Biology subjects

Gerber, T.

Publications and source records attributed to Gerber, T..

8 recordsLinked to original sources

bioRxiv2026

Multi-modal single-cell profiling reveals transcriptional states and commitment dynamics during sexual reproduction in the diatom Pseudo-nitzschia multistriata

Diatoms, single-celled photosynthetic eukaryotes, traditionally considered primarily influenced by resource availability, are now recognized to exhibit complex developmental processes reminiscent of those in multicellular organisms. Sexual reproduction is an obligate choice in many species, albeit with variable frequency and efficiency. In order to explore decision making mechanisms and cellular heterogeneity inherent to this specific phase of the diatom life cycle, we applied a multi-modal strategy to follow sexual reproduction events in the model diatom Pseudo-nitzschia multistriata: i) we employed image-enabled cell sorting to link sexual stages morphology with gene expression ii) we developed a single-nucleus RNA sequencing assay, and iii) conducted proteomic profiling. Combining phenotypes with single-cell profiling allowed us to identify sexual state-specific transcription programs and different states within morphologically identical parental cells, revealing a widespread commitment of the majority of the population to sexual reproduction. This implies that the bottleneck to successful sexual reproduction in this species can be placed downstream of the signalling phase between mating cells, with additional, yet unidentified, factors influencing mating success at sea.

microbiology↗

bioRxiv2025

Functional rescue of critical-size bone defect using molecular network analysis of axolotl limb regeneration.

The salamander limb has served as a canonical model for successful regeneration that has yielded numerous molecular insights on its basic mechanism. Harnessing such information to induce regeneration in a non-regenerative setting has been a long-sought goal. The amputated salamander limb efficiently regenerates all of its missing bones, but paradoxically, a large bone gap without amputation - commonly called a Critical Size Defect (CSD) - is not regenerated, similarly to other vertebrates1. This non-regenerating injury provides a human-relevant setting to understand how to rescue lack-of-regeneration. Satoh and colleagues demonstrated in axolotl that transplantation of blastema cells from an amputated limb into a CSD yields cartilage bridging of the CSD2. This work provided a roadmap for rescuing the CSD. Here we asked, what are the crucial molecular differences in cells populating a regenerating blastema versus the CSD and can they be used to elicit CSD bridging? Previous genetic fate mapping and single cell transcriptomics showed that limb regeneration occurs via migration and dedifferentiation of fibroblastic, soft connective tissue (CT) cells that form a multipotent, skeletal stem cell 3, 4. Here using single cell transcriptomics and genetic fate mapping we found that the CSD is populated by CT cells that undergo a divergent molecular transition compared to the blastema. Using gene regulatory network (GRN) modeling, and lipid nanoparticle (LNP) delivery of mRNA we could express a single molecular factor, Wnt3a, to induce cartilage bridging of the CSD. Our results demonstrate the power of using molecular information from successful regeneration to rescue a non-regenerating injury.

cell biology↗

bioRxiv2025

A whole-body cell type atlas mapped into an electron microscopy volume of an annelid worm

Differential gene expression establishes the distinct physiology and morphology of cell types in an animal body. Single-cell sequencing and volume EM represent milestones toward the characterization of cell types, yet are difficult to combine for a comprehensive view on the cellular genotype-phenotype link. Here, we map a whole-body single-cell transcriptome into the PlatyBrowser, a multimodal cellular atlas for the marine annelid Platynereis dumerilii, and establish this combination uniquely for an entire animal. We learn that, in the 6-days-old worm, the majority of genes are tightly co-regulated to jointly implement one of eight major cellular morphotypes representing epidermis, gut, vasculature, myofibres, glia, motile cilia, glands, or neurons. Focusing on neurons, we uncover 14 families that by transcription factor identity, axonal projection, or sensory-secretory apparatus resemble conserved neuron types found in vertebrates, insects, or nematodes. We hypothesize that these existed in urbilaterian ancestors and represent the ancient core of nervous system centralization.

evolutionary biology↗

bioRxiv2024

Systemic coordination of whole-body tissue remodeling in sea anemone local regeneration

The complexity of regeneration extends beyond local wound responses (1,2), eliciting systemic processes that engage the entire organism. However, their functional relevance, and the spatial and temporal orchestration of the underlying molecular processes distant from the injury site remain unknown. Here, we demonstrate that local regeneration in the cnidarian Nematostella vectensis involves a systemic homeostatic response, leading to coordinated whole-body remodeling. Leveraging spatial transcriptomics, endogenous protein tagging, and live imaging, we comprehensively dissect this systemic response at the organismal scale. We identify proteolysis as a critical process driven by both local and systemic upregulation of metalloproteases. We show that metalloproteinase expression levels and activity scale with the extent of tissue loss, leading to proportional long-range movement of tissue and its associated extracellular matrix. Our findings illuminate the adaptive nature of the systematic response in regeneration. We propose that this integrated regenerative mechanism, shifting the system from a steady to a dynamic homeostatic state, allows the organism to cope with a wide range of injuries.

developmental biology↗

bioRxiv2024

Somite-independent regeneration of the axolotl primary body axis

Primary body-axis development is a highly conserved process that proceeds through somitogenesis and subsequent subdivision into dermatome, myotome, and sclerotome. Defects in somitic-clock genes such as Hes7 lead to vertebral-segmentation defects in mice and fish. Here we show that in the axolotl, although Hes7 is necessary for proper embryonic vertebral segmentation, it is-- surprisingly--dispensable during tail regeneration. We investigated the mechanism of vertebral segmentation during regeneration which initially occurs through extension of a cartilage rod ventral to the spinal cord. We find that the regenerating cartilage rod undergoes a periodic wrinkling that provides a template for vertebral segmentation. Via direct mechanical measurements and biophysical perturbations, we show that a model of compression-induced buckling instability can predict vertebral segmentation. The cartilage rod and other somitic derivatives (muscle, cartilage, tendon, fibroblasts) arise from tendon-like, Lfng+ multi-potent mesenchymal progenitors, which display a gene regulatory state distinct from somitic progenitors. In summary, we uncover a mechanism of vertebral segmentation during axolotl tail regeneration that is distinct from the somite-based developmental mechanism.

developmental biology↗

bioRxiv2021

Nuclei are mobile processors enabling specialization in a gigantic single-celled syncytium

In multicellular organisms, the specification, coordination, and compartmentalization of cell types enable the formation of complex body plans. However, some eukaryotic protists such as slime molds generate diverse and complex structures while remaining in a multinucleated syncytial state. It is unknown if different regions of these giant syncytial cells have distinct transcriptional responses to environmental encounters, and if nuclei within the cell diversify into heterogeneous states. Here we performed spatial transcriptome analysis of the slime mold Physarum polycephalum in the plasmodium state under different environmental conditions, and used single-nucleus RNA-sequencing to dissect gene expression heterogeneity among nuclei. Our data identifies transcriptome regionality in the organism that associates with proliferation, syncytial substructures, and localized environmental conditions. Further, we find that nuclei are heterogenous in their transcriptional profile, and may process local signals within the plasmodium to coordinate cell growth, metabolism, and reproduction. To understand how nuclei variation within the syncytium compares to heterogeneity in single-nucleated cells, we analyzed states in single Physarum amoebal cells. We observed amoebal cell states at different stages of mitosis and meiosis, and identified cytokinetic features that are specific to nuclei divisions within the syncytium. Notably, we do not find evidence for predefined transcriptomic states in the amoebae that are observed in the syncytium. Our data shows that a single-celled slime mold can control its gene expression in a region-specific manner while lacking cellular compartmentalization, and suggests that nuclei are mobile processors facilitating local specialized functions. More broadly, slime molds offer the extraordinary opportunity to explore how organisms can evolve regulatory mechanisms to divide labor, specialize, balance competition with cooperation, and perform other foundational principles that govern the logic of life.

cell biology↗

bioRxiv2020

Lineage recording reveals dynamics of cerebral organoid regionalization

Diverse regions develop within cerebral organoids generated from human induced pluripotent stem cells (iPSCs), however it has been a challenge to understand the lineage dynamics associated with brain regionalization. Here we establish an inducible lineage recording system that couples reporter barcodes, inducible CRISPR/Cas9 scarring, and single-cell transcriptomics to analyze lineage relationships during cerebral organoid development. We infer fate-mapped whole organoid phylogenies over a scarring time course, and reconstruct progenitor-neuron lineage trees within microdissected cerebral organoid regions. We observe increased fate restriction over time, and find that iPSC clones used to initiate organoids tend to accumulate in distinct brain regions. We use lineage-coupled spatial transcriptomics to resolve lineage locations as well as confirm clonal enrichment in distinctly patterned brain regions. Using long term 4-D light sheet microscopy to temporally track nuclei in developing cerebral organoids, we link brain region clone enrichment to positions in the neuroectoderm, followed by local proliferation with limited migration during neuroepithelial formation. Our data sheds light on how lineages are established during brain organoid regionalization, and our techniques can be adapted in any iPSC-derived cell culture system to dissect lineage alterations during perturbation or in patient-specific models of disease.Competing Interest StatementThe authors have declared no competing interest.View Full Text

developmental biology↗

bioRxiv2018

Deep SNP: An End-to-end Deep Neural Network with Attention-based Localization for Break-point Detection in SNP Array Genomic data

Diagnosis and risk stratification of cancer and many other diseases require the detection of genomic breakpoints as a prerequisite of calling copy number alterations (CNA). This, however, is still challenging and requires time-consuming manual curation. As deep-learning methods outperformed classical state-of-the-art algorithms in various domains and have also been successfully applied to life science problems including medicine and biology, we here propose Deep SNP, a novel Deep Neural Network to learn from genomic data. Specifically, we used a manually curated dataset from 12 genomic single nucleotide polymorphism array (SNPa) profiles as truth-set and aimed at predicting the presence or absence of genomic breakpoints, an indicator of structural chromosomal variations, in windows of 40,000 probes. We compare our results with well-known neural network models as well as Rawcopy though this tool is designed to predict breakpoints and in addition genomic segments with high sensitivity. We show, that Deep SNP is capable of successfully predicting the presence or absence of a breakpoint in large genomic windows and outperforms state-of-the-art neural network models. Qualitative examples suggest that integration of a localization unit may enable breakpoint detection and prediction of genomic segments, even if the breakpoint coordinates were not provided for network training. These results warrant further evaluation of DeepSNP for breakpoint localization and subsequent calling of genomic segments.

genomics↗