Complexities of Inferring Symbiont Function: Paraburkholderia Symbiont Dynamics in Social Amoeba Populations and Their Impacts on the Amoeba Microbiota.

The relationship between the social amoeba Dictyostelium discoideum and its endosymbiotic bacteria Paraburkholderia provides a model system for studying the development of symbiotic relationships. Laboratory experiments have shown that any of three species of the Paraburkholderia symbiont allow D. discoideum food bacteria to persist through the amoeba life cycle and survive in amoeba spores rather than being fully digested. This phenomenon is termed "farming," as it potentially allows spores dispersed to food-poor locations to grow their own. The occurrence and impact of farming in natural populations, however, have been a challenge to measure. Here, we surveyed natural D. discoideum populations and found that only one of the three symbiont species, Paraburkholderia agricolaris, remained prevalent. We then explored the effect of Paraburkholderia on the amoeba microbiota, expecting that by facilitating bacterial food carriage, it would diversify the microbiota. Contrary to our expectations, Paraburkholderia tended to infectiously dominate the D. discoideum microbiota, in some cases decreasing diversity. Similarly, we found little evidence for Paraburkholderia facilitating the carriage of particular food bacteria. These findings highlight the complexities of inferring symbiont function in nature and suggest the possibility that Paraburkholderia could be playing multiple roles for its host. IMPORTANCE The functions of symbionts in natural populations can be difficult to completely discern. The three Paraburkholderia bacterial farming symbionts of the social amoeba Dictyostelium discoideum have been shown in the laboratory environment to allow the amoebas to carry, rather than fully digest, food bacteria. This potentially provides a fitness benefit to the amoebas upon dispersal to food-poor environments, as they could grow their food. We expected that meaningful food carriage would manifest as a more diverse microbiota. Surprisingly, we found that Paraburkholderia tended to infectiously dominate the D. discoideum microbiota rather than diversifying it. We determined that only one of the three Paraburkholderia symbionts has increased in prevalence in natural populations in the past 20 years, suggesting that this symbiont may be beneficial, however. These findings suggest that Paraburkholderia may have an alternative function for its host, which drives its prevalence in natural populations.

RESCRIPt: Reproducible sequence taxonomy reference database management.

Nucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardization limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a Python 3 software package and QIIME 2 plugin for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. To highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. RESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt.

Characterization of the bacterial microbiomes of social amoebae and exploration of the roles of host and environment on microbiome composition.

As predators of bacteria, amoebae select for traits that allow bacteria to become symbionts by surviving phagocytosis and exploiting the eukaryotic intracellular environment. Soil-dwelling social amoebae can help us answer questions about the natural ecology of these amoeba-bacteria symbioses along the pathogen-mutualist spectrum. Our objective was to characterize the natural bacterial microbiome of phylogenetically and morphologically diverse social amoeba species using next-generation sequencing of 16S rRNA amplicons directly from amoeba fruiting bodies. We found six phyla of amoeba-associated bacteria: Proteobacteria, Bacteroidetes, Actinobacteria, Chlamydiae, Firmicutes, and Acidobacteria. The most common associates of amoebae were classified to order Chlamydiales and genus Burkholderia-Caballeronia-Paraburkholderia. These bacteria were present in multiple amoeba species across multiple locations. While there was substantial intraspecific variation, there was some evidence for host specificity and differentially abundant taxa between different amoeba hosts. Amoebae microbiomes were distinct from the microbiomes of their soil habitat, and soil pH affected amoeba microbiome diversity. Alpha-diversity was unsurprisingly lower in amoebae samples compared with soil, but beta-diversity between amoebae samples was higher than between soil samples. Further exploration of social amoebae microbiomes may help us understand the roles of bacteria, host, and environment on symbiotic interactions and microbiome formation in basal eukaryotic organisms.

Mixed ancestry from wild and domestic lineages contributes to the rapid expansion of invasive feral swine.

Invasive alien species are a significant threat to both economic and ecological systems. Identifying the processes that give rise to invasive populations is essential for implementing effective control strategies. We conducted an ancestry analysis of invasive feral swine (Sus scrofa, Linnaeus, 1758), a highly destructive ungulate that is widely distributed throughout the contiguous United States, to describe introduction pathways, sources of newly emergent populations and processes contributing to an ongoing invasion. Comparisons of high-density single nucleotide polymorphism genotypes for 6,566 invasive feral swine to a comprehensive reference set of S. scrofa revealed that the vast majority of feral swine were of mixed ancestry, with dominant genetic associations to Western heritage breeds of domestic pig and European populations of wild boar. Further, the rapid expansion of invasive feral swine over the past 30 years was attributable to secondary introductions from established populations of admixed ancestry as opposed to direct introductions of domestic breeds or wild boar. Spatially widespread genetic associations of invasive feral swine to European wild boar deviated strongly from historical S. scrofa introduction pressure, which was largely restricted to domestic pigs with infrequent, localized wild boar releases. The deviation between historical introduction pressure and contemporary genetic ancestry suggests wild boar-hybridization may contribute to differential fitness in the environment and heightened invasive potential for individuals of admixed domestic pig-wild boar ancestry.

Temporal Dynamics of In-Field Bioreactor Populations Reflect the Groundwater System and Respond Predictably to Perturbation.

Temporal variability complicates testing the influences of environmental variability on microbial community structure and thus function. An in-field bioreactor system was developed to assess oxic versus anoxic manipulations on in situ groundwater communities. Each sample was sequenced (16S SSU rRNA genes, average 10,000 reads), and biogeochemical parameters are monitored by quantifying 53 metals, 12 organic acids, 14 anions, and 3 sugars. Changes in dissolved oxygen (DO), pH, and other variables were similar across bioreactors. Sequencing revealed a complex community that fluctuated in-step with the groundwater community and responded to DO. This also directly influenced the pH, and so the biotic impacts of DO and pH shifts are correlated. A null model demonstrated that bioreactor communities were driven in part not only by experimental conditions but also by stochastic variability and did not accurately capture alterations in diversity during perturbations. We identified two groups of abundant OTUs important to this system; one was abundant in high DO and pH and contained heterotrophs and oxidizers of iron, nitrite, and ammonium, whereas the other was abundant in low DO with the capability to reduce nitrate. In-field bioreactors are a powerful tool for capturing natural microbial community responses to alterations in geochemical factors beyond the bulk phase.

Enrichment of Root Endophytic Bacteria from Populus deltoides and Single-Cell-Genomics Analysis.

UNLABELLED: Bacterial endophytes that colonize Populus trees contribute to nutrient acquisition, prime immunity responses, and directly or indirectly increase both above- and below-ground biomasses. Endophytes are embedded within plant material, so physical separation and isolation are difficult tasks. Application of culture-independent methods, such as metagenome or bacterial transcriptome sequencing, has been limited due to the predominance of DNA from the plant biomass. Here, we describe a modified differential and density gradient centrifugation-based protocol for the separation of endophytic bacteria from Populus roots. This protocol achieved substantial reduction in contaminating plant DNA, allowed enrichment of endophytic bacteria away from the plant material, and enabled single-cell genomics analysis. Four single-cell genomes were selected for whole-genome amplification based on their rarity in the microbiome (potentially uncultured taxa) as well as their inferred abilities to form associations with plants. Bioinformatics analyses, including assembly, contamination removal, and completeness estimation, were performed to obtain single-amplified genomes (SAGs) of organisms from the phyla Armatimonadetes, Verrucomicrobia, and Planctomycetes, which were unrepresented in our previous cultivation efforts. Comparative genomic analysis revealed unique characteristics of each SAG that could facilitate future cultivation efforts for these bacteria. IMPORTANCE: Plant roots harbor a diverse collection of microbes that live within host tissues. To gain a comprehensive understanding of microbial adaptations to this endophytic lifestyle from strains that cannot be cultivated, it is necessary to separate bacterial cells from the predominance of plant tissue. This study provides a valuable approach for the separation and isolation of endophytic bacteria from plant root tissue. Isolated live bacteria provide material for microbiome sequencing, single-cell genomics, and analyses of genomes of uncultured bacteria to provide genomics information that will facilitate future cultivation attempts.

Plant host and soil origin influence fungal and bacterial assemblages in the roots of woody plants.

Microbial communities in plant roots provide critical links between above- and belowground processes in terrestrial ecosystems. Variation in root communities has been attributed to plant host effects and microbial host preferences, as well as to factors pertaining to soil conditions, microbial biogeography and the presence of viable microbial propagules. To address hypotheses regarding the influence of plant host and soil biogeography on root fungal and bacterial communities, we designed a trap-plant bioassay experiment. Replicate Populus, Quercus and Pinus plants were grown in three soils originating from alternate field sites. Fungal and bacterial community profiles in the root of each replicate were assessed through multiplex 454 amplicon sequencing of four loci (i.e., 16S, SSU, ITS, LSU rDNA). Soil origin had a larger effect on fungal community composition than did host species, but the opposite was true for bacterial communities. Populus hosted the highest diversity of rhizospheric fungi and bacteria. Root communities on Quercus and Pinus were more similar to each other than to Populus. Overall, fungal root symbionts appear to be more constrained by dispersal and biogeography than by host availability.

Dispersal, niche breadth and population extinction: colonization ratios predict range size in North American dragonflies.

Species' range sizes are shaped by fundamental differences in species' ecological and evolutionary characteristics, and understanding the mechanisms determining range size can shed light on the factors responsible for generating and structuring biological diversity. Moreover, because geographic range size is associated with a species' risk of extinction and their ability to respond to global changes in climate and land use, understanding these mechanisms has important conservation implications. Despite the hypotheses that dispersal behaviour is a strong determinant of species range areas, few data are available to directly compare the relationship between dispersal behaviour and range size. Here, we overcome this limitation by combining data from a multispecies dispersal experiment with additional species-level trait data that are commonly hypothesized to affect range size (e.g. niche breadth, local abundance and body size.). This enables us to examine the relationship between these species-level traits and range size across North America for fifteen dragonfly species. Ten models based on a priori predictions about the relationship between species traits and range size were evaluated and two models were identified as good predictors of species range size. These models indicated that only two species' level traits, dispersal behaviour and niche breadth were strongly related to range size. The evidence from these two models indicated that dragonfly species that disperse more often and further had larger North American ranges. Extinction and colonization dynamics are expected to be a key linkage between dispersal behaviour and range size in dragonflies. To evaluate how extinction and colonization dynamics among dragonflies were related to range size we used an independent data set of extinction and colonization rates for eleven dragonfly species and assessed the relationship between these populations rates and North American range areas for these species. We found a negative relationship between North American range size and species' extinction-to-colonization ratios. Our results indicate that metapopulation dynamics act to shape the extent of species' continental distributions. These population dynamics are likely to interact with dispersal behaviour, particularly at species range margins, to determine range limits and ultimately species range sizes.

Soil rotifer communities are extremely diverse globally but spatially autocorrelated locally.

Bdelloid rotifers are important contributors to biogeochemical cycling and trophic dynamics of both aquatic and terrestrial ecosystems, but little is known about their biogeographic distribution and community structure in terrestrial environments. This lack of knowledge stems from a lack of phylogenetic information and assumptions that microbial eukaryotes are globally distributed and have very limited diversity across vast geographic distances. However, these assumptions have been based more on assessments of their morphology than any measure of their true genetic diversity and biogeographic distribution. We developed specific primers for the cytochrome c oxidase subunit 1 (cox1) gene of bdelloid rotifers and amplified and cloned sequences using a nested sampling scheme that represented local (0-10 m) to global (up to 10,000 km) scales. Using phylogenetic community analyses (UniFrac) and geospatial statistics (semivariograms, mantel tests), we were able to reject the hypothesis that communities of rotifers are the same across even fairly small geographic distances. Bdelloid communities showed highly significant spatial structuring with spatial autocorrelation ranges of 54-133 m, but beyond that distance communities were extremely dissimilar. Furthermore, we show that these spatial patterns are driven not only by changes in relative abundance of phylotypes but also by absolute changes in phylotype occurrence (richness). There is almost no overlap in phylotype [or operational taxonomic unit (OTU)] occurrence between communities at distances beyond the autocorrelation range (~133 m). Such small species ranges, combined with their ubiquity in soils, make it increasingly clear that the biodiversity of bdelloid rotifers (and other less easily dispersed microbes) is much higher than previously thought.

Bioinformatics challenges for profiling the microbiome in cancer: pitfalls and opportunities.

Increasing evidence suggests that the human microbiome plays an important role in cancer risk and treatment. Untargeted 'omics' techniques have accelerated research into microbiome-cancer interactions, supporting the discovery of novel associations and mechanisms. However, these techniques require careful selection and use to avoid biases and other pitfalls. In this essay, we discuss selected challenges involved in the analysis of microbiome data in the context of cancer, including the application of machine learning (ML). We focus on DNA sequencing-based (e.g., metagenomics) methods, but many of the pitfalls and opportunities generalize to other omics technologies as well. We advocate for extended training opportunities, community standards, and best practices for sharing data and code to advance transparency and reproducibility in cancer microbiome research.

Short-Term Ingestion of Essential Amino Acid Based Nutritional Supplements or Whey Protein Improves the Physical Function of Older Adults Independently of Gut Microbiome.

SCOPE: Dietary proteins and essential amino acids (EAAs) are the major nutritional supplements that support the growth and activity of gut microbes contributing to the wellbeing of their host. This study hypothesizes that daily supplementation of the diet with either EAAs or whey protein for 12 weeks would improve the gut microbiome of older adults. METHODS AND RESULTS: The stool samples are processed and subjected to Illumina-based 16S ribosomal ribonucleic acid (rRNA) gene amplicon sequencing. In both groups, the most abundant families are found in order of relative abundance included: Bacteroidaceae, Lachnospiraceae, Ruminococcaceae, Prevotellaceae, Rikenellaceae, Enterobacteriaceae, Oscillospiraceae, Tannerellaceae, and Akkermansiaceae, which indicate that these subjects are able to maintain a same healthy microbial diversity in their guts. A significant finding is a reduction of proinflammatory cytokine, interleukin-18 (IL-18) in the EAAs group. It also uses the standard 6-min walking test (6MWT) as a measure of cardiopulmonary fitness. At the end of the study, the subjects in the EAAs group perform significantly better in the 6MWT as compared to the whey group. CONCLUSION: It seems plausible that the improved physical performance and reduced proinflammatory cytokine, IL-18 seen in the EAAs group, are independent of changes in gut microbiota.

Colonic epithelial hypoxia remains constant during the progression of diabetes in male UC Davis type 2 diabetes mellitus rats.

INTRODUCTION: Colonocyte oxidation of bacterial-derived butyrate has been reported to maintain synergistic obligate anaerobe populations by reducing colonocyte oxygen levels; however, it is not known whether this process is disrupted during the progression of type 2 diabetes. Our aim was to determine whether diabetes influences colonocyte oxygen levels in the University of California Davis type 2 diabetes mellitus (UCD-T2DM) rat model. RESEARCH DESIGN AND METHODS: Age-matched male UCD-T2DM rats (174±4 days) prior to the onset of diabetes (PD, n=15), within 1 month post-onset (RD, n=12), and 3 months post-onset (D3M, n=12) were included in this study. Rats were administered an intraperitoneal injection of pimonidazole (60 mg/kg body weight) 1 hour prior to euthanasia and tissue collection to estimate colonic oxygen levels. Colon tissue was fixed in 10% formalin, embedded in paraffin, and processed for immunohistochemical detection of pimonidazole. The colonic microbiome was assessed by 16S gene rRNA amplicon sequencing and content of short-chain fatty acids was measured by liquid chromatography-mass spectrometry. RESULTS: HbA1c % increased linearly across the PD (5.9±0.1), RD (7.6±0.4), and D3M (11.5±0.6) groups, confirming the progression of diabetes in this cohort. D3M rats had a 2.5% increase in known facultative anaerobes, Escherichia-Shigella, and Streptococcus (false discovery rate <0.05) genera in colon contents. The intensity of pimonidazole staining of colonic epithelia did not differ across groups (p=0.37). Colon content concentrations of acetate and propionate also did not differ across UCD-T2DM groups; however, colonic butyric acid levels were higher in D3M rats relative to PD rats (p<0.01). CONCLUSIONS: The advancement of diabetes in UCD-T2DM rats was associated with an increase in facultative anaerobes; however, this was not explained by changes in colonocyte oxygen levels. The mechanisms underlying shifts in gut microbe populations associated with the progression of diabetes in the UCD-T2DM rat model remain to be identified.

Physiological and cognitive changes after treatments of cyclophosphamide, methotrexate, and fluorouracil: implications of the gut microbiome and depressive-like behavior.

Introduction: Chemotherapy-induced cognitive impairment colloquially referred to as chemobrain is a poorly understood phenomenon affecting a highly variable proportion of patients with breast cancer. Here we investigate the association between anxiety and despair-like behaviors in mice treated with cyclophosphamide, methotrexate, and fluorouracil (CMF) along with host histological, proteomic, gene expression, and gut microbial responses. Methods: Forced swim and sociability tests were used to evaluate depression and despair-like behaviors. The tandem mass tag (TMT) proteomics approach was used to assess changes in the neural protein network of the amygdala and hippocampus. The composition of gut microbiota was assessed through 16S rRNA gene sequencing. Finally, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to evaluate changes in intestinal gap junction markers. Results and discussion: We observed that CMF induced social and despair-like behavior in mice 96 hours following treatment. Proteomic analysis identified changes in various proteins related to progressive neurological disease, working memory deficit, primary anxiety disorder, and gene expression revealing increases in NMDA and AMPA receptors in both the hippocampus and the amygdala because of CMF treatment. These changes finally, we observed immediate changes in the microbial population after chemotherapy treatment, with a notable abundance of Muribaculaceae and Romboutsia which may contribute to changes seen in the gut.

Short-Term Metformin Treatment Enriches Bacteroides dorei in an Obese Liver Steatosis Zucker Rat Model.

Obesity is the leading cause of health-related diseases in the United States and World. Previously, we reported that obesity can change gut microbiota using the Zucker rat model. Metformin is an oral anti-hyperglycemic agent approved by the FDA to treat type 2 diabetes (T2D) in adults and children older than 10 years of age. The correlation of short-term metformin treatment and specific alterations to the gut microbiota in obese models is less known. Short-term metformin has been shown to reduce liver steatosis. Here we investigate the effects of short-term metformin treatment on population of gut microbiota profile in an obese rat model. Five week old obese (n = 12) female Zucker rats after 1 week of acclimation, received AIN-93 G diet for 8 weeks and then rats were randomly assigned into two groups (6 rats/group): (1) obese without metformin (ObC), or (2) obese with metformin (ObMet). Metformin was mixed with AIN-93G diet at 1,000 mg/kg of diet. Rats were weighed twice per week. All rats were sacrificed at the end of metformin treatment at 10 weeks and fecal samples were collected and kept at -80°C. Total microbial DNA was collected directly from the fecal samples used for shotgun-metagenomics sequencing and subsequently analyzed using MetaPlAn and HUMAnN. After stringent data filtering and quality control we found significant differences (p = 0.0007) in beta diversity (Aitchison distances) between the ObC vs. ObMet groups. Supervised and unsupervised analysis of the log-ratios Bacteroides dorei and B. massiliensis vs. all other Bacteroides spp., revealed that B. dorei and B. massiliensis were enriched in the ObMet group, while the remaining Bacteroides spp. where enriched in the ObC group (p = 0.002). The contributional diversity of pathways is also significantly associated by treatment group (p = 0.008). In summary, in the obese Zucker rat model, short-term metformin treatment changes the gut microbiota profile, particularly altering the composition Bacteroides spp. between ObC and ObMet.

Bacterial and Fungal Adaptations in Cecum and Distal Colon of Piglets Fed With Dairy-Based Milk Formula in Comparison With Human Milk.

Exclusive breastfeeding is recommended to newborns during the first 6 months of life, whereas dairy-based infant formula is an alternative nutrition source offered to infants. Several studies demonstrated that breastfed infants have a different gut bacterial composition relative to formula-fed infants. In addition, animal models have shown that human milk (HM)-fed piglets had a distinct intestinal bacterial composition compared with milk formula (MF)-fed piglets. However, the gut fungal composition and the interactions with the bacterial community in breastfed compared with formula-fed infants remain to be investigated. In an attempt to evaluate such differences, we used an animal model to perform a shotgun metagenomics analysis on the cecal and distal colon contents of neonatal piglets fed with pasteurized HM or a dairy-based infant formula (MF) during the first 21 days of life. At postnatal day 21 (PND 21), a subset of piglets from each diet group (n = 11 per group) was euthanized. The remaining piglets in each group were weaned to a solid diet and euthanized at PND 51 (n = 13 per group). Large intestine contents (i.e., cecum and distal colon) were subjected to shotgun metagenomics analysis. The differential taxonomic composition of bacteria and fungi and the predicted functional gene profiling were evaluated. Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria are the most abundant bacterial phyla observed in piglets at PND 21 and PND 51. In the large intestine at PND 21 and PND 51, Proteobacteria phylum was significantly higher in MF-fed group, and species Burkholderiales bacterium of phyla was significantly higher in MF group relative to HM group. In addition, in HM group, several Lactobacillus spp. and Bacteroides spp. were higher relative to MF group in the large intestine at PND 21 and PND 51. Fungal genus Aspergillus was higher in MF, whereas Malassezia was lower relative to HM group. Persistent effects of the neonatal diets were observed at PND 51, where alpha- and beta-diversity differences were detected for bacterial and fungal species in the large intestine. Overall, our findings indicate that neonatal diet affects the large intestinal microbial community during the exclusive milk-feeding period, as well as after the introduction of the complementary food.

Iron deficient diets modify the gut microbiome and reduce the severity of enteric infection in a mouse model of S. Typhimurium-induced enterocolitis.

Enteric infections are widespread in infants and children living in low-resource settings. Iron availability in the gastrointestinal tract may modify the gut microbiome and impact the incidence and severity of enteropathy. This study was designed to determine the effect of an iron-deplete compared to an iron-rich environment in the lower intestine on the gut microbiome, and whether iron availability in the lower intestine affects the host immune response and severity of enteric infection in young mice. Weanling C57BL/6 female mice were fed an iron deficient (Fe-, <6 ppm iron) or an iron fortified (Fe+, 300 ppm iron) diet for 6 weeks. Mice were pretreated with streptomycin prior to oral inoculation of Salmonella enterica subspecies enterica serovar Typhimurium to induce enteric infection (Sal+) or saline control (Sal-). Cecal iron concentrations were 55-fold greater with Fe+Sal- compared to Fe-Sal-. Microbiome sequencing revealed shifts in gut microbiota with dietary iron and enteric infection. There was ∼30% more S. Typhimurium in the cecum of Fe+Sal+ compared to Fe-Sal+. Plasma hepcidin increased with dietary iron and enteric infection, but was greatest in Fe+Sal+. Plasma lipocalin-2 and spleen size relative to bodyweight were greater in Fe+Sal+ compared to Fe+Sal-, Fe-Sal- and Fe-Sal+, and Fe+Sal+ lost more bodyweight compared to Fe-Sal+. Unabsorbed iron in the lower intestine modifies the gut microbiome and promotes a more severe enteropathy. These findings could suggest the need for alternative iron supplementation strategies in areas where enteric infection are common.

Gut Microbes Are Associated with the Vascular Beneficial Effects of Dietary Strawberry on Metabolic Syndrome-Induced Vascular Inflammation.

SCOPE: Metabolic syndrome (MetS) alters the gut microbial ecology and increases the risk of cardiovascular disease. This study investigates whether strawberry consumption reduces vascular complications in an animal model of MetS and identifies whether this effect is associated with changes in the composition of gut microbes. METHODS AND RESULTS: Seven-week-old male mice consume diets with 10% (C) or 60% kcal from fat (high-fat diet fed mice; HF) for 12 weeks and subgroups are fed a 2.35% freeze-dried strawberry supplemented diet (C+SB or HF+SB). This nutritional dose is equivalent to ≈160 g of strawberry. After 12 weeks treatment, vascular inflammation is enhanced in HF versus C mice as shown by an increased monocyte binding to vasculature, elevated serum chemokines, and increased mRNA expression of inflammatory molecules. However, strawberry supplementation suppresses vascular inflammation in HF+SB versus HF mice. Metabolic variables, blood pressure, and indices of vascular function were similar among the groups. Further, the abundance of opportunistic microbe is decreased in HF+SB. Importantly, circulating chemokines are positively associated with opportunistic microbes and negatively associated with the commensal microbes (Bifidobacterium and Facalibaculum). CONCLUSION: Dietary strawberry decreases the abundance of opportunistic microbe and this is associated with a decrease in vascular inflammation resulting from MetS.

Evaluation of DNA extraction protocols from liquid-based cytology specimens for studying cervical microbiota.

Cervical microbiota (CM) are considered an important factor affecting the progression of cervical intraepithelial neoplasia (CIN) and are implicated in the persistence of human papillomavirus (HPV). Collection of liquid-based cytology (LBC) samples is routine for cervical cancer screening and HPV genotyping and can be used for long-term cytological biobanking. We sought to determine whether it is possible to access microbial DNA from LBC specimens, and compared the performance of four different extraction protocols: (ZymoBIOMICS DNA Miniprep Kit; QIAamp PowerFecal Pro DNA Kit; QIAamp DNA Mini Kit; and IndiSpin Pathogen Kit) and their ability to capture the diversity of CM from LBC specimens. LBC specimens from 20 patients (stored for 716 ± 105 days) with CIN values of 2 or 3 were each aliquoted for each of the four kits. Loss of microbial diversity due to long-term LBC storage could not be assessed due to lack of fresh LBC samples. Comparisons with other types of cervical sampling were not performed. We observed that all DNA extraction kits provided equivalent accessibility to the cervical microbial DNA within stored LBC samples. Approximately 80% microbial genera were shared among all DNA extraction protocols. Potential kit contaminants were observed as well. Variation between individuals was a significantly greater influence on the observed microbial composition than was the method of DNA extraction. We also observed that HPV16 was significantly associated with community types that were not dominated by Lactobacillus iners.

Mash-based analyses of Escherichia coli genomes reveal 14 distinct phylogroups.

In this study, more than one hundred thousand Escherichia coli and Shigella genomes were examined and classified. This is, to our knowledge, the largest E. coli genome dataset analyzed to date. A Mash-based analysis of a cleaned set of 10,667 E. coli genomes from GenBank revealed 14 distinct phylogroups. A representative genome or medoid identified for each phylogroup was used as a proxy to classify 95,525 unassembled genomes from the Sequence Read Archive (SRA). We find that most of the sequenced E. coli genomes belong to four phylogroups (A, C, B1 and E2(O157)). Authenticity of the 14 phylogroups is supported by several different lines of evidence: phylogroup-specific core genes, a phylogenetic tree constructed with 2613 single copy core genes, and differences in the rates of gene gain/loss/duplication. The methodology used in this work is able to reproduce known phylogroups, as well as to identify previously uncharacterized phylogroups in E. coli species.

Multi-omics data integration considerations and study design for biological systems and disease.

With the advancement of next-generation sequencing and mass spectrometry, there is a growing need for the ability to merge biological features in order to study a system as a whole. Features such as the transcriptome, methylome, proteome, histone post-translational modifications and the microbiome all influence the host response to various diseases and cancers. Each of these platforms have technological limitations due to sample preparation steps, amount of material needed for sequencing, and sequencing depth requirements. These features provide a snapshot of one level of regulation in a system. The obvious next step is to integrate this information and learn how genes, proteins, and/or epigenetic factors influence the phenotype of a disease in context of the system. In recent years, there has been a push for the development of data integration methods. Each method specifically integrates a subset of omics data using approaches such as conceptual integration, statistical integration, model-based integration, networks, and pathway data integration. In this review, we discuss considerations of the study design for each data feature, the limitations in gene and protein abundance and their rate of expression, the current data integration methods, and microbiome influences on gene and protein expression. The considerations discussed in this review should be regarded when developing new algorithms for integrating multi-omics data.