Biology subjects

Siuzdak, G.

Publications and source records attributed to Siuzdak, G..

7 recordsLinked to original sources

bioRxiv2025

Erucamide regulates retinal neurovascular crosstalk

Neurovasculoglial crosstalk is critical in establishing and maintaining a functional neurovascular unit. Breakdown in the unit is central to many neurodegenerative disorders of the CNS of which the retina is a component. A growing literature indicated that primary fatty acid amides (PFAMs) can regulate this crosstalk between vasculature and neuronal tissues. In this study we describe a central role for erucamide, a 22:1 mono-unsaturated omega-9 fatty acid amide, in degenerating retinal tissues. Using high-resolution global mass spectrometry-based metabolomics, we cataloged metabolites in murine models of retinal degeneration and show that while PFAMs, in general, are highly dysregulated, erucamide is the one most significantly diminished during photoreceptor atrophy. Using rodent models of retinal degeneration and novel organosilane-modified porous silicon nanoparticles (pSiNPs) for the in vivo delivery of erucamide, we demonstrate that erucamide activates CD11b+ myeloid cells, leading to the upregulation of angiogenic and neurotrophic cytokines that stabilize retinal degeneration. We identified TMEM19 as a novel binding protein for erucamide that is crucial for human iPSC-derived macrophage precursor cells activation and subsequent neurotrophic and angiogenic factor production. These findings reveal a previously unknown PFAM pathway that is modulated during retinal degenerative diseases, demonstrating that erucamide or functional analogues and their action through TMEM19 may be useful as a therapeutic alternative to neuroprotective and stem cell-based approaches for the treatment of retinal degenerative diseases.

neuroscience↗

bioRxiv2022

Mixed Heavy Metals Stress Induces Global Iron Starvation as Revealed by System Level Multi-Omic Analyses

Globally, multiple heavy metal contamination is an increasingly common problem. As heavy metals have the potential to disrupt microbially-mediated biogeochemical cycling, it is critical to understand their impact on microbial physiology. However, systems-level studies on the effects of a combination of heavy metals on bacteria are lacking. Here, we use a native Bacillus cereus isolate from the subsurface of the Oak Ridge Reservation (ORR; Oak Ridge, TN, USA) -- representing a highly abundant species at the site-- to assess the combined impact of eight metal contaminants. Using this metal mixture and individual metals, all at concentrations based on the ORR site geochemistry, we performed growth experiments and proteomic analyses of the B. cereus strain, in combination with targeted MS-based metabolomics and gene expression profiling. The combination of eight metals impacts cell physiology in a manner that could not have been predicted from summing phenotypic responses to the individual metals. Specifically, exposure to the metal mixture elicited global iron starvation responses not observed in any of the individual metal treatments. As nitrate is also a significant contaminant at the ORR site and nitrate and nitrite reductases are iron-containing enzymes, we also examined the effects of the metal mixture on reduction of nitrogen oxides. We found that the metal mixture inhibits the activity of these enzymes through a combination of direct enzymatic damage and post-transcriptional and post-translational regulation. Altogether, these data suggest that metal mixture studies are critical for understanding how multiple rather than individual metals influence microbial processes in the environment.

microbiology↗

bioRxiv2021

METLIN Neutral Loss Database Enhances Similarity Analysis

Tandem mass spectrometry (MS2) data is an effective resource for the identification of known molecules and the putative identification of novel, previously uncharacterized molecules (unknowns). Yet, MS2 data alone is limited in characterizing structurally closely related molecules with different masses. Neutral loss data is key in retrieving this structural similarity. To facilitate unknown identification and complement METLINs MS2 fragment ion data for characterizing structurally related molecules, we have created the METLIN neutral loss database (https://metlin-nl.scripps.edu).

biochemistry↗

bioRxiv2020

LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications

We present LipidFinder 2.0, incorporating four new modules that apply artefact filters, remove lipid and contaminant stacks, in-source fragments and salt clusters, and a new isotope deletion method which is significantly more sensitive than available open-access alternatives. We also incorporate a novel false discovery rate (FDR) method, utilizing a target-decoy strategy, which allows users to assess data quality. A renewed lipid profiling method is introduced which searches three different databases from LIPID MAPS and returns bulk lipid structures only, and a lipid category scatter plot with color blind friendly pallet. An API interface with XCMS Online is made available on LipidFinders online version. We show using real data that LipidFinder 2.0 provides a significant improvement over non-lipid metabolite filtering and lipid profiling, compared to available tools. AvailabilityLipidFinder 2.0 is freely available at https://github.com/ODonnell-Lipidomics/LipidFinder and http://lipidmaps.org/resources/tools/lipidfinder. Contactlipidfinder@cardiff.ac.uk Supplementary informationSupplementary data are available at Bioinformatics online.

biochemistry↗

bioRxiv2018

Palbociclib and fulvestrant act in synergy to modulate central carbon metabolism in breast cancer cells

Palbociclib, is a selective inhibitor of cyclin-dependent kinases 4 and 6 and used as a first-line treatment for patients with estrogen receptor positive breast cancer. It has been shown that patients have improved progression-free survival when treated in combination with fulvestrant, an estrogen receptor antagonist. However, the mechanisms for this survival advantage are not known. We sought to analyze metabolic and transcriptomic changes in MCF-7 adenocarcinoma breast cancer cells following single and combined treatments to determine if selective metabolic pathways are targeted during combination therapy. Our results showed that individually, the drugs caused metabolic disruption to the same metabolic pathways, however fulvestrant additionally attenuated the pentose phosphate pathway and the production of important coenzymes. A comprehensive effect was observed when the drugs were applied together, confirming the combinatory therapy's synergism in the cell model. This study highlights the power of merging high-dimensional datasets to unravel mechanisms involved in cancer metabolism and therapy.\n\nHighlights{circ} First study employing multi-omics to investigate combined therapy on breast cancer cells\n{circ}Fulvestrant attenuates the pentose phosphate pathway and coenzyme production\n{circ}Synergism of palbociclib and fulvestrant was confirmed in vitro\n{circ}Altered key pathways have been identified\n\n\neTOC BlurbJohnson et al. applied an innovative multi-omics approach to decipher metabolic pathways affected by single versus combination dosing of palbociclib and fulvestrant in estrogen receptor positive breast cancer. Key metabolites and genes were correlated within metabolic pathways and shown to be involved in the drugs' synergism.

biochemistry↗

bioRxiv2017

Dietary xenoestrogens significantly alter cellular metabolism induced by palbociclib/letrozole combination cancer therapy

HighlightsO_LISynergism of combined palbociclib/letrozole chemotherapy was examined by global metabolomics\nC_LIO_LICombination therapy led to more pronounced effects on the MCF-7 metabolome than single agents\nC_LIO_LIDietary phyto- and mycoestrogens significantly affected the metabolic and anti-oncogenic response of the drugs\nC_LIO_LIImplications of these bio-active chemicals on therapeutic success in breast cancer patients appear plausible\nC_LI\n\nIn BriefWarth et al. used innovative global metabolomics and pathway prediction technology to describe the metabolic effects of the combined palbociclib/letrozole breast cancer therapy. Moreover, the role of dietary xenoestrogens on this treatment was examined by metabolite data, proliferation experiments, and functional assays.\n\nSummaryRecently, the palbociclib/letrozole combination therapy was granted accelerated FDA approval for the treatment of estrogen receptor (ER) positive breast cancer. Since the underlying metabolic effects of these drugs are yet unknown, we investigated their synergism at the metabolome level in MCF-7 cells. As xenoestrogens interact with the ER, we additionally aimed at deciphering the impact of the phytoestrogen genistein, and the estrogenic mycotoxin zearalenone on this treatment. A global metabolomics approach was applied to unravel metabolite and pathway modifications. The results clearly showed that the combined effects of palbociclib and letrozole on cellular metabolism were far more pronounced than that of each agent alone and potently influenced by xenoestrogens. This behavior was confirmed in proliferation experiments and functional assays. Specifically, amino acids and central carbon metabolites were attenuated while higher abundances were observed for fatty acids and most nucleic acid related metabolites. Interestingly, exposure to model xenoestrogens appeared to partially counteract these effects.

cancer biology↗

bioRxiv2017

Exposing the Exposome with Global Metabolomics andCognitive Computing

Concurrent exposure to a wide variety of xenobiotics and their combined toxic effects can play a pivotal role in health and disease, yet are largely unexplored. Investigating the totality of these exposures, i.e. the exposome, and their specific biological effects constitutes a new paradigm for environmental health but still lacks high-throughput, user-friendly technology. We demonstrate the utility of mass spectrometry-based global exposure metabolomics combined with tailored database queries and cognitive computing for comprehensive exposure assessment and the straightforward elucidation of biological effects. The METLIN Exposome database has been redesigned to help identify environmental toxicants, food contaminants and supplements, drugs, and antibiotics as well as their biotransformation products, through its expansion with over 700,000 chemical structures to now include more than 950,000 unique small molecules. More importantly, we demonstrate how the XCMS/METLIN platform now allows for the readout of the biological effect of a toxicant through metabolomic-derived pathway analysis and further, cognitive computing provides a means of assessing the role of a potential toxicant. The presented workflow addresses many of the outstanding methodological challenges current exposome research is facing and will serve to gain a deeper understanding of the impact of environmental exposures and combinatory toxic effects on human health.

epidemiology↗