A Combined Analysis of Gut and Skin Microbiota in Infants with Food Allergy and Atopic Dermatitis: A Pilot Study

The gut microbiota in patients with food allergy, and the skin microbiota in atopic dermatitis patients differ from those of healthy people. We hypothesize that relationships may exist between gut and skin microbiota in patients with allergies. The aim of this study was to determine the possible relationship between gut and skin microbiota in patients with allergies, hence simultaneous analysis of the two compartments of microbiota was performed in infants with and without allergic symptoms. Fifty-nine infants with food allergy and/or atopic dermatitis and 28 healthy children were enrolled in the study. The skin and gut microbiota were evaluated using 16S rRNA gene amplicon sequencing. No significant differences in the α-diversity of dermal or fecal microbiota were observed between allergic and non-allergic infants; however, a significant relationship was found between bacterial community structure and allergy phenotypes, especially in the fecal samples. Certain clinical conditions were associated with characteristic bacterial taxa in the skin and gut microbiota. Positive correlations were found between skin and fecal samples in the abundance of Gemella among allergic infants, and Lactobacillus and Bacteroides among healthy infants. Although infants with allergies and healthy infants demonstrate microbiota with similar α-diversity, some differences in β-diversity and bacterial species abundance can be seen, which may depend on the phenotype of the allergy. For some organisms, their abundance in skin and feces samples may be correlated, and these correlations might serve as indicators of the host’s allergic state.

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High-Throughput Quantitative Analysis of the Human Intestinal Microbiota with a Phylogenetic Microarray

Applied and Environmental Microbiology ◽

10.1128/aem.02764-08 ◽

2009 ◽

Vol 75 (11) ◽

pp. 3572-3579 ◽

Cited By ~ 67

Author(s):

Oleg Paliy ◽

Harshavardhan Kenche ◽

Frank Abernathy ◽

Sonia Michail

Keyword(s):

Gut Microbiota ◽

Genomic Dna ◽

Bacterial Species ◽

Detection Sensitivity ◽

Rrna Gene ◽

Healthy Children ◽

Data Set ◽

Fecal Samples ◽

Human Intestinal Microbiota ◽

Validation Experiments

ABSTRACT Gut microbiota carry out key functions in health and participate in the pathogenesis of a growing number of diseases. The aim of this study was to develop a custom microarray that is able to identify hundreds of intestinal bacterial species. We used the Entrez nucleotide database to compile a data set of bacterial 16S rRNA gene sequences isolated from human intestinal and fecal samples. Identified sequences were clustered into separate phylospecies groups. Representative sequences from each phylospecies were used to develop a microbiota microarray based on the Affymetrix GeneChip platform. The designed microbiota array contains probes to 775 different bacterial phylospecies. In our validation experiments, the array correctly identified genomic DNA from all 15 bacterial species used. Microbiota array has a detection sensitivity of at least 1 pg of genomic DNA and can detect bacteria present at a 0.00025% level of overall sample. Using the developed microarray, fecal samples from two healthy children and two healthy adults were analyzed for bacterial presence. Between 227 and 232 species were detected in fecal samples from children, whereas 191 to 208 species were found in adult stools. The majority of identified phylospecies belonged to the classes Clostridia and Bacteroidetes. The microarray revealed putative differences between the gut microbiota of healthy children and adults: fecal samples from adults had more Clostridia and less Bacteroidetes and Proteobacteria than those from children. A number of other putative differences were found at the genus level.

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Mother’s Milk Microbiome Shaping Fecal and Skin Microbiota in Infants with Food Allergy and Atopic Dermatitis: A Pilot Analysis

Nutrients ◽

10.3390/nu13103600 ◽

2021 ◽

Vol 13 (10) ◽

pp. 3600

Author(s):

Marcin Gołębiewski ◽

Ewa Łoś-Rycharska ◽

Marcin Sikora ◽

Tomasz Grzybowski ◽

Marta Gorzkiewicz ◽

...

Keyword(s):

Atopic Dermatitis ◽

Food Allergy ◽

Rrna Gene ◽

Skin Microbiota ◽

Healthy Infants ◽

Mother's Milk ◽

Total Dna ◽

Mother’S Milk ◽

Fragment Libraries ◽

Essential Food

The child microbiome, including gut and skin communities, is shaped by a multitude of factors, and breastfeeding is one of the most essential. Food allergy (FA) and atopic dermatitis (AD) are among the most common diseases in pediatrics, with the prevalence of each up to 6% and 20%, respectively. Therefore, we aimed at finding differences between the fecal and skin microbiomes of FA and AD patients in the context of breastfeeding, by means of the Illumina sequencing of 16S rRNA gene fragment libraries amplified from the total DNA isolated from samples collected from allergic and healthy infants. We also analyzed milk samples from the mothers of the examined children and searched for patterns of incidence suggesting milk influence on an infant’s allergy status. Here we show that a mother’s milk influences her child’s fecal and skin microbiomes and identify Acinetobacter as the taxon whose abundance is correlated with milk and child-derived samples. We demonstrate that breastfeeding makes allergic children's fecal and skin communities more similar to those of healthy infants than in the case of formula-feeding. We also identify signature taxa that might be important in maintaining health or allergy development.

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Microbial signature in IgE-mediated food allergies

Genome Medicine ◽

10.1186/s13073-020-00789-4 ◽

2020 ◽

Vol 12 (1) ◽

Cited By ~ 1

Author(s):

Michael R. Goldberg ◽

Hadar Mor ◽

Dafna Magid Neriya ◽

Faiga Magzal ◽

Efrat Muller ◽

...

Keyword(s):

Food Allergy ◽

Gut Microbiota ◽

Learning Algorithm ◽

Area Under The Curve ◽

Food Allergies ◽

Rrna Gene ◽

Microbiota Composition ◽

Α Diversity ◽

Ige Mediated ◽

Gut Microbiota Composition

Abstract Background Multiple studies suggest a key role for gut microbiota in IgE-mediated food allergy (FA) development, but to date, none has studied it in the persistent state. Methods To characterize the gut microbiota composition and short-chain fatty acid (SCFAs) profiles associated with major food allergy groups, we recruited 233 patients with FA including milk (N = 66), sesame (N = 38), peanut (N = 71), and tree nuts (N = 58), and non-allergic controls (N = 58). DNA was isolated from fecal samples, and 16S rRNA gene sequences were analyzed. SCFAs in stool were analyzed from patients with a single allergy (N = 84) and controls (N = 31). Results The gut microbiota composition of allergic patients was significantly different compared to age-matched controls both in α-diversity and β-diversity. Distinct microbial signatures were noted for FA to different foods. Prevotella copri (P. copri) was the most overrepresented species in non-allergic controls. SCFAs levels were significantly higher in the non-allergic compared to the FA groups, whereas P. copri significantly correlated with all three SCFAs. We used these microbial differences to distinguish between FA patients and non-allergic healthy controls with an area under the curve of 0.90, and for the classification of FA patients according to their FA types using a supervised learning algorithm. Bacteroides and P. copri were identified as taxa potentially contributing to KEGG acetate-related pathways enriched in non-allergic compared to FA. In addition, overall pathway dissimilarities were found among different FAs. Conclusions Our results demonstrate a link between IgE-mediated FA and the composition and metabolic activity of the gut microbiota.

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Characterization of skin microbiota in patients with atopic dermatitis and in normal subjects using 16S rRNA gene-based comprehensive analysis

Journal of Medical Microbiology ◽

10.1099/jmm.0.47268-0 ◽

2007 ◽

Vol 56 (12) ◽

pp. 1675-1683 ◽

Cited By ~ 54

Author(s):

Itaru Dekio ◽

Mitsuo Sakamoto ◽

Hidenori Hayashi ◽

Masayuki Amagai ◽

Makoto Suematsu ◽

...

Keyword(s):

Atopic Dermatitis ◽

16S Rrna ◽

16S Rrna Gene ◽

Bacterial Species ◽

Rrna Genes ◽

Rrna Gene ◽

Healthy Controls ◽

Skin Microbiota ◽

Micro Organisms ◽

Normal Controls

A previous study using bacterial 16S rRNA gene-based clone libraries revealed that the microbiota in healthy human skin included uncultured micro-organisms, although the micro-organisms in skin exposed to disease conditions remain to be examined. To compare the profiles of skin microbiota in 13 patients with atopic dermatitis (AD) and 10 healthy controls, terminal RFLP analysis of bacterial 16S rRNA genes was applied to 23 swab-scrubbed samples from facial skin. This culture-independent analysis successfully revealed the complex bacterial members of the microbiota as peak patterns following capillary electrophoresis of terminal restriction fragments (T-RFs). Each T-RF peak reflected a micro-organism, and the micro-organism to which each peak was assigned could be identified by computer simulation of T-RF length using the nucleotide sequence data of bacterial species residing in the skin. Among 18 species detected in the study, Stenotrophomonas maltophilia was detected significantly more commonly in AD patients (5/13 for AD patients vs 0/10 for controls), whilst Dietzia maris was detected significantly more commonly in normal controls (8/10 for controls vs 2/13 for AD patients). Moreover, Streptococcus species, which are considered to be uncommon in uninfected skin, were detected in seven patients and eight normal controls. Although further studies should be undertaken to investigate the roles of these micro-organisms in AD, the microbiota were presumed to include hitherto uninvestigated bacterial species in the major population of patients with AD and of healthy controls.

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Infant Gut Microbiota Associated with Fine Motor Skills

Nutrients ◽

10.3390/nu13051673 ◽

2021 ◽

Vol 13 (5) ◽

pp. 1673

Author(s):

Inmaculada Acuña ◽

Tomás Cerdó ◽

Alicia Ruiz ◽

Francisco J. Torres-Espínola ◽

Ana López-Moreno ◽

...

Keyword(s):

Gut Microbiota ◽

Infant Development ◽

16S Rrna Gene Sequencing ◽

Fine Motor ◽

Rrna Gene ◽

Neurodevelopmental Outcomes ◽

Gut Colonization ◽

Healthy Infants ◽

Behavioural Characteristics ◽

Rrna Gene Sequencing

BACKGROUND: During early life, dynamic gut colonization and brain development co-occur with potential cross-talk mechanisms affecting behaviour. METHODS: We used 16S rRNA gene sequencing to examine the associations between gut microbiota and neurodevelopmental outcomes assessed by the Bayley Scales of Infant Development III in 71 full-term healthy infants at 18 months of age. We hypothesized that children would differ in gut microbial diversity, enterotypes obtained by Dirichlet multinomial mixture analysis and specific taxa based on their behavioural characteristics. RESULTS: In children dichotomized by behavioural trait performance in above- and below-median groups, weighted Unifrac b-diversity exhibited significant differences in fine motor (FM) activity. Dirichlet multinomial mixture modelling identified two enterotypes strongly associated with FM outcomes. When controlling for maternal pre-gestational BMI and breastfeeding for up to 3 months, the examination of signature taxa in FM groups showed that Turicibacter and Parabacteroides were highly abundant in the below-median FM group, while Collinsella, Coprococcus, Enterococcus, Fusobacterium, Holdemanella, Propionibacterium, Roseburia, Veillonella, an unassigned genus within Veillonellaceae and, interestingly, probiotic Bifidobacterium and Lactobacillus were more abundant in the above-median FM group. CONCLUSIONS: Our results suggest an association between enterotypes and specific genera with FM activity and may represent an opportunity for probiotic interventions relevant to treatment for motor disorders.

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Nanopore-Sequencing Characterization of the Gut Microbiota of Melolontha melolontha Larvae: Contribution to Protection against Entomopathogenic Nematodes?

Pathogens ◽

10.3390/pathogens10040396 ◽

2021 ◽

Vol 10 (4) ◽

pp. 396

Author(s):

Ewa Sajnaga ◽

Marcin Skowronek ◽

Agnieszka Kalwasińska ◽

Waldemar Kazimierczak ◽

Karolina Ferenc ◽

...

Keyword(s):

Gut Microbiota ◽

Entomopathogenic Nematodes ◽

Bacterial Species ◽

Antagonistic Activity ◽

Rrna Gene ◽

Nanopore Sequencing ◽

Bacterial Phyla ◽

Melolontha Melolontha

This study focused on the potential relationships between midgut microbiota of the common cockchafer Melolontha melolontha larvae and their resistance to entomopathogenic nematodes (EPN) infection. We investigated the bacterial community associated with control and unsusceptible EPN-exposed insects through nanopore sequencing of the 16S rRNA gene. Firmicutes, Proteobacteria, Actinobacteria, and Bacteroidetes were the most abundant bacterial phyla within the complex and variable midgut microbiota of the wild M. melolontha larvae. The core microbiota was found to include 82 genera, which accounted for 3.4% of the total number of identified genera. The EPN-resistant larvae differed significantly from the control ones in the abundance of many genera belonging to the Actinomycetales, Rhizobiales, and Clostridiales orders. Additionally, the analysis of the microbiome networks revealed different sets of keystone midgut bacterial genera between these two groups of insects, indicating differences in the mutual interactions between bacteria. Finally, we detected Xenorhabdus and Photorhabdus as gut residents and various bacterial species exhibiting antagonistic activity against these entomopathogens. This study paves the way to further research aimed at unravelling the role of the host gut microbiota on the output of EPN infection, which may contribute to enhancement of the efficiency of nematodes used in eco-friendly pest management.

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Microbial Diversity Profiling of Gut Microbiota of Macropus giganteus Using Three Hypervariable Regions of the Bacterial 16S rRNA

Microorganisms ◽

10.3390/microorganisms9081721 ◽

2021 ◽

Vol 9 (8) ◽

pp. 1721

Author(s):

Christian O’Dea ◽

Roger Huerlimann ◽

Nicole Masters ◽

Anna Kuballa ◽

Cameron Veal ◽

...

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

Microbial Diversity ◽

Surface Waters ◽

Bacterial Species ◽

Rrna Gene ◽

Faecal Contamination ◽

Hypervariable Regions ◽

Geographical Regions ◽

V3 Region

Animal faecal contamination of surface waters poses a human health risk, as they may contain pathogenic bacteria or viruses. Of the numerous animal species residing along surface waterways in Australia, macropod species are a top contributor to wild animals’ faecal pollution load. We characterised the gut microbiota of 30 native Australian Eastern Grey Kangaroos from six geographical regions (five kangaroos from each region) within South East Queensland in order to establish their bacterial diversity and identify potential novel species-specific bacteria for the rapid detection of faecal contamination of surface waters by these animals. Using three hypervariable regions (HVRs) of the 16S rRNA gene (i.e., V1–V3, V3–V4, and V5–V6), for their effectiveness in delineating the gut microbial diversity, faecal samples from each region were pooled and microbial genomic DNA was extracted, sequenced, and analysed. Results indicated that V1-V3 yielded a higher taxa richness due to its larger target region (~480 bp); however, higher levels of unassigned taxa were observed using the V1-V3 region. In contrast, the V3–V4 HVR (~569 bp) attained a higher likelihood of a taxonomic hit identity to the bacterial species level, with a 5-fold decrease in unassigned taxa. There were distinct dissimilarities in beta diversity between the regions, with the V1-V3 region displaying the highest number of unique taxa (n = 42), followed by V3–V4 (n = 11) and V5–V6 (n = 8). Variations in the gut microbial diversity profiles of kangaroos from different regions were also observed, which indicates that environmental factors may impact the microbial development and, thus, the composition of the gut microbiome of these animals.

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The effects of gestational age on the composition and predicted function of gut microbiota in neonates and early infants

World Journal of Advanced Research and Reviews ◽

10.30574/wjarr.2021.12.2.0648 ◽

2021 ◽

Vol 12 (2) ◽

pp. 567-573

Author(s):

Kaiyu Pan ◽

Lianfang Yu ◽

Chengyue Zhang ◽

Jianhua Zhan ◽

Rongliang Tu

Keyword(s):

Gut Microbiota ◽

Gestational Age ◽

Full Term ◽

Rrna Gene ◽

Delivery Mode ◽

16S Sequencing ◽

Α Diversity ◽

Preterm Group ◽

Stool Samples ◽

Predicted Function

Gut microbiota can influence cell differentiation, metabolism, and immune function and is key for the normal development and future health of early infants. Several factors have been reported to be related to the microbiota composition of neonates, such as gestational age, delivery mode, feeding method, antibiotics consumption, and ethnicity, among others. So we investigated the relationship between gestational age and the composition and predicted function of the gut microbiota of neonates and early infants by sequencing the 16S rRNA gene present in stool samples obtained from 100 prospectively enrolled full-term and preterm newborns. In the 3-day-old neonates samples, the prominent genera in the full-term group were Escherichia-Shigella, Streptococcus, Bifidobacterium, and Bacteroides, while in the preterm group, Staphylococcus, Streptococcus, Escherichia-Shigella and Clostridium were the most abundant genera identified. There were statistical difference between two groups(P<0.05). Moreover, the predominant genera in the full-term group were Bifidobacterium, Lactobacillus, Bacteroides, and Clostridium , whereas the main genera in the preterm group were Escherichia-Shigella, Clostridium, Bifidobacterium and Bacteroides, in stool samples from 30-42-day-old infants. We found the α-diversity in 3-day-old group was significantly lower than in the 30-42-day-old group whether it’s full-term or preterm (P<0.001). Functional inference analysis revealed higher levels of biodegradation and metabolism of carbohydrates, vitamins in the full-term group than in the preterm group, both in neonates and early infants, which may contribute to the stability of the microbiota in the full-term group. There were significant differences in the composition and predicted function of the gut microbiota of early infants due to gestational age. The 16S sequencing technology was an effective and reliable tool in the detection of gut microbiota in early infants.

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The Effect of White Rice and White Bread as Staple Foods on Gut Microbiota and Host Metabolism

Nutrients ◽

10.3390/nu10091323 ◽

2018 ◽

Vol 10 (9) ◽

pp. 1323 ◽

Cited By ~ 2

Author(s):

Fumika Mano ◽

Kaori Ikeda ◽

Erina Joo ◽

Yoshihito Fujita ◽

Shunsuke Yamane ◽

...

Keyword(s):

Gut Microbiota ◽

Dietary Intervention ◽

16S Rrna Gene Sequencing ◽

Rrna Gene ◽

White Bread ◽

Fecal Samples ◽

White Rice ◽

Staple Foods ◽

Glucagon Like Peptide 1 ◽

Side Dishes

The purpose of this study was to examine the influence of two kinds of major Japanese staple foods, white rice and white bread, on gut microbiota against the background in which participants eat common side dishes. Seven healthy subjects completed the dietary intervention with two 1-week test periods with a 1-week wash-out period in cross-over design (UMIN registration UMIN000023142). White bread or white rice and 21 frozen prepared side dishes were consumed during the test periods. At baseline and at the end of each period, fasting blood samples, breath samples, and fecal samples were collected. For fecal samples, 16S rRNA gene sequencing was used to analyze the gut microbiota. After the bread period, the abundance of fecal Bifidobacterium genus (19.2 ± 14.5 vs. 6.2 ± 6.6 (%), p = 0.03), fasting glucagon-like peptide 1 (GLP-1) (13.6 ± 2.0 vs. 10.5 ± 2.9 (pg/mL), p = 0.03), and breath hydrogen (23.4 ± 9.9 vs. 8.2 ± 5.5 (ppm), p = 0.02) were significantly higher than those of after the rice period. Plasma SCFAs also tended to be higher after the bread period. White bread contains more dietary fiber than refined short grain rice. These findings suggest that indigestible carbohydrate intake from short grain rice as a staple food may be smaller than that of white bread.

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199 Do the Microbiomes of Horses Process Nutrients Differently Based on Keeper Status?

Journal of Animal Science ◽

10.1093/jas/skab235.192 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 106-106

Author(s):

Alexa C Johnson ◽

Amy S Biddle

Keyword(s):

Fixed Effects ◽

High Performance ◽

16S Rrna Gene Sequencing ◽

Gas Production ◽

Rrna Gene ◽

Total N ◽

Fermentation Products ◽

Fecal Samples ◽

Α Diversity ◽

C 50

Abstract This study reports the differential response of the equine gut microbiome to protein and/or carbohydrate based on keeper status (easy keeper (EK), medium keeper (MK), hard keeper (HK)). Anaerobic equine fecal samples (n = 12 total, n = 3 / EK, MK, HK of four breeds) inoculated microcosms with three dietary conditions (C = Carb (cornmeal), P = Protein (soybean meal), and M = mix (50% C, 50% P)). Over 48 hours, fermentation products were measured using colorimetric assays and high-performance liquid chromatography. Microbial populations were surveyed using 16S rRNA gene sequencing analyzed by QIIME2. Linear mixed models were fit with fixed effects of Treatment and Keeper status and their interactions, with random effects of HorseID. Differences in fermentation products by keeper status included: MK had higher pH and greater gas production, EK produced higher hydrogen sulfide, and HK had greater total protein. Total SCFA was not different between keeper status (P = 0.89) but the acetate: propionate ratio was highest for HK (2.45mM) and lowest for EK (1.85mM) (P = 0.05). Isobutyrate production was highest in HK (2.34mM) compared to MK (0.85mM) and EK (0.17mM). Treatment had significant effects across all measurements; M and C treatment values were similar reflecting microbial preferences for carbohydrates before protein. P treated trials had increased fermentation outputs due to lower acidity effects. Keeper status had no effect on α-diversity (P > 0.05) however HK horses were least affected by treatments. P treated samples were more diverse than C and M (P < 0.001). Spearman correlation of Keeper x Treatment identified Oligosphaeria spp. in EK (r = 0.49) and Fusobacteria spp. in HK whole fecal samples (r = 0.37). These data suggest that while the compositions of the gut microbiomes of keeper groups were similar, they were functionally different in processing key nutrients.

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