Biology subjects

Roichman, A.

Publications and source records attributed to Roichman, A..

9 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

Lack of consistent effect of dietary fiber on immune checkpoint blockade efficacy across diverse murine tumor models

Immune checkpoint blockade (ICB) has transformed cancer treatment, but success rates remain low in most cancers. Recent research suggest that dietary fiber enhances ICB response in melanoma patients and murine preclinical models through microbiome-dependent mechanisms. Yet, the robustness of this effect across cancer types and dietary contexts remains unclear. Specifically, prior literature compared grain-based chow (high fiber) to low-fiber purified diet, but these diets differ also on other dimensions including phytochemicals. Here we investigated, in mice fed grain-based chow or purified diets with differing quantities of isolated fibers (cellulose and inulin), metabolite levels and ICB activity in multiple tumor models. The blood and fecal metabolome were relatively similar between mice fed high- and low-fiber purified diets, but differed massively between mice fed purified diets or chow, identifying the factor as diet type, independent of fiber. Tumor growth studies in three implantable and two spontaneous genetically engineered tumor models revealed that fiber has a weaker impact on ICB (anti-PD-1) efficacy than previously reported. In some models, dietary modulation impacted ICB activity, but not in a consistent direction across models. In none of the models did we observe the pattern expected if fiber controlled ICB efficacy: strong efficacy in both chow and high-fiber purified diet but low efficacy in low-fiber purified diet. Thus, dietary fiber appears to have limited or inconsistent effect on ICB efficacy in mouse models, and other dietary factors that correlate with fiber intake may underlie the clinical correlations between fiber consumption and immunotherapy outcomes.

cancer biology↗

bioRxiv2024

Language model-guided anticipation and discovery of unknown metabolites

Despite decades of study, large parts of the mammalian metabolome remain unexplored. Mass spectrometry-based metabolomics routinely detects thousands of small molecule-associated peaks within human tissues and biofluids, but typically only a small fraction of these can be identified, and structure elucidation of novel metabolites remains a low-throughput endeavor. Biochemical large language models have transformed the interpretation of DNA, RNA, and protein sequences, but have not yet had a comparable impact on understanding small molecule metabolism. Here, we present an approach that leverages chemical language models to discover previously uncharacterized metabolites. We introduce DeepMet, a chemical language model that learns the latent biosynthetic logic embedded within the structures of known metabolites and exploits this understanding to anticipate the existence of as-of-yet undiscovered metabolites. Prospective chemical synthesis of metabolites predicted to exist by DeepMet directs their targeted discovery. Integrating DeepMet with tandem mass spectrometry (MS/MS) data enables automated metabolite discovery within complex tissues. We harness DeepMet to discover several dozen structurally diverse mammalian metabolites. Our work demonstrates the potential for language models to accelerate the mapping of the metabolome.

bioinformatics↗

bioRxiv2024

A Ketogenic Diet Sensitizes Pancreatic Cancer to Inhibition of Glutamine Metabolism

Pancreatic cancer is the third leading cause of cancer death in the United States, and while conventional chemotherapy remains the standard treatment, responses are poor. Safe and alternative therapeutic strategies are urgently needed1. A ketogenic diet has been shown to have anti-tumor effects across diverse cancer types but will unlikely have a significant effect alone. However, the diet shifts metabolism in tumors to create new vulnerabilities that can be targeted (1). Modulators of glutamine metabolism have shown promise in pre-clinical models but have failed to have a marked impact against cancer in the clinic. We show that a ketogenic diet increases TCA and glutamine-associated metabolites in murine pancreatic cancer models and under metabolic conditions that simulate a ketogenic diet in vitro. The metabolic shift leads to increased reliance on glutamine-mediated anaplerosis to compensate for low glucose abundance associated with a ketogenic diet. As a result, glutamine metabolism inhibitors, such as DON and CB839 in combination with a ketogenic diet had robust anti-cancer effects. These findings provide rationale to study the use of a ketogenic diet with glutamine targeted therapies in a clinical context. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=186 SRC="FIGDIR/small/604377v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1ebeefforg.highwire.dtl.DTLVardef@97e2ceorg.highwire.dtl.DTLVardef@1ab45c3org.highwire.dtl.DTLVardef@1713540_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical Abstract Description: Mechanistic rationale for combining a ketogenic diet and glutamine metabolism inhibitors. The combination of low glucose from a ketogenic diet and pharmacologic glutamine inhibition impairs nutrient input to mitochondria, reducing cancer growth.

cancer biology↗

bioRxiv2023

Adaptations to water stress and pastoralism in the Turkana of northwest Kenya

The Turkana people inhabit arid regions of east Africa--where temperatures are high and water is scarce--and they practice subsistence pastoralism, such that their diet is primarily composed of animal products. Working with Turkana communities, we sequenced 367 genomes and identified 8 regions putatively involved in adaptation to water stress and pastoralism. One of these regions includes a putative enhancer for STC1--a kidney-expressed gene involved in the response to dehydration and the metabolism of purine-rich foods such as red meat. We show that STC1 is induced by antidiuretic hormone in humans, is associated with urea levels in the Turkana themselves, and is under strong selection in this population (s[~]0.041). This work highlights that partnerships with subsistence-level groups can lead to new models of human physiology with biomedical relevance.

evolutionary biology↗

bioRxiv2022

Systematic identification and characterization of novel genes in the regulation and biogenesis of photosynthetic machinery

Photosynthesis is central to food production and the Earths biogeochemistry, yet the molecular basis for its regulation remains poorly understood. Here, using high-throughput genetics in the model eukaryotic alga Chlamydomonas reinhardtii, we identify with high confidence (FDR<0.11) 70 previously-uncharacterized genes required for photosynthesis. We then provide a resource of mutant proteomes that enables functional characterization of these novel genes by revealing their relationship to known genes. The data allow assignment of 34 novel genes to the biogenesis or regulation of one or more specific photosynthetic complexes. Additional analysis uncovers at least seven novel critical regulatory proteins, including five Photosystem I mRNA maturation factors and two master regulators: MTF1, which impacts chloroplast gene expression directly; and PMR1, which impacts expression via nuclear-expressed factors. Our work provides a rich resource identifying novel regulatory and functional genes and placing them into pathways, thereby opening the door to a system-level understanding of photosynthesis. HighlightsO_LIHigh-confidence identification of 70 previously-uncharacterized genes required for photosynthesis C_LIO_LIProteomic analysis of mutants allows assignment of function to novel genes C_LIO_LICharacterization of 5 novel Photosystem I mRNA maturation factors validates this resource C_LIO_LIMTF1 and PMR1 identified as master regulators of photosynthesis C_LI

cell biology↗

bioRxiv2022

Gut bacterial nutrient preferences quantified in vivo

Great progress has been made in understanding gut microbiomes products and their effects on health and disease. Less attention, however, has been given to the inputs that gut bacteria consume. Here we quantitatively examine inputs and outputs of the mouse gut microbiome, using isotope tracing. The main input to microbial carbohydrate fermentation is dietary fiber, and to branched-chain fatty acids and aromatic metabolites is dietary protein. In addition, circulating host lactate, 3-hydroxybutyrate and urea (but not glucose or amino acids) feed the gut microbiome. To determine nutrient preferences across bacteria, we traced into genus-specific bacterial protein sequences. We find systematic differences in nutrient use: Most genera in the phylum Firmicutes prefer dietary protein, Bacteroides dietary fiber, and Akkermansia circulating host lactate. Such preferences correlate with microbiome composition changes in response to dietary modifications. Thus, diet shapes the microbiome by promoting the growth of bacteria that preferentially use the ingested nutrients.

molecular biology↗

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↗

bioRxiv2018

Inhibition of retrotransposition improves health and extends lifespan of SIRT6 knockout mice

Mice deficient for SIRT6 exhibit a severely shortened lifespan, growth retardation, and highly elevated LINE1 (L1) activity. Here we report that SIRT6 deficient cells and tissues accumulate abundant cytoplasmic L1 cDNA which triggers massive type I interferon response via activation of cGAS. Remarkably, nucleoside reverse transcriptase inhibitors (NRTIs), which inhibit L1 retrotransposition, significantly improved health and lifespan of SIRT6 knockout mice and completely rescued type I interferon response. In tissue culture, inhibition of L1 with siRNA or NRTIs abrogated type I interferon response, in addition to a significant reduction of DNA damage markers. These results indicate that L1 activation contributes to the pathologies of SIRT6 knockout mice. Similarly, L1 transcription, cytoplasmic cDNA copy number and type I interferons were elevated in the wild type aged mice. As sterile inflammation is a hallmark of aging we propose that modulating L1 activity may be an important strategy for attenuating age-related pathologies.\n\nHighlightsO_LISIRT6 KO mice accumulate L1 cDNA triggering type I interferon response via cGAS pathway\nC_LIO_LIWild type aged mice accumulate L1 cDNA and display type I interferon response\nC_LIO_LIReverse transcriptase inhibitors rescue type I interferon response and DNA damage\nC_LIO_LIReverse transcriptase inhibitors extend lifespan and improve health of SIRT6 KO mice\nC_LI

molecular biology↗