Pathologic polyglutamine aggregation begins with a self-poisoning polymer crystal.

A long-standing goal of amyloid research has been to characterize the structural basis of the rate-determining nucleating event. However, the ephemeral nature of nucleation has made this goal unachievable with existing biochemistry, structural biology, and computational approaches. Here, we addressed that limitation for polyglutamine (polyQ), a polypeptide sequence that causes Huntington's and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. To identify essential features of the polyQ amyloid nucleus, we used a direct intracellular reporter of self-association to quantify frequencies of amyloid appearance as a function of concentration, conformational templates, and rational polyQ sequence permutations. We found that nucleation of pathologically expanded polyQ involves segments of three glutamine (Q) residues at every other position. We demonstrate using molecular simulations that this pattern encodes a four-stranded steric zipper with interdigitated Q side chains. Once formed, the zipper poisoned its own growth by engaging naive polypeptides on orthogonal faces, in a fashion characteristic of polymer crystals with intramolecular nuclei. We further show that self-poisoning can be exploited to block amyloid formation, by genetically oligomerizing polyQ prior to nucleation. By uncovering the physical nature of the rate-limiting event for polyQ aggregation in cells, our findings elucidate the molecular etiology of polyQ diseases.

Diseases that typically occur later in life, such as Alzheimer's, are often caused by specific proteins clumping together into structures known as amyloids. Once the process starts, amyloids will continue to form, leading to worse symptoms that cannot be cured. The best way to treat these diseases is therefore to stop amyloids from arising in the first place. Amyloids initially develop by proteins coming together to create an unstable structure referred to as the nucleus. The instability of the nucleus means it cannot be observed directly, making it hard to study this nucleation process. To overcome this, Kandola, Venkatesan et al. investigated the simplest protein known to form an amyloid ­ polyglutamine, which is made up of a chain of repeating building blocks known as amino acids. Polyglutamine forms only one type of amyloid which is associated with nine neurodegenerative diseases, including Huntington's disease. However, it only does this when its chain of amino acids exceeds a certain length, suggesting that a specific structure may be required for nucleation to begin. Kandola, Venkatesan et al. made alternative versions of the polyglutamine protein which each contained slightly different sequences of amino acids that will alter the way the protein folds. They then tested how well these different variants could form amyloids in yeast cells. This revealed that in order to join together into a nucleus, polyglutamine needs to be able to fold into a zipper shape made up of four interlocking strands. The length of the protein required to form this shape is also the same length that causes the amyloid associated with neurodegenerative diseases. Kandola, Venkatesan et al. also found that polyglutamine tends to bind to nuclei that have already formed in a way that hinders their growth. This 'self-poisoning' affect could potentially be exploited as a way to pre-emptively stop amyloids from initially arising. These findings have uncovered a potential therapeutic strategy for blocking amyloid formation that could eventually benefit people with or at risk of developing neurodegenerative diseases linked to polyglutamine. Additionally, this approach provides a blueprint for understanding how other proteins undergo amyloid nucleation, including those responsible for Alzheimer's, Parkinson's, and other diseases.

Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach.

The evolution of omics and computational competency has accelerated discoveries of the underlying biological processes in an unprecedented way. High throughput methodologies, such as flow cytometry, can reveal deeper insights into cell processes, thereby allowing opportunities for scientific discoveries related to health and diseases. However, working with cytometry data often imposes complex computational challenges due to high-dimensionality, large size, and nonlinearity of the data structure. In addition, cytometry data frequently exhibit diverse patterns across biomarkers and suffer from substantial class imbalances which can further complicate the problem. The existing methods of cytometry data analysis either predict cell population or perform feature selection. Through this study, we propose a "wisdom of the crowd" approach to simultaneously predict rare cell populations and perform feature selection by integrating a pool of modern machine learning (ML) algorithms. Given that our approach integrates superior performing ML models across different normalization techniques based on entropy and rank, our method can detect diverse patterns existing across the model features. Furthermore, the method identifies a dynamic biomarker structure that divides the features into persistently selected, unselected, and fluctuating assemblies indicating the role of each biomarker in rare cell prediction, which can subsequently aid in studies of disease progression.

Identification of rare, transient post-mitotic cell states that are induced by injury and required for whole-body regeneration in Schmidtea mediterranea.

Regeneration requires the coordination of stem cells, their progeny and distant differentiated tissues. Here, we present a comprehensive atlas of whole-body regeneration in Schmidtea mediterranea and identify wound-induced cell states. An analysis of 299,998 single-cell transcriptomes captured from regeneration-competent and regeneration-incompetent fragments identified transient regeneration-activated cell states (TRACS) in the muscle, epidermis and intestine. TRACS were independent of stem cell division with distinct spatiotemporal distributions, and RNAi depletion of TRACS-enriched genes produced regeneration defects. Muscle expression of notum, follistatin, evi/wls, glypican-1 and junctophilin-1 was required for tissue polarity. Epidermal expression of agat-1/2/3, cyp3142a1, zfhx3 and atp1a1 was important for stem cell proliferation. Finally, expression of spectrinß and atp12a in intestinal basal cells, and lrrk2, cathepsinB, myosin1e, polybromo-1 and talin-1 in intestinal enterocytes regulated stem cell proliferation and tissue remodelling, respectively. Our results identify cell types and molecules that are important for regeneration, indicating that regenerative ability can emerge from coordinated transcriptional plasticity across all three germ layers.

Image3C, a multimodal image-based and label-independent integrative method for single-cell analysis.

Image-based cell classification has become a common tool to identify phenotypic changes in cell populations. However, this methodology is limited to organisms possessing well-characterized species-specific reagents (e.g., antibodies) that allow cell identification, clustering, and convolutional neural network (CNN) training. In the absence of such reagents, the power of image-based classification has remained mostly off-limits to many research organisms. We have developed an image-based classification methodology we named Image3C (Image-Cytometry Cell Classification) that does not require species-specific reagents nor pre-existing knowledge about the sample. Image3C combines image-based flow cytometry with an unbiased, high-throughput cell clustering pipeline and CNN integration. Image3C exploits intrinsic cellular features and non-species-specific dyes to perform de novo cell composition analysis and detect changes between different conditions. Therefore, Image3C expands the use of image-based analyses of cell population composition to research organisms in which detailed cellular phenotypes are unknown or for which species-specific reagents are not available.

Cells are the building blocks of all living organisms. They come in many types, each with a different role. Understanding the composition of cells, i.e., how many cells and which types of cells are present inside an organ can indicate what that organ does. It can also reveal how that organ changes under different conditions, like during an infection or treatment. The most powerful methods for studying cells work well for species researchers already know a lot about, such as mice, zebrafish or humans, but not for less studied animals. To change this Accorsi, Box, Peuß et al. created a new tool called Image3C to be used for studying the composition of cells in less researched organisms. Instead of using reagents that only work for specific species, the tool uses molecules that work across many species, like dyes that stain the cell nucleus. A cell-sorting machine, known as a flow cytometer, connected to a microscope then takes pictures of hundreds of stained cells each second and Image3C groups them based on their appearance, without the need for any prior knowledge about the cell types. Accorsi et al. then tested Image3C on immune system cells of zebrafish, a well-studied animal, and apple snails, an under-studied animal. For both species, the tool was able to sort cells into groups representing different parts of the immune system. Image3C speeds up the grouping process and reduces the need for user intervention and time. This lowers the risk of bias compared to manual counting of cells. It can sort cells even when the types of cells in an organism are unknown and even when specialized reagents for an organism do not exist. This means that it could characterise the cell make-up of new tissues coming from organisms never studied before. Access to this uncharted world of cells stands to reveal previously inaccessible clues about how organs behave and evolve and allow researchers to investigate the impact of environmental changes on these cells.

Identification of stem cells from large cell populations with topological scoring.

Machine learning and topological analysis methods are becoming increasingly used on various large-scale omics datasets. Modern high dimensional flow cytometry data sets share many features with other omics datasets like genomics and proteomics. For example, genomics or proteomics datasets can be sparse and have high dimensionality, and flow cytometry datasets can also share these features. This makes flow cytometry data potentially a suitable candidate for employing machine learning and topological scoring strategies, for example, to gain novel insights into patterns within the data. We have previously developed a Topological Score (TopS) and implemented it for the analysis of quantitative protein interaction network datasets. Here we show that TopS approach for large scale data analysis is applicable to the analysis of a previously described flow cytometry sorted human hematopoietic stem cell dataset. We demonstrate that TopS is capable of effectively sorting this dataset into cell populations and identify rare cell populations. We demonstrate the utility of TopS when coupled with multiple approaches including topological data analysis, X-shift clustering, and t-Distributed Stochastic Neighbor Embedding (t-SNE). Our results suggest that TopS could be effectively used to analyze large scale flow cytometry datasets to find rare cell populations.

Author Correction: Insulin resistance in cavefish as an adaptation to a nutrient-limited environment.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Adaptation to low parasite abundance affects immune investment and immunopathological responses of cavefish.

Reduced parasitic infection rates in the developed world are suspected to underlie the rising prevalence of autoimmune disorders. However, the long-term evolutionary consequences of decreased parasite exposure on an immune system are not well understood. We used the Mexican tetra Astyanax mexicanus to understand how loss of parasite diversity influences the evolutionary trajectory of the vertebrate immune system, by comparing river with cave morphotypes. Here, we present field data affirming a strong reduction in parasite diversity in the cave ecosystem, and show that cavefish immune cells display a more sensitive pro-inflammatory response towards bacterial endotoxins. Surprisingly, other innate cellular immune responses, such as phagocytosis, are drastically decreased in cavefish. Using two independent single-cell approaches, we identified a shift in the overall immune cell composition in cavefish as the underlying cellular mechanism, indicating strong differences in the immune investment strategy. While surface fish invest evenly into the innate and adaptive immune systems, cavefish shifted immune investment to the adaptive immune system, and here, mainly towards specific T-cell populations that promote homeostasis. Additionally, inflammatory responses and immunopathological phenotypes in visceral adipose tissue are drastically reduced in cavefish. Our data indicate that long-term adaptation to low parasite diversity coincides with a more sensitive immune system in cavefish, which is accompanied by a reduction in the immune cells that play a role in mediating the pro-inflammatory response.

Insulin resistance in cavefish as an adaptation to a nutrient-limited environment.

Periodic food shortages are a major challenge faced by organisms in natural habitats. Cave-dwelling animals must withstand long periods of nutrient deprivation, as-in the absence of photosynthesis-caves depend on external energy sources such as seasonal floods. Here we show that cave-adapted populations of the Mexican tetra, Astyanax mexicanus, have dysregulated blood glucose homeostasis and are insulin-resistant compared to river-adapted populations. We found that multiple cave populations carry a mutation in the insulin receptor that leads to decreased insulin binding in vitro and contributes to hyperglycaemia. Hybrid fish from surface-cave crosses carrying this mutation weigh more than non-carriers, and zebrafish genetically engineered to carry the mutation have increased body weight and insulin resistance. Higher body weight may be advantageous in caves as a strategy to cope with an infrequent food supply. In humans, the identical mutation in the insulin receptor leads to a severe form of insulin resistance and reduced lifespan. However, cavefish have a similar lifespan to surface fish and do not accumulate the advanced glycation end-products in the blood that are typically associated with the progression of diabetes-associated pathologies. Our findings suggest that diminished insulin signalling is beneficial in a nutrient-limited environment and that cavefish may have acquired compensatory mechanisms that enable them to circumvent the typical negative effects associated with failure to regulate blood glucose levels.

Single-cell transcriptome analysis of avian neural crest migration reveals signatures of invasion and molecular transitions.

Neural crest cells migrate throughout the embryo, but how cells move in a directed and collective manner has remained unclear. Here, we perform the first single-cell transcriptome analysis of cranial neural crest cell migration at three progressive stages in chick and identify and establish hierarchical relationships between cell position and time-specific transcriptional signatures. We determine a novel transcriptional signature of the most invasive neural crest Trailblazer cells that is consistent during migration and enriched for approximately 900 genes. Knockdown of several Trailblazer genes shows significant but modest changes to total distance migrated. However, in vivo expression analysis by RNAscope and immunohistochemistry reveals some salt and pepper patterns that include strong individual Trailblazer gene expression in cells within other subregions of the migratory stream. These data provide new insights into the molecular diversity and dynamics within a neural crest cell migratory stream that underlie complex directed and collective cell behaviors.

Using Fluorescent Reporters in Conjunction with Cytometry and Statistics to Assess Nuclear Accumulation of Ribosomal Proteins.

Fluorescently labeled ribosomal proteins can be used to detect and monitor the intracellular localization of these proteins. Both Rps2, a subunit of the 40S ribosome, and Rpl25, a subunit of the 60S ribosome, have been fused to the coding sequence of GFP at their C-termini and the fusions have been used to monitor their localization within cells using fluorescent microscopy. Normally these proteins are efficiently incorporated into ribosomes and exported into the cytoplasm where they exhibit a low uniform fluorescence. However, these Rps2- and Rpl25-GFP proteins accumulate in the nucleus of mutants defective in ribosome biogenesis or export. Here, we describe a single-cell quantitative method to assess the nuclear accumulation of ribosomal proteins using cytometry and biostatistics. This assay was developed for use with GFP reporters for ribosome biogenesis in budding yeast but could be adapted for use with any GFP reporter that accumulates into the nucleus under adverse conditions.

Transcriptome analysis of tetraploid cells identifies cyclin D2 as a facilitator of adaptation to genome doubling in the presence of p53.

Tetraploidization, or genome doubling, is a prominent event in tumorigenesis, primarily because cell division in polyploid cells is error-prone and produces aneuploid cells. This study investigates changes in gene expression evoked in acute and adapted tetraploid cells and their effect on cell-cycle progression. Acute polyploidy was generated by knockdown of the essential regulator of cytokinesis anillin, which resulted in cytokinesis failure and formation of binucleate cells, or by chemical inhibition of Aurora kinases, causing abnormal mitotic exit with formation of single cells with aberrant nuclear morphology. Transcriptome analysis of these acute tetraploid cells revealed common signatures of activation of the tumor-suppressor protein p53. Suppression of proliferation in these cells was dependent on p53 and its transcriptional target, CDK inhibitor p21. Rare proliferating tetraploid cells can emerge from acute polyploid populations. Gene expression analysis of single cell-derived, adapted tetraploid clones showed up-regulation of several p53 target genes and cyclin D2, the activator of CDK4/6/2. Overexpression of cyclin D2 in diploid cells strongly potentiated the ability to proliferate with increased DNA content despite the presence of functional p53. These results indicate that p53-mediated suppression of proliferation of polyploid cells can be averted by increased levels of oncogenes such as cyclin D2, elucidating a possible route for tetraploidy-mediated genomic instability in carcinogenesis.

Karyotyping human and mouse cells using probes from single-sorted chromosomes and open source software.

Multispectral karyotyping analyzes all chromosomes in a single cell by labeling them with chromosome-specific probes conjugated to unique combinations of fluorophores. Currently available multispectral karyotyping systems require the purchase of specialized equipment and reagents. However, conventional laser scanning confocal microscopes that are capable of separating multiple overlapping emission spectra through spectral imaging and linear unmixing can be utilized for classifying chromosomes painted with multicolor probes. Here, we generated multicolor chromosome paints from single-sorted human and mouse chromosomes and developed the Karyotype Identification via Spectral Separation (KISS) analysis package, a set of freely available open source ImageJ tools for spectral unmixing and karyotyping. Chromosome spreads painted with our multispectral probe sets can be imaged on widely available spectral laser scanning confocal microscopes and analyzed using our ImageJ tools. Together, our probes and software enable academic labs with access to a laser-scanning spectral microscope to perform multicolor karyotyping in a cost-effective manner.

Mitotic Transcriptional Activation: Clearance of Actively Engaged Pol II via Transcriptional Elongation Control in Mitosis.

Although it is established that some general transcription factors are inactivated at mitosis, many details of mitotic transcription inhibition (MTI) and its underlying mechanisms are largely unknown. We have identified mitotic transcriptional activation (MTA) as a key regulatory step to control transcription in mitosis for genes with transcriptionally engaged RNA polymerase II (Pol II) to activate and transcribe until the end of the gene to clear Pol II from mitotic chromatin, followed by global impairment of transcription reinitiation through MTI. Global nascent RNA sequencing and RNA fluorescence in situ hybridization demonstrate the existence of transcriptionally engaged Pol II in early mitosis. Both genetic and chemical inhibition of P-TEFb in mitosis lead to delays in the progression of cell division. Together, our study reveals a mechanism for MTA and MTI whereby transcriptionally engaged Pol II can progress into productive elongation and finish transcription to allow proper cellular division.

VEGF signals induce trailblazer cell identity that drives neural crest migration.

Embryonic neural crest cells travel in discrete streams to precise locations throughout the head and body. We previously showed that cranial neural crest cells respond chemotactically to vascular endothelial growth factor (VEGF) and that cells within the migratory front have distinct behaviors and gene expression. We proposed a cell-induced gradient model in which lead neural crest cells read out directional information from a chemoattractant profile and instruct trailers to follow. In this study, we show that migrating chick neural crest cells do not display distinct lead and trailer gene expression profiles in culture. However, exposure to VEGF in vitro results in the upregulation of a small subset of genes associated with an in vivo lead cell signature. Timed addition and removal of VEGF in culture reveals the changes in neural crest cell gene expression are rapid. A computational model incorporating an integrate-and-switch mechanism between cellular phenotypes predicts migration efficiency is influenced by the timescale of cell behavior switching. To test the model hypothesis that neural crest cellular phenotypes respond to changes in the VEGF chemoattractant profile, we presented ectopic sources of VEGF to the trailer neural crest cell subpopulation and show diverted cell trajectories and stream alterations consistent with model predictions. Gene profiling of trailer cells that diverted and encountered VEGF revealed upregulation of a subset of 'lead' genes. Injection of neuropilin1 (Np1)-Fc into the trailer subpopulation or electroporation of VEGF morpholino to reduce VEGF signaling failed to alter trailer neural crest cell trajectories, suggesting trailers do not require VEGF to maintain coordinated migration. These results indicate that VEGF is one of the signals that establishes lead cell identity and its chemoattractant profile is critical to neural crest cell migration.

Neural crest migration is driven by a few trailblazer cells with a unique molecular signature narrowly confined to the invasive front.

Neural crest (NC) cell migration is crucial to the formation of peripheral tissues during vertebrate development. However, how NC cells respond to different microenvironments to maintain persistence of direction and cohesion in multicellular streams remains unclear. To address this, we profiled eight subregions of a typical cranial NC cell migratory stream. Hierarchical clustering showed significant differences in the expression profiles of the lead three subregions compared with newly emerged cells. Multiplexed imaging of mRNA expression using fluorescent hybridization chain reaction (HCR) quantitatively confirmed the expression profiles of lead cells. Computational modeling predicted that a small fraction of lead cells that detect directional information is optimal for successful stream migration. Single-cell profiling then revealed a unique molecular signature that is consistent and stable over time in a subset of lead cells within the most advanced portion of the migratory front, which we term trailblazers. Model simulations that forced a lead cell behavior in the trailing subpopulation predicted cell bunching near the migratory domain entrance. Misexpression of the trailblazer molecular signature by perturbation of two upstream transcription factors agreed with the in silico prediction and showed alterations to NC cell migration distance and stream shape. These data are the first to characterize the molecular diversity within an NC cell migratory stream and offer insights into how molecular patterns are transduced into cell behaviors.

Quantitative single cell gene expression profiling in the avian embryo.

BACKGROUND: Single cell gene profiling has been successfully applied to cultured cells. However, isolation and preservation of a cell's native gene expression state from an intact embryo remain problematic. RESULTS: Here, we present a strategy for in vivo single cell profiling that optimizes cell identification, isolation and amplification of nucleic acids with nominal bias and sufficient material detection. We first tested several photoconvertible fluorescent proteins to selectively mark a cell(s) of interest in living chick embryos then accurately identify and isolate the same cell(s) in fixed tissue slices. We determined that the dual color mDendra2 provided the optimal signal/noise ratio for this purpose. We developed proper procedures to minimize cell death and preserve gene expression, and suggest nucleic acid amplification strategies for downstream analysis by microfluidic reverse transcriptase quantitative polymerase chain reaction or RNAseq. Lastly, we compared methods for single cell isolation and found that our fluorescence-activated cell sorting (FACS) protocol was able to preserve native transcripts and generate expression profiles with much higher efficiency than laser capture microdissection (LCM). CONCLUSIONS: Quantitative single cell gene expression profiling may be accurately applied to interrogate complex cell dynamics events during embryonic development by combining photoconversion cell labeling, FACS, proper handling of isolated cells, and amplification strategies.

A Phospho-SIM in the Antiviral Protein PML is Required for Its Recruitment to HSV-1 Genomes.

Herpes simplex virus type 1 (HSV-1) is a significant human pathogen that infects a large portion of the human population. Cells deploy a variety of defenses to limit the extent to which the virus can replicate. One such factor is the promyelocytic leukemia (PML) protein, the nucleating and organizing factor of nuclear domain 10 (ND10). PML responds to a number of stimuli and is implicated in intrinsic and innate cellular antiviral defenses against HSV-1. While the role of PML in a number of cellular pathways is controlled by post-translational modifications, the effects of phosphorylation on its antiviral activity toward HSV-1 have been largely unexplored. Consequently, we mapped phosphorylation sites on PML, mutated these and other known phosphorylation sites on PML isoform I (PML-I), and examined their effects on a number of PML's activities. Our results show that phosphorylation at most sites on PML-I is dispensable for the formation of ND10s and colocalization between PML-I and the HSV-1 regulatory protein, ICP0, which antagonizes PML-I function. However, inhibiting phosphorylation at sites near the SUMO-interaction motif (SIM) of PML-I impairs its ability to respond to HSV-1 infection. Overall, our data suggest that PML phosphorylation regulates its antiviral activity against HSV-1.

Nuclear cGMP-dependent kinase regulates gene expression via activity-dependent recruitment of a conserved histone deacetylase complex.

Elevation of the second messenger cGMP by nitric oxide (NO) activates the cGMP-dependent protein kinase PKG, which is key in regulating cardiovascular, intestinal, and neuronal functions in mammals. The NO-cGMP-PKG signaling pathway is also a major therapeutic target for cardiovascular and male reproductive diseases. Despite widespread effects of PKG activation, few molecular targets of PKG are known. We study how EGL-4, the Caenorhabditis elegans PKG ortholog, modulates foraging behavior and egg-laying and seeks the downstream effectors of EGL-4 activity. Using a combination of unbiased forward genetic screen and proteomic analysis, we have identified a conserved SAEG-1/SAEG-2/HDA-2 histone deacetylase complex that is specifically recruited by activated nuclear EGL-4. Gene expression profiling by microarrays revealed >40 genes that are sensitive to EGL-4 activity in a SAEG-1-dependent manner. We present evidence that EGL-4 controls egg laying via one of these genes, Y45F10C.2, which encodes a novel protein that is expressed exclusively in the uterine epithelium. Our results indicate that, in addition to cytoplasmic functions, active EGL-4/PKG acts in the nucleus via a conserved Class I histone deacetylase complex to regulate gene expression pertinent to behavioral and physiological responses to cGMP. We also identify transcriptional targets of EGL-4 that carry out discrete components of the physiological response.

Genetic and dietary regulation of lipid droplet expansion in Caenorhabditis elegans.

Dietary fat accumulates in lipid droplets or endolysosomal compartments that undergo selective expansion under normal or pathophysiological conditions. We find that genetic defects in a peroxisomal beta-oxidation pathway cause size expansion in lipid droplets that are distinct from the lysosome-related organelles in Caenorhabditis elegans. Expansion of lipid droplets is accompanied by an increase in triglycerides (TAG) that are resistant to fasting- or TAG lipase-triggered lipolysis. Nevertheless, in mutant animals, a diet poor in vaccenic acid reduced the TAG level and lipid droplet size. Our results implicate peroxisomal dysfunction in pathologic lipid droplet expansion in animals and illustrate how dietary factors modulate the phenotype of such genetic defects.