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 crisis1-9. Deep learning approaches have aided in exploring chemical spaces1,10-15; 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. We tested this hypothesis by developing an explainable, substructure-based approach for the efficient, deep learning-guided exploration of chemical spaces. We determined the antibiotic activities and human cell cytotoxicity profiles of 39,312 compounds and applied ensembles of graph neural networks to predict antibiotic activity and cytotoxicity for 12,076,365 compounds. Using explainable graph algorithms, we identified substructure-based rationales for compounds with high predicted antibiotic activity and low predicted cytotoxicity. We empirically tested 283 compounds and found that compounds exhibiting antibiotic activity against Staphylococcus aureus were enriched in putative structural classes arising from rationales. Of these structural classes of compounds, one is selective against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci, evades substantial resistance, and reduces bacterial titres in mouse models of MRSA skin and systemic thigh infection. Our approach enables the deep learning-guided discovery of structural classes of antibiotics and demonstrates that machine learning models in drug discovery can be explainable, providing insights into the chemical substructures that underlie selective antibiotic activity.

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. Our approach enriched for structurally diverse compounds with senolytic activity; of these, three drug-like compounds selectively target senescent cells across different senescence models, with more favorable medicinal chemistry properties than, and selectivity comparable to, those of a known senolytic, ABT-737. Molecular docking simulations of compound binding to several senolytic protein targets, combined with time-resolved fluorescence energy transfer experiments, indicate that these compounds act in part by inhibiting Bcl-2, a regulator of cellular apoptosis. We tested one compound, BRD-K56819078, in aged mice and found that it significantly decreased senescent cell burden and mRNA expression of senescence-associated genes in the kidneys. Our findings underscore the promise of leveraging deep learning to discover senotherapeutics.

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 ß-lactams (which disrupt commensal bacteria in the gut) through the secretion and extracellular assembly of a heterodimeric ß-lactamase. The engineered ß-lactamase-expression system does not confer ß-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. In a mouse model of parenteral ampicillin treatment, oral supplementation with the engineered live biotherapeutic minimized gut dysbiosis without affecting the ampicillin concentration in serum, precluded the enrichment of antimicrobial resistance genes in the gut microbiome and prevented the loss of colonization resistance against Clostridioides difficile. Engineered live biotherapeutics that safely degrade antibiotics in the gut may represent a suitable strategy for the prevention of dysbiosis and its associated pathologies.

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. In some cases, the affected individuals did not work directly with these nucleic acids but were exposed via a contaminated surface or object. Though researchers have long been vigilant of DNA contaminants, the transfer of these contaminants to SARS-CoV-2 testing samples can result in anomalous test results. The impact of these incidents stretches into the public sphere, placing additional burdens on public health resources, placing affected researchers and their contacts in isolation and quarantine, removing them from the testing pool for 3 months, and carrying the potential to trigger shutdowns of classrooms and workplaces. We report our observations as a call for increased stewardship over nucleic acids with the potential to impact both the use and development of diagnostics. IMPORTANCE To meet the challenges imposed by the COVID-19 pandemic, research laboratories shifted their focus and clinical diagnostic laboratories developed and utilized new assays. Nucleic acid-based testing became widespread and, for the first time, was used as a prophylactic measure. We report 15 cases of researchers at two institutes testing positive for SARS-CoV-2 on routine surveillance tests, in the absence of any symptoms or transmission. These researchers were likely contaminated with nonhazardous nucleic acids generated in the laboratory in the course of developing new SARS-CoV-2 diagnostics. These contaminating nucleic acids were persistent and widespread throughout the laboratory. We report these findings as a cautionary tale to those working with nucleic acids used in diagnostic testing and as a call for careful stewardship of diagnostically relevant molecules. Our conclusions are especially relevant as at-home COVID-19 testing gains traction in the marketplace and these amplicons may impact on the general public.

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. miSHERLOCK achieves highly sensitive multiplexed detection of SARS-CoV-2 and mutations associated with variants B.1.1.7, B.1.351, and P.1. Our modular system enables easy exchange of assays to address diverse user needs and can be rapidly reconfigured to detect different viruses and variants of concern. An adjunctive smartphone application enables output quantification, automated interpretation, and the possibility of remote, distributed result reporting.

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. The wearable devices are activated upon rehydration from aqueous exposure events and report the presence of specific molecular targets by colorimetric changes or via an optical fiber network that detects fluorescent and luminescent outputs. The detection limits for nucleic acids rival current laboratory methods such as quantitative PCR. We demonstrate the development of a face mask with a lyophilized CRISPR sensor for wearable, noninvasive detection of SARS-CoV-2 at room temperature within 90 min, requiring no user intervention other than the press of a button.

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

Asymptomatic carriers of Plasmodium 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. Molecular methods, such as PCR, have high sensitivity and specificity, but remain high-complexity technologies impractical for RLS. Here we describe a CRISPR-based diagnostic for ultrasensitive detection and differentiation of Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, and Plasmodium malariae, using the nucleic acid detection platform SHERLOCK (specific high-sensitivity enzymatic reporter unlocking). We present a streamlined, field-applicable, diagnostic comprised of a 10-min SHERLOCK parasite rapid extraction protocol, followed by SHERLOCK for 60 min for Plasmodium species-specific detection via fluorescent or lateral flow strip readout. We optimized one-pot, lyophilized, isothermal assays with a simplified sample preparation method independent of nucleic acid extraction, and showed that these assays are capable of detection below two parasites per microliter blood, a limit of detection suggested by the World Health Organization. Our P. falciparum and P. vivax assays exhibited 100% sensitivity and specificity on clinical samples (5 P. falciparum and 10 P. vivax samples). This work establishes a field-applicable diagnostic for ultrasensitive detection of asymptomatic carriers as well as a rapid point-of-care clinical diagnostic for nonfalciparum malaria species and low parasite density P. falciparum infections.

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. Halicin also effectively treated Clostridioides difficile and pan-resistant Acinetobacter baumannii infections in murine models. Additionally, from a discrete set of 23 empirically tested predictions from >107 million molecules curated from the ZINC15 database, our model identified eight antibacterial compounds that are structurally distant from known antibiotics. This work highlights the utility of deep learning approaches to expand our antibiotic arsenal through the discovery of structurally distinct antibacterial molecules.

BioBits™ Explorer: A modular synthetic biology education kit.

Hands-on demonstrations greatly enhance the teaching of science, technology, engineering, and mathematics (STEM) concepts and foster engagement and exploration in the sciences. While numerous chemistry and physics classroom demonstrations exist, few biology demonstrations are practical and accessible due to the challenges and concerns of growing living cells in classrooms. We introduce BioBits™ Explorer, a synthetic biology educational kit based on shelf-stable, freeze-dried, cell-free (FD-CF) reactions, which are activated by simply adding water. The FD-CF reactions engage the senses of sight, smell, and touch with outputs that produce fluorescence, fragrances, and hydrogels, respectively. We introduce components that can teach tunable protein expression, enzymatic reactions, biomaterial formation, and biosensors using RNA switches, some of which represent original FD-CF outputs that expand the toolbox of cell-free synthetic biology. The BioBits™ Explorer kit enables hands-on demonstrations of cutting-edge science that are inexpensive and easy to use, circumventing many current barriers for implementing exploratory biology experiments in classrooms.

BioBits™ Bright: A fluorescent synthetic biology education kit.

Synthetic biology offers opportunities for experiential educational activities at the intersection of the life sciences, engineering, and design. However, implementation of hands-on biology activities in classrooms is challenging because of the need for specialized equipment and expertise to grow living cells. We present BioBits™ Bright, a shelf-stable, just-add-water synthetic biology education kit with easy visual outputs enabled by expression of fluorescent proteins in freeze-dried, cell-free reactions. We introduce activities and supporting curricula for teaching the central dogma, tunable protein expression, and design-build-test cycles and report data generated by K-12 teachers and students. We also develop inexpensive incubators and imagers, resulting in a comprehensive kit costing

A low-cost paper-based synthetic biology platform for analyzing gut microbiota and host biomarkers.

There is a need for large-scale, longitudinal studies to determine the mechanisms by which the gut microbiome and its interactions with the host affect human health and disease. Current methods for profiling the microbiome typically utilize next-generation sequencing applications that are expensive, slow, and complex. Here, we present a synthetic biology platform for affordable, on-demand, and simple analysis of microbiome samples using RNA toehold switch sensors in paper-based, cell-free reactions. We demonstrate species-specific detection of mRNAs from 10 different bacteria that affect human health and four clinically relevant host biomarkers. We develop a method to quantify mRNA using our toehold sensors and validate our platform on clinical stool samples by comparison to RT-qPCR. We further highlight the potential clinical utility of the platform by showing that it can be used to rapidly and inexpensively detect toxin mRNA in the diagnosis of Clostridium difficile infections.

Genetic and Small Molecule Disruption of the AID/RAD51 Axis Similarly Protects Nonobese Diabetic Mice from Type 1 Diabetes through Expansion of Regulatory B Lymphocytes.

B lymphocytes play a key role in type 1 diabetes (T1D) development by serving as a subset of APCs preferentially supporting the expansion of autoreactive pathogenic T cells. As a result of their pathogenic importance, B lymphocyte-targeted therapies have received considerable interest as potential T1D interventions. Unfortunately, the B lymphocyte-directed T1D interventions tested to date failed to halt ß cell demise. IgG autoantibodies marking humans at future risk for T1D indicate that B lymphocytes producing them have undergone the affinity-maturation processes of class switch recombination and, possibly, somatic hypermutation. This study found that CRISPR/Cas9-mediated ablation of the activation-induced cytidine deaminase gene required for class switch recombination/somatic hypermutation induction inhibits T1D development in the NOD mouse model. The activation-induced cytidine deaminase protein induces genome-wide DNA breaks that, if not repaired through RAD51-mediated homologous recombination, result in B lymphocyte death. Treatment with the RAD51 inhibitor 4,4'-diisothiocyanatostilbene-2, 2'-disulfonic acid also strongly inhibited T1D development in NOD mice. The genetic and small molecule-targeting approaches expanded CD73+ B lymphocytes that exert regulatory activity suppressing diabetogenic T cell responses. Hence, an initial CRISPR/Cas9-mediated genetic modification approach has identified the AID/RAD51 axis as a target for a potentially clinically translatable pharmacological approach that can block T1D development by converting B lymphocytes to a disease-inhibitory CD73+ regulatory state.

Nucleic acid detection with CRISPR-Cas13a/C2c2.

Rapid, inexpensive, and sensitive nucleic acid detection may aid point-of-care pathogen detection, genotyping, and disease monitoring. The RNA-guided, RNA-targeting clustered regularly interspaced short palindromic repeats (CRISPR) effector Cas13a (previously known as C2c2) exhibits a "collateral effect" of promiscuous ribonuclease activity upon target recognition. We combine the collateral effect of Cas13a with isothermal amplification to establish a CRISPR-based diagnostic (CRISPR-Dx), providing rapid DNA or RNA detection with attomolar sensitivity and single-base mismatch specificity. We use this Cas13a-based molecular detection platform, termed Specific High-Sensitivity Enzymatic Reporter UnLOCKing (SHERLOCK), to detect specific strains of Zika and Dengue virus, distinguish pathogenic bacteria, genotype human DNA, and identify mutations in cell-free tumor DNA. Furthermore, SHERLOCK reaction reagents can be lyophilized for cold-chain independence and long-term storage and be readily reconstituted on paper for field applications.

Portable, On-Demand Biomolecular Manufacturing.

Synthetic biology uses living cells as molecular foundries for the biosynthesis of drugs, therapeutic proteins, and other commodities. However, the need for specialized equipment and refrigeration for production and distribution poses a challenge for the delivery of these technologies to the field and to low-resource areas. Here, we present a portable platform that provides the means for on-site, on-demand manufacturing of therapeutics and biomolecules. This flexible system is based on reaction pellets composed of freeze-dried, cell-free transcription and translation machinery, which can be easily hydrated and utilized for biosynthesis through the addition of DNA encoding the desired output. We demonstrate this approach with the manufacture and functional validation of antimicrobial peptides and vaccines and present combinatorial methods for the production of antibody conjugates and small molecules. This synthetic biology platform resolves important practical limitations in the production and distribution of therapeutics and molecular tools, both to the developed and developing world.

Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components.

The recent Zika virus outbreak highlights the need for low-cost diagnostics that can be rapidly developed for distribution and use in pandemic regions. Here, we report a pipeline for the rapid design, assembly, and validation of cell-free, paper-based sensors for the detection of the Zika virus RNA genome. By linking isothermal RNA amplification to toehold switch RNA sensors, we detect clinically relevant concentrations of Zika virus sequences and demonstrate specificity against closely related Dengue virus sequences. When coupled with a novel CRISPR/Cas9-based module, our sensors can discriminate between viral strains with single-base resolution. We successfully demonstrate a simple, field-ready sample-processing workflow and detect Zika virus from the plasma of a viremic macaque. Our freeze-dried biomolecular platform resolves important practical limitations to the deployment of molecular diagnostics in the field and demonstrates how synthetic biology can be used to develop diagnostic tools for confronting global health crises. PAPERCLIP.

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. Additionally, deficiency in the DNA-damage sensor ATM impaired the phosphorylation of AID at Ser38 and the interaction of AID with APE1. Our results identify a positive feedback loop for the amplification of DNA breaks at S regions through the phosphorylation- and ATM-dependent interaction of AID with 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. Using a combination of human B lymphoid leukemia cells and mouse models, we now show that AID expression can be harnessed for antileukemic effect, after inhibition of the RAD51 homologous recombination (HR) factor with 4,4'-diisothiocyanatostilbene-2-2'-disulfonic acid (DIDS). As a proof of principle, we show that DIDS treatment inhibits repair of AID-initiated DNA breaks, induces apoptosis, and promotes cytotoxicity preferentially in AID-expressing human CLL. This reveals a novel antineoplastic role of AID that can be triggered by inhibition of HR, suggesting a potential new paradigm to treat AID-expressing tumors. Given the growing list of tumor types with aberrant AID expression, this novel therapeutic approach has potential to impact a significant patient population.

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. Although little is known about the connection between the cell cycle and either induction or resolution of AID-mediated non-Igh DSBs, their repair by homologous recombination implicates post-G1 phases. Coordination of DNA breakage and repair during the cell cycle is critical to promote normal class switching and prevent genomic instability. To understand how AID-mediated events are regulated through the cell cycle, we have investigated G1-to-S control in AID-dependent genome-wide DSBs. We find that AID-mediated off-target DSBs, like those induced in the Igh locus, are generated during G1. These data suggest that AID-mediated DSBs can evade G1/S checkpoint activation and persist beyond G1, becoming resolved during S phase. Interestingly, DSB resolution during S phase can promote not only non-Igh break repair, but also Ig CSR. Our results reveal novel cell cycle dynamics in response to AID-initiated DSBs, and suggest that the regulation of the repair of these DSBs through the cell cycle may ensure proper class switching while preventing AID-induced genomic instability.