Astrocytes produce an assortment of signals that promote neuronal maturation according to a precise developmental timeline. Is this orchestrated timing and signaling altered in human neurodevelopmental disorders? To address this question, the astroglial lineage was investigated in two model systems of a developmental disorder with intellectual disability caused by mutant Harvey rat sarcoma viral oncogene homolog (HRAS) termed Costello syndrome: mutant HRAS human induced pluripotent stem cells (iPSCs) and transgenic mice. Human iPSCs derived from patients with Costello syndrome differentiated to astroglia more rapidly in vitro than those derived from wild-type cell lines with normal HRAS, exhibited hyperplasia, and also generated an abundance of extracellular matrix remodeling factors and proteoglycans. Acute treatment with a farnesyl transferase inhibitor and knockdown of the transcription factor SNAI2 reduced expression of several proteoglycans in Costello syndrome iPSC-derived astrocytes. Similarly, mice in which mutant HRAS was expressed selectively in astrocytes exhibited experience-independent increased accumulation of perineuronal net proteoglycans in cortex, as well as increased parvalbumin expression in interneurons, when compared to wild-type mice. Our data indicate that astrocytes expressing mutant HRAS dysregulate cortical maturation during development as shown by abnormal extracellular matrix remodeling and implicate excessive astrocyte-to-neuron signaling as a possible drug target for treating mental impairment and enhancing neuroplasticity.

A new functional gene database, FOAM (Functional Ontology Assignments for Metagenomes), was developed to screen environmental metagenomic sequence datasets. FOAM provides a new functional ontology dedicated to classify gene functions relevant to environmental microorganisms based on Hidden Markov Models (HMMs). Sets of aligned protein sequences (i.e. 'profiles') were tailored to a large group of target KEGG Orthologs (KOs) from which HMMs were trained. The alignments were checked and curated to make them specific to the targeted KO. Within this process, sequence profiles were enriched with the most abundant sequences available to maximize the yield of accurate classifier models. An associated functional ontology was built to describe the functional groups and hierarchy. FOAM allows the user to select the target search space before HMM-based comparison steps and to easily organize the results into different functional categories and subcategories. FOAM is publicly available at http://portal.nersc.gov/project/m1317/FOAM/.