Draft genome sequence of Ruoffia tabacinasalis isolated from a bovine nasal swab: a novel member of the bovine nasal microbiota.

We report the isolation and draft genome sequence of Ruoffia tabacinasalis, a novel member of the bovine nasal microbiota. The genome, which is estimated to be 90.5% complete, is composed of one contig comprising 2,363,349 bp with a GC content of 36.66%.

The nasal microbiota is a potential diagnostic biomarker for sepsis in critical care units.

This study aimed to characterize the composition of intestinal and nasal microbiota in septic patients and identify potential microbial biomarkers for diagnosis. A total of 157 subjects, including 89 with sepsis, were enrolled from the affiliated hospital. Nasal swabs and fecal specimens were collected from septic and non-septic patients in the intensive care unit (ICU) and Department of Respiratory and Critical Care Medicine. DNA was extracted, and the V4 region of the 16S rRNA gene was amplified and sequenced using Illumina technology. Bioinformatics analysis, statistical processing, and machine learning techniques were employed to differentiate between septic and non-septic patients. The nasal microbiota of septic patients exhibited significantly lower community richness (P = 0.002) and distinct compositions (P = 0.001) compared to non-septic patients. Corynebacterium, Staphylococcus, Acinetobacter, and Pseudomonas were identified as enriched genera in the nasal microbiota of septic patients. The constructed machine learning model achieved an area under the curve (AUC) of 89.08, indicating its efficacy in differentiating septic and non-septic patients. Importantly, model validation demonstrated the effectiveness of the nasal microecological diagnosis prediction model with an AUC of 84.79, while the gut microecological diagnosis prediction model had poor predictive performance (AUC = 49.24). The nasal microbiota of ICU patients effectively distinguishes sepsis from non-septic cases and outperforms the gut microbiota. These findings have implications for the development of diagnostic strategies and advancements in critical care medicine.IMPORTANCEThe important clinical significance of this study is that it compared the intestinal and nasal microbiota of sepsis with non-sepsis patients and determined that the nasal microbiota is more effective than the intestinal microbiota in distinguishing patients with sepsis from those without sepsis, based on the difference in the lines of nasal specimens collected.

Human nasal microbiota shifts in healthy and chronic respiratory disease conditions.

BACKGROUND: An increasing number of studies investigate various human microbiotas and their roles in the development of diseases, maintenance of health states, and balanced signaling towards the brain. Current data demonstrate that the nasal microbiota contains a unique and highly variable array of commensal bacteria and opportunistic pathogens. However, we need to understand how to harness current knowledge, enrich nasal microbiota with beneficial microorganisms, and prevent pathogenic developments. RESULTS: In this study, we have obtained nasal, nasopharyngeal, and bronchoalveolar lavage fluid samples from healthy volunteers and patients suffering from chronic respiratory tract diseases for full-length 16 S rRNA sequencing analysis using Oxford Nanopore Technologies. Demographic and clinical data were collected simultaneously. The microbiome analysis of 97 people from Lithuania suffering from chronic inflammatory respiratory tract disease and healthy volunteers revealed that the human nasal microbiome represents the microbiome of the upper airways well. CONCLUSIONS: The nasal microbiota of patients was enriched with opportunistic pathogens, which could be used as indicators of respiratory tract conditions. In addition, we observed that a healthy human nasal microbiome contained several plant- and bee-associated species, suggesting the possibility of enriching human nasal microbiota via such exposures when needed. These candidate probiotics should be investigated for their modulating effects on airway and lung epithelia, immunogenic properties, neurotransmitter content, and roles in maintaining respiratory health and nose-brain interrelationships.

Gut-associated microbes are present and active in the pig nasal cavity.

The nasal microbiota is a key contributor to animal health, and characterizing the nasal microbiota composition is an important step towards elucidating the role of its different members. Efforts to characterize the nasal microbiota composition of domestic pigs and other farm animals frequently report the presence of bacteria that are typically found in the gut, including many anaerobes from the Bacteroidales and Clostridiales orders. However, the in vivo role of these gut-microbiota associated taxa is currently unclear. Here, we tackled this issue by examining the prevalence, origin, and activity of these taxa in the nasal microbiota of piglets. First, analysis of the nasal microbiota of farm piglets sampled in this study, as well as various publicly available data sets, revealed that gut-microbiota associated taxa indeed constitute a substantial fraction of the pig nasal microbiota that is highly variable across individual animals. Second, comparison of herd-matched nasal and rectal samples at amplicon sequencing variant (ASV) level showed that these taxa are largely shared in the nasal and rectal microbiota, suggesting a common origin driven presumably by the transfer of fecal matter. Third, surgical sampling of the inner nasal tract showed that gut-microbiota associated taxa are found throughout the nasal cavity, indicating that these taxa do not stem from contaminations introduced during sampling with conventional nasal swabs. Finally, analysis of cDNA from the 16S rRNA gene in these nasal samples indicated that gut-microbiota associated taxa are indeed active in the pig nasal cavity. This study shows that gut-microbiota associated taxa are not only present, but also active, in the nasal cavity of domestic pigs, and paves the way for future efforts to elucidate the function of these taxa within the nasal microbiota.

Nasal Microbiota and Sensitivity Pattern in Rhinosinusitis.

Aims: To know the microorganism causing rhinosinusitis & to study the antibiotic sensitivity pattern for the isolated nasal microbiota in this region. Background: Rhinosinusitis is inflammatory condition of nose and paranasal sinuses [1]. It is multifactorial condition, in which microorganisms play pathogenic role [2]. Interactions between microorganisms, mucosa and environmental changes influence on composition of bacterial ecosystem [2]. Though antibiotics are frequently used for medical management of rhinosinusitis, sensitivity directed antibiotics are rarely prescribed. So, this study is directed to know microbial isolate in rhinosinusitis and its antibiotic sensitivity pattern. Methodology: in this 6 months prospective study during March to September 2022, done at Department of Otorhinolaryngology, Raichur Institute of Medical Sciences, Raichur; patients attending Otorhinolaryngology outpatient department and diagnosed to have rhinosinusitis were selected. Nasal swabs were collected from the middle meatus by diagnostic nasal endoscopy and were sent for culture and sensitivity. Statistical tests were applied for results(Size = 100). Results: Out of 100 patients, 52 were males, 48 were females; 88 were adults & 12 were paediatric patients. 59 patients had acute, 32 chronic and 9 had recurrent rhinosinusitis. Most common organisms isolated in acute rhinosinusitis was Klebsiella 28%, Staphylococcus aureus 56% & 66% in chronic & recurrent rhinosinusitis respectively. Klebsiella was sensitive to beta lactams & quinolones, while Staphylococcus aureus was sensitive to beta lactams & cephalosporins. Conclusion: Increase in antibiotic use has led to antibiotic resistance. Hence judicious, sensitivity directed antibiotic usage reduces the risk of antibiotic resistance and unnecessary use of antibiotics.

Can environmental nebulization of lavender essential oil (L. angustifolia) improve welfare and modulate nasal microbiota of growing pigs?

The use of phytoextracts has been proposed as a method to improve animal welfare, also in pigs, by reducing stress and anxiety and improving performances. Lavandula angustifolia (Miller) essential oil (LaEO) is an interesting calming phytoextract that could be administered by inhalation for prolonged periods of time to help pigs coping with on-farm conditions. The aim of this study was to assess the effects of daily inhalation of vaporized LaEO on pigs' welfare and health indicators, and nasal microbiota, trying to understand whether this phytoextract represents a feasible tool to improve animal welfare under intensive farming conditions. Eighty-four crossbred barrows were randomly divided into 3 experimental groups: control (C); lavender (L): 3 vaporization sessions of 10 min each of a custom made 1% solution of LaEO; sham (S): same vaporization sessions of L group but only using the solution vehicle. Experimental readouts included growth parameters, behavioural traits, tail and skin lesions, hair steroids and nasal microbiota. L group animals did not show altered growth performance and seemed calmer (increased recumbency time), with decreased amount of skin lesions also associated with lower severity class for tail lesions. They also showed decreased CORT/DHEA ratio, potentially suggesting a beneficial effect of LaEO. Inhalation of LaEO significantly affected the nasal pig microbiome by reducing its diversity. Overall, the study suggests how inhalation of Lavender essential oil may be capable of improving welfare in growing pigs, yet it is pivotal to consider the microbial modulatory capabilities of essential oils before exploiting them on larger scale.

Prolonged mask wearing changed nasal microbial characterization of young adults during the COVID-19 pandemic in Shanghai, China.

Background: Face masks have become a common sight during the Coronavirus Disease 2019 (COVID-19) pandemic in many countries. However, the impact of prolonged face mask wearing on nasal microbiota of healthy people is not fully understood. Methods: In this study, we compared the nasal microbiota of 82 young adults who wore face masks for an extended period of time to 172 mask-free peers from the same school recruited before the COVID-19 pandemic via 16S ribosomal RNA gene sequencing. Diversity, composition, and function of nasal microbiota between the two groups were analyzed. Prevalence of commensal bacteria colonized in the nasal cavity was determined by culture-based analysis. Results: We observed that prolonged face mask wearers had significantly different nasal microbial characterization and metabolic function compared to mask-free controls from 2018. Specifically, the nasal microbiota of the prolonged mask wearers displayed increased abundance of Staphylococcus, Pseudoalteromonas, Corynebacterium, etc. Meanwhile, the abundance of several genera including Bacteroides, Faecalibacterium, and Agathobacter was decreased. Moreover, we observed that COVID-19 infection history did not affect the composition of nasal microbiota significantly. Additionally, the culture-based analysis revealed that Staphylococcus aureus and Corynebacterium accolens increased, and Staphylococcus epidermidis decreased in the nasal cavity of prolonged mask wearers. Conclusions: Overall, our study suggests that prolonged face mask wearing can significantly alter the nasal microbiota.

Intensive antibiotic treatment of sows with parenteral crystalline ceftiofur and tulathromycin alters the composition of the nasal microbiota of their offspring.

The nasal microbiota plays an important role in animal health and the use of antibiotics is a major factor that influences its composition. Here, we studied the consequences of an intensive antibiotic treatment, applied to sows and/or their offspring, on the piglets' nasal microbiota. Four pregnant sows were treated with crystalline ceftiofur and tulathromycin (CTsows) while two other sows received only crystalline ceftiofur (Csows). Sow treatments were performed at D-4 (four days pre-farrowing), D3, D10 and D17 for ceftiofur and D-3, D4 and D11 for tulathromycin. Half of the piglets born to CTsows were treated at D1 with ceftiofur. Nasal swabs were taken from piglets at 22-24 days of age and bacterial load and nasal microbiota composition were defined by 16 s rRNA gene qPCR and amplicon sequencing. Antibiotic treatment of sows reduced their nasal bacterial load, as well as in their offspring, indicating a reduced bacterial transmission from the dams. In addition, nasal microbiota composition of the piglets exhibited signs of dysbiosis, showing unusual taxa. The addition of tulathromycin to the ceftiofur treatment seemed to enhance the deleterious effect on the microbiota diversity by diminishing some bacteria commonly found in the piglets' nasal cavity, such as Glaesserella, Streptococcus, Prevotella, Staphylococcus and several members of the Ruminococcaceae and Lachnospiraceae families. On the other hand, the additional treatment of piglets with ceftiofur resulted in no further effect beyond the treatment of the sows. Altogether, these results suggest that intensive antibiotic treatments of sows, especially the double antibiotic treatment, disrupt the nasal microbiota of their offspring and highlight the importance of sow-to-piglet microbiota transmission.

Secretory IgA impacts the microbiota density in the human nose.

BACKGROUND: Respiratory mucosal host defense relies on the production of secretory IgA (sIgA) antibodies, but we currently lack a fundamental understanding of how sIgA is induced by contact with microbes and how such immune responses may vary between humans. Defense of the nasal mucosal barrier through sIgA is critical to protect from infection and to maintain homeostasis of the microbiome, which influences respiratory disorders and hosts opportunistic pathogens. METHODS: We applied IgA-seq analysis to nasal microbiota samples from male and female healthy volunteers, to identify which bacterial genera and species are targeted by sIgA on the level of the individual host. Furthermore, we used nasal sIgA from the same individuals in sIgA deposition experiments to validate the IgA-seq outcomes. CONCLUSIONS: We observed that the amount of sIgA secreted into the nasal mucosa by the host varied substantially and was negatively correlated with the bacterial density, suggesting that nasal sIgA limits the overall bacterial capacity to colonize. The interaction between mucosal sIgA antibodies and the nasal microbiota was highly individual with no obvious differences between potentially invasive and non-invasive bacterial species. Importantly, we could show that for the clinically relevant opportunistic pathogen and frequent nasal resident Staphylococcus aureus, sIgA reactivity was in part the result of epitope-independent interaction of sIgA with the antibody-binding protein SpA through binding of sIgA Fab regions. This study thereby offers a first comprehensive insight into the targeting of the nasal microbiota by sIgA antibodies. It thereby helps to better understand the shaping and homeostasis of the nasal microbiome by the host and may guide the development of effective mucosal vaccines against bacterial pathogens. Video Abstract.

Microbiota members from body sites of dairy cows are largely shared within individual hosts throughout lactation but sharing is limited in the herd.

BACKGROUND: Host-associated microbes are major determinants of the host phenotypes. In the present study, we used dairy cows with different scores of susceptibility to mastitis with the aim to explore the relationships between microbiota composition and different factors in various body sites throughout lactation as well as the intra- and inter-animal microbial sharing. RESULTS: Microbiotas from the mouth, nose, vagina and milk of 45 lactating dairy cows were characterized by metataxonomics at four time points during the first lactation, from 1-week pre-partum to 7 months post-partum. Each site harbored a specific community that changed with time, likely reflecting physiological changes in the transition period and changes in diet and housing. Importantly, we found a significant number of microbes shared among different anatomical sites within each animal. This was between nearby anatomic sites, with up to 32% of the total number of Amplicon Sequence Variants (ASVs) of the oral microbiota shared with the nasal microbiota but also between distant ones (e.g. milk with nasal and vaginal microbiotas). In contrast, the share of microbes between animals was limited (< 7% of ASVs shared by more than 50% of the herd for a given site and time point). The latter widely shared ASVs were mainly found in the oral and nasal microbiotas. These results thus indicate that despite a common environment and diet, each animal hosted a specific set of bacteria, supporting a tight interplay between each animal and its microbiota. The score of susceptibility to mastitis was slightly but significantly related to the microbiota associated to milk suggesting a link between host genetics and microbiota. CONCLUSIONS: This work highlights an important sharing of microbes between relevant microbiotas involved in health and production at the animal level, whereas the presence of common microbes was limited between animals of the herd. This suggests a host regulation of body-associated microbiotas that seems to be differently expressed depending on the body site, as suggested by changes in the milk microbiota that were associated to genotypes of susceptibility to mastitis.

Metabolic capabilities are highly conserved among human nasal-associated Corynebacterium species in pangenomic analyses.

Corynebacterium species are globally ubiquitous in human nasal microbiota across the lifespan. Moreover, nasal microbiota profiles typified by higher relative abundances of Corynebacterium are often positively associated with health. Among the most common human nasal Corynebacterium species are C. propinquum, C. pseudodiphtheriticum, C. accolens, and C. tuberculostearicum. Based on the prevalence of these species, at least two likely coexist in the nasal microbiota of 82% of adults. To gain insight into the functions of these four species, we identified genomic, phylogenomic, and pangenomic properties and estimated the functional protein repertoire and metabolic capabilities of 87 distinct human nasal Corynebacterium strain genomes: 31 from Botswana and 56 from the U.S. C. pseudodiphtheriticum had geographically distinct clades consistent with localized strain circulation, whereas some strains from the other species had wide geographic distribution across Africa and North America. All four species had similar genomic and pangenomic structures. Gene clusters assigned to all COG metabolic categories were overrepresented in the persistent (core) compared to the accessory genome of each species indicating limited strain-level variability in metabolic capacity. Moreover, core metabolic capabilities were highly conserved among the four species indicating limited species-level metabolic variation. Strikingly, strains in the U.S. clade of C. pseudodiphtheriticum lacked genes for assimilatory sulfate reduction present in the Botswanan clade and in the other studied species, indicating a recent, geographically related loss of assimilatory sulfate reduction. Overall, the minimal species and strain variability in metabolic capacity implies coexisting strains might have limited ability to occupy distinct metabolic niches.

Association between short-term exposure to PM2.5 and nasal microbiota dysbiosis, inflammation and oxidative stress: A panel study of healthy young adults.

Fine particulate matter (PM2.5) is the primary environmental stressor and a significant threat to public health. However, the effect of PM2.5 exposure on human nasal microbiota and its pathophysiological implication remain less understood. This study aimed to explore the associations of PM2.5 exposure with indices of nasal microbiota and biomarkers of nasal inflammation and oxidative stress. We conducted a panel study with 75 students in Xinxiang, Henan Province, China, from September to December 2017. Biomarkers of nasal inflammation and oxidative stress including interleukin-6 (IL-6), IL-8, tumor necrosis factor-α (TNF-α), 8-epi-prostaglandin F2 alpha (8-epi-PGF2α) and indices of nasal microbiota diversity and phenotypes were measured. Linear mixed-effect models and bioinformatic analyses were performed to assess the association of PM2.5 concentrations with the abovementioned biomarkers and indices. It was found that per 1 µg/m3 increase in PM2.5 was associated with increments of 13.15% (95 % CI: 5.53-20.76 %) and 78.98 % (95 % CI: 21.61-136.36 %) in TNF-α on lag2 and lag02. Indices of microbial diversity and phenotypes including equitability, Shannon index, biofilm forming, and oxidative stress tolerant decreased to different extent with the increment in PM2.5. Notably, thirteen differential microbes in Clostridia, Bacilli, and Gammaproteobacteria classes were recognized as keystone taxa and eight of them were associated with TNF-α, IL-6, or 8-epi-PGF2α. Moreover, environmental adaptation was the most critical functional pathway of nasal microbiota associated with PM2.5 exposure. In summary, short-term exposure to PM2.5 is associated with nasal inflammation, microbiota diversity reduction, and the microbiota phenotype alterations.

When does a Lotka-Volterra model represent microbial interactions? Insights from in vitro nasal bacterial communities.

To alter microbial community composition for therapeutic purposes, an accurate and reliable modeling framework capable of predicting microbial community outcomes is required. Lotka-Volterra (LV) equations have been utilized to describe a breadth of microbial communities, yet, the conditions in which this modeling framework is successful remain unclear. Here, we propose that a set of simple in vitro experiments-growing each member in cell-free spent medium obtained from other members-can be used as a test to decide whether an LV model is appropriate for describing microbial interactions of interest. We show that for LV to be a good candidate, the ratio of growth rate to carrying capacity of each isolate when grown in the cell-free spent media of other isolates should remain constant. Using an in vitro community of human nasal bacteria as a tractable system, we find that LV can be a good approximation when the environment is low-nutrient (i.e., when growth is limited by the availability of nutrients) and complex (i.e., when multiple resources, rather than a few, determine growth). These findings can help clarify the range of applicability of LV models and reveal when a more complex model may be necessary for predictive modeling of microbial communities. IMPORTANCE Although mathematical modeling can be a powerful tool to draw useful insights in microbial ecology, it is crucial to know when a simplified model adequately represents the interactions of interest. Here, we take advantage of bacterial isolates from the human nasal passages as a tractable model system and conclude that the commonly used Lotka-Volterra model can represent interactions among microbes well when the environment is complex (with many interaction mediators) and low-nutrient. Our work highlights the importance of considering both realism and simplicity when choosing a model to represent microbial interactions.

Detection of antimicrobial producing Staphylococcus from migratory birds: Potential role in nasotracheal microbiota modulation.

A collection of 259 staphylococci of 13 different species [212 coagulase-negative (CoNS) and 47 coagulase-positive (CoPS)] recovered from nasotracheal samples of 87 healthy nestling white storks was tested by the spot-on-lawn method for antimicrobial-activity (AA) against 14 indicator bacteria. Moreover, extracts of AP isolates were obtained [cell-free-supernatants (CFS) both crude and concentrated and butanol extracts] and tested against the 14 indicator bacteria. The microbiota modulation capacity of AP isolates was tested considering: (a) intra-sample AA, against all Gram-positive bacteria recovered in the same stork nasotracheal sample; (b) inter-sample AA against a selection of representative Gram-positive bacteria of the nasotracheal microbiota of all the storks (30 isolates of 29 different species and nine genera). In addition, enzymatic susceptibility test was carried out in selected AP isolates and bacteriocin encoding genes was studied by PCR/sequencing. In this respect, nine isolates (3.5%; seven CoNS and two CoPS) showed AA against at least one indicator bacteria and were considered antimicrobial-producing (AP) isolates. The AP isolates showed AA only for Gram-positive bacteria. Three of these AP isolates (S. hominis X3764, S. sciuri X4000, and S. chromogenes X4620) revealed AA on all extract conditions; other four AP isolates only showed activity in extracts after concentration; the remaining two AP isolates did not show AA in any of extract conditions. As for the microbiota modulation evaluation, three of the nine AP-isolates revealed intra-sample AA. It is to highlight the potent inter-sample AA of the X3764 isolate inhibiting 73% of the 29 representative Gram-positive species of the nasotracheal stork microbiota population. On the other hand, enzymatic analysis carried out in the two highest AP isolates (X3764 and X4000) verified the proteinaceous nature of the antimicrobial compound and PCR analysis revealed the presence of lantibiotic-like encoding genes in the nine AP isolates. In conclusion, these results show that nasotracheal staphylococci of healthy storks, and especially CoNS, produce antimicrobial substances that could be important in the modulations of their nasal microbiota.

Residential greenness and air pollution's association with nasal microbiota among asthmatic children.

Both greenness and air pollution have widely been linked with asthma. However, the potential mechanism has rarely been investigated. This study aimed to identify the association between residential greenness and air pollution (fine particulate matter [PM2.5]; nitrogen dioxide [NO2]; ozone [O3]) with nasal microbiota among asthmatic children during the recovery phase. The normalized difference vegetation index was used to assess the extent of residential greenness. Spatiotemporal air pollution variation was estimated using an integrated hybrid kriging-LUR with the XG-Boost algorithm. These exposures were measured in 250-m intervals for four incremental buffer ranges. Nasal microbiota was collected from 47 children during the recovery phase. A generalized additive model controlled for various covariates was applied to evaluate the exposure-outcome association. The lag-time effect of greenness and air pollution related to the nasal microbiota also was examined. A significant negative association was observed between short-term exposure to air pollution and nasal bacterial diversity, as a one-unit increment in PM2.5 or O3 significantly decreased the observed species (PM2.5: -0.59, 95%CI -1.13, -0.05 and O3: -0.93, 95%CI -1.54, -0.32) and species richness (PM2.5: -0.64, 95%CI -1.25, -0.02 and O3: -0.68, 95%CI -1.43, -0.07). Considering the lag-time effect, we found a significant positive association between greenness and both the observed species and species richness. In addition, we identified a significant negative association for all pollutants with the observed species richness. These findings add to the evidence base of the links between nasal microbiota and air pollution and greenness. This study establishes a foundation for future studies of how environmental exposure plays a role in nasal microbiota, which in turn may affect the development of asthma.

Airborne polystyrene microplastics and nanoplastics induce nasal and lung microbial dysbiosis in mice.

Microplastics (MP) and nanoplastics (NP) have been found in multiple environments and creatures. However, their effects on the airway microbiota still remain poorly understood. In this study, a series of bioinformatic and statistical analyses were carried out to explore the influence of airborne MP and NP on the nasal and lung microbiota in mice. Both MP and NP were capable of inducing nasal microbial dysbiosis, and MP had a stronger influence on the lung microbiota than NP. Multiple nasal and lung bacteria were associated with MP and NP groups, among which nasal Staphylococcus and lung Roseburia were most associated with MP group, while nasal Prevotella and lung unclassified_Muribaculaceae were most associated with NP group. The nasal Staphylococcus, lung Roseburia, lung Eggerthella and lung Corynebacterium were associated with both MP and NP groups, which were potential biomarkers of micro/nanoplastics-induced airway dysbiosis. SAR11_Clade_Ia and SAR11_Clade_II were associated with both nasal and lung microbiota in MP group, while no such bacterium was determined in NP group. The relevant results suggest that both airborne MP and NP could induce nasal and lung microbial dysbiosis, and the relevant preventative and curable strategies deserve further investigations.

Nasal Microbiota and Neuroinflammation: Relationship between Nasal Flora and Multiple Sclerosis Onset/Progression.

The role of nasal microbiota in contributing to neuroinflammation is gradually emerging. Multiple sclerosis and chronic rhinosinusitis share important clinical and epidemiological similarities, and the hypothetical connection among these two pathological entities should be carefully investigated. This editorial is based on a review of available literature on this topic. The main international databases were searched using the following keywords: neuroinflammation, nasal microbiota, multiple sclerosis, chronic rhino-sinusal disorders, chronic sinusitis. Four fully-consistent articles that investigated nasal microbiota alteration and/or chronic rhinosinusitis presence in subjects affected by multiple sclerosis were identified. Overall, these studies showed a significant connection between nasal microbiota dysbiosis and the presence of multiple sclerosis. New specific studies to analyze the nasal microbiota and its metabolism in patients affected by multiple sclerosis should be performed. In fact, a series of treatments able to change this flora could improve the rhino-sinusal state with consequent reduction of recurrent episodes of neuro-inflammation.

Effect of microplastics on nasal and intestinal microbiota of the high-exposure population.

Background: Microplastic has become a growing environmental problem. A balanced microbial environment is an important factor in human health. This study is the first observational cross-sectional study focusing on the effects of microplastics on the nasal and gut microbiota in a highly exposed population. Methods: We recruited 20 subjects from a Plastic Factory (microplastics high-exposure area) and the other 20 from Huanhuaxi Park (microplastics low-exposure area) in Chengdu, China. We performed the microplastic analysis of soil, air, and intestinal secretions by laser infrared imaging, and microbiological analysis of nasal and intestinal secretions by 16S rDNA sequencing. Results: The result shows that the detected points of microplastics in the environment of the high-exposure area were significantly more than in the low-exposure area. Polyurethane was the main microplastic component detected. The microplastic content of intestinal secretions in the high-exposure group was significantly higher than in the low-exposure group. Specifically, the contents of polyurethane, silicone resin, ethylene-vinyl acetate copolymer, and polyethylene in the high-exposure group were significantly higher than in the low-exposure group. Moreover, high exposure may increase the abundance of nasal microbiotas, which are positively associated with respiratory tract diseases, such as Klebsiella and Helicobacter, and reduce the abundance of those beneficial ones, such as Bacteroides. Simultaneously, it may increase the abundance of intestinal microbiotas, which are positively associated with digestive tract diseases, such as Bifidobacterium, Streptococcus, and Sphingomonas, and reduce the abundance of intestinal microbiotas, which are beneficial for health, such as Ruminococcus Torquesgroup, Dorea, Fusobacterium, and Coprococcus. A combined analysis revealed that high exposure to microplastics may not only lead to alterations in dominant intestinal and nasal microbiotas but also change the symbiotic relationship between intestinal and nasal microbiotas. Conclusion: The results innovatively revealed how microplastics can affect the intestinal and nasal microecosystems. Clinical trial registration: ChiCTR2100049480 on August 2, 2021.

Integrative Analysis of the Nasal Microbiota and Serum Metabolites in Bovines with Respiratory Disease by 16S rRNA Sequencing and Gas Chromatography/Mass Selective Detector-Based Metabolomics.

Bovine respiratory disease (BRD) continues to pose a serious threat to the cattle industry, resulting in substantial economic losses. As a multifactorial disease, pathogen infection and respiratory microbial imbalance are important causative factors in the occurrence and development of BRD. Integrative analyses of 16S rRNA sequencing and metabolomics allow comprehensive identification of the changes in microbiota and metabolism associated with BRD, making it possible to determine which pathogens are responsible for the disease and to develop new therapeutic strategies. In our study, 16S rRNA sequencing and metagenomic analysis were used to describe and compare the composition and diversity of nasal microbes in healthy cattle and cattle with BRD from different farms in Yinchuan, Ningxia, China. We found a significant difference in nasal microbial diversity between diseased and healthy bovines; notably, the relative abundance of Mycoplasma bovis and Pasteurella increased. This indicated that the composition of the microbial community had changed in diseased bovines compared with healthy ones. The data also strongly suggested that the reduced relative abundance of probiotics, including Pasteurellales and Lactobacillales, in diseased samples contributes to the susceptibility to bovine respiratory disease. Furthermore, serum metabolomic analysis showed altered concentrations of metabolites in BRD and that a significant decrease in lactic acid and sarcosine may impair the ability of bovines to generate energy and an immune response to pathogenic bacteria. Based on the correlation analysis between microbial diversity and the metabolome, lactic acid (2TMS) was positively correlated with Gammaproteobacteria and Bacilli and negatively correlated with Mollicutes. In summary, microbial communities and serum metabolites in BRD were characterized by integrative analysis. This study provides a reference for monitoring biomarkers of BRD, which will be critical for the prevention and treatment of BRD in the future.