Biofilm-forming bacteria have the potential to contribute to the health, physiology, behavior, and ecology of the host and serve as its first line of defense against adverse conditions in the environment. While metabarcoding and metagenomic information furthers our understanding of microbiome composition, fewer studies use cultured samples to study the diverse interactions among the host and its microbiome, as cultured representatives are often lacking. This study examines the surface microbiomes cultured from three shallow-water coral species and two whale species. These unique marine animals place strong selective pressures on their microbial symbionts and contain members under similar environmental and anthropogenic stress. We developed an intense cultivation procedure, utilizing a suite of culture conditions targeting a rich assortment of biofilm-forming microorganisms. We identified 592 microbial isolates contained within 15 bacterial orders representing 50 bacterial genera, and two fungal species. Culturable bacteria from coral and whale samples paralleled taxonomic groups identified in culture-independent surveys, including 29% of all bacterial genera identified in the Megaptera novaeangliae skin microbiome through culture-independent methods. This microbial repository provides raw material and biological input for more nuanced studies which can explore how members of the microbiome both shape their micro-niche and impact host fitness.
We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets.
Large deletions and duplications are the most frequent causative mutations in Becker muscular dystrophy (BMD), but genetic profile varied greatly among reports. We performed a comprehensive molecular investigation in 95 Chinese BMD patients. All patients were divided into three subtypes: normal muscle strength (type 1) in 18 cases, quadriceps myopathy (type 2) in 20 cases, and limb-girdle weakness (type 3) in 57 cases. Nineteen cases (20.0%) had small mutations and 76 cases (80.0%) had major rearrangements, including 67 cases (70.5%) of exonic deletions and 9 cases (9.5%) of exonic duplications. We identified 50 cases (65.8%) of in-frame mutations, and 26 cases (34.2%) of frame-shift mutations. The frequency of deletion in exons 13-19 was 30.6% in type 1 patients, 9.7% in type 2 patients, and 10.4% in type 3 patients. The frequency of deletion in exons 45-55 was 28.6% in type 1 patients, 40.8% in type 2, and 50.0% in type 3 patients. All major rearrangements of DMD gene in type 1 patients were also observed in type 3 patients. Our study suggested that frame-shift mutation was not rare in Chinese BMD patients. Although no difference was observed on the forms of DMD gene mutations among the three types of patients, the mutation in proximal region of DMD gene has higher frequency for patients without weakness. Effect of exon skipping for DMD depends on the size and location of the mutation. Additional studies are required to determine whether exon-skipping strategies in proximal region of DMD gene could yield more functional dystrophin.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.