Microbial community networks across body sites are associated with susceptibility to respiratory infections in infants

A novel robust network construction and analysis workflow for mining infant microbiota relationships

The gut microbiota plays a crucial role in infant health, with its development during the first 1,000 days influencing health outcomes. Understanding the relationships within the microbiota is essential to linking its maturation process to these outcomes. Several network-based methods have been developed to analyze the developing patterns of infant microbiota, but evaluating the reliability and effectiveness of these approaches remains a challenge. In this study, we created a test data pool using public infant microbiome data sets to assess the performance of four different network-based methods, employing repeated sampling strategies. We found that our proposed Probability-Based Co-Detection Model (PBCDM) demonstrated the best stability and robustness, particularly in network attributes such as node counts, average links per node, and the positive-to-negative link (P/N) ratios. Using the PBCDM, we constructed microbial co-existence networks for infants at various ages, identifying core genera networks through a novel network shearing method. Analysis revealed that core genera were more similar between adjacent age ranges, with increasing competitive relationships among microbiota as the infant microbiome matured. In conclusion, the PBCDM-based networks reflect known features of infant microbiota and offer a promising approach for investigating microbial relationships. This methodology could also be applied to future studies of genomic, metabolic, and proteomic data.

IMPORTANCE

As a research method and strategy, network analysis holds great potential for mining the relationships of bacteria. However, consistency and solid workflows to construct and evaluate the process of network analysis are lacking. Here, we provide a solid workflow to evaluate the performance of different microbial networks, and a novel probability-based co-existence network construction method used to decipher infant microbiota relationships. Besides, a network shearing strategy based on percolation theory is applied to find the core genera and connections in microbial networks at different age ranges. And the PBCDM method and the network shearing workflow hold potential for mining microbiota relationships, even possibly for the future deciphering of genome, metabolite, and protein data.

Bisphenol A exposure affects specific gut taxa and drives microbiota dynamics in childhood obesity

Cumulative xenobiotic exposure has an environmental and human health impact which is currently assessed under the One Health approach. Bisphenol A (BPA) exposure and its potential link with childhood obesity that has parallelly increased during the last decades deserve special attention. It stands during prenatal or early life and could trigger comorbidities and non-communicable diseases along life. Accumulation in the nature of synthetic chemicals supports the "environmental obesogen" hypothesis, such as BPA. This estrogen-mimicking xenobiotic has shown endocrine disruptive and obesogenic effects accompanied by gut microbiota misbalance that is not yet well elucidated. This study aimed to investigate specific microbiota taxa isolated and selected by direct BPA exposure and reveal its role on the overall children microbiota community and dynamics, driving toward specific obesity dysbiosis. A total of 333 BPA-resistant isolated species obtained through culturing after several exposure conditions were evaluated for their role and interplay with the global microbial community. The selected BPA-cultured taxa biomarkers showed a significant impact on alpha diversity. Specifically, Clostridium and Romboutsia were positively associated promoting the richness of microbiota communities, while Intestinibacter, Escherichia-Shigella, Bifidobacterium, and Lactobacillus were negatively associated. Microbial community dynamics and networks analyses showed differences according to the study groups. The normal-weight children group exhibited a more enriched, structured, and connected taxa network compared to overweight and obese groups, which could represent a more resilient community to xenobiotic substances. In this sense, subnetwork analysis generated with the BPA-cultured genera showed a correlation between taxa connectivity and more diverse potential enzymatic BPA degradation capacities.IMPORTANCEOur findings indicate how gut microbiota taxa with the capacity to grow in BPA were differentially represented within differential body mass index children study groups and how these taxa affected the overall dynamics toward patterns of diversity generally recognized in dysbiosis. Community network and subnetwork analyses corroborated the better connectedness and stability profiles for normal-weight group compared to the overweight and obese groups.

Evidence linking COVID-19 and the health/well-being of children and adolescents: an umbrella review

BACKGROUND

Experiences during childhood and adolescence have enduring impacts on physical and mental well-being, overall quality of life, and socioeconomic status throughout one's lifetime. This underscores the importance of prioritizing the health of children and adolescents to establish an impactful healthcare system that benefits both individuals and society. It is crucial for healthcare providers and policymakers to examine the relationship between COVID-19 and the health of children and adolescents, as this understanding will guide the creation of interventions and policies for the long-term management of the virus.

METHODS

In this umbrella review (PROSPERO ID: CRD42023401106), systematic reviews were identified from the Cochrane Database of Systematic Reviews; EMBASE (OvidSP); and MEDLINE (OvidSP) from December 2019 to February 2023. Pairwise and single-arm meta-analyses were extracted from the included systematic reviews. The methodological quality appraisal was completed using the AMSTAR-2 tool. Single-arm meta-analyses were re-presented under six domains associated with COVID-19 condition. Pairwise meta-analyses were classified into five domains according to the evidence classification criteria. Rosenberg's FSN was calculated for both binary and continuous measures.

RESULTS

We identified 1551 single-arm and 301 pairwise meta-analyses from 124 systematic reviews that met our predefined criteria for inclusion. The focus of the meta-analytical evidence was predominantly on the physical outcomes of COVID-19, encompassing both single-arm and pairwise study designs. However, the quality of evidence and methodological rigor were suboptimal. Based on the evidence gathered from single-arm meta-analyses, we constructed an illustrative representation of the disease severity, clinical manifestations, laboratory and radiological findings, treatments, and outcomes from 2020 to 2022. Additionally, we discovered 17 instances of strong or highly suggestive pairwise meta-analytical evidence concerning long-COVID, pediatric comorbidity, COVID-19 vaccines, mental health, and depression.

CONCLUSIONS

The findings of our study advocate for the implementation of surveillance systems to track health consequences associated with COVID-19 and the establishment of multidisciplinary collaborative rehabilitation programs for affected younger populations. In future research endeavors, it is important to prioritize the investigation of non-physical outcomes to bridge the gap between research findings and clinical application in this field.

Rat microbial biogeography and age-dependent lactic acid bacteria in healthy lungs

The laboratory rat emerges as a useful tool for studying the interaction between the host and its microbiome. To advance principles relevant to the human microbiome, we systematically investigated and defined the multitissue microbial biogeography of healthy Fischer 344 rats across their lifespan. Microbial community profiling data were extracted and integrated with host transcriptomic data from the Sequencing Quality Control consortium. Unsupervised machine learning, correlation, taxonomic diversity and abundance analyses were performed to determine and characterize the rat microbial biogeography and identify four intertissue microbial heterogeneity patterns (P1-P4). We found that the 11 body habitats harbored a greater diversity of microbes than previously suspected. Lactic acid bacteria (LAB) abundance progressively declined in lungs from breastfed newborn to adolescence/adult, and was below detectable levels in elderly rats. Bioinformatics analyses indicate that the abundance of LAB may be modulated by the lung-immune axis. The presence and levels of LAB in lungs were further evaluated by PCR in two validation datasets. The lung, testes, thymus, kidney, adrenal and muscle niches were found to have age-dependent alterations in microbial abundance. The 357 microbial signatures were positively correlated with host genes in cell proliferation (P1), DNA damage repair (P2) and DNA transcription (P3). Our study established a link between the metabolic properties of LAB with lung microbiota maturation and development. Breastfeeding and environmental exposure influence microbiome composition and host health and longevity. The inferred rat microbial biogeography and pattern-specific microbial signatures could be useful for microbiome therapeutic approaches to human health and life quality enhancement.

The correlation of the intestinal with pharyngeal microbiota in early neonates

Introduction

The gut-lung axis has long been recognized as an important mechanism affecting intestinal and lung immunity. Still, few studies have examined the correlation between the intestinal and pharyngeal microbiota in early neonates, especially when feeding patterns are one of the main drivers of microbiota development.

Methods

To explore the composition and function of intestinal and pharyngeal microbiota and to analyze the effect of limited formula feeding on the initial microbiota colonization in early full-term neonates, we characterized the stool and oropharyngeal microbiota of 20 healthy full-term newborns sampled on days 0 and 5-7 after birth using 16S rRNA gene sequencing. Based on the sequencing results, a comparison was made of the compositions and functions of the intestinal and oropharyngeal microbiota for analysis.

Results and discussion

At the phylum level, Firmicutes, Actinobacteria, Proteobacteria, and Bacteroidetes were the most abundant in both niches. At the genus level, the species of pioneer bacteria were rich in the intestine and oropharynx but low in abundance on day 0. On days 5-7, Bifidobacterium (25.40%) and Escherichia-Shigella (22.16%) were dominant in the intestine, while Streptococcus (38.40%) and Staphylococcus (23.13%) were dominant in the oropharynx. There were eight core bacteria genera in the intestine and oropharynx on days 5-7, which were Bifidobacterium, Escherichia-Shigella, Staphylococcus, Streptococcus, Bacteroides, Parabacteroides, Rothia, and Acinetobacter. As indicated by PICRUSt analysis, on days 5-7, the intestinal microbiota was more predictive than the oropharyngeal microbiota in transcription, metabolism, cell motility, cellular processes and signaling, and organismal system function in the KEGG pathway. Compared to exclusive breastfeeding, limited formula feeding (40-60%) had no significant effect on the neonatal intestinal and oropharyngeal microbiota composition during the initial colonization period. Our results suggest that the initial colonization of microbiota is closely related to the ecological niche environment in the intestine and oropharynx, with their core microbiota being closely correlated. We found that early limited formula feeding could not significantly affect the initial colonization of microbiota in the intestine and oropharynx.

Oral and gut microbial biomarkers of susceptibility to respiratory tract infection in adults: A feasibility study

We conducted a feasibility cohort study which aimed to recruit and retain adults from the community to collect saliva (oral) and stool (gut) samples at three time points, at the start of the study (baseline), during a respiratory tract infection (RTI) and post-RTI. Community RTIs place a huge burden on health care services, and a non-invasive microbial diagnostic tool to predict the most vulnerable to respiratory infection would be ideal. To this aim, we analysed oral-gut baseline samples comparing those who reported RTI symptoms to those who remained healthy throughout the study for microbial biomarkers of respiratory susceptibility. Amplicon sequence variants (ASV) were identified by 16S sequence profiling to reveal oral-gut microbes. Reverse transcriptase-polymerase chain reaction (RT-PCR) was applied to target common respiratory microbes. Two general practices were recruited, and the participant recruitment rate was 1.3%. A total of 40 adult participants were retained, of which 19 acquired an RTI whereas 21 remained healthy. In healthy baseline oral and gut samples, ASVs from participants with RTI symptoms compared to those who remained healthy were similar with a high relative abundance of Streptococcus sp., and Blautia sp., respectively. Linear discriminant analysis effect size (LEfSe) revealed baseline oral microbes differed, indicating participants who suffered RTI symptoms had enhanced Streptococcus sobrinus and Megamonas sp., and depletion of Lactobacillus salivarius, Synergistetes, Verrucomicrobia and Dethiosulfovibrio. Furthermore, a random forest model ranked Streptococcus (4.13) as the highest mean decrease in accuracy (MDA) and RT-PCR showed a higher level of carriage of coagulase-negative Staphylococcus. Baseline core gut microbes were similar in both participant groups whereas LEfSe analysis revealed enhanced Veillonella, Rikenellaceae, Enhydobacteria, Eggerthella and Xanthomonsdales and depleted Desulfobulbus and Coprobacillus. Sutterella (4.73) had a high MDA value. Overall, we demonstrated the feasibility of recruiting and retaining adult participants from the community to provide multiple biological samples for microbial profiling. Our analyses identified potential oral-gut microbial biomarkers of respiratory infection susceptibility in otherwise healthy participants.

Unraveling the impact of primary immunodeficiency disorders on the microbiota of dental caries in children through 16S rRNA gene-based metagenomic analysis

Background/aim

Dental caries is a frequently occurring and multifactorial chronic disease in children resulting from the interaction of cariogenic bacteria and host susceptibility. The aim of this study was to elucidate the impacts of primary immunodeficiency disorders (PIDs) on microbiota of dental caries in children by 16S rRNA gene-based metagenomic analysis.

Materials and methods

Enrolled in this study were 15 children with primary PID with caries (PID group) and 15 healthy children with caries as a control (CG). The DMFT index, saliva flow rate, and buffering capacity of each participant were assessed before the metagenomic analyses were conducted. For taxonomic profiling, the reads were obtained by high-throughput sequencing of the V3-V4 hypervariable region of 16S rRNA.

Results

The DMFT score, saliva flow rate, and buffering capacity of the groups were similar. The flow rate and buffering capacity had no correlation with the number of species with 95% confidence. The metagenomic analysis resulted in the identification of 2440 bacterial species in all of the samples. Among the 50 most prevalent species present at ≥1% relative abundance, Prevotella melaninogenica and Prevotella salivae were differentially more abundant in the PID group. The PID group and CG showed similar species richness and evenness, but 4 of the 5 samples with the highest Shannon-Weiner and Inverse Simpson indices belonged to the PID group. The Spearman test results for correlation of the species in the PID subgroups showed that Prevotella oris had a positively correlated relationship with both Scardovia wiggsiae and Saccharibacteria genera incertae sedis.

Conclusion

This study provided insight into the caries microbiota of children with immunodeficiency diseases. Differentially abundant species, novel bacterial associations, and unique bacterial species were disclosed in the PID samples, indicating the role of the immune system in altering the caries microbiota. The prominent bacterial species and associations in the PID group should be suspected in regard to their link with present or future diseases.

Rat microbial biogeography and age-dependent lactic acid bacteria in healthy lungs

The laboratory rat emerges as a useful tool for studying the interaction between the host and its microbiome. To advance principles relevant to the human microbiome, we systematically investigated and defined a multi-tissue full lifespan microbial biogeography for healthy Fischer 344 rats. Microbial community profiling data was extracted and integrated with host transcriptomic data from the Sequencing Quality Control (SEQC) consortium. Unsupervised machine learning, Spearman's correlation, taxonomic diversity, and abundance analyses were performed to determine and characterize the rat microbial biogeography and the identification of four inter-tissue microbial heterogeneity patterns (P1-P4). The 11 body habitats harbor a greater diversity of microbes than previously suspected. Lactic acid bacteria (LAB) abundances progressively declined in lungs from breastfeed newborn to adolescence/adult and was below detectable levels in elderly rats. LAB's presence and levels in lungs were further evaluated by PCR in the two validation datasets. The lung, testes, thymus, kidney, adrenal, and muscle niches were found to have age-dependent alterations in microbial abundance. P1 is dominated by lung samples. P2 contains the largest sample size and is enriched for environmental species. Liver and muscle samples were mostly classified into P3. Archaea species were exclusively enriched in P4. The 357 pattern-specific microbial signatures were positively correlated with host genes in cell migration and proliferation (P1), DNA damage repair and synaptic transmissions (P2), as well as DNA transcription and cell cycle in P3. Our study established a link between metabolic properties of LAB with lung microbiota maturation and development. Breastfeeding and environmental exposure influence microbiome composition and host health and longevity. The inferred rat microbial biogeography and pattern-specific microbial signatures would be useful for microbiome therapeutic approaches to human health and good quality of life.

Integrative web cloud computing and analytics using MiPair for design-based comparative analysis with paired microbiome data

Pairing (or blocking) is a design technique that is widely used in comparative microbiome studies to efficiently control for the effects of potential confounders (e.g., genetic, environmental, or behavioral factors). Some typical paired (block) designs for human microbiome studies are repeated measures designs that profile each subject's microbiome twice (or more than twice) (1) for pre and post treatments to see the effects of a treatment on microbiome, or (2) for different organs of the body (e.g., gut, mouth, skin) to see the disparity in microbiome between (or across) body sites. Researchers have developed a sheer number of web-based tools for user-friendly microbiome data processing and analytics, though there is no web-based tool currently available for such paired microbiome studies. In this paper, we thus introduce an integrative web-based tool, named MiPair, for design-based comparative analysis with paired microbiome data. MiPair is a user-friendly web cloud service that is built with step-by-step data processing and analytic procedures for comparative analysis between (or across) groups or between baseline and other groups. MiPair employs parametric and non-parametric tests for complete or incomplete block designs to perform comparative analyses with respect to microbial ecology (alpha- and beta-diversity) and taxonomy (e.g., phylum, class, order, family, genus, species). We demonstrate its usage through an example clinical trial on the effects of antibiotics on gut microbiome. MiPair is an open-source software that can be run on our web server ( http://mipair.micloud.kr ) or on user's computer ( https://github.com/yj7599/mipairgit ).

The microbiota in respiratory tract infections: from association to intervention

PURPOSE OF REVIEW

The respiratory microbiota has a role in respiratory tract infection (RTI) pathogenesis. On the mucosa, the respiratory microbiota interacts with potential pathogenic viruses, bacteria and the host immune system, including secretory IgA (sIgA). This review discusses the role of the respiratory microbiota and its interaction with the (mucosal) immune system in RTI susceptibility, as well as the potential to exploit the microbiota to promote health and prevent RTIs.

RECENT FINDINGS

Recent studies confirm that specific microbiota profiles are associated with RTI susceptibility and during susceptibility and found accompanying RTIs, although clear associations have not yet been found for SARS-CoV-2 infection. sIgA plays a central role in RTI pathogenesis: it stands under control of the local microbiota, while at the same time influencing bacterial gene expression, metabolism and defense mechanisms. Respiratory microbiota interventions are still newly emerging but promising candidates for probiotics to prevent RTIs, such as Corynebacterium and Dolosigranulum species, have been identified.

SUMMARY

Improved understanding of the respiratory microbiota in RTIs and its interplay with the immune system is of importance for early identification and follow-up of individuals at risk of infection. It also opens doors for future microbiota interventions by altering the microbiota towards a healthier state to prevent and/or adjunctively treat RTIs.

A Parallel Tracking of Salivary and Gut Microbiota Profiles Can Reveal Maturation and Interplay of Early Life Microbial Communities in Healthy Infants

In this study, the onset and shaping of the salivary and gut microbiota in healthy newborns during the first period of life has been followed, evaluating the impact of salivary microbiota on the development of early fecal microbial communities. The microbiota of 80 salivary and 82 fecal samples that were collected from healthy newborns in the first six months of life, was investigated by 16S rRNA amplicon profiling. The microbial relationship within and between the saliva and gut ecosystems was determined by correlation heatmaps and co-occurrence networks. Streptococcus and Staphylococcus appeared as early commensals in the salivary microbiota, dominating this ecosystem through the time, while Fusobacterium, Prevotella, Porphyromonas, Granulicatella, and Veillonella were late colonizers. Enterobacteriaceae, Staphylococcus and Streptococcus were gut pioneers, followed by the anaerobic Bifidobacterium, Veillonella, Eggerthella, and Bacteroides. Streptococcus, Staphylococcus, and Veillonella were shared by the gut and saliva ecosystems. The saliva and gut microbiota seem to evolve independently, driven by local adaptation strategies, except for the oral Streptococcus and Veillonella that are involved in gut microbiota development as seeding species. This study offers a piece of knowledge on how the oral microbiota may affect the gut microbiota in healthy newborns, shedding light onto new microbial targets for the development of therapies for early life intestinal dysbiosis.

SARS-CoV-2 infections in children: Understanding diverse outcomes

SARS-CoV-2 infections mostly lead to mild or even asymptomatic infections in children, but the reasons for this are not fully understood. More efficient local tissue responses, better thymic function, and cross-reactive immunity have all been proposed to explain this. In rare cases of children and young people, but very rarely in adults, post-infectious hyperinflammatory syndromes can develop and be serious. Here, I will discuss our current understanding of SARS-CoV-2 infections in children and hypothesize that a life history and energy allocation perspective might offer an additional explanation to mild infections, viral dynamics, and the higher incidence of rare multisystem inflammatory syndromes in children and young people.