Comparison of the upper and lower airway microbiome in early postoperative lung transplant recipients.

The upper and lower respiratory tract may share microbiome because they are directly continuous, and the nasal microbiome contributes partially to the composition of the lung microbiome. But little is known about the upper and lower airway microbiome of early postoperative lung transplant recipients (LTRs). Using 16S rRNA gene sequencing, we compared paired nasal swab (NS) and bronchoalveolar lavage fluid (BALF) microbiome from 17 early postoperative LTRs. The microbiome between the two compartments were significantly different in Shannon diversity and beta diversity. Four and eight core NS-associated and BALF-associated microbiome were identified, respectively. NS samples harbored more Corynebacterium, Acinetobacter, and Pseudomonas, while BALF contained more Ralstonia, Stenotrophomonas, Enterococcus, and Pedobacter. The within-subject dissimilarity was higher than the between-subject dissimilarity, indicating a greater impact of sampling sites than sampling individuals on microbial difference. There were both difference and homogeneity between NS and BALF microbiome in early postoperative LTRs. High levels of pathogens were detected in both samples, suggesting that both of them can reflect the diseases characteristics of transplanted lung. The differences between upper and lower airway microbiome mainly come from sampling sites instead of sampling individuals. IMPORTANCE: Lung transplantation is the only therapeutic option for patients with end-stage lung disease, but its outcome is much worse than other solid organ transplants. Little is known about the NS and BALF microbiome of early postoperative LTRs. Here, we compared paired samples of the nasal and lung microbiome from 17 early postoperative LTRs and showed both difference and homogeneity between the two samples. Most of the "core" microbiome in both NS and BALF samples were recognized respiratory pathogens, suggesting that both samples can reflect the diseases characteristics of transplanted lung. We also found that the differences between upper and lower airway microbiome in early postoperative LTRs mainly come from sampling sites instead of sampling individuals.

The Airway Microbiota Signatures of Infection and Rejection in Lung Transplant Recipients.

Infection and rejection are the two most common complications after lung transplantation (LT) and are associated with increased morbidity and mortality. We aimed to examine the association between the airway microbiota and infection and rejection in lung transplant recipients (LTRs). Here, we collected 181 sputum samples (event-free, n = 47; infection, n = 103; rejection, n = 31) from 59 LTRs, and performed 16S rRNA gene sequencing to analyze the airway microbiota. A significantly different airway microbiota was observed among event-free, infection and rejection recipients, including microbial diversity and community composition. Nineteen differential taxa were identified by linear discriminant analysis (LDA) effect size (LEfSe), with 6 bacterial genera, Actinomyces, Rothia, Abiotrophia, Neisseria, Prevotella, and Leptotrichia enriched in LTRs with rejection. Random forest analyses indicated that the combination of the 6 genera and procalcitonin (PCT) and T-lymphocyte levels showed area under the curve (AUC) values of 0.898, 0.919 and 0.895 to differentiate between event-free and infection recipients, event-free and rejection recipients, and infection and rejection recipients, respectively. In conclusion, our study compared the airway microbiota between LTRs with infection and acute rejection. The airway microbiota, especially combined with PCT and T-lymphocyte levels, showed satisfactory predictive efficiency in discriminating among clinically stable recipients and those with infection and acute rejection, suggesting that the airway microbiota can be a potential indicator to differentiate between infection and acute rejection after LT. IMPORTANCE Survival after LT is limited compared with other solid organ transplantations mainly due to infection- and rejection-related complications. Differentiating infection from rejection is one of the most important challenges to face after LT. Recently, the airway microbiota has been reported to be associated with either infection or rejection of LTRs. However, fewer studies have investigated the relationship between airway microbiota together with infection and rejection of LTRs. Here, we conducted an airway microbial study of LTRs and analyzed the airway microbiota together with infection, acute rejection, and clinically stable recipients. We found different airway microbiota between infection and acute rejection and identify several genera associated with each outcome and constructed a model that incorporates airway microbiota and clinical parameters to predict outcome. This study highlighted that the airway microbiota was a potential indicator to differentiate between infection and acute rejection after LT.

The Interactions of Airway Bacterial and Fungal Communities in Clinically Stable Asthma.

Dysbiotic airway microbiota play important roles in the inflammatory progression of asthma, and exploration of airway microbial interactions further elucidates asthma pathogenesis. However, little is known regarding the airway bacterial-fungal interactions in asthma patients. We conducted a cross-sectional survey of the sputum bacterial and fungal microbiota from 116 clinically stable asthma patients and 29 healthy controls using 16S rRNA gene and ITS1 sequencing. Compared with healthy individuals, asthma patients exhibited a significantly altered microbiota and increased bacterial and fungal alpha diversities in the airway. Microbial genera Moraxella, Capnocytophaga, and Ralstonia (bacteria) and Schizophyllum, Candida, and Phialemoniopsis (fungi) were more abundant in the asthma airways, while Rothia, Veillonella and Leptotrichia (bacteria) and Meyerozyma (fungus) were increased in healthy controls. The Moraxellaceae family and their genus Moraxella were significantly enriched in asthma patients compared with healthy controls (80.5-fold, P = 0.007 and 314.7-fold, P = 0.027, respectively). Moreover, Moraxellaceae, along with Schizophyllum, Candida, and Aspergillus (fungal genera), were positively associated with fungal alpha diversity. Correlation networks revealed 3 fungal genera (Schizophyllum, Candida, and Aspergillus) as important airway microbes in asthma that showed positive correlations with each other and multiple co-exclusions with other common microbiota. Moraxellaceae members were positively associated with asthma-enriched fungal taxa but negatively related to several healthy-enriched bacterial taxa. Collectively, our findings revealed an altered microbiota and complex microbial interactions in the airways of asthma patients. The Moraxellaceae family and their genus Moraxella, along with 3 important fungal taxa, showed significant interactions with the airway microbiota, providing potential insights into the novel pathogenic mechanisms of asthma.

Skin microbiome differences relate to the grade of acne vulgaris.

The skin microbiome plays important roles in the pathogenesis and development of acne. We aimed to investigate the facial skin microbiome of acne and microbiome differences related to different grades of acne. Skin swabs from nine healthy controls and 67 acne patients were collected, and the skin microbiomes were analyzed using 16S rRNA gene sequencing. Compared with healthy controls, acne patients harbored significantly altered skin microbiomes. The skin microbiomes of patients with grade 1-3 acne were similar, but patients with grade 4 acne showed a significantly different skin microbiome compared with grade 1-3 acne, including increased alpha diversity and increased proportions of four Gram-negative bacteria (Faecalibacterium, Klebsiella, Odoribacter and Bacteroides). In conclusion, acne patients harbored an altered skin microbiome, and more significant dysbiosis was found in patients with grade 4 acne (severe acne). Our findings may provide evidence for the pathogenic mechanisms of acne and microbial-based strategies to avoid and treat acne, especially grade 4 acne.

Septic patients in the intensive care unit present different nasal microbiotas.

AIM: The primary objective of this study was to evaluate correlations among mortality, intensive care unit (ICU) length of stay and airway microbiotas in septic patients. MATERIALS & METHODS: A deep-sequencing analysis of the 16S rRNA gene V4 region was performed. RESULTS: The nasal microbiota in septic patients was dominated by three nasal bacterial types (Corynebacterium, Staphylococcus and Acinetobacter). The Acinetobacter type was associated with the lowest diversity and longest length of stay (median: 9 days), and the Corynebacterium type was associated with the shortest length of stay. We found that the Acinetobacter type in the >9-day group was associated with the highest mortality (33%). CONCLUSION: Septic patients have three nasal microbiota types, and the nasal microbiota is related to the length of stay and mortality.

Moderate-Intensity Exercise Affects Gut Microbiome Composition and Influences Cardiac Function in Myocardial Infarction Mice.

Physical exercise is commonly regarded as protective against cardiovascular disease (CVD). Recent studies have reported that exercise alters the gut microbiota and that modification of the gut microbiota can influence cardiac function. Here, we focused on the relationships among exercise, the gut microbiota and cardiac function after myocardial infarction (MI). Four-week-old C57BL/6J mice were exercised on a treadmill for 4 weeks before undergoing left coronary artery ligation. Cardiac function was assessed using echocardiography. Gut microbiomes were evaluated post-exercise and post-MI using 16S rRNA gene sequencing on an Illumina HiSeq platform. Exercise training inhibited declines in cardiac output and stroke volume in post-MI mice. In addition, physical exercise and MI led to alterations in gut microbial composition. Exercise training increased the relative abundance of Butyricimonas and Akkermansia. Additionally, key operational taxonomic units were identified, including 24 lineages (mainly from Bacteroidetes, Barnesiella, Helicobacter, Parabacteroides, Porphyromonadaceae, Ruminococcaceae, and Ureaplasma) that were closely related to exercise and cardiac function. These results suggested that exercise training improved cardiac function to some extent in addition to altering the gut microbiota; therefore, they could provide new insights into the use of exercise training for the treatment of CVD.

Oropharyngeal and Sputum Microbiomes Are Similar Following Exacerbation of Chronic Obstructive Pulmonary Disease.

Growing evidence suggests that the airway microbiota might be involved in acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Understanding this relationship requires examination of a large-scale population for a long duration to accurately monitor changes in the microbiome. This type of longitudinal study requires an appropriate sampling strategy; two options are the collection of sputum or oropharyngeal swabs. Comparative analysis of the changes that occur in these two specimen types has not been previously performed. This observational study was conducted to explore oropharyngeal microbial community dynamics over time and to examine the relationship between oropharyngeal swabs and sputum. A total of 114 samples were collected from four patients suffering from severe AECOPD. Bacterial and fungal communities were evaluated using 16S rRNA and ITS sequencing. Inter-individual differences were found in bacterial community structure, but the core genera were shared by both sample types and included 32 lineages. Most of the core genera were members of the phyla Proteobacteria, Firmicutes and Ascomycota. Although the oropharyngeal samples showed higher bacterial alpha diversity, the two sample types generated rather similar taxonomic profiles. These results suggest that the sputum microbiome is remarkably similar to the oropharyngeal microbiome. Thus, oropharyngeal swabs can potentially be used instead of sputum samples for patients with exacerbation of COPD.

The Potential Effect of Oral Microbiota in the Prediction of Mucositis During Radiotherapy for Nasopharyngeal Carcinoma.

BACKGROUND: Oral mucositis is probably the most debilitating complication that can arise in treating a patient with head and neck cancer. Little is known about the impacts of oral microbiota on the initiation and progression of mucositis. METHODS: Based on 16S rRNA gene sequencing, dynamic changes in oral bacterial profile as well as correlations between the severity of mucositis and bacterial shifts during radiotherapy were investigated. FINDINGS: Our results revealed that bacterial community structure altered progressively during radiation therapy, in parallel with a marked increase in the relative abundance of some Gram-negative bacteria. Patients who eventually developed severe mucositis harbored a significantly lower bacterial alpha diversity and higher abundance of Actinobacillus during the phase of erythema - patchy mucositis. Accordingly, a random forest model for predicting exacerbation of mucositis was generated, which achieved a high predictive accuracy (AUC) of 0.89. INTERPRETATION: Oral microbiota changes correlate with the progression and aggravation of radiotherapy-induced mucositis in patients with nasopharyngeal carcinoma. Microbiota-based strategies can be used for the early prediction and prevention of the incidence of severe mucositis during radiotherapy.

[Analysis of Theory and Performance of Multi Layer Graphene Nanoribbons Photodetector].

Multilayer graphene, with wide absorption spectrum and unique photoelectric properties, is an ideal material to make the next generation of photoelectric detector. Taking graphene interband tunneling theory as the foundation, a photoelectric detector model with the structure of multilayer graphene nanoribbons was proposed. Nanoribbons which contacted with source and drain electrode at the end were sandwiched between the semiconductor substrate and the top and back gate. Using this model, a photoelectric conversion mechanism of multilayer graphene nanoribbon detector was established. It discussed the working principle of the detector at different top gate voltage, studied the relationship between the source-drain current and the incident light energy, researched the influence of the bias voltage, the length of depletion and the values of band gap on the dark current, and analyzed the change of detector responsibility and detectivity with the incident light energy under the different parameters. The results show that, the responsibility of detector increases with the layers of nanoribbons, and are affected by the band gap, the length of depletion and the bias voltage. The maximum responsibility up to 10(3) A·W(-1); By limiting on the top gate voltage, the band gap and other variables can control the dark current of system and increase the detectivity, the detectivity up to a maximum value of 10(9) cm Hz(1/2)·W(-1). The structure of multilayer graphene nanoribbons can enhance the absorption of the incident light, improve the sensitivity of the detector and the detection capability of weak light, and realize the detection from THz to far infrared wavelength of incident light. The detection performance is far better than that of many quantum structures and narrow-band semiconductor structure of photoelectric detector.

[Climate change risk of nature reserve and its assessment: A case study of Dalinuoer National Nature Reserve in Inner Mongolia Autonomous Region]. / è‡ªç„¶ä¿æŠ¤åŒºæ°”å€™å˜åŒ–é£Žé™©åŠå ¶è¯„ä¼°­­ä»¥è¾¾é‡Œè¯ºå°”国家级自然保护区为例.

According to the theoretical framework of addressing climate change based on risk mana-gement and the challenge to nature reserve management under climate change, climate change risk of nature reserve was analyzed and defined. Focus on birds and water habitat, grassland habitat, forest habitat, wetland habitat in Dalinuoer Nature Reserve, risk assessment method of nature reserve under climate change was formulated, climate change risks to Dalinuoer Nature Reserve and its habitats were assessed and predicted. The results showed that, during the period from 1997 to 2010, there was significant volatility in dynamic changes of climate change risks to Dalinuoer Nature Reserve and waterbody, grassland, forest, wetland in the region, Dalinuoer Nature Reserve and its habitats were in status of risk in 1999, 2001, 2005 and 2008, wetland habitat was also in status of risk in 2002 and 2004. Under scenario A, B and C, climate change risks to Dalinuoer Nature Reserve and waterbody, grassland, forest, wetland in the region would be more serious in 2020 and 2030, compared with the 2010 level. Climate change risks to different habitats were different significantly, with most serious climate change risk to wetland habitat due to its sensitivity to climate change and rich bird resources. The effect of climate change on nature reserve and related risk would be aggravated by excess utilization of water resource and grassland resource. As climate change risks had appeared in Dalinuoer Nature Reserve, risk management associated with climate change could greatly help to maintain and enhance biodiversity protection function of nature reserves.

Sputum Bacterial and Fungal Dynamics during Exacerbations of Severe COPD.

The changes in the microbial community structure during acute exacerbations of severe chronic obstructive pulmonary disease (COPD) in hospitalized patients remain largely uncharacterized. Therefore, further studies focused on the temporal dynamics and structure of sputum microbial communities during acute exacerbation of COPD (AECOPD) would still be necessary. In our study, the use of molecular microbiological techniques provided insight into both fungal and bacterial diversities in AECOPD patients during hospitalization. In particular, we examined the structure and varieties of lung microbial community in 6 patients with severe AECOPD by amplifying 16S rRNA V4 hyper-variable and internal transcribed spacer (ITS) DNA regions using barcoded primers and the Illumina sequencing platform. Sequence analysis showed 261 bacterial genera representing 20 distinct phyla, with an average number of genera per patient of >157, indicating high diversity. Acinetobacter, Prevotella, Neisseria, Rothia, Lactobacillus, Leptotrichia, Streptococcus, Veillonella, and Actinomyces were the most commonly identified genera, and the average total sequencing number per sputum sample was >10000 18S ITS sequences. The fungal population was typically dominated by Candia, Phialosimplex, Aspergillus, Penicillium, Cladosporium and Eutypella. Our findings highlight that COPD patients have personalized structures and varieties in sputum microbial community during hospitalization periods.