Jonathan M. Stokes

Bio: Jonathan M. Stokes is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Antibiotics & Medicine. The author has an hindex of 14, co-authored 22 publications receiving 1230 citations. Previous affiliations of Jonathan M. Stokes include Wyss Institute for Biologically Inspired Engineering & Broad Institute.

Pentamidine sensitizes Gram-negative pathogens to antibiotics and overcomes acquired colistin resistance.

Abstract: The increasing use of polymyxins1 in addition to the dissemination of plasmid-borne colistin resistance threatens to cause a serious breach in our last line of defence against multidrug-resistant Gram-negative pathogens, and heralds the emergence of truly pan-resistant infections. Colistin resistance often arises through covalent modification of lipid A with cationic residues such as phosphoethanolamine-as is mediated by Mcr-1 (ref. 2)-which reduce the affinity of polymyxins for lipopolysaccharide3. Thus, new strategies are needed to address the rapidly diminishing number of treatment options for Gram-negative infections4. The difficulty in eradicating Gram-negative bacteria is largely due to their highly impermeable outer membrane, which serves as a barrier to many otherwise effective antibiotics5. Here, we describe an unconventional screening platform designed to enrich for non-lethal, outer-membrane-active compounds with potential as adjuvants for conventional antibiotics. This approach identified the antiprotozoal drug pentamidine6 as an effective perturbant of the Gram-negative outer membrane through its interaction with lipopolysaccharide. Pentamidine displayed synergy with antibiotics typically restricted to Gram-positive bacteria, yielding effective drug combinations with activity against a wide range of Gram-negative pathogens in vitro, and against systemic Acinetobacter baumannii infections in mice. Notably, the adjuvant activity of pentamidine persisted in polymyxin-resistant bacteria in vitro and in vivo. Overall, pentamidine and its structural analogues represent unexploited molecules for the treatment of Gram-negative infections, particularly those having acquired polymyxin resistance determinants.

Overcoming mcr-1 mediated colistin resistance with colistin in combination with other antibiotics.

Abstract: Plasmid-borne colistin resistance mediated by mcr-1 may contribute to the dissemination of pan-resistant Gram-negative bacteria. Here, we show that mcr-1 confers resistance to colistin-induced lysis and bacterial cell death, but provides minimal protection from the ability of colistin to disrupt the Gram-negative outer membrane. Indeed, for colistin-resistant strains of Enterobacteriaceae expressing plasmid-borne mcr-1, clinically relevant concentrations of colistin potentiate the action of antibiotics that, by themselves, are not active against Gram-negative bacteria. The result is that several antibiotics, in combination with colistin, display growth-inhibition at levels below their corresponding clinical breakpoints. Furthermore, colistin and clarithromycin combination therapy displays efficacy against mcr-1-positive Klebsiella pneumoniae in murine thigh and bacteremia infection models at clinically relevant doses. Altogether, these data suggest that the use of colistin in combination with antibiotics that are typically active against Gram-positive bacteria poses a viable therapeutic alternative for highly drug-resistant Gram-negative pathogens expressing mcr-1.

Bacterial metabolic state more accurately predicts antibiotic lethality than growth rate.

Abstract: Growth rate and metabolic state of bacteria have been separately shown to affect antibiotic efficacy1–3. However, the two are interrelated as bacterial growth inherently imposes a metabolic burden4; thus, determining individual contributions from each is challenging5,6. Indeed, faster growth is often correlated with increased antibiotic efficacy7,8; however, the concurrent role of metabolism in that relationship has not been well characterized. As a result, a clear understanding of the interdependence between growth and metabolism, and their implications for antibiotic efficacy, are lacking9. Here, we measured growth and metabolism in parallel across a broad range of coupled and uncoupled conditions to determine their relative contribution to antibiotic lethality. We show that when growth and metabolism are uncoupled, antibiotic lethality uniformly depends on the bacterial metabolic state at the time of treatment, rather than growth rate. We further reveal a critical metabolic threshold below which antibiotic lethality is negligible. These findings were general for a wide range of conditions, including nine representative bactericidal drugs and a diverse range of Gram-positive and Gram-negative species (Escherichia coli, Acinetobacter baumannii and Staphylococcus aureus). This study provides a cohesive metabolic-dependent basis for antibiotic-mediated cell death, with implications for current treatment strategies and future drug development. Metabolic state and ATP levels are better predictors of antibiotic lethality across diverse bacterial species than growth rate.

Open Graph Benchmark: Datasets for Machine Learning on Graphs

Abstract: We present the Open Graph Benchmark (OGB), a diverse set of challenging and realistic benchmark datasets to facilitate scalable, robust, and reproducible graph machine learning (ML) research. OGB datasets are large-scale, encompass multiple important graph ML tasks, and cover a diverse range of domains, ranging from social and information networks to biological networks, molecular graphs, source code ASTs, and knowledge graphs. For each dataset, we provide a unified evaluation protocol using meaningful application-specific data splits and evaluation metrics. In addition to building the datasets, we also perform extensive benchmark experiments for each dataset. Our experiments suggest that OGB datasets present significant challenges of scalability to large-scale graphs and out-of-distribution generalization under realistic data splits, indicating fruitful opportunities for future research. Finally, OGB provides an automated end-to-end graph ML pipeline that simplifies and standardizes the process of graph data loading, experimental setup, and model evaluation. OGB will be regularly updated and welcomes inputs from the community. OGB datasets as well as data loaders, evaluation scripts, baseline code, and leaderboards are publicly available at this https URL .

Drug combinations: a strategy to extend the life of antibiotics in the 21st century.

Abstract: Antimicrobial resistance threatens a resurgence of life-threatening bacterial infections and the potential demise of many aspects of modern medicine. Despite intensive drug discovery efforts, no new classes of antibiotics have been developed into new medicines for decades, in large part owing to the stringent chemical, biological and pharmacological requisites for effective antibiotic drugs. Combinations of antibiotics and of antibiotics with non-antibiotic activity-enhancing compounds offer a productive strategy to address the widespread emergence of antibiotic-resistant strains. In this Review, we outline a theoretical and practical framework for the development of effective antibiotic combinations. Combinations of antibiotics and of antibiotics with non-antibiotic activity-enhancing compounds offer a productive strategy to address the widespread emergence of antibiotic-resistant strains. In this Review, Tyers and Wright outline a theoretical and practical framework for the development of effective drug combinations.

Next-generation approaches to understand and combat the antibiotic resistome

Abstract: Antibiotic resistance is a natural feature of diverse microbial ecosystems. Although recent studies of the antibiotic resistome have highlighted barriers to the horizontal transfer of antibiotic resistance genes between habitats, the rapid global spread of genes that confer resistance to carbapenem, colistin and quinolone antibiotics illustrates the dire clinical and societal consequences of such events. Over time, the study of antibiotic resistance has grown from focusing on single pathogenic organisms in axenic culture to studying antibiotic resistance in pathogenic, commensal and environmental bacteria at the level of microbial communities. As the study of antibiotic resistance advances, it is important to incorporate this comprehensive approach to better inform global antibiotic resistance surveillance and antibiotic development. It is increasingly becoming apparent that although not all resistance genes are likely to geographically and phylogenetically disseminate, the threat presented by those that are is serious and warrants an interdisciplinary research focus. In this Review, we highlight seminal work in the resistome field, discuss recent advances in the studies of resistomes, and propose a resistome paradigm that can pave the way for the improved proactive identification and mitigation of emerging antibiotic resistance threats.

Oxidation of the Guanine Nucleotide Pool Underlies Cell Death by Bactericidal Antibiotics

Abstract: A Specific Oxidative Catastrophe Three different classes of antibiotics induce bacterial cell death by the production of hydroxyl radicals. Hydroxyl radicals are powerful oxidizing agents in living cells and will oxidize the nucleic acid base, guanine, to form 8-oxoguanine, which is potentially mutagenic because it can pair with both cytosine and adenine and form lethal double-strand DNA breaks. Foti et al. (p. 315) discovered that overproduction of the nucleotide sanitizer MutT, which hydrolyzes 8-oxo-dGTP to 8-oxo-dGMP, gives striking protection against cell death. Several antibiotics kill bacteria by causing oxidative damage to guanine nucleotides, which then damage nucleic acids. A detailed understanding of the mechanisms that underlie antibiotic killing is important for the derivation of new classes of antibiotics and clinically useful adjuvants for current antimicrobial therapies. Our efforts to understand why DinB (DNA polymerase IV) overproduction is cytotoxic to Escherichia coli led to the unexpected insight that oxidation of guanine to 8-oxo-guanine in the nucleotide pool underlies much of the cell death caused by both DinB overproduction and bactericidal antibiotics. We propose a model in which the cytotoxicity of beta-lactams and quinolones predominantly results from lethal double-strand DNA breaks caused by incomplete repair of closely spaced 8-oxo-deoxyguanosine lesions, whereas the cytotoxicity of aminoglycosides might additionally result from mistranslation due to the incorporation of 8-oxo-guanine into newly synthesized RNAs.