experiment, or that Blattabacterium is protected inside bacteriocytes by the host-derived symbiosomal membrane that surrounds each bacterial cell (López-Sánchez et al.2009). In this work, we have reported changes in the gut microbiota and in the Blattabacterium load associated to rifampicin treatment, which helps us to understand how microbes are transmitted across generations. Further functional studies of gut metagenomes and the evaluation of host fitness components under antibiotic treatment are needed to demonstrate the role played by microbes in the evolution of their eukaryotic hosts. We consider that the experimental system of cockroaches under rifampicin treatment is a good approach to understand the cross talk among the three components of the system: host, gut microbiota and endosymbiont. Thus, in the absence of Blattabacterium in a rifampicin-treated population, we could ascertain whether the gut microbiota can rescue the functions lost by the absence of the obligate endosymbiont. SUPPLEMENTARY DATA Supplementary data are available at FEMSEC online. Acknowledgements We thank Drs X. Bellés and D. Piulachs for their valuables advice on Blattella germanica biology and Alejandro Artacho for his help with the bioinformatics analyses. FUNDING This work was supported by grant BFU2015-64322-C2-1-R (co-financed by FEDER funds and the Ministerio de Economía y Competitividad, Spain) to AL and PrometeoII/2014/065 (Conselleria d’Educació, Generalitat Valenciana, Spain) to AM. Conflict of interest. None declared. REFERENCES Bandi C, Sironi M, Damiani G et al. The establishment of intracellular symbiosis in an ancestor of cockroaches and termites. P Roy Soc Lond B Bio 1995; 259: 293– 9. Google Scholar CrossRef Search ADS Bauer E, Lampert N, Mikaelyan A et al. Physicochemical conditions, metabolites and community structure of the bacterial microbiota in the gut of wood-feeding cockroaches (Blaberidae: Panesthiinae). FEMS Microbiol Ecol 2015; 91: 1– 14. Google Scholar CrossRef Search ADS PubMed Berlanga M. Functional symbiosis and communication in microbial ecosystems. The case of wood-eating termites and cockroaches. Int Microbiol 2015; 18: 159– 69. Google Scholar PubMed Berlanga M, Paster BJ, Guerrero R. The taxophysiological paradox: changes in the intestinal microbiota of the xylophagous cockroach Cryptocercus punctulatus depending on the physiological state of the host. Int Microbiol 2009; 12: 227– 36. Google Scholar PubMed Bertino-Grimaldi D, Medeiros MN, Vieira RP et al. Bacterial community composition shifts in the gut of Periplaneta americana fed on different lignocellulosic materials. Springerplus 2013; 2: 609. Google Scholar CrossRef Search ADS PubMed Bourguignon T, Lo N, Cameron SL et al. The evolutionary history of termites as inferred from 66 mitochondrial genomes. Mol Biol Evol 2015; 32: 406– 21. Google Scholar CrossRef Search ADS PubMed Bray JR, Curtis JT. An ordination of the upland forest communities of Southern Wisconsin. Ecol Monogr 1957; 27: 325– 49. Google Scholar CrossRef Search ADS Breunig MM, Kriegel H-P, Ng RT et al. LOF: Identifying Density-Based Local Outliers. Proc 2000 Acm Sigmod Int Conf Manag Data 2000, 1– 12. Bright M, Bulgheresi S. A complex journey: transmission of microbial symbionts. Nat Rev Microbiol 2010; 8: 218– 30. Google Scholar CrossRef Search ADS PubMed Brune A. Symbiotic digestion of lignocellulose in termite guts. Nat Rev Microbiol 2014; 12: 168– 80. Google Scholar CrossRef Search ADS PubMed Brune A, Dietrich C. The gut microbiota of termites: digesting the diversity in the light of ecology and evolution. Annu Rev Microbiol 2015; 69: 145– 66. Google Scholar CrossRef Search ADS PubMed Campbell EA, Korzheva N, Mustaev A et al. Structural mechanism for rifampicin inhibition of bacterial RNA polymerase. Cell 2001; 104: 901– 12. Google Scholar CrossRef Search ADS PubMed Caporaso JG, Bittinger K, Bushman FD et al. PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 2010a; 26: 266– 7. Google Scholar CrossRef Search ADS Caporaso JG, Kuczynski J, Stombaugh J et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 2010b; 7: 335– 6. Google Scholar CrossRef Search ADS Carlson JM, Hyde ER, Petrosino JF et al. The host effects of Gambusia affinis with an antibiotic-disrupted microbiome. Comp Biochem Phys C 2015; 178: 163– 8. Carlson JM, Leonard AB, Hyde ER et al. Microbiome disruption and recovery in the fish Gambusia affinis following exposure to broad - spectrum antibiotic. Infect Drug Resist 2017; 10: 143– 54. Google Scholar CrossRef Search ADS PubMed Carrasco P, Pérez-Cobas AE, van de Pol C et al. Succession of the gut microbiota in the cockroach Blattella germanica. Int Microbiol 2014; 17: 99– 109. Google Scholar PubMed Cayrou C, Raoult D, Drancourt M. Broad-spectrum antibiotic resistance of Planctomycetes organisms determined by Etest. J Antimicrob Chemother 2010; 65: 2119– 22. Google Scholar CrossRef Search ADS PubMed Chao A. Nonparametric estimation of the number of classes in a population. Scand J Stat 1984; 11: 265– 70. Dhillon J, Mitchison DA. Activity and penetration of antituberculosis drugs in mouse peritoneal macrophages infected with Mycobacterium microti OV254. Antimicrob Agents Ch 1989; 33: 1255– 9. Google Scholar CrossRef Search ADS Dietrich C, Köhler T, Brune A. The cockroach origin of the termite gut microbiota: patterns in bacterial community structure reflect major evolutionary events. Appl Environ Microb 2014; 80: 2261– 9. Google Scholar CrossRef Search ADS Douglas SE. Nutritional interactions in insect-microbial symbioses: aphids and their symbiotic bacteria Buchnera. Annu Rev Entomol 1998; 43: 17– 37. Google Scholar CrossRef Search ADS PubMed Dzierzewicz Z, Cwalina B, Jaworska-Kik M et al. Susceptibility to antibiotics and biochemical properties of Desulfovibrio desulfuricans strains. Acta Pol Pharm 2001; 58: 439– 44. Google Scholar PubMed Engel P, Moran NA. The gut microbiota of insects - diversity in structure and function. FEMS Microbiol Rev 2013; 37: 699– 735. Google Scholar CrossRef Search ADS PubMed Giorgi F, Nordin JH. Structure of yolk granules in oocytes and eggs of Blattella germanica and their interaction with vitellophages and endosymbiotic bacteria during granule degradation. J Insect Physiol 1994; 40: 1077– 92. Google Scholar CrossRef Search ADS Goldstein BP. Resistance to rifampicin: a review. J Antibiot (Tokyo) 2014; 67: 625– 30. Google Scholar CrossRef Search ADS PubMed Gontang EA, Aylward FO, Carlos C et al. Major changes in microbial diversity and community composition across gut sections of a juvenile Panchlora cockroach. PLoS One 2017; 12: 1– 21. Google Scholar CrossRef Search ADS González-Domenech C, Belda E, Patiño-Navarrete R et al. Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two Blattabacterium cuenoti strains, primary endosymbionts of cockroaches. BMC Microbiol 2012; 12: S5. Google Scholar CrossRef Search ADS PubMed Hartkoorn RC, Chandler B, Owen A et al. Differential drug susceptibility of intracellular and extracellular tuberculosis, and the impact of P-glycoprotein. Tuberculosis (Edinb) 2007; 87: 248– 55. Google Scholar CrossRef Search ADS PubMed Hongoh Y. Diversity and genomes of uncultured microbial symbionts in the termite gut. Biosci Biotech Bioch 2010; 74: 1145– 51. Google Scholar CrossRef Search ADS Koga R, Tsuchida T, Fukatsu T. Changing partners in an obligate symbiosis: a facultative endosymbiont can compensate for loss of the essential endosymbiont Buchnera in an aphid. Proceedings Biol Sci 2003; 270: 2543– 50. Google Scholar CrossRef Search ADS Kopanic RJ, Jr, Holbrook GL, Sevala V et al. An adaptative benefit of facultative coprophagy in the German cockroach Blattella germanica. Ecol Entomol 2001; 26: 154– 62. Google Scholar CrossRef Search ADS Kopanic RJ, Jr, Schal C. Coprophagy facilitates horizontal transmission of bait among cockroaches (Dictyoptera: Blattellidae). Environ Entomol 1999; 28: 431– 8. Google Scholar CrossRef Search ADS Lo N, Bandi C, Watanabe H et al. Evidence for cocladogenesis between diverse dictyopteran lineages and their intracellular endosymbionts. Mol Biol Evol 2003; 20: 907– 13. Google Scholar CrossRef Search ADS PubMed Lo N, Tokuda G, Watanabe H et al. Evidence from multiple gene sequences indicates that termites evolved from wood-feeding cockroaches. Curr Biol 2000; 10: 801– 4. Google Scholar CrossRef Search ADS PubMed López-Sánchez MJ, Neef A, Peretó J et al. Evolutionary convergence and nitrogen metabolism in Blattabacterium strain Bge, primary endosymbiont of the cockroach Blattella germanica. PLoS Genet 2009; 5: e1000721. Google Scholar CrossRef Search ADS PubMed Maestro O, Cruz J, Pascual N et al. Differential expression of two RXR/ultraspiracle isoforms during the life cycle of the hemimetabolous insect Blattella germanica (Dictyoptera, Blattellidae). Mol Cell Endocrinol 2005; 238: 27– 37. Google Scholar CrossRef Search ADS PubMed Mikaelyan A, Thompson CL, Hofer MJ et al. Deterministic assembly of complex bacterial communities in guts of germ-free cockroaches. Appl Environ Microb 2016; 82: 1256– 63. Google Scholar CrossRef Search ADS Moran NA, McCutcheon JP, Nakabachi A. Genomics and evolution of heritable bacterial symbionts. Annu Rev Genet 2008; 42: 165– 90. Google Scholar CrossRef Search ADS PubMed Moya A, Gil R, Latorre A et al. Toward minimal bacterial cells: evolution vs. design. FEMS Microbiol Rev 2009; 33: 225– 35. Google Scholar CrossRef Search ADS PubMed Nalepa CA. Origin of termite eusociality: Trophallaxis integrates the social, nutritional, and microbial environments. Ecol Entomol 2015; 40: 323– 35. Google Scholar CrossRef Search ADS Neef A, Latorre A, Pereto J et al. Genome economization in the endosymbiont of the wood roach Cryptocercus punctulatus due to drastic loss of amino acid synthesis capabilities. Genome Biol Evol 2011; 3: 1437– 48. Google Scholar CrossRef Search ADS PubMed Oksanen J, Blanchet F, Kindt R et al. Vegan: Community Ecology Package 2016. R Package Version 23-3 . 2016. https://cran.r-project.org/index.html. Patiño-Navarrete R, Moya A, Latorre A et al. Comparative genomics of Blattabacterium cuenoti: the frozen legacy of an ancient endosymbiont genome. Genome Biol Evol 2013; 5: 351– 61. Google Scholar CrossRef Search ADS PubMed Patiño-Navarrete R, Piulachs M-D, Belles X et al. The cockroach Blattella germanica obtains nitrogen from uric acid through a metabolic pathway shared with its bacterial endosymbiont. Biol Lett 2014; 10: 20140407. Google Scholar CrossRef Search ADS PubMed Pérez-Cobas AE, Maiques E, Angelova A et al. Diet shapes the gut microbiota of the omnivorous cockroach Blattella germanica. FEMS Microbiol Ecol 2015; 91: 1– 14. Google Scholar CrossRef Search ADS R Development Core Team. R: A Language and Environment for Statistical Computing . Vienna, Austria: R Foundation for Statistical Computing, 2011. http://www.r-project.org/ . (11 January 2018, date last accessed) Rosengaus RB, Zecher CN, Schultheis KF et al. Disruption of the termite gut microbiota and its prolonged consequences for fitness. Appl Environ Microb 2011; 77: 4303– 12. Google Scholar CrossRef Search ADS Sabree ZL, Huang CY, Arakawa G et al. Genome shrinkage and loss of nutrient-providing potential in the obligate symbiont of the primitive termite Mastotermes darwiniensis. Appl Environ Microb 2012; 78: 204– 10. Google Scholar CrossRef Search ADS Sabree ZL, Kambhampati S, Moran NA. Nitrogen recycling and nutritional provisioning by Blattabacterium, the cockroach endosymbiont. P Natl Acad Sci USA 2009; 106: 19521– 6. Google Scholar CrossRef Search ADS Sabree ZL, Moran NA. Host-specific assemblages typify gut microbial communities of related insect species. Springerplus 2014; 3: 138. Google Scholar CrossRef Search ADS PubMed Sacchi L, Corona S, Grigolo A et al. The fate of the endocytobionts of Blattella germanica (Blattaria: Blattellidae) and Periplaneta Americana (Blattaria: Blattidae) during embryo development. Ital J Zool 1996; 63: 1– 11. Google Scholar CrossRef Search ADS Sacchi L, Grigolo A, Mazzinit M et al. Symbionts in the oocytes of Blattella germanica (L.) (Dictyoptera: Blattellidae): their mode of transmission. Int J lnsect Morphol Embryol 1988; 17: 437– 46. Google Scholar CrossRef Search ADS Schauer C, Thompson C, Brune A. Pyrotag sequencing of the gut microbiota of the cockroach Shelfordella lateralis reveals a highly dynamic core but only limited effects of diet on community structure. PLoS One 2014; 9: 1– 8. Google Scholar CrossRef Search ADS Schauer C, Thompson CL, Brune A. The bacterial community in the gut of the cockroach Shelfordella lateralis reflects the close evolutionary relatedness of cockroaches and termites. Appl Environ Microb 2012; 78: 2758– 67. Google Scholar CrossRef Search ADS Schmieder R, Edwards R. Quality control and preprocessing of metagenomic datasets. Bioinformatics 2011; 27: 863– 4. Google Scholar CrossRef Search ADS PubMed Shan H-W, Zhang C-R, Yan T-T et al. Temporal changes of symbiont density and host fitness after rifampicin treatment in a whitefly of the Bemisia tabaci species complex. Insect Sci 2016; 23: 200– 14. Google Scholar CrossRef Search ADS PubMed Shannon CE. A mathematical theory of communication. Bell Syst Tech J 1948; 27: 379– 423. Google Scholar CrossRef Search ADS Silverman J, Vitale GI, Shapas TJ. Hydramethylnon uptake by Blattella germanica (Orthoptera: Blattellidae) by coprophagy. J Econ Entomol 1991; 84: 176– 80. Google Scholar CrossRef Search ADS PubMed Tanaka A. General accounts on the oöcyte growth and the identification of vitellogenin by means of immunospecificity in the cockroach, Blattella germanica (L.). Dev Growth Differ 1973; 15: 153– 68. Google Scholar CrossRef Search ADS Thakur A, Dhammi P, Saini HS et al. Effect of antibiotic on survival and development of Spodoptera litura (Lepidoptera: Noctuidae) and its gut microbial diversity. Bull Entomol Res 2016; 106: 387– 94. Google Scholar CrossRef Search ADS PubMed Tegtmeier D, Thompson CL, Schauer C et al. Oxygen affects gut bacterial colonization and metabolic activities in a gnotobiotic cockroach model. Appl Environ Microb 2016; 82: 1080– 9. Google Scholar CrossRef Search ADS ter Braak CJF. Canonical correspondence analysis: a new eigenvector method for multivariate direct gradient analysis. Ecology 1986; 67: 1167– 79. Google Scholar CrossRef Search ADS Tokuda G, Elbourne LDH, Kinjo Y et al. Maintenance of essential amino acid synthesis pathways in the Blattabacterium cuenoti symbiont of a wood-feeding cockroach. Biol Lett 2013; 9: 20121153. Google Scholar CrossRef Search ADS PubMed Tupin A, Gualtieri M, Roquet-Banères F et al. Resistance to rifampicin: at the crossroads between ecological, genomic and medical concerns. Int J Antimicrob Ag 2010; 35: 519– 23. Google Scholar CrossRef Search ADS Wada-Katsumata A, Zurek L, Nalyanya G et al. Gut bacteria mediate aggregation in the German cockroach. P Natl Acad Sci USA 2015; 112: 201504031. Google Scholar CrossRef Search ADS Yun J-H, Roh SW, Whon TW et al. Insect gut bacterial diversity determined by environmental habitat, diet, developmental stage, and phylogeny of host. Appl Environ Microb 2014; 80: 5254– 64. Google Scholar CrossRef Search ADS Zhang F, Sun XX, Zhang XC et al. The interactions between gut microbiota and entomopathogenic fungi: a potential approach for biological control of Blattella germanica (L.). Pest Manag Sci 2017, doi: 10.1002/ps.4726. © FEMS 2018. All rights reserved. For permissions, please e-mail: email@example.com
FEMS Microbiology Ecology – Oxford University Press
Published: Feb 1, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.
All for just $49/month
Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.
Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.
It’s easy to organize your research with our built-in tools.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera