The diagnosis of endometriosis is typically delayed by years for the unexclusive symptom and the traumatic diagnostic method. Several studies have demonstrated that gut microbiota and cervical mucus potentially can be used as auxiliary diagnostic biomarkers. However, none of the previous studies has compared the robustness of endometriosis classifiers based on microbiota of different body sites or demonstrated the correlation among microbiota of gut, cervical mucus, and peritoneal fluid of endometriosis, searching for alternative diagnostic approaches. Herein, we enrolled 41 women (control, n = 20; endometriosis, n = 21) and collected 122 well-matched samples, derived from feces, cervical mucus, and peritoneal fluid, to explore the nature of microbiome of endometriosis patients. Our results indicated that microbial composition is remarkably distinguished between three body sites, with 19 overlapped taxa. Moreover, endometriosis patients harbor distinct microbial communities versus control group especially in feces and peritoneal fluid, with increased abundance of pathogens in peritoneal fluid and depletion of protective microbes in feces. Particularly, genera of Ruminococcus and Pseudomonas were identified as potential biomarkers in gut and peritoneal fluid, respectively. Furthermore, novel endometriosis classifiers were constructed based on taxa selected by a robust machine learning method. These results demonstrated that gut microbiota exceeds cervical microbiota in diagnosing endometriosis. Collectively, this study reveals important insights into the microbial profiling in different body sites of endometriosis, which warrant future exploration into the role of microbiota in endometriosis and highlighted values on gut microbiota in early diagnosis of endometriosis.

Obesity and its related complications pose a serious threat to human health. Short-term low-carbohydrate diet (LCD) intervention without calorie restriction has a significant weight loss effect for overweight/obese people.

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This paper aims to establish evidence for available phosphorous (AP) binding with total nitrogen (N) in subtropical forest soils. Soil organic carbon (SOC), total N, total phosphorous (P) and AP concentration were measured for three contrasting forest types in southern China: Masson pine forest (MPF), coniferous and broadleaved mixed forest (CBMF) and monsoon evergreen broadleaved forest (MEBF). A pot experiment with N addition was conducted to confirm the dominant factor to affect on soil AP concentration. The results showed that mean soil total N concentration in 0–10 cm soil layer was 440±50 for MPF, 840±80 for CBMF and 1020±50 mg kg−1 for MEBF, respectively. The mean soil AP concentration in 0–10 cm soil layer was 2.67±0.87 for MPF, 2.65±0.58 for CBMF, 4.10±0.29 mg kg−1 for MEBF, respectively. The soil total N concentration could explain about 70% of the variations in soil AP concentration in the top 20 cm soil layers in the three forest types. A pot experiment with N addition also showed an increase of AP concentration from 2.56 to 5.63 mg kg−1, when N addition increased from 5 g to 17 g NH4NO3. Our results therefore suggested that N addition significantly increased soil AP concentration, which might be beneficial for stabilizing the net primary production of subtropical forests that were limited by soil AP. This finding may provide a theory basis for tropical and subtropical forests management.

We investigated the effects of major environmental drivers associated with urbanization on species diversity and plant functional traits (PFTs) in the remnant subtropical evergreen broad-leaved forests in Metropolitan Guangzhou (Guangdong, China). Twenty environmental factors including topography, light, and soil properties were used to quantify the effects of urbanization. Vegetation data and soil properties were collected from 30 400-m(2) plots at 6 study sites in urban and rural areas. The difference of plant species diversity and PFTs of remnant forests between urban and rural areas were analyzed. To discern the complex relationships, multivariate statistical analyses (e.g., canonical correspondence analysis and regression analysis) were employed. Pioneer species and stress-tolerant species can survive and vigorously establish their population dominance in the urban environment. The native herb diversity was lower in urban forests than in rural forests. Urban forests tend to prefer the species with Mesophanerophyte life form. In contrast, species in rural forests possessed Chamaephyte and Nanophanerophyte life forms and gravity/clonal growth dispersal mode. Soil pH and soil nutrients (K, Na, and TN) were positively related to herb diversity, while soil heavy metal concentrations (Cu) were negatively correlated with herb diversity. The herb plant species diversity declines and the species in the remnant forests usually have stress-tolerant functional traits in response to urbanization. The factors related to urbanization such as soil acidification, nutrient leaching, and heavy metal pollution were important in controlling the plant diversity in the forests along the urban-rural gradients. Urbanization affects the structure and functional traits of remnant subtropical evergreen broad-leaved forests.

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Advances in next-generation sequencing (NGS) have revolutionized microbial studies in many fields, especially in clinical investigation. As the second human genome, microbiota has been recognized as a new approach and perspective to understand the biological and pathologic basis of various diseases. However, massive amounts of sequencing data remain a huge challenge to researchers, especially those who are unfamiliar with microbial data analysis. The mathematic algorithm and approaches introduced from another scientific field will bring a bewildering array of computational tools and acquire higher quality of script experience. Moreover, a large cohort research together with extensive meta-data including age, body mass index (BMI), gender, medical results, and others related to subjects also aggravate this situation. Thus, it is necessary to develop an efficient and convenient software for clinical microbiome data analysis. EasyMicroPlot (EMP) package aims to provide an easy-to-use microbial analysis tool based on R platform that accomplishes the core tasks of metagenomic downstream analysis, specially designed by incorporation of popular microbial analysis and visualization used in clinical microbial studies. To illustrate how EMP works, 694 bio-samples from Guangdong Gut Microbiome Project (GGMP) were selected and analyzed with EMP package. Our analysis demonstrated the influence of dietary style on gut microbiota and proved EMP package's powerful ability and excellent convenience to address problems for this field.

The actinobacterial genus Frankia establishes nitrogen-fixing root nodule symbioses with specific hosts within the nitrogen-fixing plant clade. Of four genetically distinct subgroups of Frankia, cluster I, II, and III strains are capable of forming effective nitrogen-fixing symbiotic associations, while cluster IV strains generally do not. Cluster II Frankia strains have rarely been detected in soil devoid of host plants, unlike cluster I or III strains, suggesting a stronger association with their host. To investigate the degree of host influence, we characterized the cluster II Frankia strain distribution in rhizosphere soil in three locations in northern California. The presence/absence of cluster II Frankia strains at a given site correlated significantly with the presence/absence of host plants on the site, as determined by glutamine synthetase (glnA) gene sequence analysis, and by microbiome analysis (16S rRNA gene) of a subset of host/nonhost rhizosphere soils. However, the distribution of cluster II Frankia strains was not significantly affected by other potential determinants such as host-plant species, geographical location, climate, soil pH, or soil type. Rhizosphere soil microbiome analysis showed that cluster II Frankia strains occupied only a minute fraction of the microbiome even in the host-plant-present site and further revealed no statistically significant difference in the ␣-diversity or in the microbiome composition between the host-plantpresent or -absent sites. Taken together, these data suggest that host plants provide a factor that is specific for cluster II Frankia strains, not a general growthpromoting factor. Further, the factor accumulates or is transported at the site level, i.e., beyond the host rhizosphere.IMPORTANCE Biological nitrogen fixation is a bacterial process that accounts for a major fraction of net new nitrogen input in terrestrial ecosystems. Transfer of fixed nitrogen to plant biomass is especially efficient via root nodule symbioses, which represent evolutionarily and ecologically specialized mutualistic associations. Frankia spp. (Actinobacteria), especially cluster II Frankia spp., have an extremely broad host range, yet comparatively little is known about the soil ecology of these organisms in relation to the host plants and their rhizosphere microbiomes. This study reveals a strong influence of the host plant on soil distribution of cluster II Frankia spp.