Biology subjects

Sprenger, H.

Publications and source records attributed to Sprenger, H..

5 recordsLinked to original sources

bioRxiv2026

Cell line identity rather than medium composition determines transcriptomic profiles of HepaRG and HuH7 cells cultured in chemically defined or serum-based media: comparison with primary human hepatocytes

The composition of culture medium is a major, yet frequently undercontrolled, determinant of hepatic cell state in vitro. For decades, fetal bovine serum (FBS) has been routinely incorporated into liver cell culture. Its undefined and lot-to-lot variable composition can, however, confound cell identity and experimental reproducibility. Serum-free, chemically defined media (CDM) represent an alternative approach that can improve standardization, but the consequences of transitioning from FBS-supplemented media (FBS-SM) to CDM remain insufficiently characterized in hepatic models, particularly with respect to metabolic and detoxification programs that govern xenobiotic handling and hepatotoxicity readouts. Here, we systematically assessed how replacing FBS-SM with CDM remodels transcriptomic profiles in two widely used human hepatic cell lines (HepaRG and HuH7 cells) and compared the results to that obtained from primary human hepatocytes (PHH). Global transcriptomic analyses indicated that cell type was the primary driver of variance, whereas medium induced a model-dependent secondary effect. Functional interpretation showed preferential enhancement of xenobiotic metabolism and transport-associated programs in HepaRG cells, while HuH7 cells response was dominated by lipid/sterol homeostasis and stress-linked processes. Benchmarking against PHH based on hepatic identity and detoxification gene panels further supported improved PHH alignment for HepaRG cells under CDM compared to cultures with FBS-SM, with limited improvement for HuH7 cells. Collectively, these findings address a key knowledge gap by defining how FBS-SM and CDM impact the transcriptomic profiles of HepaRG and HuH7 cells.

cell biology↗

bioRxiv2025

High-resolution transcriptional atlas of growing maize shoot organs throughout plant development under well-watered and drought conditions

Crop improvement goals for maize (Zea mays L.) involve the targeted optimization of various organs, making it crucial to understand the developmental characteristics and gene expression patterns during organ development and in response to environmental stresses such as drought. In this study, we investigated the development of maize leaves and internodes at both macroscopic and cellular level, and identified a shared fundamental growth design with distinct timing between the two organs. By transcriptome profiling developmental zones of leaves and internodes of different ranks, and of the ear, at different growth stages under both well-watered and drought conditions, we generated a high-resolution spatiotemporal transcriptome dataset on 272 different tissues and conditions, which we make available as a searchable database. While the gene regulatory networks governing cell division and cell elongation were highly conserved across organs, precise expression regulation of particular gene families was observed across organs and within the same organ. Additionally, we highlight the expression of key genes involved in regulating leaf angle and vascular development, showing spatiotemporal regulation of differentiation parallel to growth. This comprehensive expression atlas, combined with phenotypic data, offers a deeper understanding of the similarities and differences among shoot organs and tissues during development and drought response, and provides a valuable resource for engineering organ-specific traits in maize.

plant biology↗

bioRxiv2023

Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform

BackgroundThermography is a popular tool to assess plant water use behavior, as plant temperature is influenced by transpiration rate, and is commonly used in field experiments to detect drought stress. Its application in indoor automated phenotyping platforms is still limited and mainly focuses on differences in plant temperature between genotypes or treatments, instead of estimating stomatal conductance or transpiration rate. In this study, the transferability of commonly used thermography analysis protocols from the field to greenhouse phenotyping platforms was evaluated. In addition, the added value of combining thermal infrared (TIR) with hyperspectral imaging to monitor drought effects on plant transpiration rate (E) was evaluated. ResultsThe sensitivity of commonly used TIR indices to detect drought-induced and genotypic differences in water status was investigated in eight maize inbred lines in the automated phenotyping platform PHENOVISION. Indices that normalized plant temperature for vapor pressure deficit and/or air temperature at the time of imaging were most sensitive to drought and could detect genotypic difference in the plants water use behavior. However, these indices were not strongly correlated to stomatal conductance and E. The canopy temperature depression index, the crop water stress index and the simplified stomatal conductance index were more suitable to monitor these traits, and were consequently used to develop empirical E prediction models by combining them with hyperspectral indices and/or environmental variables. Different modeling strategies were evaluated including single index-based, machine learning and mechanistic models. Model comparison showed that combining multiple thermal infrared indices in a random forest model can improve E prediction accuracy, and that the contribution of the hyperspectral data is limited when multiple indices are used. However, the empirical models trained on one genotype were not transferable to all eight inbred lines. ConclusionOverall, this study demonstrates that existing TIR indices can be used to monitor drought stress and develop E prediction models in an indoor setup, as long as the indices normalize plant temperature for ambient air temperature or relative humidity.

plant biology↗

bioRxiv2022

Predicting yield traits of individual field-grown Brassica napus plants from rosette-stage leaf gene expression

BackgroundIn the plant sciences, results of laboratory studies often do not translate well to the field because lab growth conditions are very different from field conditions. To help close this lab-field gap, we developed a new strategy for studying the wiring of plant traits directly in the field, based on molecular profiling and phenotyping of individual plants of the same genetic background grown in the same field. This single-plant omics strategy leverages uncontrolled micro-environmental variation across the field and stochastic variation among the individual plants as information sources, rather than controlled perturbations. Here, we use single-plant omics on winter-type Brassica napus (rapeseed) plants to investigate to what extent rosette-stage gene expression profiles can be linked to the early and late phenotypes of individual field-grown plants. ResultsWe find that rosette leaf gene expression in autumn has substantial predictive power for both autumnal leaf phenotypes and final yield in spring. Many of the top predictor genes are linked to developmental processes known to occur in autumn in winter-type B. napus accessions, such as the juvenile-to-adult and vegetative-to-reproductive phase transitions, indicating that the yield potential of winter-type B. napus is influenced by autumnal development. ConclusionsOur results show that profiling individual plants under uncontrolled field conditions is a valid strategy for identifying genes and processes influencing crop yield in the field.

systems biology↗

bioRxiv2020

Using single-plant -omics in the field to link maize genes to functions and phenotypes

Most of our current knowledge on plant molecular biology is based on experiments in controlled lab environments. Over the years, lab experiments have generated substantial insights in the molecular wiring of plant developmental processes, stress responses and phenotypes. However, translating these insights from the lab to the field is often not straightforward, in part because field growth conditions are very different from lab conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field, and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional lab-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict at least some individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.

systems biology↗