RiboTaxa: combined approaches for rRNA genes taxonomic resolution down to the species level from metagenomics data revealing novelties

Gene horizontal transfers and functional diversity negatively correlated with bacterial taxonomic diversity along a nitrogen gradient

Horizontal gene transfer (HGT) mediated diversification is a critical force driving evolutionary and ecological processes. However, how HGT might relate to anthropogenic activity such as nitrogen addition, and its subsequent effect on functional diversity and cooccurrence networks remain unknown. Here we approach this knowledge gap by blending bacterial 16S rRNA gene amplicon and shotgun metagenomes from a platform of cessation of nitrogen additions and continuous nitrogen additions. We found that bacterial HGT events, functional genes, and virus diversities increased whereas bacterial taxonomic diversity decreased by nitrogen additions, resulting in a counterintuitive strong negative association between bacterial taxonomic and functional diversities. Nitrogen additions, especially the ceased one, complexified the cooccurrence network by increasing the contribution of vitamin B12 auxotrophic Acidobacteria, indicating cross-feeding. These findings advance our perceptions of the causes and consequences of the diversification process in community ecology.

Deep underground metagenome-assembled genomes from hydrothermal spring

We report 19 metagenome-assembled genomes from a deep underground microbial community found in mineralized hydrothermal spring in the Baksan Neutrino Observatory tunnel. The community is predominantly occupied by members of Pseudomonadota (Gamma-, Beta-, and Alphaproteobacteria), Planctomycetota, Myxococcota, Nitrospirota, Cyanobacteria, Gemmatimonadota, and Armatimonadota.

DeepMPTB: a vaginal microbiome-based deep neural network as artificial intelligence strategy for efficient preterm birth prediction

In recent decades, preterm birth (PTB) has become a significant research focus in the healthcare field, as it is a leading cause of neonatal mortality worldwide. Using five independent study cohorts including 1290 vaginal samples from 561 pregnant women who delivered at term (n = 1029) or prematurely (n = 261), we analysed vaginal metagenomics data for precise microbiome structure characterization. Then, a deep neural network (DNN) was trained to predict term birth (TB) and PTB with an accuracy of 84.10% and an area under the receiver operating characteristic curve (AUROC) of 0.875 ± 0.11. During a benchmarking process, we demonstrated that our DL model outperformed seven currently used machine learning algorithms. Finally, our results indicate that overall diversity of the vaginal microbiota should be taken in account to predict PTB and not specific species. This artificial-intelligence based strategy should be highly helpful for clinicians in predicting preterm birth risk, allowing personalized assistance to address various health issues. DeepMPTB is open source and free for academic use. It is licensed under a GNU Affero General Public License 3.0 and is available at https://deepmptb.streamlit.app/ . Source code is available at https://github.com/oschakoory/DeepMPTB and can be easily installed using Docker ( https://www.docker.com/ ).

Protist predation promotes antimicrobial resistance spread through antagonistic microbiome interactions

Antibiotic resistance has grown into a major public health threat. In this study, we reveal predation by protists as an overlooked driver of antibiotic resistance dissemination in the soil microbiome. While previous studies have primarily focused on the distribution of antibiotic resistance genes, our work sheds light on the pivotal role of soil protists in shaping antibiotic resistance dynamics. Using a combination of metagenomics and controlled experiments in this study, we demonstrate that protists cause an increase in antibiotic resistance. We mechanistically link this increase to a fostering of antimicrobial activity in the microbiome. Protist predation gives a competitive edge to bacteria capable of producing antagonistic secondary metabolites, which secondary metabolites promote in turn antibiotic-resistant bacteria. This study provides insights into the complex interplay between protists and soil microbiomes in regulating antibiotic resistance dynamics. This study highlights the importance of top-down control on the spread of antibiotic resistance and directly connects it to cross-kingdom interactions within the microbiome. Managing protist communities may become an important tool to control outbreaks of antibiotic resistance in the environment.

Mock community experiments can inform on the reliability of eDNA metabarcoding data: a case study on marine phytoplankton

Environmental DNA metabarcoding is increasingly implemented in biodiversity monitoring, including phytoplankton studies. Using 21 mock communities composed of seven unicellular diatom and dinoflagellate algae, assembled with different composition and abundance by controlling the number of cells, we tested the accuracy of an eDNA metabarcoding protocol in reconstructing patterns of alpha and beta diversity. This approach allowed us to directly evaluate both qualitative and quantitative metabarcoding estimates. Our results showed non-negligible rates (17-25%) of false negatives (i.e., failure to detect a taxon in a community where it was included), for three taxa. This led to a statistically significant underestimation of metabarcoding-derived alpha diversity (Wilcoxon p = 0.02), with the detected species richness being lower than expected (based on cell numbers) in 8/21 mock communities. Considering beta diversity, the correlation between metabarcoding-derived and expected community dissimilarities was significant but not strong (R2 = 0.41), indicating suboptimal accuracy of metabarcoding results. Average biovolume and rDNA gene copy number were estimated for the seven taxa, highlighting a potential, though not exhaustive, role of the latter in explaining the recorded biases. Our findings highlight the importance of mock communities for assessing the reliability of phytoplankton eDNA metabarcoding studies and identifying their limitations.

Temporal Changes in the Skin Microbiome of Epidermolysis Bullosa Patients following the Application of Wound Dressings

OBJECTIVE

Epidermolysis bullosa (EB) is a group of rare hereditary skin disorders characterized by the formation of painful blisters, erosions, and ulcers. In addition, the wounds can easily become infected with different pathogens. Therefore, the dynamics in the microbial populations across the various stages of EB can shed light on pathophysiology, the effect of treatment, and the factors involved in its recovery, but they are understudied. We thus sought to characterize the skin microbiome among patients with EB over time.

METHODS

A prospective study conducted in the pediatric dermatology clinic at Soroka Medical Center, Beer-Sheva, Israel. Children (0-18) with simplex and recessive dystrophic EB were sampled at two different time points: before a therapeutic regimen and 90 days (±14 days) later. Samples were obtained from lesional skin (wound), healthy, non-lesional skin, and seborrheic skin (forehead). Samples were subject to 16S rRNA amplicon sequencing. Analyses performed included comparisons of relative abundance at the phyla and genera taxonomic levels, alpha and beta diversity comparisons, and differential abundance.

RESULTS

32 children with EB were enrolled, for whom 192 skin microbiome samples were obtained. Lesional skin samples harbored significantly less Bacteroidota and Fusobacteriota before the initiation of treatment. Following topical dressing, we observed more Firmicutes and less Proteobacteria in lesional skin samples than healthy and seborrheic skin samples. In addition, Staphylococcus was significantly more abundant in lesional samples than in non-lesional and seborrheic samples following treatment.

CONCLUSIONS

Our study recaptured the reduced bacterial diversity and increased staphylococcal carriage in EB patients, showing a potential effect of topical dressing either directly on the wound microbiome or indirectly through the contribution towards skin healing. The detection of Firmicutes in general, and S. aureus specifically, commensurate with the application of a wound dressing may warrant the use of additional treatment methods to facilitate wound healing. Future studies in these patients should prospectively correlate the temporal changes in the microbiome associated with various treatment modalities in order to optimize the care of EB patients.