scholarly journals Fetal gut colonization: meconium does not have a detectable microbiota before birth

2021 ◽  
Author(s):  
Katherine M. Kennedy ◽  
Max J. Gerlach ◽  
Thomas Adam ◽  
Markus M. Heimesaat ◽  
Laura Rossi ◽  
...  
Keyword(s):  
Positive Culture ◽  
16S Rrna Gene Sequencing ◽  
Microbial Colonization ◽  
Rrna Gene ◽  
Bacterial Dna ◽  
Gut Colonization ◽  
First Pass ◽  
Rrna Gene Sequencing ◽  
Negative Controls ◽  
Host Metabolism

AbstractMicrobial colonization of the human intestine impacts host metabolism and immunity, however when colonization occurs is unclear. Although numerous studies have reported bacterial DNA in first-pass meconium samples, these samples are collected hours to days after birth. We investigated whether bacteria could be detected in meconium prior to birth. Fetal meconium (n = 20) was collected by rectal swab during elective breech Cesarean sections without labour prior to antibiotics and compared to technical and procedural controls (n = 5), first-pass meconium (neonatal meconium; n = 14), and infant stool (n = 25). Unlike first-pass meconium, no microbial signal distinct from negative controls was detected in fetal meconium by 16S rRNA gene sequencing. Additionally, positive aerobic (n = 10 of 20) and anaerobic (n = 12 of 20) clinical cultures of fetal meconium (13 of 20 samples positive in at least one culture) were identified as likely skin contaminants, most frequently Staphylococcus epidermidis, and not detected by sequencing in most samples (same genera detected by culture and sequencing in 2 of 13 samples with positive culture). We conclude that fetal gut colonization does not occur before birth, and that microbial profiles of neonatal meconium reflect populations acquired during and after birth.

scholarly journals Infant Gut Microbiota Associated with Fine Motor Skills

Nutrients ◽  
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.

scholarly journals The Viable Microbiome of Human Milk Differs from the Metataxonomic Profile

Nutrients ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 4445
Author(s):  
Lisa F. Stinson ◽  
Michelle L. Trevenen ◽  
Donna T. Geddes
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Human Milk ◽  
Dna Content ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Bacterial Dna ◽  
Cutibacterium Acnes ◽  
Rrna Gene Sequencing

Bacteria in human milk contribute to the establishment of the infant gut microbiome. As such, numerous studies have characterized the human milk microbiome using DNA sequencing technologies, particularly 16S rRNA gene sequencing. However, such methods are not able to differentiate between DNA from viable and non-viable bacteria. The extent to which bacterial DNA detected in human milk represents living, biologically active cells is therefore unclear. Here, we characterized both the viable bacterial content and the total bacterial DNA content (derived from viable and non-viable cells) of fresh human milk (n = 10). In order to differentiate the living from the dead, a combination of propidium monoazide (PMA) and full-length 16S rRNA gene sequencing was used. Our results demonstrate that the majority of OTUs recovered from fresh human milk samples (67.3%) reflected DNA from non-viable organisms. PMA-treated samples differed significantly in their bacterial composition compared to untreated samples (PERMANOVA p < 0.0001). Additionally, an OTU mapping to Cutibacterium acnes had a significantly higher relative abundance in PMA-treated (viable) samples. These results demonstrate that the total bacterial DNA content of human milk is not representative of the viable human milk microbiome. Our findings raise questions about the validity of conclusions drawn from previous studies in which viability testing was not used, and have broad implications for the design of future work in this field.

scholarly journals Abundant DNase I-Sensitive Bacterial DNA in Healthy Porcine Lungs and Its Implications for the Lung Microbiome

2013 ◽  
Vol 79 (19) ◽  
pp. 5936-5941 ◽  
Author(s):  
Alejandro A. Pezzulo ◽  
Patrick H. Kelly ◽  
Boulos S. Nassar ◽  
Cedric J. Rutland ◽  
Nicholas D. Gansemer ◽  
...  
Keyword(s):  
Bacterial Diversity ◽  
Defense Mechanisms ◽  
16S Rrna Gene Sequencing ◽  
Dnase I ◽  
Rrna Gene ◽  
Bacterial Dna ◽  
Lung Microbiome ◽  
Rrna Gene Sequencing ◽  
Porcine Lungs

ABSTRACTHuman lungs are constantly exposed to bacteria in the environment, yet the prevailing dogma is that healthy lungs are sterile. DNA sequencing-based studies of pulmonary bacterial diversity challenge this notion. However, DNA-based microbial analysis currently fails to distinguish between DNA from live bacteria and that from bacteria that have been killed by lung immune mechanisms, potentially causing overestimation of bacterial abundance and diversity. We investigated whether bacterial DNA recovered from lungs represents live or dead bacteria in bronchoalveolar lavage (BAL) fluid and lung samples in young healthy pigs. Live bacterial DNA was DNase I resistant and became DNase I sensitive upon human antimicrobial-mediated killingin vitro. We determined live and total bacterial DNA loads in porcine BAL fluid and lung tissue by comparing DNase I-treated versus untreated samples. In contrast to the case for BAL fluid, we were unable to culture bacteria from most lung homogenates. Surprisingly, total bacterial DNA was abundant in both BAL fluid and lung homogenates. In BAL fluid, 63% was DNase I sensitive. In 6 out of 11 lung homogenates, all bacterial DNA was DNase I sensitive, suggesting a predominance of dead bacteria; in the remaining homogenates, 94% was DNase I sensitive, and bacterial diversity determined by 16S rRNA gene sequencing was similar in DNase I-treated and untreated samples. Healthy pig lungs are mostly sterile yet contain abundant DNase I-sensitive DNA from inhaled and aspirated bacteria killed by pulmonary host defense mechanisms. This approach and conceptual framework will improve analysis of the lung microbiome in disease.

scholarly journals Caterpillars lack a resident gut microbiome

2017 ◽  
Author(s):  
Tobin J. Hammer ◽  
Daniel H. Janzen ◽  
Winnifred Hallwachs ◽  
Samuel L. Jaffe ◽  
Noah Fierer
Keyword(s):  
16S Rrna Gene Sequencing ◽  
The United States ◽  
Microbial Colonization ◽  
Rrna Gene ◽  
Ecological Interactions ◽  
Agricultural Pests ◽  
Evolutionary Diversification ◽  
Transit Times ◽  
Microbial Symbionts ◽  
Rrna Gene Sequencing

AbstractMany animals are inhabited by microbial symbionts that influence their hosts’ development, physiology, ecological interactions, and evolutionary diversification. However, firm evidence for the existence and functional importance of resident microbiomes in larval Lepidoptera (caterpillars) is lacking, despite the fact that these insects are enormously diverse, major agricultural pests, and dominant herbivores in many ecosystems. Using 16S rRNA gene sequencing and quantitative PCR, we characterized the gut microbiomes of wild leaf-feeding caterpillars in the United States and Costa Rica, representing 124 species from 16 families. Compared with other insects and vertebrates assayed using the same methods, the microbes we detected in caterpillar guts were unusually low-density and highly variable among individuals. Furthermore, the abundance and composition of leaf-associated microbes were reflected in the feces of caterpillars consuming the same plants. Thus, microbes ingested with food are present (though possibly dead or dormant) in the caterpillar gut, but host-specific, resident symbionts are largely absent. To test whether transient microbes might still contribute to feeding and development, we conducted an experiment on field-collected caterpillars of the model speciesManduca sexta. Antibiotic suppression of gut bacterial activity did not significantly affect caterpillar weight gain, development, or survival. The high pH, simple gut structure, and fast transit times that typify caterpillar digestive physiology may prevent microbial colonization. Moreover, host-encoded digestive and detoxification mechanisms likely render microbes unnecessary for caterpillar herbivory. Caterpillars illustrate the potential ecological and evolutionary benefits of independence from symbionts, a lifestyle which may be widespread among animals.

scholarly journals Endotoxemia and circulating bacteriome in severe COVID-19 patients

2020 ◽  
Author(s):  
Phatadon Sirivongrangson ◽  
Win Kulvichit ◽  
Sunchai Payungporn ◽  
Trairak Pisitkun ◽  
Ariya Chindamporn ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Significant Contribution ◽  
16S Rrna Gene Sequencing ◽  
High Serum ◽  
Rrna Gene ◽  
Bacterial Dna ◽  
Endotoxin Activity ◽  
Rrna Gene Sequencing ◽  
Bacterial Products

AbstractPurposeWhen severe, COVID-19 shares many clinical features with bacterial sepsis. Yet, secondary bacterial infection is uncommon. However, as epithelium are injured and barrier function is lost, bacterial products entering the circulation might contribute to the pathophysiology of COVID-19.MethodsWe studied 19 adults, severely ill patients with COVID-19 infection, who were admitted to King Chulalongkorn Memorial Hospital, Bangkok, Thailand, between 13th March and 17th April 2020. Blood samples on day 1, 3, and 7 of enrollment were analyzed for endotoxin activity assay (EAA), (1→3)-β-D-Glucan (BG), and 16S rRNA gene sequencing to determine the circulating bacteriome.ResultsOf the 19 patients, 14 were in intensive care and 10 patients received mechanical ventilation. We found 8 patients with high EAA (≥ 0.6) and about half of the patients had high serum BG levels which tended to be higher in later in the illness. Although only 1 patient had a positive blood culture, 18 of 19 patients were positive for 16S rRNA gene amplification. Proteobacteria was the most abundant phylum. The diversity of bacterial genera was decreased overtime.ConclusionsBacterial DNA and toxins were discovered in virtual all severely ill COVID-19 pneumonia patients. This raises a previously unrecognized concern for significant contribution of bacterial products in the pathogenesis of this disease

scholarly journals Caterpillars lack a resident gut microbiome

2017 ◽  
Vol 114 (36) ◽  
pp. 9641-9646 ◽  
Author(s):  
Tobin J. Hammer ◽  
Daniel H. Janzen ◽  
Winnie Hallwachs ◽  
Samuel P. Jaffe ◽  
Noah Fierer
Keyword(s):  
16S Rrna Gene Sequencing ◽  
The United States ◽  
Microbial Colonization ◽  
Rrna Gene ◽  
Ecological Interactions ◽  
Agricultural Pests ◽  
Evolutionary Diversification ◽  
Transit Times ◽  
Microbial Symbionts ◽  
Rrna Gene Sequencing

Many animals are inhabited by microbial symbionts that influence their hosts’ development, physiology, ecological interactions, and evolutionary diversification. However, firm evidence for the existence and functional importance of resident microbiomes in larval Lepidoptera (caterpillars) is lacking, despite the fact that these insects are enormously diverse, major agricultural pests, and dominant herbivores in many ecosystems. Using 16S rRNA gene sequencing and quantitative PCR, we characterized the gut microbiomes of wild leaf-feeding caterpillars in the United States and Costa Rica, representing 124 species from 15 families. Compared with other insects and vertebrates assayed using the same methods, the microbes that we detected in caterpillar guts were unusually low-density and variable among individuals. Furthermore, the abundance and composition of leaf-associated microbes were reflected in the feces of caterpillars consuming the same plants. Thus, microbes ingested with food are present (although possibly dead or dormant) in the caterpillar gut, but host-specific, resident symbionts are largely absent. To test whether transient microbes might still contribute to feeding and development, we conducted an experiment on field-collected caterpillars of the model speciesManduca sexta. Antibiotic suppression of gut bacterial activity did not significantly affect caterpillar weight gain, development, or survival. The high pH, simple gut structure, and fast transit times that typify caterpillar digestive physiology may prevent microbial colonization. Moreover, host-encoded digestive and detoxification mechanisms likely render microbes unnecessary for caterpillar herbivory. Caterpillars illustrate the potential ecological and evolutionary benefits of independence from symbionts, a lifestyle that may be widespread among animals.

scholarly journals Controlling for Contaminants in Low-Biomass 16S rRNA Gene Sequencing Experiments

mSystems ◽  
2019 ◽  
Vol 4 (4) ◽  
Author(s):  
Lisa Karstens ◽  
Mark Asquith ◽  
Sean Davin ◽  
Damien Fair ◽  
W. Thomas Gregory ◽  
...  
Keyword(s):  
Microbial Biomass ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Bacterial Dna ◽  
Dilution Series ◽  
Rrna Gene Sequencing

ABSTRACTMicrobial communities are commonly studied using culture-independent methods, such as 16S rRNA gene sequencing. However, one challenge in accurately characterizing microbial communities is exogenous bacterial DNA contamination, particularly in low-microbial-biomass niches. Computational approaches to identify contaminant sequences have been proposed, but their performance has not been independently evaluated. To identify the impact of decreasing microbial biomass on polymicrobial 16S rRNA gene sequencing experiments, we created a mock microbial community dilution series. We evaluated four computational approaches to identify and remove contaminants, as follows: (i) filtering sequences present in a negative control, (ii) filtering sequences based on relative abundance, (iii) identifying sequences that have an inverse correlation with DNA concentration implemented in Decontam, and (iv) predicting the sequence proportion arising from defined contaminant sources implemented in SourceTracker. As expected, the proportion of contaminant bacterial DNA increased with decreasing starting microbial biomass, with 80.1% of the most diluted sample arising from contaminant sequences. Inclusion of contaminant sequences led to overinflated diversity estimates and distorted microbiome composition. All methods for contaminant identification successfully identified some contaminant sequences, which varied depending on the method parameters used and contaminant prevalence. Notably, removing sequences present in a negative control erroneously removed >20% of expected sequences. SourceTracker successfully removed over 98% of contaminants when the experimental environments were well defined. However, SourceTracker misclassified expected sequences and performed poorly when the experimental environment was unknown, failing to remove >97% of contaminants. In contrast, the Decontam frequency method did not remove expected sequences and successfully removed 70 to 90% of the contaminants.IMPORTANCEThe relative scarcity of microbes in low-microbial-biomass environments makes accurate determination of community composition challenging. Identifying and controlling for contaminant bacterial DNA are critical steps in understanding microbial communities from these low-biomass environments. Our study introduces the use of a mock community dilution series as a positive control and evaluates four computational strategies that can identify contaminants in 16S rRNA gene sequencing experiments in order to remove them from downstream analyses. The appropriate computational approach for removing contaminant sequences from an experiment depends on prior knowledge about the microbial environment under investigation and can be evaluated with a dilution series of a mock microbial community.

scholarly journals Endotoxemia and circulating bacteriome in severe COVID-19 patients

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Phatadon Sirivongrangson ◽  
Win Kulvichit ◽  
Sunchai Payungporn ◽  
Trairak Pisitkun ◽  
Ariya Chindamporn ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Significant Contribution ◽  
16S Rrna Gene Sequencing ◽  
High Serum ◽  
Rrna Gene ◽  
Bacterial Dna ◽  
Endotoxin Activity ◽  
Rrna Gene Sequencing ◽  
Bacterial Products

Abstract Background When severe, COVID-19 shares many clinical features with bacterial sepsis. Yet, secondary bacterial infection is uncommon. However, as epithelium is injured and barrier function is lost, bacterial products entering the circulation might contribute to the pathophysiology of COVID-19. Methods We studied 19 adults, severely ill patients with COVID-19 infection, who were admitted to King Chulalongkorn Memorial Hospital, Bangkok, Thailand, between 13th March and 17th April 2020. Blood samples on days 1, 3, and 7 of enrollment were analyzed for endotoxin activity assay (EAA), (1 → 3)-β-d-glucan (BG), and 16S rRNA gene sequencing to determine the circulating bacteriome. Results Of the 19 patients, 13 were in intensive care and 10 patients received mechanical ventilation. We found 8 patients with high EAA (≥ 0.6) and about half of the patients had high serum BG levels which tended to be higher in later in the illness. Although only 1 patient had a positive blood culture, 18 of 19 patients were positive for 16S rRNA gene amplification. Proteobacteria was the most abundant phylum. The diversity of bacterial genera was decreased overtime. Conclusions Bacterial DNA and toxins were discovered in virtually all severely ill COVID-19 pneumonia patients. This raises a previously unrecognized concern for significant contribution of bacterial products in the pathogenesis of this disease.

scholarly journals Controlling for contaminants in low biomass 16S rRNA gene sequencing experiments

2018 ◽  
Author(s):  
Lisa Karstens ◽  
Mark Asquith ◽  
Sean Davin ◽  
Damien Fair ◽  
W. Thomas Gregory ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Biomass ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Bacterial Dna ◽  
Computational Approaches ◽  
Rrna Gene Sequencing

AbstractBackgroundMicrobial communities are commonly studied using culture-independent methods such as 16S rRNA gene sequencing. However, one challenge in accurately characterizing microbial communities is exogenous bacterial DNA contamination. This is particularly problematic for sites of low microbial biomass such as the urinary tract, placenta, and lower airway. Computational approaches have been proposed as a post-processing step to identify and remove potential contaminants, but their performance has not been independently evaluated.To identify the impact of decreasing microbial biomass on polymicrobial 16S rRNA gene sequencing experiments, we used a serial dilution of a mock microbial community. We evaluated two computational approaches to identify and remove contaminants: 1) identifying sequences that have an inverse correlation with DNA concentration implemented in Decontam and 2) predicting the proportion of experimental sample arising from defined contaminant sources implemented in SourceTracker.ResultsAs expected, the proportion of contaminant bacterial DNA increased with decreasing starting microbial biomass, with 79.12% of the most dilute sample arising from contaminant sequences. Inclusion of contaminant sequences in analyses leads to overinflated diversity estimates (up to 12 times greater than the expected values) and distorts microbiome composition. SourceTracker successfully removed over 98% of contaminants when the experimental environments are well defined. However, SourceTracker performed poorly when the experimental environment is unknown, failing to remove the majority of contaminants. Decontam successfully removed 74-91% of contaminants regardless of prior knowledge of the experimental environment.ConclusionsOur study indicates that computational methods can reduce the amount of contaminants in 16S rRNA gene sequencing experiments. The appropriate computational approach for removing contaminant sequences from an experiment depends on the prior knowledge about the microbial environment under investigation and can be evaluated with a dilution series of a mock microbial community.

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