Biology subjects

Seeber, A.

Publications and source records attributed to Seeber, A..

4 recordsLinked to original sources

bioRxiv2024

Dissecting heterogeneity of tumor microenvironment in colorectal cancer using high-resolution single-cell atlas

The immune composition of the tumor microenvironment (TME) has a major impact on the therapeutic response and clinical outcome in patients with colorectal cancer (CRC). Here, we comprehensively characterize the TME at the single-cell level by first building a large-scale atlas that integrates 4.27 million single cells from 1,670 patient samples. We then complemented the atlas with single-cell profiles from four CRC cohorts with 266 patients, including cells with low mRNA content, spatial transcriptional profiles from 3.7 million cells, and protein profiles from 0.7 million cells. The analysis of the atlas allows refined tumor classification into four immune phenotypes: immune desert, B cell enriched, T cell enriched, and myeloid cell enriched subtypes. Within the myeloid compartment we uncover distinct subpopulations of neutrophils that acquire new functional properties in blood and in the TME, including anti-tumorigenic capabilities. Further, spatial multimodal single-cell profiling reveals that neutrophils are organized in clusters within distinct functional niches. Finally, using an orthotopic mouse model we show that cancer-derived systemic signals modify neutrophil production in the bone marrow, providing evidence for tumor-induced granulopoiesis. Our study provides a big data resource for the CRC and suggests novel therapeutic strategies targeting neutrophils.

bioinformatics↗

bioRxiv2021

Physics Augmented U-Net: A High-Frequency Aware Generative Prior for Microscopy

A key challenge in optical microscopy is to image fast at high-resolution. To address this problem, we propose "Physics Augmented U-Net", which combines deep learning and structured illumination microscopy (SIM). In SIM, the structured illumination aliases out-of-band high-frequencies to the passband of the microscope; thus SIM captures some high-frequencies even when the image is sampled at low-resolution. To utilize these features, we propose a three-element method: 1) a modified U-Net model, 2) a physics-based forward model of SIM 3) an inference algorithm combining the two models. The modified U-Net architecture is similar to the seminal work, but the bottleneck is modified by concatenating two latent vectors, one encoding low-frequencies (LFLV), and the other encoding high-frequencies (HFLV). LFLV is learned by U-Net contracting path, and HFLV is learned by a second encoding path. In the inference mode, the high-frequency encoder is removed; HFLV is then optimized to fit the measured microscopy images to the output of the forward model for the generated image by the U-Net. We validated our method on two different datasets under different experimental conditions. Since a latent vector is optimized instead of a 2D image, the inference mode is less computationally complex. The proposed model is also more stable compared to other generative prior-based methods. Finally, as the forward model is independent of the U-Net, Physics Augmented U-Net can enhance resolution on any variation of SIM without further retraining.

bioinformatics↗

bioRxiv2019

Single particle trajectory statistic to reconstruct chromatin organization and dynamics

Chromatin organization remains complex and far from understood. We discuss here recent statistical methods to extract biophysical parameters from in vivo single particle trajectories of loci to reconstruct chromatin reorganization in response to cellular stress such as DNA damages. We look at the methods to analyze both single loci as well as multiple loci tracked simultaneously and explain how to quantify and describe chromatin motion using a combination of extractable parameters. These parameters can be converted into information about chromatin dynamics and function. Furthermore, we discuss how the time scale of recurrent motion of a locus can be extracted and converted into local chromatin dynamics. We also discuss the effect of various sampling rates on the estimated parameters. Finally, we discuss polymer methods based on cross-linkers that account for minimal loop constraints hidden in tracked loci, that reveal chromatin organization at the 250nm spatial scale. We list and refer to some algorithm packages that are now publicly available. To conclude, chromatin organization and dynamics at hundreds of nanometers can be reconstructed from locus trajectories and predicted based on polymer models.

genomics↗

bioRxiv2018

Local decondensation at double-stranded DNA breaks modifies chromatin at long distances and reduces encounter times during homology search

Double-strand break (DSB) repair by homologous recombination (HR) requires an efficient and timely search for a homologous template. Here we first study global chromatin re-organization following a single DSB: due to the potential release of cross-linkers such as cohesin and CTCF molecules near the DSB site, loops are released and chromatin is decondensed, explaining the change of chromatin locus motion at larger genomic distances. This mechanism provides an elementary explanation for the increase of the anomalous exponent at sites located far away from the DSB, after break induction. Second, we explore the consequences of chromatin reorganization for the homology search during DNA repair: using polymer models, we estimate the mean first encounter time (MFET) between two loci on the chromatin in a confined nucleus. Reducing tethering forces, as reported experimentally on chromatin, is associated with a local de-condensation near the break followed by the extrusion of the breaks. Consequently, we report here that the mean first encounter time between homologous sites is decreased by two orders of magnitude even when the homologue sequence is located on the nuclear boundary. To conclude, our results suggest that local changes in inter-nucleosomal contacts near DSBs, by cohesin removal, remodel the chromatin and drastically shorten the time required to complete a long-range search for a homologous template.

genetics↗