Complete genome of Flavobacterium pectinovorum str. ZE23VCel01 obtained through Nanopore Q20+ chemistry

This study reports the complete genome of Flavobacterium pectinovorum str. ZE23VCel01 isolated from a freshwater environment. By means of Nanopore Q20+ chemistry, the chromosome was assembled as a circular element with a length of 5.9 Mbp, a GC content of 33.58%, and a coverage of 122×

Pseudomonas kielensis str. Ze23jcel16 complete genome obtained through R10.4.1 Nanopore Flow cell chemistry

Here, we report the complete genome of Pseudomonas kielensis str. Ze23jcel16 isolated from a freshwater sample. The high-quality chromosome was obtained employing R10.4.1 Nanopore Flow cell chemistry and was assembled as a circular element at 45× coverage, a length of 5.8 Mbp, and a G+C content of 61.15%

Q20+ Nanopore sequencing data recover a high-quality Asticcacaulis sp. genome

We present here the complete genome of Asticcacaulis sp. ZE23SCel15. The strain was isolated from the surface water of Lake Zurich, Switzerland. The assembly of high-quality Q20+ Nanopore data yielded a circular genome with ~3.8 Mb (coverage: 34×) and a GC content of 56.81%

A high-quality genome of an undescribed Flavobacterium species uncovered using Q20+ Nanopore chemistry

Herein, we document the complete genome of the Flavobacterium strain ZE23DGlu08, isolated from Lake Zurich, Switzerland. The circular genome was assembled using long-read Nanopore data (coverage: 226×) with the Q20+ chemistry. The described strain displays a genome size of ~3.9 Mbp with a GC content of 34%

Intravital Dynamic and Correlative Imaging of Mouse Livers Reveals Diffusion-Dominated Canalicular and Flow-Augmented Ductular Bile Flux

Background and Aims Small‐molecule flux in tissue microdomains is essential for organ function, but knowledge of this process is scant due to the lack of suitable methods. We developed two independent techniques that allow the quantification of advection (flow) and diffusion in individual bile canaliculi and in interlobular bile ducts of intact livers in living mice, namely fluorescence loss after photoactivation and intravital arbitrary region image correlation spectroscopy. Approach and Results The results challenge the prevailing “mechano‐osmotic” theory of canalicular bile flow. After active transport across hepatocyte membranes, bile acids are transported in the canaliculi primarily by diffusion. Only in the interlobular ducts is diffusion augmented by regulatable advection. Photoactivation of fluorescein bis‐(5‐carboxymethoxy‐2‐nitrobenzyl)‐ether in entire lobules demonstrated the establishment of diffusive gradients in the bile canalicular network and the sink function of interlobular ducts. In contrast to the bile canalicular network, vectorial transport was detected and quantified in the mesh of interlobular bile ducts. Conclusions The liver consists of a diffusion‐dominated canalicular domain, where hepatocytes secrete small molecules and generate a concentration gradient and a flow‐augmented ductular domain, where regulated water influx creates unidirectional advection that augments the diffusive flux

A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging

Inference of action potentials (‘spikes’) from neuronal calcium signals is complicated by the scarcity of simultaneous measurements of action potentials and calcium signals (‘ground truth’). In this study, we compiled a large, diverse ground truth database from publicly available and newly performed recordings in zebrafish and mice covering a broad range of calcium indicators, cell types and signal-to-noise ratios, comprising a total of more than 35 recording hours from 298 neurons. We developed an algorithm for spike inference (termed CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level; therefore, no parameters need to be adjusted by the user. In addition, we developed systematic performance assessments for unseen data, openly released a resource toolbox and provide a user-friendly cloud-based implementation