Consistent spatial patterns in microbial taxa of red squirrel gut microbiomes.

Gut microbiomes are diverse ecosystems whose drivers of variation remain largely unknown, especially in time and space. We analysed a dataset with over 900 red squirrel (Tamiasciurus hudsonicus) gut microbiome samples to identify the drivers of gut microbiome composition in this territorial rodent. The large-scale spatiotemporal replication in the data analysed was an essential component of understanding the assembly of these microbial communities. We identified that the spatial location of the sampled squirrels in their local environment is a key contributor to gut microbial community composition. The non-core gut microbiome (present in less than 75% of gut microbiome samples) had highly localised spatial patterns throughout different seasons and different study areas in the host squirrel population. The core gut microbiome, on the other hand, showed some spatial patterns, though fewer than in the non-core gut microbiome. Environmental transmission of microbiota is the likely contributor to the spatiotemporal distribution observed in the North American red squirrel gut microbiome.

Alanyl-glutamine supplementation for Clostridioides difficile infection treatment (ACT): a double-blind randomised controlled trial study protocol.

INTRODUCTION: Clostridioides difficile is the leading cause of healthcare-associated infections in the USA, with an estimated 1 billion dollars in excess cost to the healthcare system annually. C. difficile infection (CDI) has high recurrence rate, up to 25% after first episode and up to 60% for succeeding episodes. Preliminary in vitro and in vivo studies indicate that alanyl-glutamine (AQ) may be beneficial in treating CDI by its effect on restoring intestinal integrity in the epithelial barrier, ameliorating inflammation and decreasing relapse. METHODS AND ANALYSIS: This study is a randomised, placebo-controlled, double-blind, phase II clinical trial. The trial is designed to determine optimal dose and safety of oral AQ at 4, 24 and 44 g doses administered daily for 10 days concurrent with standard treatment of non-severe or severe uncomplicated CDI in persons age 18 and older. The primary outcome of interest is CDI recurrence during 60 days post-treatment follow-up, with the secondary outcome of mortality during 60 days post-treatment follow-up. Exploratory analysis will be done to determine the impact of AQ supplementation on intestinal and systemic inflammation, as well as intestinal microbial and metabolic profiles. ETHICS AND DISSEMINATION: The study has received University of Virginia Institutional Review Board approval (HSR200046, Protocol v9, April 2023). Findings will be disseminated via conference presentations, lectures and peer-reviewed publications. TRIAL REGISTRATION NUMBER: NCT04305769.

Accounting for 16S rRNA copy number prediction uncertainty and its implications in bacterial diversity analyses.

16S rRNA gene copy number (16S GCN) varies among bacterial species and this variation introduces potential biases to microbial diversity analyses using 16S rRNA read counts. To correct the biases, methods have been developed to predict 16S GCN. A recent study suggests that the prediction uncertainty can be so great that copy number correction is not justified in practice. Here we develop RasperGade16S, a novel method and software to better model and capture the inherent uncertainty in 16S GCN prediction. RasperGade16S implements a maximum likelihood framework of pulsed evolution model and explicitly accounts for intraspecific GCN variation and heterogeneous GCN evolution rates among species. Using cross-validation, we show that our method provides robust confidence estimates for the GCN predictions and outperforms other methods in both precision and recall. We have predicted GCN for 592605 OTUs in the SILVA database and tested 113842 bacterial communities that represent an exhaustive and diverse list of engineered and natural environments. We found that the prediction uncertainty is small enough for 99% of the communities that 16S GCN correction should improve their compositional and functional profiles estimated using 16S rRNA reads. On the other hand, we found that GCN variation has limited impacts on beta-diversity analyses such as PCoA, NMDS, PERMANOVA and random-forest test.

The Roles of Gut Microbiome and Plasma Metabolites in the Associations between ABO Blood Groups and Insulin Homeostasis: The Microbiome and Insulin Longitudinal Evaluation Study (MILES).

Non-O blood groups are associated with decreased insulin sensitivity and risk of type 2 diabetes. A recent study pinpointed the associations between ABO blood groups and gut microbiome, which may serve as potential mediators for the observed increased disease risks. We aimed to characterize associations between ABO haplotypes and insulin-related traits as well as potential mediating pathways. We assessed insulin homeostasis in African Americans (AAs; n = 109) and non-Hispanic whites (n = 210) from the Microbiome and Insulin Longitudinal Evaluation Study. The ABO haplotype was determined by six SNPs located in the ABO gene. Based on prior knowledge, we included 21 gut bacteria and 13 plasma metabolites for mediation analysis. In the white study cohort (60 ± 9 years, 42% male), compared to the O1 haplotype, A1 was associated with a higher Matsuda insulin sensitivity index, while a lower relative abundance of Bacteroides massiliensis and lactate levels. Lactate was a likely mediator of this association but not Bacteroides massiliensis. In the AAs group (57 ± 8 years, 33% male), we found no association between any haplotype and insulin-related traits. In conclusion, the A1 haplotype may promote healthy insulin sensitivity in non-Hispanic whites and lactate likely play a role in this process but not selected gut bacteria.

Butyrate-Producing Bacteria and Insulin Homeostasis: The Microbiome and Insulin Longitudinal Evaluation Study (MILES).

Gut microbiome studies have documented depletion of butyrate-producing taxa in type 2 diabetes. We analyzed associations between butyrate-producing taxa and detailed measures of insulin homeostasis, whose dysfunction underlies diabetes in 224 non-Hispanic Whites and 129 African Americans, all of whom completed an oral glucose tolerance test. Stool microbiome was assessed by whole-metagenome shotgun sequencing with taxonomic profiling. We examined associations among 36 butyrate-producing taxa (n = 7 genera and 29 species) and insulin sensitivity, insulin secretion, disposition index, insulin clearance, and prevalence of dysglycemia (prediabetes plus diabetes, 46% of cohort), adjusting for age, sex, BMI, and race. The genus Coprococcus was associated with higher insulin sensitivity (ß = 0.14; P = 0.002) and disposition index (ß = 0.12; P = 0.012) and a lower rate of dysglycemia (odds ratio [OR] 0.91; 95% CI 0.85-0.97; P = 0.0025). In contrast, Flavonifractor was associated with lower insulin sensitivity (ß = -0.13; P = 0.004) and disposition index (ß = -0.11; P = 0.04) and higher prevalence of dysglycemia (OR 1.22; 95% CI 1.08-1.38; P = 0.0013). Species-level analyses found 10 bacteria associated with beneficial directions of effects and two bacteria with adverse associations on insulin homeostasis and dysglycemia. Although most butyrate producers analyzed appear to be metabolically beneficial, this is not the case for all such bacteria, suggesting that microbiome-directed therapeutic measures to prevent or treat diabetes should be targeted to specific butyrate-producing taxa rather than all butyrate producers.

Influence of Binary Toxin Gene Detection and Decreased Susceptibility to Antibiotics among Clostridioides difficile Strains on Disease Severity: a Single-Center Study.

Clostridioides difficile infection (CDI) is the fifth leading cause of death from nonmalignant gastrointestinal disease in the United States. The contribution of resistance to C. difficile-active antibiotics to the outcomes of CDI is unclear. We evaluated the antimicrobial susceptibility of C. difficile isolates in a U.S. hospital and determined associations of clinical variables and binary toxin positivity with antibiotic resistance. C. difficile spores were cultured from fecal specimens of adult patients with CDI for genotyping and antimicrobial susceptibility assay (for clindamycin [CLI], fidaxomicin [FDX], metronidazole [MTZ], moxifloxacin [MXF], tigecycline [TGC], and vancomycin [VAN]). Electronic medical records were reviewed for clinical data extraction. Ninety-seven of 130 (75%) fecal samples grew toxigenic C. difficile in culture. Most of the isolates were tcdA+ tcdB+ cdtB- (80.4%), and 18.6% and 1% were tcdA+ tcdB+ cdtB+ and tcdA-tcdB+ cdtB+, respectively. Susceptibility to VAN, MTZ, FDX, TGC, MXF, and CLI was 96%, 94%, 100%, 100%, 8%, and 79%, respectively. Six isolates, all cdtB positive and belonging to the 027 ribotype, were resistant to VAN and/or MTZ. Higher MICs were found in isolates with a mutation in the VAN-related resistance gene vanR, but not vanS. In addition, cdtB+ isolates exhibited higher MICs of VAN, MTZ, TGC, CLI, and MXF compared to cdtB- strains. Patients with greater intestinal inflammation or severe disease were more likely to be infected with cdtB+ strains. Decreased susceptibility to antibiotics is not directly associated with either severe or recurrent CDI. However, antimicrobial susceptibility of C. difficile is decreased in strains positive for the binary toxin gene.

Microbial genomic trait evolution is dominated by frequent and rare pulsed evolution.

On the macroevolutionary time scale, does trait evolution proceed gradually or by rapid bursts (pulses) separated by prolonged periods of stasis or slow evolution? Although studies have shown that pulsed evolution is prevalent in animals, our knowledge about the tempo and mode of evolution across the tree of life is very limited. This long-standing debate calls for a test in bacteria and archaea, the most ancient and diverse forms of life with unique population genetic properties. Using a likelihood-based framework, we show that pulsed evolution is not only present but also prevalent and predominant in microbial genomic trait evolution. We detected two distinct types of pulsed evolution (small frequent and large rare jumps) that are predicted by the punctuated equilibrium and quantum evolution theories. Our findings suggest that major bacterial lineages could have originated in quick bursts and that pulsed evolution is a common theme across the tree of life.

An isothermal amplification-coupled dipstick for the rapid detection of COVID-19.

Early detection of coronavirus disease 2019 (COVID-19) is critical for both initiating appropriate treatment and preventing the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent. A simple and rapid diagnostic test that can be performed without any expensive equipment would be valuable for clinicians working in a low-resource setting. Here, we report a point-of-care detection technique for COVID-19 that combines the power of isothermal amplification (reverse transcription helicase-dependent amplification, RT-HDA) and dipstick technologies. The limit of detection of this diagnostic test is six copies of SARS-CoV-2 µl-1 in clinical specimens. Of the 22 clinical specimens tested, RT-HDA-coupled dipstick correctly identified all positive and negative specimens. The RT-HDA can be performed over a heating block and the results can be interpreted visually with the dipstick technology without any specialized equipment. Furthermore, the RT-HDA-coupled dipstick could be performed in a short turnaround time of ~2 h. Thus, the RT-HDA-coupled dipstick could serve as a point-of-care diagnostic test for COVID-19 in a low-resource environment.

Modeling Pulsed Evolution and Time-Independent Variation Improves the Confidence Level of Ancestral and Hidden State Predictions.

Ancestral state reconstruction is not only a fundamental tool for studying trait evolution, but also very useful for predicting the unknown trait values (hidden states) of extant species. A well-known problem in ancestral and hidden state predictions is that the uncertainty associated with predictions can be so large that predictions themselves are of little use. Therefore, for meaningful interpretation of predicted traits and hypothesis testing, it is prudent to accurately assess the uncertainty of the predictions. Commonly used constant-rate Brownian motion (BM) model fails to capture the complexity of tempo and mode of trait evolution in nature, making predictions under the BM model vulnerable to lack-of-fit errors from model misspecification. Using empirical data (mammalian body size and bacterial genome size), we show that the distribution of residual Z-scores under the BM model is neither homoscedastic nor normal as expected. Consequently, the 95% confidence intervals of predicted traits are so unreliable that the actual coverage probability ranges from 33% (strongly permissive) to 100% (strongly conservative). Alternative methods such as BayesTraits and StableTraits that allow variable rates in evolution improve the predictions but are computationally expensive. Here, we develop Reconstructing Ancestral State under Pulsed Evolution in R by Gaussian Decomposition (RasperGade), a method of ancestral and hidden state prediction that uses the Levy process to explicitly model gradual evolution, pulsed evolution, and time-independent variation. Using the same empirical data, we show that RasperGade outperforms both BayesTraits and StableTraits in providing reliable confidence estimates and is orders-of-magnitude faster. Our results suggest that, when predicting the ancestral and hidden states of continuous traits, the rate variation should always be assessed and the quality of confidence estimates should always be examined. [Bacterial genomic traits; model misspecification; trait evolution.].

Glucocorticoids coordinate changes in gut microbiome composition in wild North American red squirrels.

The gut microbiome impacts host health and fitness, in part through the diversification of gut metabolic function and pathogen protection. Elevations in glucocorticoids (GCs) appear to reduce gut microbiome diversity in experimental studies, suggesting that a loss of microbial diversity may be a negative consequence of increased GCs. However, given that ecological factors like food availability and population density may independently influence both GCs and microbial diversity, understanding how these factors structure the GC-microbiome relationship is crucial to interpreting its significance in wild populations. Here, we used an ecological framework to investigate the relationship between GCs and gut microbiome diversity in wild North American red squirrels (Tamiasciurus hudsonicus). As expected, higher GCs predicted lower gut microbiome diversity and an increase in metabolic taxa. Surprisingly, but in line with prior empirical studies on wild animals, gastrointestinal pathogens decreased as GCs increased. Both dietary heterogeneity and an upcoming food pulse exhibited direct effects on gut microbiome diversity, whereas conspecific density and reproductive activity impacted diversity indirectly via changes in host GCs. Our results provide evidence of a gut-brain axis in wild red squirrels and highlight the importance of situating the GC-gut microbiome relationship within an ecological framework.

Apple cider vinegar soaks do not alter the skin bacterial microbiome in atopic dermatitis.

INTRODUCTION: Atopic dermatitis is a common skin disease characterized by altered cutaneous immunity in which patients often exhibit lower skin microbiota diversity compared to healthy skin and are prone to colonization by Staphylococcus aureus. Apple cider vinegar has been shown to have antibacterial effects; however, its effects on the skin microbiome have not previously been well-described. OBJECTIVES: We aimed to examine the effects of topical dilute apple cider vinegar soaks on Staphylococcus aureus abundance, skin bacterial microbiome composition, and skin bacterial microbiome diversity in atopic dermatitis participants compared to healthy skin. METHODS: Eleven subjects with atopic dermatitis and 11 healthy controls were enrolled in this randomized, non-blinded, single-institution, split-arm pilot study. Subjects soaked one forearm in dilute apple cider vinegar (0.5% acetic acid) and the other forearm in tap water for 10 minutes daily. Skin bacteria samples were collected from subjects' volar forearms before and after 14 days of treatment. 16S sequencing was used to analyze Staphylococcus aureus abundance and skin bacterial microbiome composition, and alpha diversity of microbiota were determined using Shannon diversity index. RESULTS: There was no difference in skin bacterial microbiome in atopic dermatitis subjects after 2 weeks of daily water or apple cider vinegar treatments (p = 0.056 and p = 0.22, respectively), or in mean abundance of S. aureus on apple cider vinegar-treated forearms (p = 0.60). At 2 weeks, the skin bacterial microbiomes of healthy control subjects were not significantly different from the skin bacterial microbiome of atopic dermatitis subjects (p = 0.14, 0.21, 0.12, and 0.05). CONCLUSIONS: Our results suggest that daily soaks in 0.5% apple cider vinegar are not an effective method of altering the skin bacterial microbiome in atopic dermatitis. Further studies are needed to explore the effects of different concentrations of apple cider vinegar on skin microflora and disease severity. TRIAL NUMBER: UVA IRB-HSR #19906.

Rationale, design and baseline characteristics of the Microbiome and Insulin Longitudinal Evaluation Study (MILES).

AIM: To investigate the role of the gut microbiome in regulating key insulin homeostasis traits (insulin sensitivity, insulin secretion and insulin clearance) whose dysfunction leads to type 2 diabetes (T2D). MATERIALS AND METHODS: The Microbiome and Insulin Longitudinal Evaluation Study (MILES) focuses on African American and non-Hispanic white participants aged 40-80 years without diabetes. Three study visits are planned (at baseline, 15 and 30 months). Baseline measurements include assessment of the stool microbiome and administration of an oral glucose tolerance test, which will yield indexes of insulin sensitivity, insulin secretion and insulin clearance. The gut microbiome profile (composition and function) will be determined using whole metagenome shotgun sequencing along with analyses of plasma short chain fatty acids. Additional data collected include dietary history, sociodemographic factors, health habits, anthropometry, medical history, medications and family history. Most assessments are repeated 15 and 30 months following baseline. RESULTS: After screening 875 individuals, 129 African American and 224 non-Hispanic white participants were enrolled. At baseline, African American participants have higher blood pressure, weight, body mass index, waist and hip circumferences but similar waist-hip ratio compared with the non-Hispanic white participants. On average, African American participants are less insulin-sensitive and have higher acute insulin secretion and lower insulin clearance. CONCLUSIONS: The longitudinal design and robust characterization of potential mediators will allow for the assessment of glucose and insulin homeostasis and gut microbiota as they change over time, improving our ability to discern causal relationships between the microbiome and the insulin homeostasis traits whose deterioration determines T2D, setting the stage for future microbiome-directed therapies to prevent and treat T2D.

Multi-omic meta-analysis identifies functional signatures of airway microbiome in chronic obstructive pulmonary disease.

The interaction between airway microbiome and host in chronic obstructive pulmonary disease (COPD) is poorly understood. Here we used a multi-omic meta-analysis approach to characterize the functional signature of airway microbiome in COPD. We retrieved all public COPD sputum microbiome datasets, totaling 1640 samples from 16S rRNA gene datasets and 26 samples from metagenomic datasets from across the world. We identified microbial taxonomic shifts using random effect meta-analysis and established a global classifier for COPD using 12 microbial genera. We inferred the metabolic potentials for the airway microbiome, established their molecular links to host targets, and explored their effects in a separate meta-analysis on 1340 public human airway transcriptome samples for COPD. 29.6% of differentially expressed human pathways were predicted to be targeted by microbiome metabolism. For inferred metabolite-host interactions, the flux of disease-modifying metabolites as predicted from host transcriptome was generally concordant with their predicted metabolic turnover in microbiome, suggesting a synergistic response between microbiome and host in COPD. The meta-analysis results were further validated by a pilot multi-omic study on 18 COPD patients and 10 controls, in which airway metagenome, metabolome, and host transcriptome were simultaneously characterized. 69.9% of the proposed "microbiome-metabolite-host" interaction links were validated in the independent multi-omic data. Butyrate, homocysteine, and palmitate were the microbial metabolites showing strongest interactions with COPD-associated host genes. Our meta-analysis uncovered functional properties of airway microbiome that interacted with COPD host gene signatures, and demonstrated the possibility of leveraging public multi-omic data to interrogate disease biology.

Dopamine Signaling in the Suprachiasmatic Nucleus Enables Weight Gain Associated with Hedonic Feeding.

The widespread availability of energy-dense, rewarding foods is correlated with the increased incidence of obesity across the globe. Overeating during mealtimes and unscheduled snacking disrupts timed metabolic processes, which further contribute to weight gain. The neuronal mechanism by which the consumption of energy-dense food restructures the timing of feeding is poorly understood. Here, we demonstrate that dopaminergic signaling within the suprachiasmatic nucleus (SCN), the central circadian pacemaker, disrupts the timing of feeding, resulting in overconsumption of food. D1 dopamine receptor (Drd1)-null mice are resistant to diet-induced obesity, metabolic disease, and circadian disruption associated with energy-dense diets. Conversely, genetic rescue of Drd1 expression within the SCN restores diet-induced overconsumption, weight gain, and obesogenic symptoms. Access to rewarding food increases SCN dopamine turnover, and elevated Drd1-signaling decreases SCN neuronal activity, which we posit disinhibits downstream orexigenic responses. These findings define a connection between the reward and circadian pathways in the regulation of pathological calorie consumption.

Evidence for the Role of the Cecal Microbiome in Maintenance of Immune Regulation and Homeostasis.

OBJECTIVE (S): Our objective was to investigate alterations in the cecal microbial composition during the development of type 1 diabetes (T1D) with or without IgM therapy, and correlate these alterations with the corresponding immune profile. METHODS: (1) Female nonobese diabetic (NOD) mice treated with IgM or saline (n = 20/group) were divided into 5-week-old nondiabetic; 9 to 12-week-old prehyperglycemic stage-1; ≥13-week-old prehyperglycemic stage-2; and diabetic groups. 16S rRNA libraries were prepared from bacterial DNA and deep-sequenced. (2) New-onset diabetic mice were treated with IgM (200 µg on Days 1, 3, and 5) and their blood glucose monitored for 2 months. RESULTS: Significant dysbiosis was observed in the cecal microbiome with the progression of T1D development. The alteration in microbiome composition was characterized by an increase in the bacteroidetes:firmicutes ratio. In contrast, IgM conserved normal bacteroidetes:firmicutes ratio and this effect was long-lasting. Furthermore, oral gavage using cecal content from IgM-treated mice significantly diminished the incidence of diabetes compared with controls, indicating that IgM specifically affected mucosa-associated microbes, and that the affect was causal and not an epiphenomenon. Also, regulatory immune cell populations (myeloid-derived suppressor cells and regulatory T cells) were expanded and insulin autoantibody production diminished in the IgM-treated mice. In addition, IgM therapy reversed hyperglycemia in 70% of new-onset diabetic mice (n = 10) and the mice remained normoglycemic for the entire post-treatment observation period. CONCLUSIONS: The cecal microbiome appears to be important in maintaining immune homeostasis and normal immune responses.

Innate Immune Response and Outcome of Clostridium difficile Infection Are Dependent on Fecal Bacterial Composition in the Aged Host.

Background: Clostridium difficile infection (CDI) is a serious threat for an aging population. Using an aged mouse model, we evaluated the effect of age and the roles of innate immunity and intestinal microbiota. Methods: Aged (18 months) and young (8 weeks) mice were infected with C difficile, and disease severity, immune response, and intestinal microbiome were compared. The same experiment was repeated with intestinal microbiota exchange between aged and young mice before infection. Results: Higher mortality was observed in aged mice with weaker neutrophilic mobilization in blood and intestinal tissue and depressed proinflammatory cytokines in early infection. Microbiota exchange improved survival and early immune response in aged mice. Microbiome analysis revealed that aged mice have significant deficiencies in Bacteroidetes phylum and, specifically, Bacteroides, Alistipes, and rc4-4 genera, which were replenished by cage switching. Conclusions: Microbiota-dependent alteration in innate immune response early on during infection may explain poor outcome in aged host with CDI.

Seasonal, spatial, and maternal effects on gut microbiome in wild red squirrels.

BACKGROUND: Our understanding of gut microbiota has been limited primarily to findings from human and laboratory animals, but what shapes the gut microbiota in nature remains largely unknown. To fill this gap, we conducted a comprehensive study of gut microbiota of a well-studied North American red squirrel (Tamiasciurus hudsonicus) population. Red squirrels are territorial, solitary, and live in a highly seasonal environment and therefore represent a very attractive system to study factors that drive the temporal and spatial dynamics of gut microbiota. RESULT: For the first time, this study revealed significant spatial patterns of gut microbiota within a host population, suggesting limited dispersal could play a role in shaping and maintaining the structure of gut microbial communities. We also found a remarkable seasonal rhythm in red squirrel's gut microbial composition manifested by a tradeoff between relative abundance of two genera Oscillospira and Corpococcus and clearly associated with seasonal variation in diet availability. Our results show that in nature, environmental factors exert a much stronger influence on gut microbiota than host-associated factors including age and sex. Despite strong environmental effects, we found clear evidence of individuality and maternal effects, but host genetics did not seem to be a significant driver of the gut microbial communities in red squirrels. CONCLUSION: Taken together, the results of this study emphasize the importance of external ecological factors rather than host attributes in driving temporal and spatial patterns of gut microbiota in natural environment.

Comparative Genomic Analysis of Acanthamoeba Endosymbionts Highlights the Role of Amoebae as a "Melting Pot" Shaping the Rickettsiales Evolution.

Amoebae have been considered as a genetic "melting pot" for its symbionts, facilitating genetic exchanges of the bacteria that co-inhabit the same host. To test the "melting pot" hypothesis, we analyzed six genomes of amoeba endosymbionts within Rickettsiales, four of which belong to Holosporaceae family and two to Candidatus Midichloriaceae. For the first time, we identified plasmids in obligate amoeba endosymbionts, which suggests conjugation as a potential mechanism for lateral gene transfers (LGTs) that underpin the "melting pot" hypothesis. We found strong evidence of recent LGTs between the Rickettsiales amoeba endosymbionts, suggesting that the LGTs are continuous and ongoing. In addition, comparative genomic and phylogenomic analyses revealed pervasive and recurrent LGTs between Rickettsiales and distantly related amoeba-associated bacteria throughout the Rickettsiales evolution. Many of these exchanged genes are important for amoeba-symbiont interactions, including genes in transport system, antibiotic resistance, stress response, and bacterial virulence, suggesting that LGTs have played important roles in the adaptation of endosymbionts to their intracellular habitats. Surprisingly, we found little evidence of LGTs between amoebae and their bacterial endosymbionts. Our study strongly supports the "melting pot" hypothesis and highlights the role of amoebae in shaping the Rickettsiales evolution.