The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD’s Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.

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Autism spectrum disorder (ASD) is a genetically heterogeneous disorder. Sequencing studies have identified hundreds of risk genes for autism spectrum disorder (ASD), but the signaling networks of genes at the protein level remain largely unexplored, which can provide insight into previously unknown individual and convergent disease pathways in the brain. To address this gap, we used neuron-specific proximity-labeling proteomics (BioID) to identify protein-protein interaction (PPI) networks of 41 ASD-risk genes. Network analysis revealed the combined 41 risk gene PPI network map had more shared connectivity between unrelated ASD-risk genes than represented in existing public databases. We identified common pathways between established and uncharacterized risk genes, including synaptic transmission, mitochondrial/metabolic processes, Wnt signaling pathways, ion channel activity and MAPK signaling. Investigation of the mitochondrial and metabolic network using gene knockouts revealed a functional hub in neurons for multiple risk genes not previously associated with this pathway. Further, we identified that the uncharacterized ASD-risk gene PPP2R5D localizes to the synapse, which is disrupted by patient de novo missense mutations. Investigation of de novo missense variants of additional synaptic ASD-risk genes demonstrated that changes in PPI networks can capture synaptic transmission deficits. The neuronal 41 ASD-risk gene PPI network map also revealed enrichment for an additional 112 ASD-risk genes and human brain cell types implicated in ASD pathology. Interestingly, clustering of ASD-risk genes based on their PPI network connectivity identified multiple gene groups that correlate mutation-type to clinical behavior scores. Together, our data reveal that using PPI networks to map ASD risk genes can identify previously unknown individual and convergent neuronal signaling networks, provide a method to assess the impact of patient variants, and reveal new biological insight into disease mechanisms.

SCN2A is an autism spectrum disorder (ASD) risk gene and encodes a voltage-gated sodium channel. However, the impact of autism-associated SCN2A de novo variants on human neuron development is unknown. We studied SCN2A using isogenic SCN2A-/- induced pluripotent stem cells (iPSCs), and patient-derived iPSCs harboring a p.R607* or a C-terminal p.G1744* de novo truncating variant. We used Neurogenin2 to generate excitatory glutamatergic neurons and found that SCN2A+/p.R607* and SCN2A-/- neurons displayed a reduction in synapse formation and excitatory synaptic activity using multielectrode arrays and electrophysiology. However, the p.G1744* variant, which leads to early-onset seizures in addition to ASD, altered action-potential dynamics but not synaptic activity. Proteomic and functional analysis of SCN2A+/p.R607* neurons revealed defects in neuronal morphology and bioenergetic pathways, which were not present in SCN2A+/p.G1744* neurons. Our study reveals that SCN2A de novo variants can have differential impact on human neuron function and signaling.