About

Tim S. Bugni, PhD, is a professor at the School of Pharmacy at the University of Wisconsin–Madison, where he is part of the Pharmaceutical Sciences Division. His research interests include marine natural products chemistry, symbiotic microorganisms, drug discovery, metabolomics, and the use of NMR and MS for structure elucidation of novel natural products. His work focuses on exploring under-explored niches for bacterial cultivation, particularly from marine invertebrates such as sponges and ascidians, to discover new therapeutics. He employs metabolomics approaches to prioritize promising strains for the discovery of natural products with potential applications in neurodegenerative disease, infectious disease, and cancer. The overarching goal of his research is to develop diverse natural product libraries from unique microbes for drug discovery, facilitating the identification of novel therapeutic leads and the development of chemical probes for cellular function investigation. Dr. Bugni received his bachelor's degree in chemistry from Montana Tech in 1995 and his PhD from the University of Utah in 2003. He held a postdoctoral appointment at Scripps Institution of Oceanography and was a research assistant professor at the University of Utah before joining the faculty at the School of Pharmacy in 2009.

Research topics

• Biology
• Computational biology
• Biochemistry
• Computer Science
• Genetics
• Chemistry
• Ecology
• Stereochemistry
• Bioinformatics
• Botany
• Internal medicine
• Cancer research
• Data science
• Pharmacology
• Oncology
• Combinatorial chemistry
• Medicine
• Microbiology

Selected publications

• The antimicrobial potential from insect microbiomes of Streptomyces

  The Catalogue of Life · 2026-02-16

  datasetOpen access
  PublisherDOI

• Code and knowledgebase data for "IDBac: an open-access web platform and compendium for the identification of bacteria by MALDI-TOF mass spectrometry"

  Open MIND · 2026-05-06

  datasetOpen access

  About This repository contains the complete codebase and infrastructure for the IDBac platform, a centralized knowledgebase and analysis system for bacterial dereplication using MALDI-TOF mass spectrometry protein signatures. Please note: While the current IDBac knowledgebase contains version 4.2 of the RKI database, the JSON file listed here intentionally excludes this. Please find the source data for RKI used in the publication here. Abstract The identification of bacteria is central to microbiological sciences. While gene sequencing methods have been the standard to identify bacteria, use of MALDI-TOF mass spectrometry (MS) in clinical microbiology provides high-throughput identification to the subspecies level. However, biotyping has yet to be adopted outside of clinical microbiology due to the lack of a centralized public database of MS protein signatures that would facilitate strain identification via spectral comparison. Herein we present the IDBac web platform, a crowd-sourced central knowledgebase of protein MS signatures of >1400 strains spanning 6 bacterial phyla. Accompanying the knowledgebase is analysis infrastructure to identify unknown isolates, probe relationships within culture collections, and visualize specialized metabolite differences within groups of closely related bacteria. We highlight this utility by demonstrating the dereplication of bacterial isolates using the seed knowledgebase, identifying trends in culture collections using metadata integration, and reporting the discovery of a new metabolite from a Paraburkholderia isolate.

  PublisherDOI

• Code and knowledgebase data for "IDBac: an open-access web platform and compendium for the identification of bacteria by MALDI-TOF mass spectrometry"

  Zenodo (CERN European Organization for Nuclear Research) · 2026-05-06

  datasetOpen access

  About This repository contains the complete codebase and infrastructure for the IDBac platform, a centralized knowledgebase and analysis system for bacterial dereplication using MALDI-TOF mass spectrometry protein signatures. Please note: While the current IDBac knowledgebase contains version 4.2 of the RKI database, the JSON file listed here intentionally excludes this. Please find the source data for RKI used in the publication here. Abstract The identification of bacteria is central to microbiological sciences. While gene sequencing methods have been the standard to identify bacteria, use of MALDI-TOF mass spectrometry (MS) in clinical microbiology provides high-throughput identification to the subspecies level. However, biotyping has yet to be adopted outside of clinical microbiology due to the lack of a centralized public database of MS protein signatures that would facilitate strain identification via spectral comparison. Herein we present the IDBac web platform, a crowd-sourced central knowledgebase of protein MS signatures of >1400 strains spanning 6 bacterial phyla. Accompanying the knowledgebase is analysis infrastructure to identify unknown isolates, probe relationships within culture collections, and visualize specialized metabolite differences within groups of closely related bacteria. We highlight this utility by demonstrating the dereplication of bacterial isolates using the seed knowledgebase, identifying trends in culture collections using metadata integration, and reporting the discovery of a new metabolite from a Paraburkholderia isolate.

  PublisherDOI

• Bioactive Natural Products Produced by Streptomyces from the Microbiome of Cadaveric Fly Larvae

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-03-15

  articleOpen accessSenior author

  Streptomyces are prolific producers of bioactive compounds and increasingly recognized as members of insect microbiomes, yet the microbiome of cadaveric fly larvae remain an overlooked system for discovering metabolically versatile Streptomyces species. Here, we conduct targeted bacterial isolations from the microbiome of fly larvae collected from pig cadavers, generating 42 Streptomyces isolates of interest, and systematically evaluated their metabolic potential through genomic analysis, antimicrobial screening, biosynthetic gene cluster assessment, untargeted LC-MS/MS metabolomics, and compound purification. The Streptomyces isolates spanned nine species, including underrepresented lineages for which we added genomic representatives. Streptomyces from carrion fly larvae exhibited broad-spectrum antimicrobial activity and substantial BGC diversity, supported by metabolomic detection of antimycins, surugamides, and macrotetrolides. From a deep phylogenetic lineage, we purified JBIR-68 and Simamycin and demonstrated their potent anthelmintic activity against Brugia malayi microfilariae. GNPS molecular networking revealed three additional JBIR-68 analogs, establishing the first taxonomically resolved Streptomyces lineage capable of producing these rare metabolites. Our findings position cadaveric fly larvae as a rich ecological reservoir for discovering Streptomyces with the potential to produce chemically diverse natural products with biomedical applications.

  PublisherOA PDFDOI

• IDBac: an open-access web platform to identify bacteria and analyze relationships in culture collections using MALDI-TOF mass spectrometry

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-15

  preprintOpen access

  Abstract The identification and analysis of bacteria is central to the microbiological sciences. While gene sequencing methods have been the standard to achieve this, use of MALDI-TOF mass spectrometry (MS), particularly in clinical microbiology, provides high-throughput identification to the subspecies level. However, biotyping has yet to be adopted outside of clinical settings due to the lack of a centralized public database of MS protein signatures that would facilitate isolate identification via spectral comparison. Further, current platforms lack meaningful ways to compare multiple properties from large numbers of bacterial isolates. Herein we present the IDBac web platform, a crowd-sourced central knowledgebase of protein MS signatures of >1400 strains spanning 6 bacterial phyla. Accompanying the knowledgebase is analysis infrastructure to identify unknown isolates, probe relationships within culture collections using metadata integration, and visualize specialized metabolite differences within groups of closely related bacteria. To highlight this utility and encourage wide community contribution, examples of each are presented.

  PublisherOA PDFDOI

• Ion Mobility-Coupled Mass Spectrometry for Metallophore Detection

  Journal of Natural Products · 2025-02-10 · 3 citations

  articleOpen accessSenior authorCorresponding

  Metal chelating small molecules (metallophores) play significant roles in microbial interactions and bacterial survival; however, current methods to identify metallophores are limited by low sensitivity, a lack of metal selectivity, and/or complicated data analysis. To overcome these limitations, we developed a novel approach for detecting metallophores in natural product extracts using ion mobility-coupled mass spectrometry (IM-MS). As a proof of concept, marine bacterial extracts containing known metallophores were analyzed by IM-MS with and without added metals, and the data were compared between conditions to identify metal-binding metabolites. Ions with changes in both mass and mobility were specific to metallophores, enabling their identification within these complex extracts. Additionally, we compared the use of direct infusion (DI) and liquid chromatography (LC) separation with IM-MS. For most samples, DI outperformed LC by minimizing the time required for data collection and simplifying analysis. However, for some samples, LC improved the detection of metallophores likely by reducing ion suppression. IM-MS was then used to identify 10 metallophores in an extract from a marine Micromonospora sp. Overall, incorporating IM-MS facilitated the rapid detection of metal-binding natural products in complex bacterial extracts through the comparison of mass and mobility data in the presence and absence of metals.

  PublisherOA PDFDOI

• Discovery of New Everninomicin Analogs from a Marine-Derived Micromonospora sp. by Metabolomics and Genomics Approaches

  Marine Drugs · 2025-07-31 · 2 citations

  articleOpen accessSenior authorCorresponding

  During the course of genome mining initiatives, we identified a marine-derived Micromonospora, assigned here as strain WMMD956; the genome of WMMD956 appeared to contain a number of features associated with everninomicins, well-known antimicrobial orthosomycins. In addition, LCMS-based hierarchical clustering analysis and principal component analysis (hcapca) revealed that WMMD956 displayed an extreme degree of metabolomic and genomic novelty. Dereplication of high-resolution tandem mass spectrometry (HRMS/MS) and Global Natural Product Social molecular networking platform (GNPS) analysis of WMMD956 resulted in the identification of several analogs of the previously known everninomicin. Chemical structures were unambiguously confirmed by HR-ESI-MS, 1D and 2D NMR experiments, and the use of MS/MS data. The isolated metabolites, 1–3, were evaluated for their antibacterial activity against methicillin-resistant Staphylococcus aureus (MRSA).

  PublisherOA PDFDOI

• Machine Learning-Based Bioactivity Classification of Natural Products Using LC-MS/MS Metabolomics

  Journal of Natural Products · 2025-02-07 · 8 citations

  articleOpen accessSenior authorCorresponding

  The rediscovery of known drug classes represents a major challenge in natural products drug discovery. Compound rediscovery inhibits the ability of researchers to explore novel natural products and wastes significant amounts of time and resources. This study introduces a novel machine learning framework that can effectively characterize the bioactivity of natural products by leveraging liquid chromatography tandem mass spectrometry and untargeted metabolomics analysis. This accelerates natural product drug discovery by addressing the challenge of dereplicating previously discovered bioactive compounds. Utilizing the SIRIUS 5 metabolomics software suite and in-silico-generated fragmentation spectra, we have trained a ML model capable of predicting a compound’s drug class. This approach enables the rapid identification of bioactive scaffolds from LC-MS/MS data, even without reference experimental spectra. The model was trained on a diverse set of molecular fingerprints generated by SIRIUS 5 to effectively classify compounds based on their core pharmacophores. Our model robustly classified 21 diverse bioactive drug classes, achieving accuracies greater than 93% on experimental spectra. This study underscores the potential of ML combined with MFPs to dereplicate bioactive natural products based on pharmacophore, streamlining the discovery process and expediting improved methods of isolating novel antibacterial and antifungal agents.

  PublisherOA PDFDOI

• Utilizing the HiBiT System to Identify CARM1 Degraders for Targeted Cancer Therapy

  Journal of Medicinal Chemistry · 2025-12-26

  articleOpen access

  Preclinical studies validated coactivator-associated arginine methyltransferase 1 (CARM1) as a targetable therapeutic vulnerability, leading to the development of Proteolysis-Targeting Chimeras that specifically degrade CARM1. These compounds face significant translational challenges, including poor oral bioavailability and limited metabolic stability, which require extensive optimization. To identify more drug-like CARM1 degraders, we developed a high-throughput screening platform. We enabled antibody-free monitoring of CARM1 levels by fusing a HiBiT tag to CARM1 in MCF7 breast cancer cells. Complementation with LgBiT produces luciferase activity. Using this platform, we screened 1408 plant-derived natural product fractions to identify compounds that reduce CARM1 protein levels. This screen revealed two promising natural compounds, kusunokinin and exostemin, that specifically target CARM1 for degradation with selectivity over other protein arginine methyltransferases. Both compounds demonstrated functional anticancer activity, significantly inhibiting breast cancer cell colony formation and migration. Kusunokinin and exostemin represent lead compounds for developing next-generation CARM1-targeted therapeutics with enhanced translational potential.

  PublisherDOI

• Actinomycetoquinones A–E, Anthraquinone-γ-Pyrones Discovered from Marine-Derived <i>Actinomycetospora</i> sp. Bacterium

  Journal of Natural Products · 2025-09-25 · 1 citations

  articleOpen accessSenior authorCorresponding

  Facilitated by LC–MS–PCA metabolomics methods and effective molecular networking for strain prioritization and dereplication, five new anthraquinone-γ-pyrones, actinomycetoquinones A–E (1–5), were isolated from a marine-derived Actinomycetospora sp. bacterium. The structures of 1–5 were elucidated by analysis of their HRMS and NMR spectroscopic data. The absolute configuration of 1 was unequivocally determined by single-crystal X-ray diffraction analysis using Cu Kα radiation. Actinomycetoquinone C exhibited antibacterial activity against methicillin-resistant S. aureus (MRSA) and E. coli with MIC values of 1 and 4 μg/mL, respectively.

  PublisherDOI

Recent grants

• NIH Grant P41RR002301

  NIH · $6.0M · 2015

• Cancer Center Administration

  NIH · $99.8M · 1997–2028

• Mode of Action Core

  NIH · $61.7M · 2019–2025

• Omics approaches for natural products discovery

  NIH · $2.0M · 2013–2021

Frequent coauthors

• Chris M. Ireland

  University of Utah

  75 shared

• Mary Kay Harper

  University of Utah

  45 shared

• Thomas P. Wyche

  Quantitative BioSciences

  44 shared

• Scott R. Rajski

  41 shared

• Doug R. Braun

  35 shared

• Cameron R. Currie

  University of Wisconsin–Madison

  33 shared

• Yanpeng Hou

  University of Wisconsin–Madison

  31 shared

• Gisela P. Concepción

  24 shared

Labs

• Bugni Research GroupPI

Education

• Ph.D., Pharmaceutical Sciences

  University of Wisconsin–Madison