Biology subjects

Jankowski, C. S. R.

Publications and source records attributed to Jankowski, C. S. R..

5 recordsLinked to original sources

bioRxiv2026

Mapping the mammalian dark metabolome by in vivo isotope tracing

Despite decades of biochemical study, a comprehensive map of the mammalian metabolome remains elusive. Mass spectrometry-based metabolomics detects thousands of small molecule-associated signals in mammalian tissues, but it is currently unclear how many of these reflect products of endogenous metabolism. Here, we leverage systematic in vivo isotope tracing to infer the biosynthetic origins of unidentified metabolites. We administered 26 different isotopically labelled nutrients to mice, measured circulating and tissue metabolite labelling by mass spectrometry, and developed a statistical framework to infer the number of carbon atoms incorporated from each of these precursors into more than 4,000 putative metabolites. We show this information can be harnessed for biosynthesis-aware structure elucidation using a multimodal AI model that co-embeds isotopic labelling patterns with chemical structures. This approach revealed several previously unrecognized families of mammalian metabolites, including cysteine-derived alkylthiazolidines, dithioacetal mercapturic acid derivatives, short-chain N-acyltaurines, acylglycyltaurines, and N-oxidized taurines. It further uncovered a family of mevalonate-derived isoprenoid metabolites that includes 2,3-dihydrofarnesoic acid, which is markedly depleted in both mouse and human aging. Age-related depletion of these isoprenoids is driven by impaired coenzyme A synthesis. Our work establishes the biosynthetic precursors for thousands of unidentified metabolites and reveals multiple previously unrecognized branches of mammalian metabolism.

biochemistry↗

bioRxiv2025

Itaconate is metabolized to 2-hydroxymethylsuccinate through a CoA-independent degradation pathway in mitochondria

The immunometabolite itaconate modulates cellular metabolism and is converted into structurally similar C5 dicarboxylates that require advanced analytics to decipher their metabolic fate. Here, we employ high-resolution mass spectrometry and tracing approaches and identify 2-hydroxymethylsuccinate (2HMS) as a previously unrecognized C5 dicarboxylate derived from itaconate. 2HMS synthesis occurs during inflammatory responses and upon itaconate treatment, as detected by 13C itaconate tracing. Pathway analysis reveals that methylglutaconyl-CoA hydratase (AUH) drives 2HMS synthesis through a CoA-independent conversion (CIC) pathway. This pathway is distinct from the CoA-dependent conversion (CDC) pathway that generates mesaconate and itaconyl-CoA influencing B12-dependent processes. In vivo inflammation studies reveal that adipose tissue prefers CIC to produce 2HMS and liver favors CDC-mediated mesaconate synthesis, highlighting tissue-specific itaconate degradation routes. This study identifies a new branch of itaconate metabolism, provides an analytical framework to resolve C5 dicarboxylate networks, and links 2HMS to inflammation and mitochondrial metabolism that might be targeted therapeutically.

cell biology↗

bioRxiv2025

Spatial metabolic gradients in the liver and small intestine

Mammalian organs are composed of cells, whose properties differ depending upon their spatial location. Gene expression in liver varies between periportal and pericentral hepatocytes1-3, and in intestine from crypts to villus tips4,5. A key element of tissue spatial organization is likely metabolic, but direct assessments of spatial metabolism remain limited. Here we map spatial metabolic gradients in murine liver and intestine. We developed an integrated experimental-computational workflow using MALDI imaging mass spectrometry, isotope tracing, and deep-learning artificial intelligence. Most measured metabolites (> 95%) showed significant spatial concentration gradients in liver lobules and intestinal villi. In the liver, tricarboxylic acid (TCA)-cycle metabolites and their labeling from both glutamine and lactate localized periportally. Energy-stress metabolites including adenosine monophosphate (AMP) also localized periportally, consistent with high periportal energy demand. In intestine, the TCA intermediates malate (tip) and citrate (crypt) showed opposite spatial patterns, which aligned with higher glutamine catabolism in tips and lactate oxidation in crypts based on isotope tracing. Finally, we mapped the fate of the obesogenic dietary sugar fructose. In the intestine, oral fructose was catabolized faster in the villus bottom than the tips. In the liver, fructose-derived carbon accumulated pericentrally as fructose-1-phosphate and triggered pericentral adenosine triphosphate (ATP) depletion. Thus, we both provide foundational knowledge regarding intestine and liver metabolic organization and identify fructose-induced focal derangements in liver metabolism.

biochemistry↗

bioRxiv2021

Slow TCA flux implies low ATP production in tumors

The tricarboxylic acid (TCA) cycle oxidizes carbon substrates to carbon dioxide, with the resulting high energy electrons fed into the electron transport chain to produce ATP by oxidative phosphorylation. Healthy tissues derive most of their ATP from oxidative metabolism, and the remainder from glycolysis. The corresponding balance in tumors remains unclear. Tumors upregulate aerobic glycolysis (the Warburg effect), yet they also typically require an intact TCA cycle and electron transport chain1-6. Recent studies have measured which nutrients contribute carbon to the tumor TCA metabolites7,8, but not tumor TCA flux: how fast the cycle turns. Here, we develop and validate an in vivo dynamic isotope tracing-mass spectrometry strategy for TCA flux quantitation, which we apply to all major mouse organs and to five tumor models. We show that, compared to the tissue of origin, tumor TCA flux is markedly suppressed. Complementary glycolytic flux measurements confirm tumor glycolysis acceleration, but the majority of tumor ATP is nevertheless made aerobically, and total tumor ATP production is suppressed compared to healthy tissues. In murine pancreatic cancer, this is accommodated by downregulation of the major energy-using pathway in the healthy exocrine pancreas, protein synthesis. Thus, instead of being hypermetabolic as commonly assumed, tumors apparently make ATP at a lower than normal rate. We propose that, as cells de-differentiate into cancer, they eschew ATP-intensive processes characteristic of the host tissue, and that the resulting suppressed ATP demand contributes to the Warburg effect and facilitates cancer growth in the nutrient-poor tumor microenvironment.

cancer biology↗

bioRxiv2021

Metabolic function in aging retina and retinal pigment epithelium remains robust despite vision loss

PurposeCharacterize how metabolic function in the murine retina and retinal pigment epithelium-choroid-sclera (eyecup) complex is impacted by natural aging. MethodsWe examined scotopic and photopic visual function of young (3-6 months) and aged (23-26 months) C57Bl/6J mice using electroretinograms (ERGs). Metabolic changes in retina and eyecup explants were characterized by measuring uptake and usage of U-13C-glucose or U-13C-glutamine at different timepoints by gas chromatography-mass spectrometry (GC-MS), measuring oxygen consumption rate (OCR) using a perifusion apparatus, and determining ATP levels with a bioluminescence assay. ResultsScotopic and photopic ERG responses declined in aged mice. Glucose metabolism, glutamine metabolism, OCR, and ATP pools in retinal explants were mostly unaffected by the age of the mouse. In eyecups, glutamine usage in the Krebs Cycle decreased while glucose metabolism, OCR, and ATP pools remained stable. ConclusionsThe ex vivo approach in our study to examine aging glucose and glutamine metabolism in retina and RPE showed negligible impact of age on retina and an impairment of glutamine anaplerosis in eyecups. The surprising metabolic stability of these tissues ex vivo suggests age-related metabolic alterations in these tissues may not be intrinsic. Future experiments should focus on determining whether external factors including nutrient supply, oxygen availability, or other structural changes influence ocular metabolism in vivo.

biochemistry↗