Biology subjects

Baskoylu, S.

Publications and source records attributed to Baskoylu, S..

4 recordsLinked to original sources

bioRxiv2024

Deep Neural Networks to Register and Annotate the Cells of the C. elegans Nervous System

Aligning and annotating the heterogeneous cell types that make up complex cellular tissues remains a major challenge in the analysis of biomedical imaging data. Here, we present a series of deep neural networks that allow for automatic non-rigid registration and cell identification, developed in the context of freely moving and deforming invertebrate nervous systems. A semi-supervised learning approach was used to train a C. elegans registration network (BrainAlignNet) that aligns pairs of images of the bending C. elegans head with single pixel-level accuracy. When incorporated into an image analysis pipeline, this network can link neurons over time with 99.6% accuracy. This network could also be readily purposed to align neurons from the jellyfish Clytia hemisphaerica, an organism with a vastly different body plan and set of movements. A separate network (AutoCellLabeler) was trained to annotate >100 neuronal cell types in the C. elegans head based on multi-spectral fluorescence of genetic markers. This network labels >100 different cell types per animal with 98% accuracy, exceeding individual human labeler performance by aggregating knowledge across manually labeled datasets. Finally, we trained a third network (CellDiscoveryNet) to perform unsupervised discovery of >100 cell types in the C. elegans nervous system: by comparing multi-spectral imaging data from many animals, it can automatically identify and annotate cell types without using any human labels. The performance of CellDiscoveryNet matched that of trained human labelers. These tools should be immediately useful for a wide range of biological applications and should be straightforward to generalize to many other contexts requiring alignment and annotation of dense heterogeneous cell types in complex tissues.

neuroscience↗

bioRxiv2023

Programmed Cell Death Modifies Neural Circuits and Tunes Intrinsic Behavior

Programmed cell death (PCD) is a common feature of animal development. During development of the C. elegans hermaphrodite, programmed cell death eliminates 131 cells in stereotyped positions in the cell lineage, mostly in neuronal lineages. Blocking cell death results in supernumerary "undead" neurons. We find that undead neurons can be wired into circuits, can display activity, and can modify specific behaviors. The two undead RIM-like neurons participate in the RIM-containing circuit that computes movement. The presence of these two extra neurons results in animals that initiate fewer reversals and lengthens the duration of those reversals that do occur. We describe additional behavioral alterations of cell-death mutants, including in locomotory turning angle and pharyngeal pumping. These findings indicate that physiological or evolutionary variations in PCD might reveal latent neuronal elements that the nervous system can incorporate to modify nervous system function and animal behavior.

neuroscience↗

bioRxiv2022

Brain-wide representations of behavior spanning multiple timescales and states in C. elegans

Changes in an animals behavior and internal state are accompanied by widespread changes in activity across its brain. However, how neurons across the brain encode behavior and how this is impacted by state is poorly understood. We recorded brain-wide activity and the diverse motor programs of freely-moving C. elegans and built probabilistic models that explain how each neuron encodes quantitative features of the animals behavior. By determining the identities of the recorded neurons, we created, for the first time, an atlas of how the defined neuron classes in the C. elegans connectome encode behavior. Many neuron classes have conjunctive representations of multiple behaviors. Moreover, while many neurons encode current motor actions, others encode recent actions. Changes in behavioral state are accompanied by widespread changes in how neurons encode behavior, and we identify these flexible nodes in the connectome. Our results provide a global map of how the cell types across an animals brain encode its behavior.

neuroscience↗

bioRxiv2019

Disrupted Autophagy and Neuronal Dysfunction in C. elegans Knockin Models of FUS Amyotrophic Lateral Sclerosis

It remains unclear how mutations in FUS, a ribonucleoprotein, lead to neuronal dysfunction in Amyotrophic Lateral Sclerosis (ALS) patients. To examine mechanisms underlying ALS FUS dysfunction, we generated the first C. elegans knock-in models using CRISPR/Cas9-mediated genome editing, creating R524S and P525L ALS FUS models. Although FUS inclusions were not detected, ALS FUS animals showed defective neuromuscular function, as well as stress-induced locomotion defects. Unlike C. elegans lacking the endogenous FUS ortholog, ALS FUS animals had impaired neuronal autophagy and increased SQST-1 accumulation in ALS FUS motor neurons. Loss of sqst-1, the C. elegans ortholog for ALS-linked, autophagy adaptor protein SQSTM1/p62, suppressed both neuromuscular and stress-induced locomotion defects in ALS FUS animals, but did not suppress neuronal autophagy defects. Therefore, autophagy dysfunction is upstream of, and not dependent on, SQSTM1 function in ALS FUS pathogenesis. Combined, our findings demonstrate that autophagy dysfunction likely contributes to protein homeostasis and neuromuscular defects in ALS FUS knock-in animals.

neuroscience↗