Same Exposure but Two Radically Different Responses to Antibiotics: Resilience of the Salivary Microbiome versus Long-Term Microbial Shifts in Feces

ABSTRACT Due to the spread of resistance, antibiotic exposure receives increasing attention. Ecological consequences for the different niches of individual microbiomes are, however, largely ignored. Here, we report the effects of widely used antibiotics (clindamycin, ciprofloxacin, amoxicillin, and minocycline) with different modes of action on the ecology of both the gut and the oral microbiomes in 66 healthy adults from the United Kingdom and Sweden in a two-center randomized placebo-controlled clinical trial. Feces and saliva were collected at baseline, immediately after exposure, and 1, 2, 4, and 12 months after administration of antibiotics or placebo. Sequences of 16S rRNA gene amplicons from all samples and metagenomic shotgun sequences from selected baseline and post-antibiotic-treatment sample pairs were analyzed. Additionally, metagenomic predictions based on 16S rRNA gene amplicon data were performed using PICRUSt. The salivary microbiome was found to be significantly more robust, whereas the antibiotics negatively affected the fecal microbiome: in particular, health-associated butyrate-producing species became strongly underrepresented. Additionally, exposure to different antibiotics enriched genes associated with antibiotic resistance. In conclusion, healthy individuals, exposed to a single antibiotic treatment, undergo considerable microbial shifts and enrichment in antibiotic resistance in their feces, while their salivary microbiome composition remains unexpectedly stable. The health-related consequences for the gut microbiome should increase the awareness of the individual risks involved with antibiotic use, especially in a (diseased) population with an already dysregulated microbiome. On the other hand, understanding the mechanisms behind the resilience of the oral microbiome toward ecological collapse might prove useful in combating microbial dysbiosis elsewhere in the body. IMPORTANCE Many health care professionals use antibiotic prophylaxis strategies to prevent infection after surgery. This practice is under debate since it enhances the spread of antibiotic resistance. Another important reason to avoid nonessential use of antibiotics, the impact on our microbiome, has hardly received attention. In this study, we assessed the impact of antibiotics on the human microbial ecology at two niches. We followed the oral and gut microbiomes in 66 individuals from before, immediately after, and up to 12 months after exposure to different antibiotic classes. The salivary microbiome recovered quickly and was surprisingly robust toward antibiotic-induced disturbance. The fecal microbiome was severely affected by most antibiotics: for months, health-associated butyrate-producing species became strongly underrepresented. Additionally, there was an enrichment of genes associated with antibiotic resistance. Clearly, even a single antibiotic treatment in healthy individuals contributes to the risk of resistance development and leads to long-lasting detrimental shifts in the gut microbiome.

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Monosodium Glutamate Induces Changes in Hepatic and Renal Metabolic Profiles and Gut Microbiome of Wistar Rats

Nutrients ◽

10.3390/nu13061865 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1865

Author(s):

Kanokwan Nahok ◽

Jutarop Phetcharaburanin ◽

Jia V. Li ◽

Atit Silsirivanit ◽

Raynoo Thanan ◽

...

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

16S Rrna Gene ◽

Gut Microbiome ◽

Wistar Rats ◽

Monosodium Glutamate ◽

16S Rrna Gene Sequencing ◽

Rrna Gene ◽

Male Wistar Rats ◽

The Impact

The short- and long-term consumption of monosodium glutamate (MSG) increases urinary pH but the effects on the metabolic pathways in the liver, kidney and the gut microbiota remain unknown. To address this issue, we investigated adult male Wistar rats allocated to receive drinking water with or without 1 g% MSG for 2 weeks (n = 10, each). We performed a Nuclear Magnetic Resonance (NMR) spectroscopy-based metabolomic study of the jejunum, liver, and kidneys, while faecal samples were collected for bacterial DNA extraction to investigate the gut microbiota using 16S rRNA gene sequencing. We observed significant changes in the liver of MSG-treated rats compared to controls in the levels of glucose, pyridoxine, leucine, isoleucine, valine, alanine, kynurenate, and nicotinamide. Among kidney metabolites, the level of trimethylamine (TMA) was increased, and pyridoxine was decreased after MSG-treatment. Sequencing of the 16S rRNA gene revealed that MSG-treated rats had increased Firmicutes, the gut bacteria associated with TMA metabolism, along with decreased Bifidobacterium species. Our data support the impact of MSG consumption on liver and kidney metabolism. Based on the gut microbiome changes, we speculate that TMA and its metabolites such as trimethylamine-N-oxide (TMAO) may be mediators of the effects of MSG on the kidney health.

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Microbiome of Odontogenic Abscesses

Microorganisms ◽

10.3390/microorganisms9061307 ◽

2021 ◽

Vol 9 (6) ◽

pp. 1307

Author(s):

Sebastian Böttger ◽

Silke Zechel-Gran ◽

Daniel Schmermund ◽

Philipp Streckbein ◽

Jan-Falco Wilbrand ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Oral Microbiome ◽

Minor Role ◽

Rrna Gene ◽

Sequencing Analysis ◽

Bacterial Strains ◽

16S Rrna Gene Analysis ◽

Odontogenic Infections ◽

Odontogenic Abscess

Severe odontogenic abscesses are regularly caused by bacteria of the physiological oral microbiome. However, the culture of these bacteria is often prone to errors and sometimes does not result in any bacterial growth. Furthermore, various authors found completely different bacterial spectra in odontogenic abscesses. Experimental 16S rRNA gene next-generation sequencing analysis was used to identify the microbiome of the saliva and the pus in patients with a severe odontogenic infection. The microbiome of the saliva and the pus was determined for 50 patients with a severe odontogenic abscess. Perimandibular and submandibular abscesses were the most commonly observed diseases at 15 (30%) patients each. Polymicrobial infections were observed in 48 (96%) cases, while the picture of a mono-infection only occurred twice (4%). On average, 31.44 (±12.09) bacterial genera were detected in the pus and 41.32 (±9.00) in the saliva. In most cases, a predominantly anaerobic bacterial spectrum was found in the pus, while saliva showed a similar oral microbiome to healthy individuals. In the majority of cases, odontogenic infections are polymicrobial. Our results indicate that these are mainly caused by anaerobic bacterial strains and that aerobic and facultative anaerobe bacteria seem to play a more minor role than previously described by other authors. The 16S rRNA gene analysis detects significantly more bacteria than conventional methods and molecular methods should therefore become a part of routine diagnostics in medical microbiology.

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Exploring protocol bias in airway microbiome studies: one versus two PCR steps and 16S rRNA gene region V3 V4 versus V4

BMC Genomics ◽

10.1186/s12864-020-07252-z ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Christine Drengenes ◽

Tomas M. L. Eagan ◽

Ingvild Haaland ◽

Harald G. Wiker ◽

Rune Nielsen

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Bacterial Load ◽

Marker Gene ◽

Gene Region ◽

Lower Airway ◽

Rrna Gene ◽

Wide Range ◽

Airway Microbiome ◽

The Impact

Abstract Background Studies on the airway microbiome have been performed using a wide range of laboratory protocols for high-throughput sequencing of the bacterial 16S ribosomal RNA (16S rRNA) gene. We sought to determine the impact of number of polymerase chain reaction (PCR) steps (1- or 2- steps) and choice of target marker gene region (V3 V4 and V4) on the presentation of the upper and lower airway microbiome. Our analyses included lllumina MiSeq sequencing following three setups: Setup 1 (2-step PCR; V3 V4 region), Setup 2 (2-step PCR; V4 region), Setup 3 (1-step PCR; V4 region). Samples included oral wash, protected specimen brushes and protected bronchoalveolar lavage (healthy and obstructive lung disease), and negative controls. Results The number of sequences and amplicon sequence variants (ASV) decreased in order setup1 > setup2 > setup3. This trend appeared to be associated with an increased taxonomic resolution when sequencing the V3 V4 region (setup 1) and an increased number of small ASVs in setups 1 and 2. The latter was considered a result of contamination in the two-step PCR protocols as well as sequencing across multiple runs (setup 1). Although genera Streptococcus, Prevotella, Veillonella and Rothia dominated, differences in relative abundance were observed across all setups. Analyses of beta-diversity revealed that while oral wash samples (high biomass) clustered together regardless of number of PCR steps, samples from the lungs (low biomass) separated. The removal of contaminants identified using the Decontam package in R, did not resolve differences in results between sequencing setups. Conclusions Differences in number of PCR steps will have an impact of final bacterial community descriptions, and more so for samples of low bacterial load. Our findings could not be explained by differences in contamination levels alone, and more research is needed to understand how variations in PCR-setups and reagents may be contributing to the observed protocol bias.

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Clinical Relevance of the Microbiome in Odontogenic Abscesses

Biology ◽

10.3390/biology10090916 ◽

2021 ◽

Vol 10 (9) ◽

pp. 916

Author(s):

Sebastian Böttger ◽

Silke Zechel-Gran ◽

Daniel Schmermund ◽

Philipp Streckbein ◽

Jan-Falco Wilbrand ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Oral Microbiome ◽

Molecular Methods ◽

Gene Analysis ◽

Rrna Gene ◽

16S Rrna Gene Analysis ◽

Cultural Methods ◽

Odontogenic Abscess ◽

Polymicrobial Infections

Odontogenic abscesses are usually caused by bacteria of the oral microbiome. However, the diagnostic culture of these bacteria is often prone to errors and sometimes fails completely due to the fastidiousness of the relevant bacterial species. The question arises whether additional pathogen diagnostics using molecular methods provide additional benefits for diagnostics and therapy. Experimental 16S rRNA gene analysis with next-generation sequencing (NGS) and bioinformatics was used to identify the microbiome of the pus in patients with severe odontogenic infections and was compared to the result of standard diagnostic culture. The pus microbiome was determined in 48 hospitalized patients with a severe odontogenic abscess in addition to standard cultural pathogen detection. Cultural detection was possible in 41 (85.42%) of 48 patients, while a pus-microbiome could be determined in all cases. The microbiomes showed polymicrobial infections in 46 (95.83%) cases, while the picture of a mono-infection occurred only twice (4.17%). In most cases, a predominantly anaerobic spectrum with an abundance of bacteria was found in the pus-microbiome, while culture detected mainly Streptococcus, Staphylococcus, and Prevotella spp. The determination of the microbiome of odontogenic abscesses clearly shows a higher number of bacteria and a significantly higher proportion of anaerobes than classical cultural methods. The 16S rRNA gene analysis detects considerably more bacteria than conventional cultural methods, even in culture-negative samples. Molecular methods should be implemented as standards in medical microbiology diagnostics, particularly for the detection of polymicrobial infections with a predominance of anaerobic bacteria.

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Partial Sequencing of 16S rRNA Gene of Selected Staphylococcus aureus Isolates and its Antibiotic Resistance

Media Peternakan ◽

10.5398/medpet.2016.39.2.67 ◽

2016 ◽

Vol 39 (2) ◽

pp. 67-74

Author(s):

H. D. Kusumaningrum ◽

L. Handayani ◽

R. Novrianti

Keyword(s):

Staphylococcus Aureus ◽

Antibiotic Resistance ◽

16S Rrna ◽

16S Rrna Gene ◽

Rrna Gene ◽

Partial Sequencing

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Soil aggregate-based nucleic acid analyses of the impact of maize roots and their root hairs on the structural diversity of microbial communities

10.5194/egusphere-egu21-7620 ◽

2021 ◽

Author(s):

Christoph Tebbe ◽

Damini Damini ◽

Damien Finn ◽

Nataliya Bilyera ◽

Minh Ganther ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Root Hair ◽

Soil Aggregates ◽

Root Hairs ◽

Soil Samples ◽

Plant Roots ◽

Bulk Soil ◽

Rrna Gene ◽

The Impact

The deposition of energy rich carbon sources released by plant roots during their growth fuels microbially driven ecosystem processes in soil, but there is a lack of understanding how microorganisms interact and collaborate. The objective of this research was therefore to characterize microbial networks as they assemble under the influence of plant roots. To identify the specific importance of root hairs, we compared the impact of a maize wild-type to a root-air defective mutant (rth3; (1).The microbial community structure was analyzed by qPCR and 16S rRNA gene amplicon sequencing from soil DNA. In order to increase the probability of detecting truly interacting microbial partners as a basis for network analyses, we first evaluated a new protocol to obtain DNA from as little as 1 mg instead of the usual 250 mg soil samples, thereby approaching the aggregate level (2). While the diversity of bacterial 16S rRNA gene amplicons of 250-mg samples taken from the same soil was not distinct, DNA analyses from individual aggregates clearly differed from each other underlining that soil aggregates represent distinct microbial habitats.Soil column experiments with maize grown in a loam soil (3) revealed distinct communities between rhizosphere and bulk soil. The community composition of individual aggregates showed more differences in bulk soil compared to rhizosphere. Less elaborated networks were seen in bulk soil and a profound effect of root hairs could be unravelled. Null model testing demonstrated that Actinobacteria were equally important for network connectivity independent of the root hair mutation, but for networks of the wildtype, Acidobacteria were essential for synergistic interactions and overall network structure. In contrast, Proteobacteria and Firmicutes connectivity became more important. The observed differences in community composition and interactions suggests carbon cycling, and perhaps other microbially-driven functions, are markedly affected by the presence of root hairs.Utilizing maize root soil microcosms for studying soil zymography in the rhizosphere allowed to obtain soil samples from regions with distinct specific enzyme activities. In order to enhance the detection of actively metabolizing bacterial community members, we studied rRNA sequences and compared it to rRNA gene sequences from the same samples. Currently the data are under analysis.References(1) Wen, T-J, Schnable PS (1994) Analyses of mutants of three genes that influence root hair development in Zea mays (Gramineae) suggest that root hairs are dispensable. Am. J. Bot. 81, 833&#8211;842.(2) Szoboszlay M, Tebbe CC (2020) Hidden heterogeneity and co-occurrence networks of soil prokaryotic communities revealed at the scale of individual soil aggregates. Microbiol. Open, e1144. DOI: 10.1002/mbo3.1144(3) Vetterlein D et al. (2020) Experimental platforms for the investigation of spatiotemporal patterns in the rhizosphere &#8211; laboratory and field scale. J. Plant Nutr. Soil Sci., 000, 1&#8211;16 DOI: 10.1002/jpln.202000079

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The Impact of Primer Design on Amplicon-Based Metagenomic Profiling Accuracy: Detailed Insights into Bifidobacterial Community Structure

Microorganisms ◽

10.3390/microorganisms8010131 ◽

2020 ◽

Vol 8 (1) ◽

pp. 131 ◽

Cited By ~ 6

Author(s):

Leonardo Mancabelli ◽

Christian Milani ◽

Gabriele Andrea Lugli ◽

Federico Fontana ◽

Francesca Turroni ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

In Silico ◽

In Silico Analysis ◽

Amplification Efficiency ◽

Rrna Gene ◽

Test Case ◽

Bacterial Populations ◽

Taxonomic Marker ◽

The Impact

Next Generation Sequencing (NGS) technologies have overcome the limitations of cultivation-dependent approaches and allowed detailed study of bacterial populations that inhabit the human body. The consortium of bacteria residing in the human intestinal tract, also known as the gut microbiota, impacts several physiological processes important for preservation of the health status of the host. The most widespread microbiota profiling method is based on amplification and sequencing of a variable portion of the 16S rRNA gene as a universal taxonomic marker among members of the Bacteria domain. Despite its popularity and obvious advantages, this 16S rRNA gene-based approach comes with some important limitations. In particular, the choice of the primer pair for amplification plays a major role in defining the accuracy of the reconstructed bacterial profiles. In the current study, we performed an in silico PCR using all currently described 16S rRNA gene-targeting primer pairs (PP) in order to assess their efficiency. Our results show that V3, V4, V5, and V6 were the optimal regions on which to design 16S rRNA metagenomic primers. In detail, PP39 (Probio_Uni/Probio_Rev), PP41 (341F/534R), and PP72 (970F/1050R) were the most suitable primer pairs with an amplification efficiency of >98.5%. Furthermore, the Bifidobacterium genus was examined as a test case for accurate evaluation of intra-genus performances at subspecies level. Intriguingly, the in silico analysis revealed that primer pair PP55 (527f/1406r) was unable to amplify the targeted region of any member of this bacterial genus, while several other primer pairs seem to rather inefficiently amplify the target region of the main bifidobacterial taxa. These results highlight that selection of a 16S rRNA gene-based PP should be done with utmost care in order to avoid biases in microbiota profiling results.

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Correction: 16S rRNA gene sequencing and healthy reference ranges for 28 clinically relevant microbial taxa from the human gut microbiome

PLoS ONE ◽

10.1371/journal.pone.0212474 ◽

2019 ◽

Vol 14 (2) ◽

pp. e0212474 ◽

Cited By ~ 1

Author(s):

Daniel E. Almonacid ◽

Laurens Kraal ◽

Francisco J. Ossandon ◽

Yelena V. Budovskaya ◽

Juan Pablo Cardenas ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Gut Microbiome ◽

Gene Sequencing ◽

16S Rrna Gene Sequencing ◽

Rrna Gene ◽

Reference Ranges ◽

Human Gut ◽

Human Gut Microbiome ◽

Rrna Gene Sequencing

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Effects of Antibiotics on the Bacterial Community, Metabolic Functions and Antibiotic Resistance Genes in Mariculture Sediments during Enrichment Culturing

Journal of Marine Science and Engineering ◽

10.3390/jmse8080604 ◽

2020 ◽

Vol 8 (8) ◽

pp. 604

Author(s):

Meng-Qi Ye ◽

Guan-Jun Chen ◽

Zong-Jun Du

Keyword(s):

Antibiotic Resistance ◽

Bacterial Community ◽

16S Rrna ◽

16S Rrna Gene ◽

High Throughput ◽

Antibiotic Resistance Genes ◽

Control Group ◽

Rrna Gene ◽

Metabolic Functions ◽

Culture Dependent

The effect of antibiotics on the diversity and functioning of indigenous microorganisms in the environment has attracted much attention. In this study, effects of exposure to six different antibiotics on the bacterial community, metabolic functions and antibiotic resistance genes (ARGs) in marine sediments during enrichment culturing were investigated. Classical culture-dependent method and high-throughput 16S rRNA gene sequencing method were both applied. In the culture-dependent analysis, the obtained 1549 isolates belonged to four phyla (Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria) and 155 genera. Proteobacteria and Firmicutes were the dominant phyla. The diversity and abundance of obtained bacteria after antibiotic processing exhibited different degrees of decrease. Enrichment culturing for different time could also affect the bacterial community composition. Some genera of bacteria were not isolated in the control group, but they could be isolated in the antibiotic-treated groups. In high-throughput 16S rRNA gene amplicon sequencing analyses, all the effective reads were clustered into 2822 OTUs at 97% similarity cutoff; they were annotated to 49 phyla, 103 class, 220 orders, 347 families, 624 genera and 1122 species. An alpha diversity analysis indicated that the community diversity and richness decreased under antibiotic exposure. The changes at the genus level were much more obvious. Only 48 genera of 129 genera were shared by all the samples. A total of 29 genera which were not detected in the initial control sample could be detected in at least one antibiotic-treated group. SIMPER analysis showed that OTU2543 and OTU1450 were the most common taxa to the dissimilarity of bacterial community between antibiotic-treated groups and the control group. OTU2034 and OUT2543 were the most contributive taxa to dissimilarity of groups incubating for different time. Metabolism was the predominant bacterial function. A total of 30 ARGs were detected in the samples. This study mainly focused on the changes of microbiota under the selective pressure of antibiotics for different time and the results demonstrated that the antibiotic could affect the bacterial diversity and richness in the marine ecosystem.

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