Orientation-invariant autoencoders learn robust representations for shape profiling of cells and organelles

Abstract Cell and organelle shape are driven by diverse genetic and environmental factors and thus accurate quantification of cellular morphology is essential to experimental cell biology. Autoencoders are a popular tool for unsupervised biological image analysis because they learn a low-dimensional representation that maps images to feature vectors to generate a semantically meaningful embedding space of morphological variation. The learned feature vectors can also be used for clustering, dimensionality reduction, outlier detection, and supervised learning problems. Shape properties do not change with orientation, and thus we argue that representation learning methods should encode this orientation invariance. We show that conventional autoencoders are sensitive to orientation, which can lead to suboptimal performance on downstream tasks. To address this, we develop O2-variational autoencoder (O2-VAE), an unsupervised method that learns robust, orientation-invariant representations. We use O2-VAE to discover morphology subgroups in segmented cells and mitochondria, detect outlier cells, and rapidly characterise cellular shape and texture in large datasets, including in a newly generated synthetic benchmark

Different Stability and Proteasome-Mediated Degradation Rate of SMN Protein Isoforms.

The key pathogenic steps leading to spinal muscular atrophy (SMA), a genetic disease characterized by selective motor neuron degeneration, are not fully clarified. The full-length SMN protein (FL-SMN), the main protein product of the disease gene SMN1, plays an established role in the cytoplasm in snRNP biogenesis ultimately leading to mRNA splicing within the nucleus. It is also involved in the mRNA axonal transport. However, to what extent the impairment of these two SMN functions contributes to SMA pathogenesis remains unknown. A shorter SMN isoform, axonal-SMN or a-SMN, with more specific axonal localization, has been discovered, but whether it might act in concert with FL-SMN in SMA pathogenesis is not known. As a first step in defining common or divergent intracellular roles of FL-SMN vs a-SMN proteins, we here characterized the turn-over of both proteins and investigated which pathway contributed to a-SMN degradation. We performed real time western blot and confocal immunofluorescence analysis in easily controllable in vitro settings. We analyzed co-transfected NSC34 and HeLa cells and cell clones stably expressing both a-SMN and FL-SMN proteins after specific blocking of transcript or protein synthesis and inhibition of known intracellular degradation pathways. Our data indicated that whereas the stability of both FL-SMN and a-SMN transcripts was comparable, the a-SMN protein was characterized by a much shorter half-life than FL-SMN. In addition, as already demonstrated for FL-SMN, the Ub/proteasome pathway played a major role in the a-SMN protein degradation. We hypothesize that the faster degradation rate of a-SMN vs FL-SMN is related to the protection provided by the protein complex in which FL-SMN is assembled. The diverse a-SMN vs FL-SMN C-terminus may dictate different protein interactions and complex formation explaining the different localization and role in the neuronal compartment, and the lower expression and stability of a-SMN

Different effects of proteasome and calpain inhibitors on FL-SMN and a-SMN protein levels in NSC34 motor neurons.

<p><b>(A)</b> Western blot analysis and quantification of FL-SMN and a-SMN protein expression after proteasome or calpain inhibition. NSC34 cells were first co-transfected with N-terminally tagged human FL-SMN and a-SMN and then treated with the proteasome inhibitors MG132 or lactacystin, or the calpain inhibitor calpeptin. The “+” and “-”indications represent the presence or absence, respectively, of MG132, lactacystin or calpeptin. The MG132 treatment significantly increased both a-SMN (8 and 16 hrs vs 0 hrs, #p<0.001) and FL-SMN protein levels (8 hrs vs 0 hrs, #p<0.001; 16 hrs vs 0 hrs *p<0.05). Note however that the MG132 effect was progressive over time for a-SMN only. Non-significant differences (n.s.) were detected after either lactacystin or calpain treatment for both proteins vs untreated cells (0 hrs groups). Distinct statistical tests were performed for the two protein datasets, i.e., one for a-SMN and one for FL-SMN. Statistical analysis was performed by one-way ANOVA followed by Tukey HSD as post hoc comparison test. (<b>B</b>) Representative confocal IF images illustrating the sub-cellular localization of both SMN isoforms in NSC34 cells in the absence (B₁- B₂) or presence (B₃- B₄) of MG132. The MG132 treatment induced shorter, thicker, irregular neurites with frequent neuritic swellings (compare insets in B₂ vs B₄). FL-SMN was localized in coarser cytoplasmic granules, not extending into neurites (B₃), whereas a-SMN was diffusely distributed in the cell body and concentrated in the neuritic swellings (B₄). Scale bars: 35 μm; 20 μm in insets. (<b>C-D</b>) Bar graphs showing the quantification of neurite length (C) and soma size (D) of co-transfected cell treated and untreated with MG132. Statistical analysis was performed by Student’s t-test (*p<0.05; #p<0.001). (<b>E, F</b>) Stacked histograms showing the FL-SMN distribution (E) and cell abnormalities (F) of co-transfected cell untreated and treated with MG132. Data are presented as mean ± SEM of three different experiments. Percent ratio of FL-SMN distribution (FL-SMN only in soma/ FL-SMN in soma + neurites) and percent ratio of cell abnormalities (normal cells/ cells with abnormalities) were compared by means of chi-square test (#p<0.001) between the two experimental conditions (w/o MG132 or + MG132).</p

The proteasome inhibitor MG132 extends FL-SMN and a-SMN protein half-life.

<p>Representative Western blots (<b>A)</b> and bar graphs (<b>B</b>: OD ratio vs actin) of FL-SMN and a-SMN protein expression levels after cycloheximide (CHX) treatment in the presence <b>(A</b>, left<b>)</b> or absence <b>(A</b>, right<b>)</b> of MG132. The “+” and “-”indications represent the presence or absence, respectively, of MG132 and CHX. NSC34 cells were first co-transfected with N-terminally tagged human FL-SMN and a-SMN, then treated with CHX for 0, 1, 3, 5 and 7 hrs with or without MG132. The MG132 treatment significantly increased the a-SMN half-life at all time-point considered (<b>B</b>, left), whereas the MG132 effect on FL-SMN was not statistically significant (<b>B</b>, right). Data in <b>B</b> are presented as mean ± SEM of three different experiments. For both FL-SMN and a-SMN, distinct statistical analysis was performed by Student’s t-test between groups w/o and with MG132 treatment at each time points considered (n.s. = not significant; *p<0.05; **p<0.01; #p<0.001).</p

Effects of proteasome inhibitors on FL-SMN and a-SMN protein levels in a-SMN cell clones.

<p><b>(A)</b> Western blot analysis and quantification of FL-SMN and a-SMN protein expression after MG132 or lactacystin treatment. The “+” and “-”indications represent the presence or absence, respectively, of proteasome inhibitor. The a-SMN81 cell clone was treated with MG132 or lactacystin for 8 or 16 hrs, and endogenous FL-SMN and a-SMN protein levels analyzed by Western blot with the anti-SMN antibody clone 8 recognizing the N-terminal region of both SMN proteins (upper panel). The a-SMN expression was significantly increased by both proteasome inhibitors (MG132: 8 hrs vs 0 hrs, *p<0.05; 16 hrs vs 0 hrs, **p<0.01; lactacystin: 8 and 16 hrs vs 0 hrs, *p<0.05). Conversely, not significant (n.s.) effect was present with either MG132 or lactacystin on FL-SMN protein levels at each time point vs untreated cells (0 hrs). Statistical analysis was performed by one-way ANOVA followed by Tukey HSD as post hoc comparison test. Distinct statistical tests were performed for the two protein datasets, i.e., one for a-SMN and one for FL-SMN, and statistical differences for each time points were reported vs untreated cells (0 hrs) in the graphs. (<b>B</b>) Representative confocal IF images (red: anti a-SMN in B₁, B₃; green: anti NF-200 in B₂, B₄) illustrating the a-SMN sub-cellular localization in the absence (B₁-B₂) or presence (B₃-B₄) of MG132. MG132 treated cells were characterized by slightly more branched neurites (B₄, arrow in inset), neurofilament accumulation in the cell body and swellings along the neuritic shafts (Fig 5B₄, arrowheads). Scale bar: 30 μm; 15 μm in insets. (<b>C</b>) Bar graphs showing the quantification of neurite length of a-SMN cell clones untreated and treated with MG132. Statistical analysis was performed by Student’s t-test (**p<0.01). (<b>D</b>) Stacked histograms showing the distribution of cell abnormalities in a-SMN cell clones untreated and treated with MG132. Data are presented as mean ± SEM of three different experiments. Percent ratio of cell abnormalities (normal cells/ cells with abnormalities) was compared by means of chi-square test (#p<0.001) between the two experimental conditions (w/o MG132 or + MG132).</p

FL-SMN and a-SMN mRNA stability.

<p><b>A-C</b>. Quantitative RT-PCR analysis of FL-SMN and a-SMN transcript expression. NSC34 cells were co-transfected with human FL-SMN and a-SMN cDNA, untreated (<b>A</b>), or treated with actinomycin D (actD; <b>B</b>) or cycloheximide (CHX;<b>C</b>). Not significant (n.s.) differences in FL-SMN <i>vs</i> a-SMN transcript expression were found at any time-point and in any condition considered (A-C). Data were presented as mean ± SEM of three different experiments. Statistical analysis was performed by Student’s t-test.</p

A reference human induced pluripotent stem cell line for large-scale collaborative studies.

Human induced pluripotent stem cell (iPSC) lines are a powerful tool for studying development and disease, but the considerable phenotypic variation between lines makes it challenging to replicate key findings and integrate data across research groups. To address this issue, we sub-cloned candidate human iPSC lines and deeply characterized their genetic properties using whole genome sequencing, their genomic stability upon CRISPR-Cas9-based gene editing, and their phenotypic properties including differentiation to commonly used cell types. These studies identified KOLF2.1J as an all-around well-performing iPSC line. We then shared KOLF2.1J with groups around the world who tested its performance in head-to-head comparisons with their own preferred iPSC lines across a diverse range of differentiation protocols and functional assays. On the strength of these findings, we have made KOLF2.1J and its gene-edited derivative clones readily accessible to promote the standardization required for large-scale collaborative science in the stem cell field.Chan Zuckerberg Initiative Neurodegeneration Challenge Network, New York Stem Cell Foundatio

A reference human induced pluripotent stem cell line for large-scale collaborative studies

Human induced pluripotent stem cell (iPSC) lines are a powerful tool for studying development and disease, but the considerable phenotypic variation between lines makes it challenging to replicate key findings and integrate data across research groups. To address this issue, we sub-cloned candidate human iPSC lines and deeply characterized their genetic properties using whole genome sequencing, their genomic stability upon CRISPR-Cas9-based gene editing, and their phenotypic properties including differentiation to commonly used cell types. These studies identified KOLF2.1J as an all-around well-performing iPSC line. We then shared KOLF2.1J with groups around the world who tested its performance in head-to-head comparisons with their own preferred iPSC lines across a diverse range of differentiation protocols and functional assays. On the strength of these findings, we have made KOLF2.1J and its gene-edited derivative clones readily accessible to promote the standardization required for large-scale collaborative science in the stem cell field