Discovery of a structural class of antibiotics with explainable deep learning.

The discovery of novel structural classes of antibiotics is urgently needed to address the ongoing antibiotic resistance crisis. Deep learning approaches have aided in exploring chemical spaces; these typically use black box models and do not provide chemical insights. Here we reasoned that the chemical substructures associated with antibiotic activity learned by neural network models can be identified and used to predict structural classes of antibiotics.

Discovering small-molecule senolytics with deep neural networks.

The accumulation of senescent cells is associated with aging, inflammation and cellular dysfunction. Senolytic drugs can alleviate age-related comorbidities by selectively killing senescent cells. Here we screened 2,352 compounds for senolytic activity in a model of etoposide-induced senescence and trained graph neural networks to predict the senolytic activities of >800,000 molecules.

An engineered live biotherapeutic for the prevention of antibiotic-induced dysbiosis.

Antibiotic-induced alterations in the gut microbiota are implicated in many metabolic and inflammatory diseases, increase the risk of secondary infections and contribute to the emergence of antimicrobial resistance. Here we report the design and in vivo performance of an engineered strain of Lactococcus lactis that altruistically degrades the widely used broad-spectrum antibiotics β-lactams (which disrupt commensal bacteria in the gut) through the secretion and extracellular assembly of a heterodimeric β-lactamase. The engineered β-lactamase-expression system does not confer β-lactam resistance to the producer cell, and is encoded via a genetically unlinked two-gene biosynthesis strategy that is not susceptible to dissemination by horizontal gene transfer.

Laboratory-Generated DNA Can Cause Anomalous Pathogen Diagnostic Test Results.

The coronavirus disease 2019 (COVID-19) pandemic has brought about the unprecedented expansion of highly sensitive molecular diagnostics as a primary infection control strategy. At the same time, many laboratories have shifted focus to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) research and diagnostic development, leading to large-scale production of SARS-CoV-2 nucleic acids that can interfere with these tests. We have identified multiple instances, in independent laboratories, in which nucleic acids generated in research settings are suspected to have caused researchers to test positive for SARS-CoV-2 in surveillance testing.

Minimally instrumented SHERLOCK (miSHERLOCK) for CRISPR-based point-of-care diagnosis of SARS-CoV-2 and emerging variants.

The COVID-19 pandemic highlights the need for diagnostics that can be rapidly adapted and deployed in a variety of settings. Several SARS-CoV-2 variants have shown worrisome effects on vaccine and treatment efficacy, but no current point-of-care (POC) testing modality allows their specific identification. We have developed miSHERLOCK, a low-cost, CRISPR-based POC diagnostic platform that takes unprocessed patient saliva; extracts, purifies, and concentrates viral RNA; performs amplification and detection reactions; and provides fluorescent visual output with only three user actions and 1 hour from sample input to answer out.

Wearable materials with embedded synthetic biology sensors for biomolecule detection.

Integrating synthetic biology into wearables could expand opportunities for noninvasive monitoring of physiological status, disease states and exposure to pathogens or toxins. However, the operation of synthetic circuits generally requires the presence of living, engineered bacteria, which has limited their application in wearables. Here we report lightweight, flexible substrates and textiles functionalized with freeze-dried, cell-free synthetic circuits, including CRISPR-based tools, that detect metabolites, chemicals and pathogen nucleic acid signatures.

Ultrasensitive CRISPR-based diagnostic for field-applicable detection of species in symptomatic and asymptomatic malaria.

Asymptomatic carriers of parasites hamper malaria control and eradication. Achieving malaria eradication requires ultrasensitive diagnostics for low parasite density infections (<100 parasites per microliter blood) that work in resource-limited settings (RLS). Sensitive point-of-care diagnostics are also lacking for nonfalciparum malaria, which is characterized by lower density infections and may require additional therapy for radical cure.

A Deep Learning Approach to Antibiotic Discovery.

Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we trained a deep neural network capable of predicting molecules with antibacterial activity. We performed predictions on multiple chemical libraries and discovered a molecule from the Drug Repurposing Hub-halicin-that is structurally divergent from conventional antibiotics and displays bactericidal activity against a wide phylogenetic spectrum of pathogens including Mycobacterium tuberculosis and carbapenem-resistant Enterobacteriaceae.

A DNA break- and phosphorylation-dependent positive feedback loop promotes immunoglobulin class-switch recombination.

The ability of activation-induced cytidine deaminase (AID) to efficiently mediate class-switch recombination (CSR) is dependent on its phosphorylation at Ser38; however, the trigger that induces AID phosphorylation and the mechanism by which phosphorylated AID drives CSR have not been elucidated. Here we found that phosphorylation of AID at Ser38 was induced by DNA breaks. Conversely, in the absence of AID phosphorylation, DNA breaks were not efficiently generated at switch (S) regions in the immunoglobulin heavy-chain locus (Igh), consistent with a failure of AID to interact with the endonuclease APE1.

Attenuating homologous recombination stimulates an AID-induced antileukemic effect.

Activation-induced cytidine deaminase (AID) is critical in normal B cells to initiate somatic hypermutation and immunoglobulin class switch recombination. Accumulating evidence suggests that AID is also prooncogenic, inducing cancer-promoting mutations or chromosome rearrangements. In this context, we find that AID is expressed in >40% of primary human chronic lymphocytic leukemia (CLL) cases, consistent with other reports.

Activation-induced cytidine deaminase-initiated off-target DNA breaks are detected and resolved during S phase.

Activation-induced cytidine deaminase (AID) initiates DNA double-strand breaks (DSBs) in the IgH gene (Igh) to stimulate isotype class switch recombination (CSR), and widespread breaks in non-Igh (off-target) loci throughout the genome. Because the DSBs that initiate class switching occur during the G₁ phase of the cell cycle, and are repaired via end joining, CSR is considered a predominantly G₁ reaction. By contrast, AID-induced non-Igh DSBs are repaired by homologous recombination.

ARTEMIS stabilizes the genome and modulates proliferative responses in multipotent mesenchymal cells.

Background: Unrepaired DNA double-stranded breaks (DSBs) cause chromosomal rearrangements, loss of genetic information, neoplastic transformation or cell death. The nonhomologous end joining (NHEJ) pathway, catalyzing sequence-independent direct rejoining of DSBs, is a crucial mechanism for repairing both stochastically occurring and developmentally programmed DSBs. In lymphocytes, NHEJ is critical for both development and genome stability.

Widespread genomic breaks generated by activation-induced cytidine deaminase are prevented by homologous recombination.

Activation-induced cytidine deaminase (AID) is required for somatic hypermutation and immunoglobulin class switching in activated B cells. Because AID has no known target-site specificity, there have been efforts to identify non-immunoglobulin AID targets. We show here that AID acts promiscuously, generating widespread DNA double-strand breaks (DSBs), genomic instability and cytotoxicity in B cells with less homologous recombination ability.