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Fungi are among the most diverse and ecologically important kingdoms in life. However, the distributional ranges of fungi remain largely unknown as do the ecological mechanisms that shape their distributions1,2. To provide an integrated view of the spatial and seasonal dynamics of fungi, we implemented a globally distributed standardized aerial sampling of fungal spores3. The vast majority of operational taxonomic units were detected within only one climatic zone, and the spatiotemporal patterns of species richness and community composition were mostly explained by annual mean air temperature. Tropical regions hosted the highest fungal diversity except for lichenized, ericoid mycorrhizal and ectomycorrhizal fungi, which reached their peak diversity in temperate regions. The sensitivity in climatic responses was associated with phylogenetic relatedness, suggesting that large-scale distributions of some fungal groups are partially constrained by their ancestral niche. There was a strong phylogenetic signal in seasonal sensitivity, suggesting that some groups of fungi have retained their ancestral trait of sporulating for only a short period. Overall, our results show that the hyperdiverse kingdom of fungi follows globally highly predictable spatial and temporal dynamics, with seasonality in both species richness and community composition increasing with latitude. Our study reports patterns resembling those described for other major groups of organisms, thus making a major contribution to the long-standing debate on whether organisms with a microbial lifestyle follow the global biodiversity paradigms known for macroorganisms4,5.

Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m3 of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition.

BackgroundHuman microbiome studies in clinical settings generally focus on distinguishing the microbiota in health from that in disease at a specific point in time. However, microbiome samples may be associated with disease severity or continuous clinical health indicators that are often assessed at multiple time points. While the temporal data from clinical and microbiome samples may be informative, analysis of this type of data can be problematic for standard statistical methods.ResultsTo identify associations between microbiota and continuous clinical variables measured repeatedly in two studies of the respiratory tract, we adapted a statistical method, the lasso-penalized generalized linear mixed model (LassoGLMM). LassoGLMM can screen for associated clinical variables, incorporate repeated measures of individuals, and address the large number of species found in the microbiome. As is common in microbiome studies, when the number of variables is an order of magnitude larger than the number of samples LassoGLMM can be imperfect in its variable selection. We overcome this limitation by adding a pre-screening step to reduce the number of variables evaluated in the model. We assessed the use of this adapted two-stage LassoGLMM for its ability to determine which microbes are associated with continuous repeated clinical measures.We found associations (retaining a non-zero coefficient in the LassoGLMM) between 10 laboratory measurements and 43 bacterial genera in the oral microbiota, and between 2 cytokines and 3 bacterial genera in the lung. We compared our associations with those identified by the Wilcoxon test after dichotomizing our outcomes and identified a non-significant trend towards differential abundance between high and low outcomes. Our two-step LassoGLMM explained more of the variance seen in the outcome of interest than other variants of the LassoGLMM method.ConclusionsWe demonstrated a method that can account for the large number of genera detected in microbiome studies and repeated measures of clinical or longitudinal studies, allowing for the detection of strong associations between microbes and clinical measures. By incorporating the design strengths of repeated measurements and a prescreening step to aid variable selection, our two-step LassoGLMM will be a useful analytic method for investigating relationships between microbes and repeatedly measured continuous outcomes.

BACKGROUND:No microbe exists in isolation, and few live in environments with only members of their own kingdom or domain. As microbiome studies become increasingly more interested in the interactions between microbes than in cataloging which microbes are present, the variety of microbes in the community should be considered. However, the majority of ecological interaction networks for microbiomes built to date have included only bacteria. Joint association inference across multiple domains of life, e.g., fungal communities (the mycobiome) and bacterial communities, has remained largely elusive. RESULTS:Here, we present a novel extension of the SParse InversE Covariance estimation for Ecological ASsociation Inference (SPIEC-EASI) framework that allows statistical inference of cross-domain associations from targeted amplicon sequencing data. For human lung and skin micro- and mycobiomes, we show that cross-domain networks exhibit higher connectivity, increased network stability, and similar topological re-organization patterns compared to single-domain networks. We also validate in vitro a small number of cross-domain interactions predicted by the skin association network. CONCLUSIONS:For the human lung and skin micro- and mycobiomes, our findings suggest that fungi play a stabilizing role in ecological network organization. Our study suggests that computational efforts to infer association networks that include all forms of microbial life, paired with large-scale culture-based association validation experiments, will help formulate concrete hypotheses about the underlying biological mechanisms of species interactions and, ultimately, help understand microbial communities as a whole.

BackgroundWhile 16S ribosomal RNA (rRNA) sequencing has been used to characterize the lung's bacterial microbiota in human immunodeficiency virus (HIV)-infected individuals, taxonomic studies provide limited information on bacterial function and impact on the host. Metabolic profiles can provide functional information on host-microbe interactions in the lungs. We investigated the relationship between the respiratory microbiota and metabolic profiles in the bronchoalveolar lavage fluid of HIV-infected and HIV-uninfected outpatients.ResultsTargeted sequencing of the 16S rRNA gene was used to analyze the bacterial community structure and liquid chromatography-high-resolution mass spectrometry was used to detect features in bronchoalveolar lavage fluid. Global integration of all metabolic features with microbial species was done using sparse partial least squares regression. Thirty-nine HIV-infected subjects and 20 HIV-uninfected controls without acute respiratory symptoms were enrolled. Twelve mass-to-charge ratio (m/z) features from C18 analysis were significantly different between HIV-infected individuals and controls (false discovery rate (FDR) = 0.2); another 79 features were identified by network analysis. Further metabolite analysis demonstrated that four features were significantly overrepresented in the bronchoalveolar lavage (BAL) fluid of HIV-infected individuals compared to HIV-uninfected, including cystine, two complex carbohydrates, and 3,5-dibromo-L-tyrosine. There were 231 m/z features significantly associated with peripheral blood CD4 cell counts identified using sparse partial least squares regression (sPLS) at a variable importance on projection (VIP) threshold of 2. Twenty-five percent of these 91 m/z features were associated with various microbial species. Bacteria from families Caulobacteraceae, Staphylococcaceae, Nocardioidaceae, and genus Streptococcus were associated with the greatest number of features. Glycerophospholipid and lineolate pathways correlated with these bacteria.ConclusionsIn bronchoalveolar lavage fluid, specific metabolic profiles correlated with bacterial organisms known to play a role in the pathogenesis of pneumonia in HIV-infected individuals. These findings suggest that microbial communities and their interactions with the host may have functional metabolic impact in the lung.

RationaleMicrobiome studies typically focus on bacteria, but fungal species are common in many body sites and can have profound effects on the host. Wide gaps exist in the understanding of the fungal microbiome (mycobiome) and its relationship to lung disease.ObjectivesTo characterize the mycobiome at different respiratory tract levels in persons with and without HIV infection and in HIV-infected individuals with chronic obstructive pulmonary disease (COPD).MethodsOral washes (OW), induced sputa (IS), and bronchoalveolar lavages (BAL) were collected from 56 participants. We performed 18S and internal transcribed spacer sequencing and used the neutral model to identify fungal species that are likely residents of the lung. We used ubiquity-ubiquity plots, random forest, logistic regression, and metastats to compare fungal communities by HIV status and presence of COPD.Measurements and main resultsMycobiomes of OW, IS, and BAL shared common organisms, but each also had distinct members. Candida was dominant in OW and IS, but BAL had 39 fungal species that were disproportionately more abundant than in the OW. Fungal communities in BAL differed significantly by HIV status and by COPD, with Pneumocystis jirovecii significantly overrepresented in both groups. Other fungal species were also identified as differing in HIV and COPD.ConclusionsThis study systematically examined the respiratory tract mycobiome in a relatively large group. By identifying Pneumocystis and other fungal species as overrepresented in the lung in HIV and in COPD, it is the first to determine alterations in fungal communities associated with lung dysfunction and/or HIV, highlighting the clinical relevance of these findings. Clinical trial registered with www.clinicaltrials.gov (NCT00870857).

Pacific evidence-based clinical and translational research is greatly needed. However, there are research challenges that stem from the creation, accessibility, availability, usability, and compliance of data in the Pacific. As a result, there is a growing demand for a complementary approach to the traditional Western research process in clinical and translational research. The data lifecycle is one such approach with a history of use in various other disciplines. It was designed as a data management tool with a set of activities that guide researchers and organizations on the creation, management, usage, and distribution of data. This manuscript describes the data lifecycle and its use by the Biostatistics, Epidemiology, and Research Design core data science team in support of the Center for Pacific Innovations, Knowledge, and Opportunities program. [ABSTRACT FROM AUTHOR]

Background and Aims For symbiotic organisms, their colonization and spread across remote oceanic islands should favour generalists. Plants that form obligate symbiotic associations with microbes dominate island ecosystems, but the relationship between island inhabitance and symbiotic specificity is unclear, especially in the tropics. To fill this gap, we examined the mycorrhizal specificity of the Hawaiian endemic orchid Anoectochilus sandvicensis across multiple populations encompassing its entire geographic distribution. Methods By molecular phylogenetic approaches we identified the mycorrhizal fungi associated with A. sandvicensis across its entire geographic distribution and determined the relationship of these fungi to others found elsewhere around the globe. With richness estimators, we assessed the mycorrhizal specificity of A. sandvicensis within and among islands. We then tested whether geographic proximity of orchid populations was a significant predictor for the presence of particular mycorrhizal fungi and their community composition. Key Results We found that each population of A. sandvicensis forms specific associations with one of three fungi in the genus Ceratobasidium and that the closest relatives of these fungi are globally widespread. Based on diversity indices, A. sandvicensis populations were estimated to partner with one to four mycorrhizal taxa with an estimated total of four compatible mycorrhizal fungi across its entire distribution. However, the geographic proximity of orchid populations was not a significant predictor of mycorrhizal fungal community composition. Conclusions Our findings indicate that the colonization and survival of plant species on even the most remote oceanic islands is not restricted to symbiotic generalists, and that partnering with few, but cosmopolitan microbial symbionts is an alternative means for successful island establishment. We suggest that the spatial distribution and abundance of symbionts in addition to island age, size and isolation should also be taken into consideration for predictions of island biodiversity. [ABSTRACT FROM AUTHOR]

The fungi that reside in the human lungs represent an understudied, but medically relevant comm-unity. From the few studies published on the lung mycobiome, we find that there are fungi in both the healthy and diseased respiratory tract, that these fungi vary widely between individuals, and that there is a trend toward lower fungal diversity among individuals with disease. This review discusses the few studies of the lung mycobiome and details the challenges that accompany lung mycobiome studies. These challenges include sample collection and processing, sequence amplification and processing, and a history of multiple names for species. Some challenges may never be solved, but others can be solved with more data and additional studies of the lung mycobiome. [ABSTRACT FROM PUBLISHER]

Objective: This study aimed to compare cesarean delivery (CD) rates and maternal/neonatal outcomes before and after the 2014 ACOG/SMFM Obstetric Care Consensus for Safe Prevention of Primary CD., Study Design: This retrospective study compared unscheduled CD rates and outcomes of singleton, cephalic, term pregnancies at a tertiary-care teaching maternity hospital. Births 5 years before (March 2009-February 2014) and after (June 2014-May 2019) release of the consensus were included. Chi-square and t -test were used to compare outcomes and logistic regression to adjust for confounders., Results: In this study, 44,001 pregnancies were included, 20,887 before and 23,114 after the consensus. Unscheduled CD rates increased after the consensus (12.9 vs. 14.3%, p  < 0.001); however, there was no difference after adjustment (adjusted odds ratio [aOR], 0.97; 95% confidence interval [CI], 0.91-1.03). Vaginal birth after cesarean (VBAC) deliveries increased among multiparas (4.8 vs. 7.2%, p  < 0.001), which remained significant after adjustment (aOR, 1.51; 95% CI, 1.37-1.66). Postpartum hemorrhage, blood transfusion, and chorioamnionitis were modestly increased, while third-degree perineal lacerations decreased. Uterine rupture and neonatal outcomes were unchanged after adjustment., Conclusion: At our tertiary-care maternity hospital, the Safe Prevention of Primary CD Care Consensus was not associated with a change in unscheduled CD, though VBAC deliveries increased. We did not demonstrate improved neonatal outcomes and showed increased maternal morbidity that warrants further study., Key Points: · Consensus did not change unscheduled cesarean rates.. · Consensus associated with increased hemorrhage.. · Institutional outcomes can assist implementing changes.., Competing Interests: None declared., (Thieme. All rights reserved.)