Diversity of plasmodial slime molds (myxomycetes) in coastal, mountain, and community forests of Puerto Galera, Oriental Mindoro, the Philippines

AbstractNo profiling of diversity of myxomycetes has ever been conducted in one of the biodiversity hotspot areas in the Philippine archipelago, and this necessitates a swift survey of myxomycetes in Puerto Galera, Oriental Mindoro. An assessment of diversity of myxomycetes collected from seven collecting points of three different forest types in the study area showed a total of 926 records of myxomycetes. Of which, 42 morphospecies belonging to 16 genera are reported in this study. Species richness of myxomycetes was higher in collecting points that were found in inland lowland mountain forests, but the most taxonomically diverse species was found in coastal forests. Myxomycete species, namely, Arcyria cinerea, Diderma hemisphaericum, Physarum echinosporum, Lamproderma scintillans, and Stemonitis fusca, were found in all the collecting points. Manmade disturbances and forest structure may affect the occurrence of myxomycetes

Data from: Genetic barcoding of dark-spored myxomycetes (Amoebozoa)—Identification, evaluation and application of a sequence similarity threshold for species differentiation in NGS studies

Unicellular, eukaryotic organisms (protists) play a key role in soil food webs as major predators of microorganisms. However, due to the polyphyletic nature of protists, no single universal barcode can be established for this group, and the structure of many protistean communities remains unresolved. Plasmodial slime moulds (Myxogastria or Myxomycetes) stand out among protists by their formation of fruit bodies, which allow for a morphological species concept. By Sanger sequencing of a large collection of morphospecies, this study presents the largest database to date of dark-spored myxomycetes and evaluate a partial 18S SSU gene marker for species annotation. We identify and discuss the use of an intraspecific sequence similarity threshold of 99.1% for species differentiation (OTU picking) in environmental PCR studies (ePCR) and estimate a hidden diversity of putative species, exceeding those of described morphospecies by 99%. When applying the identified threshold to an ePCR data set (including sequences from both NGS and cloning), we find 64 OTUs of which 21.9% had a direct match (>99.1% similarity) to the database and the remaining had on average 90.2 ± 0.8% similarity to their best match, thus thought to represent undiscovered diversity of dark-spored myxomycetes

Community-intrinsic properties enhance keratin degradation from bacterial consortia

Although organic matter may accumulate sometimes (e.g. lignocellulose in peat bog), most natural biodegradation processes are completed until full mineralization. Such transformations are often achieved by the concerted action of communities of interacting microbes, involving different species each performing specific tasks. These interactions can give rise to novel "community-intrinsic" properties, through e.g. activation of so-called "silent genetic pathways" or synergistic interplay between microbial activities and functions. Here we studied the microbial community-based degradation of keratin, a recalcitrant biological material, by four soil isolates, which have previously been shown to display synergistic interactions during biofilm formation; Stenotrophomonas rhizophila, Xanthomonas retroflexus, Microbacterium oxydans and Paenibacillus amylolyticus. We observed enhanced keratin weight loss in cultures with X. retroflexus, both in dual and four-species co-cultures, as compared to expected keratin degradation by X. retroflexus alone. Additional community intrinsic properties included accelerated keratin degradation rates and increased biofilm formation on keratin particles. Comparison of secretome profiles of X. retroflexus mono-cultures to co-cultures revealed that certain proteases (e.g. serine protease S08) were significantly more abundant in mono-cultures, whereas co-cultures had an increased abundance of proteins related to maintaining the redox environment, e.g. glutathione peroxidase. Hence, one of the mechanisms related to the community intrinsic properties, leading to enhanced degradation from co-cultures, might be related to a switch from sulfitolytic to proteolytic functions between mono- and co-cultures, respectively

Chemically informed analyses of metabolomics mass spectrometry data with Qemistree

Untargeted mass spectrometry is employed to detect small molecules in complex biospecimens, generating data that are difficult to interpret. We developed Qemistree, a data exploration strategy based on the hierarchical organization of molecular fingerprints predicted from fragmentation spectra. Qemistree allows mass spectrometry data to be represented in the context of sample metadata and chemical ontologies. By expressing molecular relationships as a tree, we can apply ecological tools that are designed to analyze and visualize the relatedness of DNA sequences to metabolomics data. Here we demonstrate the use of tree-guided data exploration tools to compare metabolomics samples across different experimental conditions such as chromatographic shifts. Additionally, we leverage a tree representation to visualize chemical diversity in a heterogeneous collection of samples. The Qemistree software pipeline is freely available to the microbiome and metabolomics communities in the form of a QIIME2 plugin, and a global natural products social molecular networking workflow. [Figure not available: see fulltext.]</p

Chemically informed analyses of metabolomics mass spectrometry data with Qemistree

Untargeted mass spectrometry is employed to detect small molecules in complex biospecimens, generating data that are difficult to interpret. We developed Qemistree, a data exploration strategy based on the hierarchical organization of molecular fingerprints predicted from fragmentation spectra. Qemistree allows mass spectrometry data to be represented in the context of sample metadata and chemical ontologies. By expressing molecular relationships as a tree, we can apply ecological tools that are designed to analyze and visualize the relatedness of DNA sequences to metabolomics data. Here we demonstrate the use of tree-guided data exploration tools to compare metabolomics samples across different experimental conditions such as chromatographic shifts. Additionally, we leverage a tree representation to visualize chemical diversity in a heterogeneous collection of samples. The Qemistree software pipeline is freely available to the microbiome and metabolomics communities in the form of a QIIME2 plugin, and a global natural products social molecular networking workflow

Asthma and Wheeze Severity and the Oropharyngeal Microbiota in Children and Adolescents.

RATIONALE There is a major unmet need for improving the care of children and adolescents with severe asthma and wheeze. Identification of factors contributing to disease severity may lead to improved diagnostics, biomarkers, or therapies. The airway microbiota may be such a key factor. OBJECTIVE To compare the oropharyngeal airway microbiota of children and adolescents with severe and mild/moderate asthma/wheeze. METHODS Oropharyngeal swab samples from school-age and pre-school children in the European U-BIOPRED multicenter study of severe asthma, all receiving severity-appropriate treatment, were examined using 16S rRNA gene sequencing. Bacterial taxa were defined as Amplicon Sequence Variants (ASVs). RESULTS We analysed 241 samples from four cohorts; A) 86 school-age children with severe asthma, B) 39 school-age children with mild/moderate asthma, C) 65 pre-school children with severe wheeze and D) 51 pre-school children with mild/moderate wheeze. The most common bacteria were Streptococcus (mean relative abundance 33.5%), Veillonella (10.3%), Haemophilus (7.0%), Prevotella (5.9%) and Rothia (5.5%). Age group (school-age versus pre-school) was associated with the microbiota in beta-diversity analysis (F=3.32, p=0.011) and in a differential abundance analysis (28 significant ASVs). Among all children, we found no significant difference in the microbiota between children with severe and mild/moderate asthma/wheeze in a univariable beta-diversity analysis (F=1.99, p=0.08, n=241), but a significant difference in a multivariable model (F=2.66, p=0.035), including number of exacerbations in the previous year. Age was also significant when expressed as a Microbial Maturity Score (Spearman Rho 0.39, p=4.6e-10), however this score was not associated with asthma/wheeze severity. CONCLUSION There was a modest difference in the oropharyngeal airway microbiota between children with severe and mild/moderate asthma/wheeze across all children but not in individual age groups, and a strong association between the microbiota and age. This suggests the oropharyngeal airway microbiota as an interesting entity in studying asthma severity, but probably without the strength to serve as a biomarker for targeted intervention

Oropharyngeal Microbiota Clusters in Children with Asthma/Wheeze Associate with Allergy, Blood Transcriptomic Immune Pathways and Exacerbations Risk.

RATIONALE Children with preschool wheezing or school-age asthma are reported to have airway microbial imbalances. OBJECTIVE To identify clusters in children with asthma or wheezing using oropharyngeal microbiota profiles. METHODS Oropharyngeal swabs, from the Unbiased BIOmarkers for the Prediction of REspiratory Disease outcomes pediatric asthma/wheezing cohort, were characterized by 16S rRNA gene sequencing and unsupervised hierarchical clustering was performed on the Bray-Curtis β-diversity. Enrichment scores (ESs) of the MSigDB Hallmark gene sets were computed from the blood transcriptome using gene set variation analysis. Children with severe asthma or severe wheezing were followed up for 12-18 months, with assessing the frequency of exacerbations. MEASUREMENTS AND MAIN RESULTS Oropharyngeal samples of 241 children (age range: 1-17 years, 40% female) revealed 4 taxa-driven clusters dominated by Streptococcus, Veillonella, Rothia and Haemophilus, respectively. The clusters showed significant differences in atopic dermatitis, grass pollen sensitization, FEV1 % predicted post-salbutamol, and the annual asthma exacerbation frequency during follow-up. The Veillonella-cluster was the most allergic and included highest percentage of children with ≥2 exacerbations/year during follow-up. The oropharyngeal clusters were different in the ESs of transforming growth factor β (highest in Veillonella-cluster) and Wnt/β-Catenin signaling (highest in Haemophilus-cluster) transcriptomic pathways in blood (all q-values < 0.05). CONCLUSION The analysis of the oropharyngeal microbiota of children with asthma/wheezing identified four clusters with distinct clinical characteristics (phenotypes) that associate with exacerbations' risk and transcriptomic pathways involved in airway remodeling. This suggests that further exploration of the oropharyngeal microbiota may lead to novel pathophysiological insights and potentially new treatment approaches