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Antimicrobial resistance (AMR) is an ever-growing public health problem worldwide. The low rate of antibiotic discovery coupled with the rapid spread of drug-resistant bacterial pathogens is causing a global health crisis. To facilitate the drug discovery processes, we present a large-scale study of reference antibiotic challenge bacterial transcriptome profiles, which included 37 antibiotics across 6 mechanisms of actions (MOAs) and provide an economical approach to aid in antimicrobial dereplication in the discovery process. We demonstrate that classical MOAs can be sorted based upon the magnitude of gene expression profiles despite some overlap in the secondary effects of antibiotic exposures across MOAs. Additionally, using gene subsets, we were able to subdivide broad MOA classes into subMOAs. Furthermore, we provide a biomarker gene set that can be used to classify most antimicrobial challenges according to their canonical MOA. We also demonstrate the ability of this rapid MOA diagnostic tool to predict and classify the expression profiles of pure compounds and crude extracts to their expression profile-associated MOA class.

To better combat the expansion of antibiotic resistance in pathogens, new compounds, particularly those with novel mechanisms-of-action [MOA], represent a major research priority in biomedical science. However, rediscovery of known antibiotics demonstrates a need for approaches that accurately identify potential novelty with higher throughput and reduced labor. Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. We evaluated our methods using whole transcriptome responses from Escherichia coli challenged with 41 FDA-approved antibiotics and 9 crude extracts while depositing 306 transcriptomes. Our CoHEC model can properly predict the primary MOA of previously unobserved compounds in both purified forms and crude extracts at an accuracy above 99%, while also correctly identifying darobactin, a newly discovered antibiotic, as having a novel MOA. In addition, we deploy our methods on a recent E. coli transcriptomics dataset in a different strain and a Mycobacterium smegmatis metabolomics timeseries dataset and showcase exceptionally high performance; improving upon the performance metrics of the original publications. We not only provide insight into the biological interpretation of our model but also that the concept of MOA is a non-discrete heuristic with diverse effects for different compounds within the same MOA, suggesting substantial antibiotic diversity awaiting discovery within existing MOA.

The sponge Stylissa carteri is known to produce a number of secondary metabolites displaying anti-fouling, anti-inflammatory, and anti-cancer activity. However, the anti-viral potential of metabolites produced by S. carteri has not been extensively explored. In this study, an S. carteri extract was HPLC fractionated and a cell based assay was used to evaluate the effects of HPLC fractions on parameters of Human Immunodeficiency Virus (HIV-1) infection and cell viability. Candidate HIV-1 inhibitory fractions were then analyzed for the presence of potential HIV-1 inhibitory compounds by mass spectrometry, leading to the identification of three previously characterized compounds, i.e., debromohymenialdisine (DBH), hymenialdisine (HD), and oroidin. Commercially available purified versions of these molecules were re-tested to assess their antiviral potential in greater detail. Specifically, DBH and HD exhibit a 30%–40% inhibition of HIV-1 at 3.1 μM and 13 μM, respectively; however, both exhibited cytotoxicity. Conversely, oroidin displayed a 50% inhibition of viral replication at 50 μM with no associated toxicity. Additional experimentation using a biochemical assay revealed that oroidin inhibited the activity of the HIV-1 Reverse Transcriptase up to 90% at 25 μM. Taken together, the chemical search space was narrowed and previously isolated compounds with an unexplored anti-viral potential were found. Our results support exploration of marine natural products for anti-viral drug discovery.

Identifying the mode of action (MOA) of antibacterial compounds is the fundamental basis for the development of new antibiotics, and the challenge increases with the emerging secondary and indirect effect from antibiotic stress. Although various omics-based system biology approaches are currently available, enhanced throughput, accuracy, and comprehensiveness are still desirable to better define antibiotic MOA. Using label-free quantitative proteomics, we present here a comprehensive reference map of proteomic signatures of Escherichia coli under challenge of 19 individual antibiotics. Applying several machine learning techniques, we derived a panel of 14 proteins that can be used to classify the antibiotics into different MOAs with nearly 100% accuracy. These proteins tend to mediate diverse bacterial cellular and metabolic processes. Transcriptomic level profiling correlates well with protein expression changes in discriminating different antibiotics. The reported expression signatures will aid future studies in identifying MOA of unknown compounds and facilitate the discovery of novel antibiotics.

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Viruses are underrepresented as targets in pharmacological screening efforts, given the difficulties of devising suitable cell-based and biochemical assays. In this study we found that a pre-fractionated organic extract of the Red Sea sponge Amphimedon chloros was able to inhibit the West Nile Virus NS3 protease (WNV NS3). Using liquid chromatography–mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy, the identity of the bioactive compound was determined as a 3-alkylpyridinium with m/z = 190.16. Diffusion Ordered Spectroscopy (DOSY) NMR and NMR relaxation rate analysis suggest that the bioactive compound forms oligomers of up to 35 kDa. We observed that at 9.4 μg/mL there was up to 40–70% inhibitory activity on WNV NS3 protease in orthogonal biochemical assays for solid phase extracts (SPE) of A. chloros. However, the LC-MS purified fragment was effective at inhibiting the protease up to 95% at an approximate amount of 2 µg/mL with negligible cytotoxicity to HeLa cells based on a High-Content Screening (HCS) cytological profiling strategy. To date, 3-alkylpyridinium type natural products have not been reported to show antiviral activity since the first characterization of halitoxin, or 3-alkylpyridinium, in 1978. This study provides the first account of a 3-alkylpyridinium complex that exhibits a proposed antiviral activity by inhibiting the NS3 protease. We suggest that the here-described compound can be further modified to increase its stability and tested in a cell-based assay to explore its full potential as a potential novel antiviral capable of inhibiting WNV replication.

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