A tool to assess the mock community samples in 16S rRNA gene-based microbiota profiling studies.

Inclusion and investigation of technical controls in microbiome sequencing studies is important for understanding technical biases and errors. Here, we present chkMocks, a general R-based tool that allows researchers to compare the composition of mock communities that are processed along with samples to their theoretical composition. A visual comparison between experimental and theoretical community composition and their correlation is provided for researchers to assess the quality of their sample processing workflows.

Reducing bias in microbiome research: Comparing methods from sample collection to sequencing.

Background: Microbiota profiles are strongly influenced by many technical aspects that impact the ability of researchers to compare results. To investigate and identify potential biases introduced by technical variations, we compared several approaches throughout the entire workflow of a microbiome study, from sample collection to sequencing, using commercially available mock communities (from bacterial strains as well as from DNA) and multiple human fecal samples, including a large set of positive controls created as a random mix of several participant samples. Methods: Human fecal material was sampled, and aliquots were used to test two commercially available stabilization solutions (OMNIgene·GUT and Zymo Research) in comparison to samples frozen immediately upon collection. In addition, the methodology for DNA extraction, input of DNA, or the number of PCR cycles were analyzed. Furthermore, to investigate the potential batch effects in DNA extraction, sequencing, and barcoding, we included 139 positive controls. Results: Samples preserved in both the stabilization buffers limited the overgrowth of Enterobacteriaceae when compared to unpreserved samples stored at room temperature (RT). These stabilized samples stored at RT were different from immediately frozen samples, where the relative abundance of Bacteroidota was higher and Actinobacteriota and Firmicutes were lower. As reported previously, the method used for cell disruption was a major contributor to variation in microbiota composition. In addition, a high number of cycles during PCR lead to an increase in contaminants detected in the negative controls. The DNA extraction had a significant impact on the microbial composition, also observed with the use of different Illumina barcodes during library preparation and sequencing, while no batch effect was observed in replicate runs. Conclusion: Our study reaffirms the importance of the mechanical cell disruption method and immediate frozen storage as critical aspects in fecal microbiota studies. A comparison of storage conditions revealed that the bias was limited in RT samples preserved in stabilization systems, and these may be a suitable compromise when logistics are challenging due to the size or location of a study. Moreover, to reduce the effect of contaminants in fecal microbiota profiling studies, we suggest the use of ~125 pg input DNA and 25 PCR cycles as optimal parameters during library preparation.

Gut colonisation by extended-spectrum ß-lactamase-producing Escherichia coli and its association with the gut microbiome and metabolome in Dutch adults: a matched case-control study.

BACKGROUND: Gut colonisation by extended-spectrum ß-lactamase (ESBL)-producing Escherichia coli is a risk factor for developing overt infection. The gut microbiome can provide colonisation resistance against enteropathogens, but it remains unclear whether it confers resistance against ESBL-producing E coli. We aimed to identify a potential role of the microbiome in controlling colonisation by this antibiotic-resistant bacterium. METHODS: For this matched case-control study, we used faeces from 2751 individuals in a Dutch cross-sectional population study (PIENTER-3) to culture ESBL-producing bacteria. Of these, we selected 49 samples that were positive for an ESBL-producing E coli (ESBL-positive) and negative for several variables known to affect microbiome composition. These samples were matched 1:1 to ESBL-negative samples on the basis of individuals' age, sex, having been abroad or not in the past 6 months, and ethnicity. Shotgun metagenomic sequencing was done and taxonomic species composition and functional annotations (ie, microbial metabolism and carbohydrate-active enzymes) were determined. Targeted quantitative metabolic profiling (proton nuclear magnetic resonance spectroscopy) was done to investigate metabolomic profiles and combinations of univariate (t test and Wilcoxon test), multivariate (principal coordinates analysis, permutational multivariate analysis of variance, and partial least-squares discriminant analysis) and machine-learning approaches (least absolute shrinkage and selection operator and random forests) were used to analyse all the molecular data. FINDINGS: No differences in diversity parameters or in relative abundance were observed between ESBL-positive and ESBL-negative groups based on bacterial species-level composition. Machine-learning approaches using microbiota composition did not accurately predict ESBL status (area under the receiver operating characteristic curve [AUROC]=0·41) when using either microbiota composition or any of the functional profiles. The metabolome also did not differ between ESBL groups, as assessed by various methods including random forest (AUROC=0·61). INTERPRETATION: By combining multiomics and machine-learning approaches, we conclude that asymptomatic gut carriage of ESBL-producing E coli is not associated with an altered microbiome composition or function. This finding might suggest that microbiome-mediated colonisation resistance against ESBL-producing E coli is not as relevant as it is against other enteropathogens and antibiotic-resistant bacteria. FUNDING: None.

Pathology and Immunity After SARS-CoV-2 Infection in Male Ferrets Is Affected by Age and Inoculation Route.

Improving COVID-19 intervention strategies partly relies on animal models to study SARS-CoV-2 disease and immunity. In our pursuit to establish a model for severe COVID-19, we inoculated young and adult male ferrets intranasally or intratracheally with SARS-CoV-2. Intranasal inoculation established an infection in all ferrets, with viral dissemination into the brain and gut. Upon intratracheal inoculation only adult ferrets became infected. However, neither inoculation route induced observable COVID-19 symptoms. Despite this, a persistent inflammation in the nasal turbinates was prominent in especially young ferrets and follicular hyperplasia in the bronchi developed 21 days post infection. These effects -if sustained- might resemble long-COVID. Respiratory and systemic cellular responses and antibody responses were induced only in animals with an established infection. We conclude that intranasally-infected ferrets resemble asymptomatic COVID-19 and possibly aspects of long-COVID. Combined with the increasing portfolio to measure adaptive immunity, ferrets are a relevant model for SARS-CoV-2 vaccine research.

Benchmarking laboratory processes to characterise low-biomass respiratory microbiota.

The low biomass of respiratory samples makes it difficult to accurately characterise the microbial community composition. PCR conditions and contaminating microbial DNA can alter the biological profile. The objective of this study was to benchmark the currently available laboratory protocols to accurately analyse the microbial community of low biomass samples. To study the effect of PCR conditions on the microbial community profile, we amplified the 16S rRNA gene of respiratory samples using various bacterial loads and different number of PCR cycles. Libraries were purified by gel electrophoresis or AMPure XP and sequenced by V2 or V3 MiSeq reagent kits by Illumina sequencing. The positive control was diluted in different solvents. PCR conditions had no significant influence on the microbial community profile of low biomass samples. Purification methods and MiSeq reagent kits provided nearly similar microbiota profiles (paired Bray-Curtis dissimilarity median: 0.03 and 0.05, respectively). While profiles of positive controls were significantly influenced by the type of dilution solvent, the theoretical profile of the Zymo mock was most accurately analysed when the Zymo mock was diluted in elution buffer (difference compared to the theoretical Zymo mock: 21.6% for elution buffer, 29.2% for Milli-Q, and 79.6% for DNA/RNA shield). Microbiota profiles of DNA blanks formed a distinct cluster compared to low biomass samples, demonstrating that low biomass samples can accurately be distinguished from DNA blanks. In summary, to accurately characterise the microbial community composition we recommend 1. amplification of the obtained microbial DNA with 30 PCR cycles, 2. purifying amplicon pools by two consecutive AMPure XP steps and 3. sequence the pooled amplicons by V3 MiSeq reagent kit. The benchmarked standardized laboratory workflow presented here ensures comparability of results within and between low biomass microbiome studies.

Loss of Microbial Topography between Oral and Nasopharyngeal Microbiota and Development of Respiratory Infections Early in Life.

Rationale: The respiratory microbiota is increasingly being appreciated as an important mediator in the susceptibility to childhood respiratory tract infections (RTIs). Pathogens are presumed to originate from the nasopharyngeal ecosystem.Objectives: To investigate the association between early life respiratory microbiota and development of childhood RTIs.Methods: In a prospective birth cohort (Microbiome Utrecht Infant Study: MUIS), we characterized the oral microbiota longitudinally from birth until 6 months of age of 112 infants (nine regular samples/subject) and compared them with nasopharyngeal microbiota using 16S-rRNA-based sequencing. We also characterized oral and nasopharynx samples during RTI episodes in the first half year of life.Measurements and Main Results: Oral microbiota were driven mostly by feeding type, followed by age, mode of delivery, and season of sampling. In contrast to our previously published associations between nasopharyngeal microbiota development and susceptibility to RTIs, oral microbiota development was not directly associated with susceptibility to RTI development. However, we did observe an influx of oral taxa, such as Neisseria lactamica, Streptococcus, Prevotella nanceiensis, Fusobacterium, and Janthinobacterium lividum, in the nasopharyngeal microbiota before and during RTIs, which was accompanied by reduced presence and abundance of Corynebacterium, Dolosigranulum, and Moraxella spp. Moreover, this phenomenon was accompanied by reduced niche differentiation indicating loss of ecological topography preceding confirmed RTIs. This loss of ecological topography was further augmented by start of daycare, and linked to consecutive development of symptomatic infections.Conclusions: Together, our results link the loss of topography to subsequent development of RTI episodes. This may lead to new insights for prevention of RTIs and antibiotic use in childhood.

The Impact of Maltitol-Sweetened Chewing Gum on the Dental Plaque Biofilm Microbiota Composition.

Background: The oral cavity harbors a complex microbial ecosystem, intimately related to oral health and disease. The use of polyol-sweetened gum is believed to benefit oral health through stimulation of salivary flow and impacting oral pathogenic bacteria. Maltitol is often used as sweetener in food products. This study aimed to establish the in vivo effects of frequent consumption of maltitol-sweetened chewing gum on the dental plaque microbiota in healthy volunteers and to establish the cellular and molecular effects by in vitro cultivation and transcriptional analysis. Results: An intervention study was performed in 153 volunteers, randomly assigned to three groups (www.trialregister.nl; NTR4165). One group was requested to use maltitol gum five times daily, one group used gum-base, and the third group did not use chewing gum. At day 0 and day 28, 24 h-accumulated supragingival plaque was collected at the lingual sites of the lower jaw and the buccal sites of the upper jaw and analyzed by 16S ribosomal rRNA gene sequencing. At day 42, 2 weeks after completion of the study, lower-jaw samples were collected and analyzed. The upper buccal plaque microbiota composition had lower bacterial levels and higher relative abundances of (facultative) aerobic species compared to the lower lingual sites. There was no difference in bacterial community structure between any of the three study groups (PERMANOVA). Significant lower abundance of several bacterial phylotypes was found in maltitol gum group compared to the gum-base group, including Actinomyces massiliensis HOT 852 and Lautropia mirabilis HOT 022. Cultivation studies confirmed growth inhibition of A. massiliensis and A. johnsonii by maltitol at levels of 1% and higher. Transcriptome analysis of A. massiliensis revealed that exposure to maltitol resulted in changes in the expression of genes linked to osmoregulation, biofilm formation, and central carbon metabolism. Conclusion: The results showed that chewing itself only marginally impacted the plaque microbiota composition. Use of maltitol-sweetened gum lowered abundance of several bacterial species. Importantly, the species impacted play a key role in the early formation of dental biofilms. Further studies are required to establish if frequent use of maltitol gum impacts early dental-plaque biofilm development.

Maturation of the Infant Respiratory Microbiota, Environmental Drivers, and Health Consequences. A Prospective Cohort Study.

RATIONALE: Perinatal and postnatal influences are presumed important drivers of the early-life respiratory microbiota composition. We hypothesized that the respiratory microbiota composition and development in infancy is affecting microbiota stability and thereby resistance against respiratory tract infections (RTIs) over time. OBJECTIVES: To investigate common environmental drivers, including birth mode, feeding type, antibiotic exposure, and crowding conditions, in relation to respiratory tract microbiota maturation and stability, and consecutive risk of RTIs over the first year of life. METHODS: In a prospectively followed cohort of 112 infants, we characterized the nasopharyngeal microbiota longitudinally from birth on (11 consecutive sample moments and the maximum three RTI samples per subject; in total, n = 1,121 samples) by 16S-rRNA gene amplicon sequencing. MEASUREMENTS AND MAIN RESULTS: Using a microbiota-based machine-learning algorithm, we found that children experiencing a higher number of RTIs in the first year of life already demonstrate an aberrant microbial developmental trajectory from the first month of life on as compared with the reference group (0-2 RTIs/yr). The altered microbiota maturation process coincided with decreased microbial community stability, prolonged reduction of Corynebacterium and Dolosigranulum, enrichment of Moraxella very early in life, followed by later enrichment of Neisseria and Prevotella spp. Independent drivers of these aberrant developmental trajectories of respiratory microbiota members were mode of delivery, infant feeding, crowding, and recent antibiotic use. CONCLUSIONS: Our results suggest that environmental drivers impact microbiota development and, consequently, resistance against development of RTIs. This supports the idea that microbiota form the mediator between early-life environmental risk factors for and susceptibility to RTIs over the first year of life.

On the ecosystemic network of saliva in healthy young adults.

A dysbiotic state is believed to be a key factor in the onset of oral disease. Although oral diseases have been studied for decades, our understanding of oral health, the boundaries of a healthy oral ecosystem and ecological shift toward dysbiosis is still limited. Here, we present the ecobiological heterogeneity of the salivary ecosystem and relations between the salivary microbiome, salivary metabolome and host-related biochemical salivary parameters in 268 healthy adults after overnight fasting. Gender-specific differences in the microbiome and metabolome were observed and were associated with salivary pH and dietary protein intake. Our analysis grouped the individuals into five microbiome and four metabolome-based clusters that significantly related to biochemical parameters of saliva. Low salivary pH and high lysozyme activity were associated with high proportions of streptococcal phylotypes and increased membrane-lipid degradation products. Samples with high salivary pH displayed increased chitinase activity, higher abundance of Veillonella and Prevotella species and higher levels of amino acid fermentation products, suggesting proteolytic adaptation. An over-specialization toward either a proteolytic or a saccharolytic ecotype may indicate a shift toward a dysbiotic state. Their prognostic value and the degree to which these ecotypes are related to increased disease risk remains to be determined.

Spatial Separation of Plk1 Phosphorylation and Activity.

Polo-like kinase 1 (Plk1) is one of the major kinases controlling mitosis and cell division. Plk1 is first recruited to the centrosome in S phase, then appears on the kinetochores in late G2, and at the end of mitosis, it translocates to the central spindle. Activation of Plk1 requires phosphorylation of T210 by Aurora A, an event that critically depends on the co-factor Bora. However, conflicting reports exist as to where Plk1 is first activated. Phosphorylation of T210 is first observed at the centrosomes, but kinase activity seems to be restricted to the nucleus in the earlier phases of G2. Here, we demonstrate that Plk1 activity manifests itself first in the nucleus using a nuclear FRET-based biosensor for Plk1 activity. However, we find that Bora is restricted to the cytoplasm and that Plk1 is phosphorylated on T210 at the centrosomes. Our data demonstrate that while Plk1 activation occurs on centrosomes, downstream target phosphorylation by Plk1 first occurs in the nucleus. We discuss several explanations for this surprising separation of activation and function.

Subpopulations of bovine WC1(+) gammadelta T cells rather than CD4(+)CD25(high) Foxp3(+) T cells act as immune regulatory cells ex vivo.

Regulatory T cells (Treg) are regarded essential components for maintenance of immune homeostasis. Especially CD4(+)CD25(high) T cells are considered to be important regulators of immune reactivity. In humans and rodents these natural Treg are characterized by their anergic nature, defined as a non-proliferative state, suppressive function and expression of Foxp3. In this study the potential functional role of flowcytometry-sorted bovine white blood cell populations, including CD4(+)CD25(high) T cells and gammadelta T cell subpopulations, as distinct ex vivo regulatory cells was assessed in co-culture suppression assays. Our findings revealed that despite the existence of a distinct bovine CD4(+)CD25(high) T cell population, which showed Foxp3 transcription/expression, natural regulatory activity did not reside in this cell population. In bovine co-culture suppression assays these cells were neither anergic nor suppressive. Subsequently, the following cell populations were tested functionally for regulatory activity: CD4(+)CD25(low) T cells, WC1(+), WC1.1(+) and WC1.2(+) gammadelta T cells, NK cells, CD8(+) T cells and CD14(+) monocytes. Only the WC1.1(+) and WC1.2(+) gammadelta T cells and CD14(+) monocytes proved to act as regulatory cells in cattle, which was supported by the fact that these regulatory cells showed IL-10 transcription/expression. In conclusion, our data provide first evidence that cattle CD4(+)CD25(high)Foxp3(+) and CD4(+)CD25(low) T cells do not function as Treg ex vivo. The bovine Treg function appears to reside in the gammadelta T cell population, more precisely in the WC1.1(+) and the WC1.2(+) subpopulation, major populations present in blood of cattle in contrast to non-ruminant species.