Biology subjects

Ness, M.

Publications and source records attributed to Ness, M..

4 recordsLinked to original sources

bioRxiv2026

Systematic assessment of the impact of targeted selection methods and environment-mimicking culture conditions on fungal natural product libraries

Natural products are a rich source of bioactive molecules and undiscovered chemical scaffolds with significant potential for novel drug discovery. Among these, fungi are particularly promising, offering diverse metabolites and undiscovered structural motifs. Large, well-curated collections of crude extracts, or "libraries", are central to fungal natural product discovery, serving as starting material for bioassay-guided isolation of new compounds. However, the systematic influence of fungal selection strategies, culturing methods, and environmental factors on chemical diversity remains underexplored. In this study, we analyzed several large fungal libraries to assess how geographic origin, and phylogenetic classification shape fungal chemical profiles. We also evaluated whether culturing conditions that more closely mimic natural environments can enhance metabolite diversity. Our findings offer practical guidelines for optimizing fungal natural product library design, improving drug development efficiency and access to novel chemotypes for future drug discovery. Summary Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=60 SRC="FIGDIR/small/709592v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@70a0e0org.highwire.dtl.DTLVardef@51f84eorg.highwire.dtl.DTLVardef@184dd90org.highwire.dtl.DTLVardef@1ee2813_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Optimization of 13C stable isotope labeling for the study of tricarboxylic cycle intermediates in mouse models

The tricarboxylic acid cycle (TCA), also known as the Krebs Cycle or the citric acid cycle, is an essential metabolic pathway involved in energy production that is often impacted by disease, making it of key interest to identify effective, affordable, and simple ways to monitor the impact of disease on TCA metabolism. 13C-based stable isotope labeling is a useful technique to track pathway alterations in living hosts. However, infusion-based methodologies are slow and expensive despite achieving steady-state labeling. Bolus-based methods are cheaper, faster, and compatible with biohazardous models, but require optimization to achieve maximum labeling. Herein, we performed bolus-based stable isotope labeling experiments in mouse models to identify the optimal dosage amount, label administration length, fast length prior to label administration, 13C-labeled precursor, and route of administration for the TCA cycle in the esophagus, heart, kidney, liver, plasma, and proximal colon. 13C-glucose at a concentration of 4 mg/g administered via intraperitoneal injection followed by a 90 minute label incorporation period achieved the best overall TCA labeling. For most organs, a 3 hour fast prior to label administration improved labeling, but labeling in the heart was better with no fasting period, showcasing the need to optimize methodology on an organ-by-organ basis. We also identified that bolus administration of glucose provided little impact on metabolism compared to vehicle control. The experiments outlined here provide critical information for designing in vivo stable isotope labeling experiments for the study of the TCA cycle. HighlightsO_LIA 90 minute waiting period following label administration provides best labeling C_LIO_LILarger dosing provides better labeling with little impact on metabolism C_LIO_LIFasting prior to label administration led to worse labeling in heart tissue C_LIO_LIIntraperitoneal dosing provides better incorporation than oral dosing C_LIO_LI13C-glucose provides better label incorporation than 13C-lactate and 13C-pyruvate C_LI

biochemistry↗

bioRxiv2024

Rationally Minimizing Natural Product Libraries Using Mass Spectrometry

Natural product libraries are crucial to drug development, but large libraries drastically increase the time and cost during initial high throughput screens. Here, we developed a method that leverages liquid chromatography-tandem mass spectrometry spectral similarity to dramatically reduce library size, with minimal bioactive loss. This method offers a broadly applicable strategy for accelerated drug discovery with cost reductions, which enable implementation in resource-limited settings.

bioinformatics↗

bioRxiv2024

SARS-CoV-2 infection unevenly impacts metabolism in the coronal periphery of the lungs

HighlightsO_LICOVID-19 significantly decreases amino acids, fatty acids, and most eicosanoids C_LIO_LISARS-CoV-2 preferentially localizes to central lung tissue C_LIO_LIMetabolic disturbance is highest in peripheral tissue, not central like viral load C_LIO_LISpatial metabolomics allows detection of metabolites not altered overall C_LI SARS-CoV-2, the virus responsible for COVID-19, is a highly contagious virus that can lead to hospitalization and death. COVID-19 is characterized by its involvement in the lungs, particularly the lower lobes. To improve patient outcomes and treatment options, a better understanding of how SARS-CoV-2 impacts the body, particularly the lower respiratory system, is required. In this study, we sought to understand the spatial impact of COVID-19 on the lungs of mice infected with mouse-adapted SARS2-N501YMA30. Overall, infection caused a decrease in fatty acids, amino acids, and most eicosanoids. When analyzed by segment, viral loads were highest in central lung tissue, while metabolic disturbance was highest in peripheral tissue. Infected peripheral lung tissue was characterized by lower levels of fatty acids and amino acids when compared to central lung tissue. This study highlights the spatial impacts of SARS-CoV-2 and helps explain why peripheral lung tissue is most damaged by COVID-19.

microbiology↗