Manser, C. | bioRxiv Science

bioRxiv2025

Epigenetic-metabolic axis in the temporal scaling of mammalian cortical neurogenesis across species

Developmental timescales vary widely across species, with mammalian cortical neurogenesis ranging from just days to several months. Given the conserved laminar architecture and regulatory gene expression sequences, the underlying molecular mechanisms controlling neurogenesis rate remain unknown. Using mouse, ferret, and human models, we combined comparative transcriptomics with mathematical modelling to identify conditions that scale temporal gene expression programs during neurogenesis. We show that H3K27me3-mediated repression is critical for maintaining species-specific neurogenesis timescales, and its ablation scales down neurogenesis duration. Furthermore, we identified the tricarboxylic-acid (TCA)-cycle metabolite -ketoglutarate as a modulator of developmental timing via H3K27me3 demethylation. Together, our findings link epigenetic and metabolic states to the control of species-specific developmental timescales and, ultimately, brain size.

developmental biology↗

bioRxiv2021

The metabolome and lipidome of colorectal adenomas and cancers

IntroductionIn-depth knowledge of metabolic dysregulations in colorectal cancer (CRC) (and other cancers as well) is essential for developing treatments that specifically kill neoplastic cells. It may also allow us to pinpoint metabolites or lipids with potential for development as tumor biomarkers for use in body-fluid or breath assays. CRC onset is preceded by an interval of [~]10 years characterized by the presence of precancerous lesions, and our previous studies have revealed epigenomic, transcriptomic, and proteomic evidence in these lesions of certain metabolic changes typical of CRC. These findings prompted us to conduct untargeted metabolomic and lipidomic analyses of CRCs and colorectal adenomas (the most common precancerous lesions of the gut). MethodsWe analyzed 29 endoscopically collected tumor tissue samples (29 adenomas [ADNs], 10 CRCs, each with a colon segment-matched sample of normal mucosa [i.e., 29 NM-ADN, 10 NM-CRC]). The freshly collected samples were promptly frozen in liquid nitrogen and later processed to obtain metabolite and lipid extracts. Each of the 78 samples was analyzed with nano-flow LC-MS/MS (liquid chromatography with mass spectrometry) to characterize its metabolome (using HILIC, Hydrophilic Interaction Liquid Chromatography) and lipidome (using RP, Reversed Phase chromatography). The data acquired were processed using Progenesis QI. For statistical and multivariate analysis of the resulting peak tables, we used basic R packages and the R package made4. ResultsUnsupervised between-group analysis based on the full set of detected metabolites (n=1830) and lipids (n=2365) clearly discriminated ADNs and CRCs from their matched samples of normal mucosa at both the metabolome and lipidome levels. Compared with the NM-ADN, the ADNs contained significantly different levels of 14.6% of the metabolites and 10.8% of the lipids. Fewer compounds (9.1% of metabolites, 6.2% of lipids) displayed differential abundance in CRCs (vs. NM-CRC). The metabolome and lipidome of the NM-ADN also differed from those of the NM-CRC, probably reflecting the presence of a field cancerization effect exerted by the invasive tumors. A substantial number of metabolites (n=340) and lipids (n=201) also displayed abundance differentials across the sequential tumorigenic stages represented by the NM-ADN (considered more representative of NM from a lesion-free colon) [->] ADN [->] CRC. In most cases, the trend consisted of progressive increases or progressive decreases in abundance as the tumorigenesis advanced. ConclusionsOur findings provide a preliminary picture of the progressive metabolomic and lipidomic changes occurring during the adenomatous phase of colorectal tumorigenesis. Once definitively annotated, the numerous differentially abundant compounds detected in this study may well shed valuable light on the metabolic dysregulations occurring during this process and provide useful clues for the development of novel tools for the diagnosis and treatment of colorectal tumors.

cancer biology↗

bioRxiv2020

BOSS-RUNS: a flexible and practical dynamic read sampling framework for nanopore sequencing

One particularly promising feature of nanopore sequencing is the ability to reject reads, enabling real-time selection of molecules without complex sample preparation. This is based on the idea of deciding whether a molecule warrants full sequencing depending on reading a small initial part. Previously, such decisions have been based on a priori determination of which regions of the genome were considered of interest. Instead, here we consider more general and complex strategies that incorporate already-observed data in order to optimize the rejection strategy and maximise information gain from the sequencing process. For example, in the presence of coverage bias redistributing data from areas of high to areas of low coverage would be desirable. We present BOSS-RUNS, a mathematical and algorithmic framework to calculate the expected benefit of new reads and generate dynamically updated decision strategies for nanopore sequencing. During sequencing, in real time, we quantify the current uncertainty at each site of one or multiple reference genomes, and for each novel DNA fragment being sequenced we decide whether the potential decrease in uncertainty at the sites it will most likely cover warrants reading it in its entirety. This dynamic, adaptive sampling allows real-time focus of sequencing efforts onto areas of highest benefit. We demonstrate the effectiveness of BOSS-RUNS by mitigating coverage bias across and within the species of a microbial community. Additionally, we show that our approach leads to improved variant calling due to its ability to sample more data at the most relevant genomic positions.

genomics↗