Early nasal microbiota and acute respiratory infections during the first years of life

BackgroundEmerging evidence shows that airway microbiota may modulate local immune responses, thereby contributing to the susceptibility and severity of acute respiratory infections (ARIs). However, there are little data on the longitudinal relationships between airway microbiota and susceptibility to ARIs in children.ObjectiveWe aimed to investigate the association of early nasal microbiota and the subsequent risk of ARIs during the first years of life.MethodsIn this prospective population-based birth-cohort study in Finland, we followed 839 healthy infants for ARIs from birth to age 24 months. Nasal microbiota was tested using 16S rRNA gene sequencing at age 2 months. We applied an unsupervised clustering approach to identify early nasal microbiota profiles, and examined the association of profiles with the rate of ARIs during age 2–24 months.ResultsWe identified five nasal microbiota profiles dominated by Moraxella, Streptococcus, Dolosigranulum, Staphylococcus and Corynebacteriaceae, respectively. Incidence rate of ARIs was highest in children with an early Moraxella-dominant profile and lowest in those with a Corynebacteriaceae-dominant profile (738 vs 552/100 children years; unadjusted incidence rate ratio (IRR), 1.34; 95% CI 1.16 to 1.54; p < 0.001). After adjusting for nine potential confounders, the Moraxella-dominant profile-ARI association persisted (adjusted IRR (aIRR), 1.19; 95% CI 1.04 to 1.37; p = 0.01). Similarly, the incidence rate of lower respiratory tract infections (a subset of all ARIs) was significantly higher in children with an early Moraxella-dominant profile (aIRR, 2.79; 95% CI 1.04 to 8.09; p = 0.04).ConclusionMoraxella-dominant nasal microbiota profile in early infancy was associated with an increased rate of ARIs during the first 2 years of life.

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Necessity of 16S rRNA gene sequencing for identifying Haemophilus parainfluenzae-like strains associated with opportunistic urinary tract infections

Journal of Medical Microbiology ◽

10.1099/jmm.0.071803-0 ◽

2014 ◽

Vol 63 (6) ◽

pp. 805-811 ◽

Cited By ~ 4

Author(s):

Siu-Kei Chow ◽

Jill E. Clarridge

Keyword(s):

Urinary Tract ◽

16S Rrna ◽

16S Rrna Gene ◽

Urinary Tract Infections ◽

Gene Sequencing ◽

16S Rrna Gene Sequencing ◽

Rrna Gene ◽

Haemophilus Parainfluenzae ◽

Rrna Gene Sequencing ◽

Tract Infections

The identification of Haemophilus spp. from urogenital sites can be challenging due to the lack of appropriate media for culturing the organisms and the poor resolution of biochemical methods. By incorporating chocolate agar and 16S rRNA gene sequence analysis in our protocol to identify Haemophilus spp. from urinary specimens, we isolated and characterized 30 genetically homogeneous strains of a cryptic species that is phylogenetically close to, but distinct from, Haemophilus parainfluenzae. Commercial biochemical kits and VITEK 2 could not distinguish between the two species. Over 90 % of the strains were isolated from urine and the urogenital area, made possible with the inclusion of chocolate agar in our urine culture protocol. In contrast, no Haemophilus strains isolated from respiratory specimens were identified as the cryptic genospecies. The cryptic genospecies was associated with urinary tract infections (UTIs) in certain patient populations. Distinct from Haemophilus quentinii that also causes urogenital infection, the cryptic genospecies required V factor (NAD) but not X factor (haemin) to grow. The data indicated that 16S rRNA gene sequencing may be necessary in identifying Haemophilus species and that inaccurate categorization of Haemophilus strains isolated from urogenital specimens based on phenotypic characteristics may prevent accurate diagnosis of UTIs.

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Comparison of Illumina versus Nanopore 16S rRNA Gene Sequencing of the Human Nasal Microbiota

Genes ◽

10.3390/genes11091105 ◽

2020 ◽

Vol 11 (9) ◽

pp. 1105 ◽

Cited By ~ 1

Author(s):

Astrid P. Heikema ◽

Deborah Horst-Kreft ◽

Stefan A. Boers ◽

Rick Jansen ◽

Saskia D. Hiltemann ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Gene Sequencing ◽

16S Rrna Gene Sequencing ◽

Rrna Gene ◽

Nanopore Sequencing ◽

Oxford Nanopore ◽

Rrna Gene Sequencing ◽

Oxford Nanopore Technologies ◽

Nasal Microbiota

Illumina and nanopore sequencing technologies are powerful tools that can be used to determine the bacterial composition of complex microbial communities. In this study, we compared nasal microbiota results at genus level using both Illumina and nanopore 16S rRNA gene sequencing. We also monitored the progression of nanopore sequencing in the accurate identification of species, using pure, single species cultures, and evaluated the performance of the nanopore EPI2ME 16S data analysis pipeline. Fifty-nine nasal swabs were sequenced using Illumina MiSeq and Oxford Nanopore 16S rRNA gene sequencing technologies. In addition, five pure cultures of relevant bacterial species were sequenced with the nanopore sequencing technology. The Illumina MiSeq sequence data were processed using bioinformatics modules present in the Mothur software package. Albacore and Guppy base calling, a workflow in nanopore EPI2ME (Oxford Nanopore Technologies—ONT, Oxford, UK) and an in-house developed bioinformatics script were used to analyze the nanopore data. At genus level, similar bacterial diversity profiles were found, and five main and established genera were identified by both platforms. However, probably due to mismatching of the nanopore sequence primers, the nanopore sequencing platform identified Corynebacterium in much lower abundance compared to Illumina sequencing. Further, when using default settings in the EPI2ME workflow, almost all sequence reads that seem to belong to the bacterial genus Dolosigranulum and a considerable part to the genus Haemophilus were only identified at family level. Nanopore sequencing of single species cultures demonstrated at least 88% accurate identification of the species at genus and species level for 4/5 strains tested, including improvements in accurate sequence read identification when the basecaller Guppy and Albacore, and when flowcell versions R9.4 (Oxford Nanopore Technologies—ONT, Oxford, UK) and R9.2 (Oxford Nanopore Technologies—ONT, Oxford, UK) were compared. In conclusion, the current study shows that the nanopore sequencing platform is comparable with the Illumina platform in detection bacterial genera of the nasal microbiota, but the nanopore platform does have problems in detecting bacteria within the genus Corynebacterium. Although advances are being made, thorough validation of the nanopore platform is still recommendable.

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Alterations of Thyroid Microbiota Across Different Thyroid Microhabitats in Patients With Thyroid Carcinoma

10.21203/rs.3.rs-967650/v1 ◽

2021 ◽

Author(s):

Daofeng Dai ◽

Yang Yan ◽

Yong Yang ◽

Tianfeng Dang ◽

Jiansheng Xiao ◽

...

Keyword(s):

Thyroid Carcinoma ◽

Incidence Rate ◽

Area Under The Curve ◽

Gene Sequencing ◽

16S Rrna Gene Sequencing ◽

Rrna Gene ◽

The Core ◽

Node Metastasis ◽

Tumor Tissues ◽

Rrna Gene Sequencing

Abstract Background: In recent years, the incidence rate of Thyroid carcinoma(TC) has been increasing worldwide. Thus, research on factors of TC carcinogenesis may promote TC prevention and decrease the incidence rate. There are several studies targeting the correlation between gut microbiota and thyroid disease. Carcinogenesis of several malignancies is influenced by microbiota. However, thyroid microbiome of TC has not been revealed. This study investigated thyroid microbiota in different TC microhabitats. Methods: We performed 16s rRNA gene sequencing using tumor tissues and matched peritumor tissues from 30 patients with TC to characterize thyroid microbiota. Results: The richness and diversity of thyroid microbiota were lower in TC tumor samples than in matched peritumor tissues. At the genus level, the core microbiota of thyroid included Sphingomonas, Comamonas, Acinetobacter, Pseudomonas, Microvirgula, and Soonwooa. The abundance of Sphingomonas and Aeromonas was significantly increased in tumor tissues, while the abundance of Comamonas, Acinetobacter, and Peptostreptococcus was significantly enhanced in peritumor tissues. The combination of Comamonas and Sphingomonas could discriminate tumor samples from peritumor samples with an area under the curve (AUC) of 0.981 (95% confidence interval [CI]: 0.949-1.000). The abundance of Sphingomonas was significantly higher in N1 stage than in N0 stage. Sphingomonas could distinguish between N0 and N1 stage with an AUC of 0.964 (95% CI: 0.907-1.000).Conclusions: The microbial diversity and composition were significantly different between peritumor and tumor microhabitats from patients with TC, which may eventually affect TC carcinogenesis and progression. The combination of Comamonas and Sphingomonas could serve as a powerful biomarker for discrimination between tumor and peritumor tissues. Furthermore, the higher abundance of Sphingomonas was correlated with lymph node metastasis, indicating that it may play a role in promoting TC progression.

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Heterogeneity of Moraxella isolates found in the nasal cavities of piglets

10.21203/rs.2.17211/v2 ◽

2019 ◽

Author(s):

Sergi López-Serrano ◽

Nuria Galofré-Milà ◽

Mar Costa-Hurtado ◽

Ana M. Pérez-de-Rozas ◽

Virginia Aragon

Keyword(s):

New Species ◽

16S Rrna Gene Sequencing ◽

Phenotypic Characterization ◽

Rrna Gene ◽

Pathogenic Potential ◽

Epithelial Cell Lines ◽

Nasal Swabs ◽

Rrna Gene Sequencing ◽

Nasal Microbiota

Abstract Background: Previous studies have shown that the genus Moraxella is commonly present in the nasal microbiota of swine. Results: In this study, 51 isolates of Moraxella were obtained from nasal swabs from 3-4 week old piglets, which represented 26 different fingerprintings by enterobacterial repetitive intergenic consensus (ERIC)-PCR. Whole 16S rRNA gene sequencing allowed the identification at species level of the Moraxella spp. isolates. The majority of the field strains were identified as Moraxella pluranimalium, but Moraxella porci was also detected. In addition, a cluster of 7 strains did not group with any described Moraxella species, probably representing a new species. Subsequent phenotypic characterization indicated that strains of Moraxella pluranimalium were mainly sensitive to serum complement, while the cluster representing the putative new species was highly resistant. Biofilm formation capacity was very variable among the Moraxella spp. isolates, while adherence to epithelial cell lines was similar among selected strains. Additionally, variability was also observed in the association of selected strains to porcine alveolar macrophages. Antimicrobial tests evidenced the existence of multidrug-resistance in the strains. Conclusions : In summary, phenotypic characterization revealed heterogeneity among Moraxella strains from the nasal cavity of piglets. Strains with pathogenic potential were detected as well as those that may be commensal members of the nasal microbiota. However, the role of Moraxella in porcine diseases and health should be further evaluated.

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SCFA producing bacteria shape the subtype of ADHD in children

10.21203/rs.2.16337/v1 ◽

2019 ◽

Author(s):

Chaonan Fan ◽

Shijie Li ◽

Rui Wang ◽

Xiuqin Fan ◽

Aiming Liang ◽

...

Keyword(s):

Gut Microbiota ◽

Chromatographic Analysis ◽

Gene Sequencing ◽

16S Rrna Gene Sequencing ◽

Short Chain Fatty Acids ◽

Population Based ◽

Rrna Gene ◽

Adhd Subtypes ◽

Adhd Children ◽

Rrna Gene Sequencing

Abstract There is little data on population-based identification of the gut microbiota with ADHD subtypes in children, yet whether the degree ADHD is characterized by short-chain fatty acids (SCFAs) remains unclear. We enrolled 59 ADHD children including 21 inattentive subtypes (ADHD-I), 20 combined subtypes (ADHD-C), 18 hyperactive-Impulsive subtypes (ADHD-H) and 23 healthy controls. The microbiota was characterized by 16S rRNA gene sequencing, and SCFA concentrations were determined by gas chromatographic analysis. Compared to the controls, we observed a decrease of 14 genera belonging to Ruminococcaceae, Lachnospiraceae, Verrucomicrobiaceae and Rikenellaceae family in ADHD-I, while Megamonas, Coprococcus_2 and Paraprevotella were significantly increased in ADHD-C. In addition, a lower abundance of Faecalibacterium, and a higher proportion of Marvinbryantia, Intestinimonas, Prevotella_9 and Eggerthella were detected in the ADHD-H. Analysis of fecal SCFAs showed that elevated levels of acetate and propionate were in ADHD subtypes. Furthermore, most of the bacterium associated with SCFAs overlapped with the differential bacterium in ADHD subtypes. Conclusion: Our data support the clinical distinction among different ADHD subtypes in children may also be reflected in alterations of specific gut microbiota, most of which are SCFA producing bacteria.

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How can microbial population genomics inform community ecology?

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2019.0253 ◽

2020 ◽

Vol 375 (1798) ◽

pp. 20190253 ◽

Cited By ~ 3

Author(s):

David VanInsberghe ◽

Philip Arevalo ◽

Diana Chien ◽

Martin F. Polz

Keyword(s):

Gene Flow ◽

Community Ecology ◽

Population Genomics ◽

16S Rrna Gene Sequencing ◽

Population Based ◽

Rrna Gene ◽

Alternative Measure ◽

Ribosomal Protein Genes ◽

Contemporary Gene Flow ◽

Rrna Gene Sequencing

Populations are fundamental units of ecology and evolution, but can we define them for bacteria and archaea in a biologically meaningful way? Here, we review why population structure is difficult to recognize in microbes and how recent advances in measuring contemporary gene flow allow us to identify clearly delineated populations among collections of closely related genomes. Such structure can arise from preferential gene flow caused by coexistence and genetic similarity, defining populations based on biological mechanisms. We show that such gene flow units are sufficiently genetically isolated for specific adaptations to spread, making them also ecological units that are differentially adapted compared to their closest relatives. We discuss the implications of these observations for measuring bacterial and archaeal diversity in the environment. We show that operational taxonomic units defined by 16S rRNA gene sequencing have woefully poor resolution for ecologically defined populations and propose monophyletic clusters of nearly identical ribosomal protein genes as an alternative measure for population mapping in community ecological studies employing metagenomics. These population-based approaches have the potential to provide much-needed clarity in interpreting the vast microbial diversity in human and environmental microbiomes. This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’.

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Alterations of thyroid microbiota across different thyroid microhabitats in patients with thyroid carcinoma

Journal of Translational Medicine ◽

10.1186/s12967-021-03167-9 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Daofeng Dai ◽

Yan Yang ◽

Yong Yang ◽

Tianfeng Dang ◽

Jiansheng Xiao ◽

...

Keyword(s):

Thyroid Carcinoma ◽

Incidence Rate ◽

Area Under The Curve ◽

Gene Sequencing ◽

16S Rrna Gene Sequencing ◽

Rrna Gene ◽

The Core ◽

Node Metastasis ◽

Tumor Tissues ◽

Rrna Gene Sequencing

Abstract Background In recent years, the incidence rate of Thyroid carcinoma (TC) has been increasing worldwide. Thus, research on factors of TC carcinogenesis may promote TC prevention and decrease the incidence rate. There are several studies targeting the correlation between gut microbiota and thyroid disease. Carcinogenesis of several malignancies is influenced by microbiota. However, thyroid microbiome of TC has not been revealed. This study investigated thyroid microbiota in different TC microhabitats. Methods We performed 16s rRNA gene sequencing using tumor tissues and matched peritumor tissues from 30 patients with TC to characterize thyroid microbiota. Results The richness and diversity of thyroid microbiota were lower in TC tumor samples than in matched peritumor tissues. At the genus level, the core microbiota of thyroid included Sphingomonas, Comamonas, Acinetobacter, Pseudomonas, Microvirgula, and Soonwooa. The abundance of Sphingomonas and Aeromonas was significantly increased in tumor tissues, while the abundance of Comamonas, Acinetobacter, and Peptostreptococcus was significantly enhanced in peritumor tissues. The combination of Comamonas and Sphingomonas could discriminate tumor samples from peritumor samples with an area under the curve (AUC) of 0.981 (95% confidence interval [CI] 0.949–1.000). The abundance of Sphingomonas was significantly higher in N1 stage than in N0 stage. Sphingomonas could distinguish between N0 and N1 stage with an AUC of 0.964 (95% CI 0.907–1.000). Conclusions The microbial diversity and composition were significantly different between peritumor and tumor microhabitats from patients with TC, which may eventually affect TC carcinogenesis and progression. The combination of Comamonas and Sphingomonas could serve as a powerful biomarker for discrimination between tumor and peritumor tissues. Furthermore, the higher abundance of Sphingomonas was correlated with lymph node metastasis, indicating that the abundance of Sphingomonas may indicate a poor prognosis for TC patients, and Sphingomonas may play a role in promoting TC progression.

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Heterogeneity of Moraxella isolates found in the nasal cavities of piglets

10.21203/rs.2.17211/v1 ◽

2019 ◽

Author(s):

Sergi López-Serrano ◽

Nuria Galofré-Milà ◽

Mar Costa-Hurtado ◽

Ana M. Pérez-de-Rozas ◽

Virginia Aragon

Keyword(s):

New Species ◽

16S Rrna Gene Sequencing ◽

Phenotypic Characterization ◽

Rrna Gene ◽

Pathogenic Potential ◽

Epithelial Cell Lines ◽

Nasal Swabs ◽

Rrna Gene Sequencing ◽

Nasal Microbiota

Abstract Previous studies have shown that the genus Moraxella is commonly present in the nasal microbiota of swine. In this study, 51 isolates of Moraxella were obtained from nasal swabs from 3-4 week old piglets, which represented 26 different fingerprintings by enterobacterial repetitive intergenic consensus (ERIC)-PCR. Whole 16S rRNA gene sequencing allowed the identification at species level of the Moraxella spp. isolates. The majority of the field strains were identified as Moraxella pluranimalium, but Moraxella porci was also detected. In addition, a cluster of 7 strains did not group with any described Moraxella species, probably representing a new species. Subsequent phenotypic characterization indicated that strains of Moraxella pluranimalium were mainly sensitive to the serum complement, while the cluster representing the putative new species was highly resistant. Biofilm formation capacity was very variable among the Moraxella spp. isolates, while adherence to epithelial cell lines was similar among selected strains. Additionally, selected strains were tested in phagocytosis assays and again variability was observed in the susceptibility to alveolar macrophages. Antimicrobial tests evidenced the existence of multidrug-resistance in the strains. In summary, phenotypic characterization revealed heterogeneity among Moraxella strains from the nasal cavity of piglets. Strains with pathogenic potential were detected as well as those that may be commensal members of the nasal microbiota. However, the role of Moraxella in porcine diseases and health should be further evaluated.

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Nasal microbiota exhibit neither reproducible nor orderly dynamics following rhinoviral infection

10.1101/2020.04.11.20061911 ◽

2020 ◽

Author(s):

Sai N. Nimmagadda ◽

Firas S. Midani ◽

Heather Durand ◽

Aspen T. Reese ◽

Caitlin C. Murdoch ◽

...

Keyword(s):

Hypervariable Region ◽

Alpha Diversity ◽

16S Rrna Gene Sequencing ◽

Rrna Gene ◽

Upper Respiratory Tract ◽

Healthy Human ◽

Human Volunteers ◽

Before And After ◽

Rrna Gene Sequencing ◽

Nasal Microbiota

ABSTRACTBackgroundHow human-associated microbial communities resist and respond to perturbations remains incompletely understood. Viral challenge provides one opportunity to test how human microbiota respond to disturbance.MethodsUsing an experimental human rhinovirus infection challenge model, we explored how viral infection may alter microbiota of the upper respiratory tract (URT). Healthy human volunteers were inoculated with HRV serotype 39. Samples were collected by lavage before and after inoculation from healthy (sham inoculated, n=7) and infected (n=15) individuals and subjected to 16S rRNA gene sequencing through amplification of the V4 hypervariable region.ResultsNo evidence for differences in community alpha-diversity between cohorts was observed. The composition of microbiota of sham-treated and infected subjects did not appear distinguishable and no taxa were significantly associated with infection status. We did not observe support for a correlation between microbial dynamics and counts of specific monocytes. Subject identity was found to be the strongest determinant of community structure in our dataset.ConclusionsOverall, our findings do not suggest a consistent nasopharyngeal microbiota response to rhinovirus challenge. We support the conclusion that this microbial community is individualized. Broadly, our findings contribute to our understanding of how and when immune responses to viruses affect bacterial communities in the URT.

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Aerococcus urinae in Urinary Tract Infections

Journal of Clinical Microbiology ◽

10.1128/jcm.38.4.1703-1705.2000 ◽

2000 ◽

Vol 38 (4) ◽

pp. 1703-1705 ◽

Cited By ~ 38

Author(s):

Qing Zhang ◽

Christopher Kwoh ◽

Silvia Attorri ◽

Jill E. Clarridge

Keyword(s):

Urinary Tract ◽

16S Rrna Gene Sequencing ◽

Fatty Acid Analysis ◽

Rrna Gene ◽

Elderly Males ◽

Aerococcus Urinae ◽

Potential Pathogen ◽

Rrna Gene Sequencing ◽

Biochemical Testing ◽

Tract Infections

Aerococcus urinae is a rarely reported pathogen, possibly due to difficulties in the identification of the organism.A. urinae is a gram-positive coccus that grows in pairs and clusters, produces alpha-hemolysis on blood agar, and is negative for catalase and pyrrolidonyl aminopeptidase. Some of these characteristics and its being absent from the databases of most commercial identification systems could allow A. urinae to be misidentified as a streptococcus, enterococcus, or staphylococcus. We report two cases of urinary tract infection (UTI) caused by A. urinae and characterize these isolates by morphology, biochemical testing, whole-cell fatty acid analysis, 16S rRNA gene sequencing, and antibiotic susceptibilities. Most patients infected with A. urinae are elderly males with predisposing conditions who present initially with UTI. Because A. urinae is resistant to sulfonamides, treatment could be inappropriate, with infections resulting in serious complications, including death. It is important for the clinician and the microbiologist to consider A. urinae a potential pathogen and proceed with thorough microbiological identification.

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