Stefan Oliver Bassler

All Publications

• Randomly barcoded transposon mutant libraries for gut commensals II: Applying libraries for functional genetics. Cell reports Voogdt, C. G., Tripathi, S., Bassler, S. O., McKeithen-Mead, S. A., Guiberson, E. R., Koumoutsi, A., Bravo, A. M., Buie, C., Zimmermann, M., Sonnenburg, J. L., Typas, A., Deutschbauer, A. M., Shiver, A. L., Huang, K. C. 2023; 43 (1): 113519

  Abstract

  The critical role of the intestinal microbiota in human health and disease is well recognized. Nevertheless, there are still large gaps in our understanding of the functions and mechanisms encoded in the genomes of most members of the gut microbiota. Genome-scale libraries of transposon mutants are a powerful tool to help us address this gap. Recent advances in barcoded transposon mutagenesis have dramatically lowered the cost of mutant fitness determination in hundreds of in vitro and in vivo experimental conditions. In an accompanying review, we discuss recent advances and caveats for the construction of pooled and arrayed barcoded transposon mutant libraries in human gut commensals. In this review, we discuss how these libraries can be used across a wide range of applications, the technical aspects involved, and expectations for such screens.

  View details for DOI 10.1016/j.celrep.2023.113519

  View details for PubMedID 38142398

• Randomly barcoded transposon mutant libraries for gut commensals I: Strategies for efficient library construction. Cell reports Tripathi, S., Voogdt, C. G., Bassler, S. O., Anderson, M., Huang, P. H., Sakenova, N., Capraz, T., Jain, S., Koumoutsi, A., Bravo, A. M., Trotter, V., Zimmerman, M., Sonnenburg, J. L., Buie, C., Typas, A., Deutschbauer, A. M., Shiver, A. L., Huang, K. C. 2023; 43 (1): 113517

  Abstract

  Randomly barcoded transposon mutant libraries are powerful tools for studying gene function and organization, assessing gene essentiality and pathways, discovering potential therapeutic targets, and understanding the physiology of gut bacteria and their interactions with the host. However, construction of high-quality libraries with uniform representation can be challenging. In this review, we survey various strategies for barcoded library construction, including transposition systems, methods of transposon delivery, optimal library size, and transconjugant selection schemes. We discuss the advantages and limitations of each approach, as well as factors to consider when selecting a strategy. In addition, we highlight experimental and computational advances in arraying condensed libraries from mutant pools. We focus on examples of successful library construction in gut bacteria and their application to gene function studies and drug discovery. Given the need for understanding gene function and organization in gut bacteria, we provide a comprehensive guide for researchers to construct randomly barcoded transposon mutant libraries.

  View details for DOI 10.1016/j.celrep.2023.113517

  View details for PubMedID 38142397

• Bioactivity assessment of natural compounds using machine learning models trained on target similarity between drugs. PLoS computational biology Periwal, V., Bassler, S., Andrejev, S., Gabrielli, N., Patil, K. R., Typas, A., Patil, K. R. 2022; 18 (4): e1010029

  Abstract

  Natural compounds constitute a rich resource of potential small molecule therapeutics. While experimental access to this resource is limited due to its vast diversity and difficulties in systematic purification, computational assessment of structural similarity with known therapeutic molecules offers a scalable approach. Here, we assessed functional similarity between natural compounds and approved drugs by combining multiple chemical similarity metrics and physicochemical properties using a machine-learning approach. We computed pairwise similarities between 1410 drugs for training classification models and used the drugs shared protein targets as class labels. The best performing models were random forest which gave an average area under the ROC of 0.9, Matthews correlation coefficient of 0.35, and F1 score of 0.33, suggesting that it captured the structure-activity relation well. The models were then used to predict protein targets of circa 11k natural compounds by comparing them with the drugs. This revealed therapeutic potential of several natural compounds, including those with support from previously published sources as well as those hitherto unexplored. We experimentally validated one of the predicted pair's activities, viz., Cox-1 inhibition by 5-methoxysalicylic acid, a molecule commonly found in tea, herbs and spices. In contrast, another natural compound, 4-isopropylbenzoic acid, with the highest similarity score when considering most weighted similarity metric but not picked by our models, did not inhibit Cox-1. Our results demonstrate the utility of a machine-learning approach combining multiple chemical features for uncovering protein binding potential of natural compounds.

  View details for DOI 10.1371/journal.pcbi.1010029

  View details for PubMedID 35468126

  View details for PubMedCentralID PMC9071136

• Species-specific activity of antibacterial drug combinations NATURE Brochado, A., Telzerow, A., Bobonis, J., Banzhaf, M., Mateus, A., Selkrig, J., Huth, E., Bassler, S., Beas, J., Zietek, M., Ng, N., Foerster, S., Ezraty, B., Py, B., Barras, F., Savitski, M. M., Bork, P., Goettig, S., Typas, A. 2018; 559 (7713): 259-+

  Abstract

  The spread of antimicrobial resistance has become a serious public health concern, making once-treatable diseases deadly again and undermining the achievements of modern medicine1,2. Drug combinations can help to fight multi-drug-resistant bacterial infections, yet they are largely unexplored and rarely used in clinics. Here we profile almost 3,000 dose-resolved combinations of antibiotics, human-targeted drugs and food additives in six strains from three Gram-negative pathogens-Escherichia coli, Salmonella enterica serovar Typhimurium and Pseudomonas aeruginosa-to identify general principles for antibacterial drug combinations and understand their potential. Despite the phylogenetic relatedness of the three species, more than 70% of the drug-drug interactions that we detected are species-specific and 20% display strain specificity, revealing a large potential for narrow-spectrum therapies. Overall, antagonisms are more common than synergies and occur almost exclusively between drugs that target different cellular processes, whereas synergies are more conserved and are enriched in drugs that target the same process. We provide mechanistic insights into this dichotomy and further dissect the interactions of the food additive vanillin. Finally, we demonstrate that several synergies are effective against multi-drug-resistant clinical isolates in vitro and during infections of the larvae of the greater wax moth Galleria mellonella, with one reverting resistance to the last-resort antibiotic colistin.

  View details for PubMedID 29973719