A semi-automated machine learning-aided approach to quantitative analysis of centrosomes and microtubule organization

Vimentin supports cell polarization by enhancing centrosome function and microtubule acetylation

Cell polarity is important for controlling cell shape, motility and cell division processes. Vimentin intermediate filaments are important for cell migration and cell polarization in mesenchymal cells and assembly of vimentin and microtubule networks is dynamically coordinated, but the precise details of how vimentin mediates cell polarity remain unclear. Here, we characterize the effects of vimentin on the structure and function of the centrosome and the stability of microtubule filaments in wild-type and vimentin-null mouse embryonic fibroblasts. We find that vimentin mediates the structure of the pericentriolar material, promotes centrosome-mediated microtubule regrowth and increases the level of stable acetylated microtubules in the cell. Loss of vimentin also impairs centrosome repositioning during cell polarization and migration processes that occur during wound closure. Our results suggest that vimentin modulates centrosome structure and function as well as microtubule network stability, which has important implications for how cells establish proper cell polarization and persistent migration.

Vimentin supports cell polarization by enhancing centrosome function and microtubule acetylation

Cell polarity is important for controlling cell shape, motility, and cell division processes. Vimentin intermediate filaments are necessary for proper polarization of migrating fibroblasts and assembly of vimentin and microtubule networks is dynamically coordinated, but the precise details of how vimentin mediates cell polarity remain unclear. Here, we characterize the effects of vimentin on the structure and function of the centrosome and the stability of microtubule filaments in wild-type and vimentin-null mouse embryonic fibroblasts (mEFs). We find that vimentin mediates the structure of the pericentrosomal material, promotes centrosome-mediated microtubule regrowth, and increases the level of stable acetylated microtubules in the cell. Loss of vimentin also impairs centrosome repositioning during cell polarization and migration processes that occur during wound closure. Our results suggest that vimentin modulates centrosome structure and function as well as microtubule network stability, which has important implications for how cells establish proper cell polarization and persistent migration.

CenFind: a deep-learning pipeline for efficient centriole detection in microscopy datasets

BACKGROUND

High-throughput and selective detection of organelles in immunofluorescence images is an important but demanding task in cell biology. The centriole organelle is critical for fundamental cellular processes, and its accurate detection is key for analysing centriole function in health and disease. Centriole detection in human tissue culture cells has been achieved typically by manual determination of organelle number per cell. However, manual cell scoring of centrioles has a low throughput and is not reproducible. Published semi-automated methods tally the centrosome surrounding centrioles and not centrioles themselves. Furthermore, such methods rely on hard-coded parameters or require a multichannel input for cross-correlation. Therefore, there is a need for developing an efficient and versatile pipeline for the automatic detection of centrioles in single channel immunofluorescence datasets.

RESULTS

We developed a deep-learning pipeline termed CenFind that automatically scores cells for centriole numbers in immunofluorescence images of human cells. CenFind relies on the multi-scale convolution neural network SpotNet, which allows the accurate detection of sparse and minute foci in high resolution images. We built a dataset using different experimental settings and used it to train the model and evaluate existing detection methods. The resulting average F₁-score achieved by CenFind is > 90% across the test set, demonstrating the robustness of the pipeline. Moreover, using the StarDist-based nucleus detector, we link the centrioles and procentrioles detected with CenFind to the cell containing them, overall enabling automatic scoring of centriole numbers per cell.

CONCLUSIONS

Efficient, accurate, channel-intrinsic and reproducible detection of centrioles is an important unmet need in the field. Existing methods are either not discriminative enough or focus on a fixed multi-channel input. To fill this methodological gap, we developed CenFind, a command line interface pipeline that automates cell scoring of centrioles, thereby enabling channel-intrinsic, accurate and reproducible detection across experimental modalities. Moreover, the modular nature of CenFind enables its integration in other pipelines. Overall, we anticipate CenFind to prove critical for accelerating discoveries in the field.

Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines?

Gene therapy enables the introduction of nucleic acids like DNA and RNA into host cells, and is expected to revolutionize the treatment of a wide range of diseases. This growth has been further accelerated by the discovery of CRISPR/Cas technology, which allows accurate genomic editing in a broad range of cells and organisms in vitro and in vivo. Despite many advances in gene delivery and the development of various viral and non-viral gene delivery vectors, the lack of highly efficient non-viral systems with low cellular toxicity remains a challenge. The application of cutting-edge technologies such as artificial intelligence (AI) has great potential to find new paradigms to solve this issue. Herein, we review AI and its major subfields including machine learning (ML), neural networks (NNs), expert systems, deep learning (DL), computer vision and robotics. We discuss the potential of AI-based models and algorithms in the design of targeted gene delivery vehicles capable of crossing extracellular and intracellular barriers by viral mimicry strategies. We finally discuss the role of AI in improving the function of CRISPR/Cas systems, developing novel nanobots, and mRNA vaccine carriers.

Trisomy 21 increases microtubules and disrupts centriolar satellite localization

Trisomy 21, the source of Down syndrome, causes a 0.5-fold protein increase of the chromosome 21-resident gene Pericentrin (PCNT) and reduces primary cilia formation and signaling. We investigate how PCNT imbalances disrupt cilia. Using isogenic RPE-1 cells with increased chromosome 21 dosage, we find PCNT accumulates around the centrosome as a cluster of enlarged cytoplasmic puncta that localize along microtubules (MTs) and at MT ends. Cytoplasmic PCNT puncta impact the density, stability, and localization of the MT trafficking network required for primary cilia. The PCNT puncta appear to sequester cargo peripheral to centrosomes in what we call pericentrosomal crowding. The centriolar satellite proteins PCM1, CEP131, and CEP290, important for ciliogenesis, accumulate at enlarged PCNT puncta in trisomy 21 cells. Reducing PCNT when chromosome 21 ploidy is elevated is sufficient to decrease PCNT puncta and pericentrosomal crowding, reestablish a normal density of MTs around the centrosome, and restore ciliogenesis to wild-type levels. A transient reduction in MTs also decreases pericentrosomal crowding and partially rescues ciliogenesis in trisomy 21 cells, indicating that increased PCNT leads to defects in the MT network deleterious to normal centriolar satellite distribution. We propose that chromosome 21 aneuploidy disrupts MT-dependent intracellular trafficking required for primary cilia.

The SON RNA splicing factor is required for intracellular trafficking structures that promote centriole assembly and ciliogenesis

Control of centrosome assembly is critical for cell division, intracellular trafficking, and cilia. Regulation of centrosome number occurs through the precise duplication of centrioles that reside in centrosomes. Here we explored transcriptional control of centriole assembly and find that the RNA splicing factor SON is specifically required for completing procentriole assembly. Whole genome mRNA sequencing identified genes whose splicing and expression are affected by the reduction of SON, with an enrichment in genes involved in the microtubule (MT) cytoskeleton, centrosome, and centriolar satellites. SON is required for the proper splicing and expression of CEP131, which encodes a major centriolar satellite protein and is required to organize the trafficking and MT network around the centrosomes. This study highlights the importance of the distinct MT trafficking network that is intimately associated with nascent centrioles and is responsible for procentriole development and efficient ciliogenesis.

A semi-automated machine learning-aided approach to quantitative analysis of centrosomes and microtubule organization

Microtubules (MTs) promote important cellular functions including migration, intracellular trafficking, and chromosome segregation. The centrosome, comprised of two centrioles surrounded by the pericentriolar material (PCM), is the cell's central MT-organizing center. Centrosomes in cancer cells are commonly numerically amplified. However, the question of how the amplification of centrosomes alters MT organization capacity is not well studied. We developed a quantitative image-processing and machine learning-aided approach for the semi-automated analysis of MT organization. We designed a convolutional neural network-based approach for detecting centrosomes, and an automated pipeline for analyzing MT organization around centrosomes, encapsulated in a semi-automatic graphical tool. Using this tool, we find that breast cancer cells with supernumerary centrosomes not only have more PCM protein per centrosome, which gradually increases with increasing centriole numbers, but also exhibit expansion in PCM size. Furthermore, cells with amplified centrosomes have more growing MT ends, higher MT density and altered spatial distribution of MTs around amplified centrosomes. Thus, the semi-automated approach developed here enables rapid and quantitative analyses revealing important facets of centrosomal aberrations.