AI in microbiome-related healthcare.

Artificial intelligence (AI) has the potential to transform clinical practice and healthcare. Following impressive advancements in fields such as computer vision and medical imaging, AI is poised to drive changes in microbiome-based healthcare while facing challenges specific to the field. This review describes the state-of-the-art use of AI in microbiome-related healthcare.

The FeatureCloud Platform for Federated Learning in Biomedicine: Unified Approach.

Background: Machine learning and artificial intelligence have shown promising results in many areas and are driven by the increasing amount of available data. However, these data are often distributed across different institutions and cannot be easily shared owing to strict privacy regulations. Federated learning (FL) allows the training of distributed machine learning models without sharing sensitive data.

Longitudinal, Multi-Platform Metagenomics Yields a High-Quality Genomic Catalog and Guides an Model for Cheese Communities.

Microbiomes are intricately intertwined with human health, geochemical cycles, and food production. While many microbiomes of interest are highly complex and experimentally intractable, cheese rind microbiomes have proven to be powerful model systems for the study of microbial interactions. To provide a more comprehensive view of the genomic potential and temporal dynamics of cheese rind communities, we combined longitudinal, multi-platform metagenomics of three ripening washed-rind cheeses with whole-genome sequencing of community isolates.

Native mass spectrometry-based metabolomics identifies metal-binding compounds.

Although metals are essential for the molecular machineries of life, systematic methods for discovering metal-small molecule complexes from biological samples are limited. Here, we describe a two-step native electrospray ionization-mass spectrometry method, in which post-column pH adjustment and metal infusion are combined with ion identity molecular networking, a rule-based data analysis workflow. This method enabled the identification of metal-binding compounds in complex samples based on defined mass (m/z) offsets of ion species with the same chromatographic profiles.

Experimental approaches to tracking mobile genetic elements in microbial communities.

Horizontal gene transfer is an important mechanism of microbial evolution and is often driven by the movement of mobile genetic elements between cells. Due to the fact that microbes live within communities, various mechanisms of horizontal gene transfer and types of mobile elements can co-occur. However, the ways in which horizontal gene transfer impacts and is impacted by communities containing diverse mobile elements has been challenging to address.

A Proposed Chaperone of the Bacterial Type VI Secretion System Functions To Constrain a Self-Identity Protein.

The bacterium can communicate identity through the secretion of the self-identity protein IdsD via the type VI secretion (T6S) system. IdsD secretion is essential for self-versus-nonself recognition behaviors in these populations. Here we provide an answer to the unresolved question of how the activity of a T6S substrate, such as IdsD, is regulated before secretion.

A single point mutation in a TssB/VipA homolog disrupts sheath formation in the type VI secretion system of Proteus mirabilis.

The type VI secretion (T6S) system is a molecular device for the delivery of proteins from one cell into another. T6S function depends on the contractile sheath comprised of TssB/VipA and TssC/VipB proteins. We previously reported on a mutant variant of TssB that disrupts T6S-dependent export of the self-identity protein, IdsD, in the bacterium Proteus mirabilis.