Biology subjects

Siegle, J.

Publications and source records attributed to Siegle, J..

7 recordsLinked to original sources

bioRxiv2026

Hypothermic and Normothermic Machine Perfusion Differentially Shape the Renal Cellular Landscape

The shortage of donor organs has led to an increased use of extended-criteria donors and donation after circulatory death for kidney transplantation, both of which are associated with graft injury. Although machine perfusion (MP) offers a preservation strategy, the most beneficial approach for kidneys with respect to effective graft preservation remains unclear. We compared oxygenated hypothermic (HMP) and normothermic machine perfusion (NMP) using a murine kidney perfusion model regarding intra-graft immune cell composition, viability, and inflammatory responses. NMP resulted in more severe tubular injury, accompanied by increased immune cell mobilization out of the graft. NMP increased early apoptosis among kidney-resident immune-cell populations, whereas endothelial cells showed increased late apoptosis after both strategies. Proximal tubular-cell apoptosis remained comparable to naive tissue, and neither modality reduced reactive oxygen species levels. Both protocols induced antioxidant and hypoxia-responsive genes compared with static cold storage, while NMP elicited a stronger inflammatory response. Treatment with the senolytic ABT-263 demonstrated the models feasibility for investigating renal injury, cellular viability, and immune activation during MP.

immunology↗

bioRxiv2026

3D-MAESTRO: A scalable, modular, portable pipeline for automated processing of large-scale volumetric brain microscopy data

Light microscopy is routinely used to explore the cellular and molecular structure of tissues, but the scale and complexity of data remains a bottleneck for discovery. We introduce 3D-MAESTRO (3D-Microscopy Automation and Execution with Scalable Tools, Rendering, and Orchestration): an automated image processing workflow for large-scale microscopy data, built for scalable execution across cloud and local computing environments. 3D-MAESTRO orchestrates denoising, stitching of image tiles, atlas registration, and segmentation. Its modular architecture permits the integration and benchmarking of new packages, ensuring that performance evolves as more efficient or accurate algorithms emerge. We introduce a new 3D image template for automated registration of mouse brains cleared with aqueous reagents and an efficient method for detection of fluorescent cells. We apply 3D-MAESTRO to lightsheet images of whole mouse brains in the context of diverse anatomical and functional experiments, illustrating high-throughput and reproducible mapping of microscopic structures across the brain.

neuroscience↗

bioRxiv2026

Topographic structure and function of locus coeruleus norepinephrine neurons

Norepinephrine (NE) is released throughout most of the central nervous system by neurons in the locus coeruleus (LC). We found a relationship between the morphologies, gene expression, and activity of LC-NE neurons in mice. Axonal projections of individual neurons were extensive but largely confined to subsets of brain regions. Axonal projections and graded gene expression correlated with locations of cell bodies in LC. In a behavioral task requiring ongoing learning from actions, neurons in dorsal LC projecting to the cerebral cortex were excited when mice made a different choice from the previous one and by reward prediction errors, a signal driving learning. Background activity of neurons in ventral LC was higher when mice ignored stimuli indicating potential reward availability. These observations reveal a topographically organized structure and function of a neurotransmitter system and show that it contains learning signals for flexible behavior.

neuroscience↗

bioRxiv2023

Associations between in vitro, in vivo and in silico cell classes in mouse primary visual cortex

The brain consists of many cell classes yet in vivo electrophysiology recordings are typically unable to identify and monitor their activity in the behaving animal. Here, we employed a systematic approach to link cellular, multi-modal in vitro properties from experiments with in vivo recorded units via computational modeling and optotagging experiments. We found two one-channel and six multi-channel clusters in mouse visual cortex with distinct in vivo properties in terms of activity, cortical depth, and behavior. We used biophysical models to map the two one- and the six multi-channel clusters to specific in vitro classes with unique morphology, excitability and conductance properties that explain their distinct extracellular signatures and functional characteristics. These concepts were tested in ground-truth optotagging experiments with two inhibitory classes unveiling distinct in vivo properties. This multi-modal approach presents a powerful way to separate in vivo clusters and infer their cellular properties from first principles.

neuroscience↗

bioRxiv2021

SOX2-phosphorylation toggles a bistable differentiation-switch in squamous cell carcinoma

The fate choice between stem cell self-renewal and differentiation is regulated by bistable transcriptional networks, which are balanced in homeostasis and imbalanced in tumors. Yet, how stem cells switch from self-renewal to differentiation remains a conundrum. Here, we discover a molecular mechanism that allows stem cell-like tumor propagating cells (TPCs) in squamous cell carcinomas (SCCs) to switch from a mutually exclusive SOX2-PITX1-TP63 self-renewal circuit to a KLF4 driven differentiation program, dependent on the relative occupancy of a novel Klf4-regulatory enhancer cluster (Klf4EC944) by SOX2 or KLF4, respectively. We find SOX2 occupies this site in TPCs to inhibit Klf4 transcription, but upon phosphorylation SOX2 becomes evicted from Klf4EC944, allowing residual KLF4 to occupy this site instead, boost the expression of KLF4 and its downstream targets, and differentiate self-renewing TPCs into post-mitotic SCC cells. This mechanism allows SOX2 to promote self-renewal and tumor formation, while preserving the differentiation potential in SCC cells. Our data suggest that stochastic cell fate decisions depend on the effective concentration of enzymatically regulated transcription factors. The surprising specificity by which SOX2-phosphorylation governs the bistable Klf4EC944 network-switch in SCCs reveals a conceptual framework for the identification of similar switches in other stem cell and cancer types and their potential development into cell type specific differentiation therapies for diseases in which tissue homeostasis has gone awry.

cancer biology↗

bioRxiv2019

Does the neuronal noise in cortex help generalization?

One remarkable feature of neuronal activity in the mammalian cortex is the high level of variability in response to repeated stimuli. First, we used an open dataset, the Allen Brain Observatory, to quantify the distribution of responses to repeated presentations of natural movies. We find that even for their preferred moment in the movie clip, neurons have high variability which cannot be well captured by Gaussian or Poisson distributions. A large fraction of responses are better fit by log-normal or Gaussian mixture models with two components. These distributions are similar to activity distributions during training of deep neural networks using dropout. This poses the interesting hypothesis: is the role of cortical noise to help in generalization during learning?\n\nSecond, to ensure the robustness of our results we analyzed electrophysiological recordings in the same areas of mouse visual cortex, again using repeated natural movie presentations and found similar response distributions. To make sure that the trial-by-trial variations we observe are not due exclusively to the result of changes in state, we constructed a population coupling model, where each neurons activity is coupled to a low-dimension version of the activity of all other simultaneously recorded neurons. The population coupling model can capture global, brain-wide activity fluctuations that are state-dependent. The residuals from this model also show non-Gaussian noise distributions.\n\nThird, we ask a more specific question: is the noise in the cortex more likely to move the representation of the stimulus in-class versus out-of-class? To address this question, we analyzed the responses of neurons across trials from multiple sections of different movie clips. We observe that the noise in the cortex better aligns to in-class variations. We argue that a useful noise for learning generalizations is to move from representations of different exemplars in-class, similar to cortical noise.

neuroscience↗

bioRxiv2018

High-density extracellular probes reveal dendritic backpropagation and facilitate neuron classification

Different neuron types serve distinct roles in neural processing. Extracellular electrical recordings are extensively used to study brain function but are typically blind to cell identity. Morpho-electric properties of neurons measured on spatially dense electrode arrays might be useful for distinguishing neuron types. Here we used Neuropixels probes to record from cortical and subcortical regions of the mouse brain. Extracellular waveforms of each neuron were detected across many channels and showed distinct spatiotemporal profiles among brain regions. Classification of neurons by brain region was improved with multi-channel compared to single-channel waveforms. In visual cortex, waveform clustering identified the canonical regular spiking (RS) and fast spiking (FS) classes, but also uncovered a subclass of RS units with unidirectional backpropagating action potentials (BAPs). Moreover, BAPs were observed in many hippocampal RS cells. Overall, waveform analysis of spikes from high-density probes aids neuron identification and can reveal dendritic backpropagation.

neuroscience↗