Biology subjects

Berg, C.

Publications and source records attributed to Berg, C..

4 recordsLinked to original sources

bioRxiv2026

Same-section spatial metabolo-transcriptomics using Stereo-meta-seq reveals DHA-driven kidney maturation

A central unresolved question in developmental biology is whether local metabolites merely accompany, or actively instruct, tissue maturation. Addressing this question requires direct spatial coupling of metabolic states with genome-wide transcriptional programs in situ at high spatial resolution, which existing approaches do not readily achieve. Here, we introduce Stereo-meta-seq, a workflow that integrates quantitative MALDI-MSI with Stereo-seq spatial transcriptomics within a single tissue section. A conductive adapter was designed to overcome the electrical incompatibility of non-conductive Stereo-seq chips with vacuum MALDI platforms, improving efficiency of MSI detection that preserves RNA integrity. MALDI laser-ablation marks are retained in downstream Stereo-seq data and serve as intrinsic fiducials for direct co-registration at 10 m or 20 m resolution, enabling fine grained spatial metabolite-transcript integration. Applying Stereo-meta-seq to human kidney development, we uncover selective enrichment of docosahexaenoic acid (DHA) in maturing proximal tubules. Functional studies in human kidney organoids demonstrate that DHA activates PPAR-and HNF4-driven transcriptional programs and promotes proximal tubule maturation in vitro and after transplantation in vivo. These findings identify lipid metabolism as an instructive regulator of human nephrogenesis and establish Stereo-meta-seq as a practical platform for dissecting metabolite-gene coupling and tissue heterogeneity in situ.

Cell Biology↗

bioRxiv2025

RP3Net: a deep learning model for predicting recombinant protein production in Escherichia coli

Recombinant protein expression can be a limiting step in the production of protein reagents for drug discovery and other biotechnology applications. We introduce RP3Net (Recombinant Protein Production Prediction Network), an AI model of small-scale heterologous soluble protein expression in Escherichia coli. RP3Net utilizes the most recent protein and genomic foundational models. A curated dataset of internal experimental results from AstraZeneca (AZ) and publicly available data from the Structural Genomics Consortium (SGC) was used for training, validation and testing of RP3Net. Set Transformer Pooling (STP) aggregation and Meta Label Correction (MLC) with large scale purification data enabled RP3Net to improve Area Under Receiver Operator Curve (AUROC) by 0.15, compared to the baseline model. When experimentally validated on an independent, manually selected set of 97 constructs, RP3Net outperformed currently available models, with an AUROC of 0.83, delivering accurate predictions in 77% of the cases, and correctly identifying successfully expressing constructs in 92% of cases.

bioinformatics↗

bioRxiv2022

ReSurveyGermany: Vegetation-plot time-series over the past hundred years in Germany

Vegetation-plot resurvey data are a main source of information on terrestrial biodiversity change, with records reaching back more than one century. Although more and more data from re-sampled plots have been published, there is not yet a comprehensive open-access dataset available for analysis. Here, we compiled and harmonised vegetation-plot resurvey data from Germany covering almost 100 years. We show the distribution of the plot data in space, time and across habitat types of the European Nature Information System (EUNIS). In addition, we include metadata on geographic location, plot size and vegetation structure. The data allow calculating temporal biodiversity change at the community scale and reach back further into the past than most comparable data yet available. They also enable tracking changes in the incidence and distribution of individual species across Germany. In summary, the data come at a level of detail that holds promise for broadening our understanding of the mechanisms and drivers behind plant diversity change over the last century.

ecology↗

bioRxiv2018

Generation of functional human adipose tissue in mice from primed progenitor cells

AbstarctAdipose tissue is used extensively in reconstructive and regenerative therapies, but transplanted fat often undergoes inflammation and cell death, requiring further revision surgery. We report that functional human adipose tissue can be generated from mesenchymal progenitor cells in-vivo, providing an alternative approach to its therapeutic use. We leveraged previous findings that progenitor cells within the vasculature of human adipose tissue robustly proliferate in 3-dimensional culture under proangiogenic conditions. Implantation of these progenitor cells into immunocompromised mice results in differentiation towards non-adipocyte fates, incapable of generating a distinct tissue structure. However, priming of these progenitor cells in-vitro towards adipogenic differentiation results in formation of functional adipose tissue in-vivo. Mechanistically, priming induces the expression of genes encoding specific extracellular matrix and remodeling proteins, and induces extensive vascularization by host blood vessels. In comparison, grafts from adipose tissue obtained by liposuction undergo poor vascularization, adipocyte death, cyst formation, calcification and inefficient adiponectin secretion. Thus, primed mesenchymal adipose tissue progenitors reveal mechanisms of human adipose tissue development, and have potential to improve outcomes in reconstructive and regenerative medicine.

bioengineering↗