Biology subjects

Meistermann, D.

Publications and source records attributed to Meistermann, D..

5 recordsLinked to original sources

bioRxiv2025

Maternal low protein diet alters the development of reward circuits from childhood to adulthood by reshaping its function

Inadequate nutrition during pregnancy can lead to intrauterine growth retardation and low birth weight, which in turn increases the risk of developing metabolic disorders in adulthood, according to various epidemiological and clinical studies. The inclination of individuals born with low birth weight towards palatable foods indicates a possible modification in the hedonic aspect of their eating behavior. However, our understanding of the ontogenesis of structural organization and function within the brains reward circuits remains limited. Therefore, the objective of this research is to investigate the preferences for palatable food, molecular signatures of reward circuits, and functional properties of the nucleus accumbens (NAc) in a rat model of perinatal protein restriction (LP). Starting from weaning, continuing into adolescence and adulthood, a longitudinal analysis was conducted on rats born to mothers with protein-restricted diets during gestation and lactation (LP pups), comparing them to pups born from control dams (CD pups). The LP group exhibited an increased preference for palatable food at day 25 after birth (P25), followed by a decreased preference during adolescence (P50), and no significant difference in palatable food preference at P95 (young adult) compared to CD rats. Molecular and electrophysiological assessments of medium spiny neurons (MSN) in the NAc revealed a reorganization of reward circuits during crucial developmental periods, potentially influencing the attractiveness of palatable food for the LP group. This study represents the first exploration of how preferences for palatable food evolve throughout an individuals lifespan and how these observations correlate with the remodeling of reward circuits. By shedding light on the molecular and functional aspects of reward circuits, we contribute to a better understanding of the link between perinatal nutrition, behavioral preferences, and the underlying neural mechanisms.

neuroscience↗

bioRxiv2023

DeconV: Probabilistic Cell Type Deconvolution from Bulk RNA-sequencing Data

Bulk RNA-Seq remains a widely adopted technique to profile gene expression, primarily due to the persistent challenges associated with achieving single-cell resolution. However, a key challenge is accurately estimating the proportions of different cell types within these bulk samples. To address this issue, we introduce DeconV, a probabilistic framework for cell-type deconvolution that uses scRNA-Seq data as a reference. This approach aims to mitigate some of the limitations in existing methods by incorporating statistical frameworks developed for scRNA-Seq, thereby simplifying issues related to reference preprocessing such as normalization and marker gene selection. We benchmarked DeconV against established methods, including MuSiC, CIBERSORTx, and Scaden. Our results show that DeconV performs comparably in terms of accuracy to the best-performing method, Scaden, but provides additional interpretability by offering confidence intervals for its predictions. Furthermore, the modular design of DeconV allows for the investigation of discrepancies between bulk-sequenced samples and artificially generated pseudo-bulk samples.

bioinformatics↗

bioRxiv2023

Characterization of cortical neurodevelopment in vitro using gene expression and morphology profiles from single cells

AbstractDifferentiation of induced pluripotent stem cells (iPSC) towards neuronal lineages has enabled diverse cellular models of human neurodevelopment and related disorders. However, in vitro differentiation is a variable process that frequently leads to heterogeneous cell populations that may confound disease-relevant phenotypes. Here, we report a thorough characterization of cortical neuron differentiation from iPSCs using joint profiling of neuronal morphology and transcriptomics in single cells. We assayed 60,000 developing neurons across three timepoints with CellPainting, a high-content imaging method, and single-cell RNA-sequencing (scRNA-seq). By modeling the relationship between morphological features and gene expression within our differentiation system, we annotated image-based features with biological functions and found that while phenotypes related to cell morphology capture broader neuronal classes than scRNA-seq, they enhance our ability to quantify the biological processes that drive neuronal differentiation over time, such as mitochondrial function and cell cycle. Further, we found that while over 60% of the cells match those seen in the fetal brain, 28% represented metabolically abnormal cell states and broader neuronal classes specific to in vitro cells. Finally, we show that specific subtypes of iPSC-derived cortical neurons are a relevant model for a range of brain-related complex traits, including schizophrenia and bipolar disorder, highlighting the potential of multi-modal single cell phenotyping for disease modeling.

genomics↗

bioRxiv2019

Spatio-temporal analysis of human preimplantation development reveals dynamics of epiblast and trophectoderm

Recent technological advances such as single-cell RNAseq1-3 and CRISPR-CAS9-mediated knock-out4 have allowed an unprecedented access into processes orchestrating human preimplantation development5. However, the sequence of events which occur during human preimplantation development are still unknown. In particular, timing of first human lineage specification, the process by which the morula cells acquire a specific fate, remains elusive. Here, we present a human preimplantation development model based on transcriptomic pseudotime modelling of scRNAseq biologically validated by spatial information and precise time-lapse staging. In contrast to mouse, we show that trophectoderm (TE) / inner cell mass (ICM) lineage specification in human is only detectable at the transcriptomic level at the blastocyst stage, just prior to expansion. We validated the expression profile of novel markers enabling precise staging of human preimplantation embryos, such as IFI16 which highlights establishment of epiblast (EPI) and NR2F2 which appears at the transition from specified to mature TE. Strikingly, mature TE cells arise from the polar side, just after specification, supporting a model of polar TE cells driving TE maturation. Altogether, our study unravels the first lineage specification event in the human embryo and provides a browsable resource for mapping spatio-temporal events underlying human lineage specification.

cell biology↗

bioRxiv2018

Development of a robust automated tool for the annotation of embryo morphokinetic parameters

Study QuestionIs it possible to automatically annotate human embryo development in time-lapse devices, with results comparable to manual annotation?\n\nSummary AnswerWe developed an automated tool for the annotation of embryo morphokinetic parameters having a high concordance with expert manual annotation in a large scale-study.\n\nWhat is Known AlreadyMorphokinetic parameters obtained with time-lapse devices are increasingly used for human embryo quality assessment. However, their annotation is timeconsuming and can be operator-dependent, highlighting the need of developing automated approaches.\n\nStudy Design, Size, DurationThis monocentric pilot study was conducted using 701 blastocysts originating from 584 couples undergoing IVF with embryo culture in a time-lapse device and on 4 mouse embryos.\n\nParticipants/Materials, Setting, MethodsAn automated annotation tool was developed based on grey level coefficient of variation and detection of the thickness of the zona pellucida. The timings of cellular events obtained with the automated tool were compared with those obtained manually by 2 expert embryologists. The same procedure was applied on 4 mouse preimplantation embryos obtained with a different device in a different setting.\n\nMain Results and the Role of ChanceAlthough some differences were found when embryos were considered individually, we found an overall excellent concordance between automated and manual annotation of human embryo morphokinetics from fertilization to expanded blastocyst stage (r2=0.94). Moreover, the automated annotation tool gave promising results across species (human, mice).\n\nLimitations, Reasons for CautionThese results should undergo multi-centric external evaluation in order to test the overall performance of the annotation tool.\n\nWider Implications of the FindingsOur system performs significantly better than the ones reported in the literature and on a bigger cohort, paving the way for high-throughput analysis of multicentric morphokinetic databases, providing new insights into the clinical value of morphokinetics as predictor of embryo quality and implantation.\n\nStudy Funding/Competing Interest(s)This study was partly funded by Finox Forward Grant 2016.\n\nTrial Registration NumberNA

developmental biology↗