Morphological hallmarks of dopaminergic neurodegeneration are associated with altered neuron function in Caenorhabditis elegans.

Caenorhabditis elegans (C. elegans) is an excellent model system to study neurodegenerative diseases, such as Parkinson's disease, as it enables analysis of both neuron morphology and function in live animals. Multiple structural changes in neurons, such as cephalic dendrite morphological abnormalities, have been considered hallmarks of neurodegeneration in this model, but their relevance to changes in neuron function are not entirely clear. We sought to test whether hallmark morphological changes associated with chemically induced dopaminergic neuron degeneration, such as dendrite blebbing, breakage, and loss, are indicative of neuronal malfunction and result in changes in behavior. We adapted an established dopaminergic neuronal function assay by measuring paralysis in the presence of exogenous dopamine, which revealed clear differences between cat-2 dopamine deficient mutants, wildtype worms, and dat-1 dopamine abundant mutants. Next, we integrated an automated image processing algorithm and a microfluidic device to segregate worm populations by their cephalic dendrite morphologies. We show that nematodes with dopaminergic dendrite degeneration markers, such as blebbing or breakage, paralyze at higher rates in a dopamine solution, providing evidence that dopaminergic neurodegeneration morphologies are correlated with functional neuronal outputs.

Morphological hallmarks of dopaminergic neurodegeneration are associated with altered neuron function in Caenorhabditis elegans.

Caenorhabditis elegans (C. elegans) is an excellent model system to study neurodegenerative diseases, such as Parkinson's disease, as it enables analysis of both neuron morphology and function in live animals. Multiple structural changes in neurons, such as cephalic dendrite morphological abnormalities, have been considered hallmarks of neurodegeneration in this model, but their relevance to changes in neuron function are not entirely clear. We sought to test whether hallmark morphological changes associated with chemically induced dopaminergic neuron degeneration, such as dendrite blebbing, breakage, and loss, are indicative of neuronal malfunction and result in changes in behavior. We adapted an established dopaminergic neuronal function assay by measuring paralysis in the presence of exogenous dopamine, which revealed clear differences between cat-2 dopamine deficient mutants, wildtype worms, and dat-1 dopamine abundant mutants. Next, we integrated an automated image processing algorithm and a microfluidic device to segregate worm populations by their cephalic dendrite morphologies. We show that nematodes with dopaminergic dendrite degeneration markers, such as blebbing or breakage, paralyze at higher rates in a dopamine solution, providing evidence that dopaminergic neurodegeneration morphologies are correlated with functional neuronal outputs.

An unbiased, automated platform for scoring dopaminergic neurodegeneration in C. elegans.

Caenorhabditis elegans (C. elegans) has served as a simple model organism to study dopaminergic neurodegeneration, as it enables quantitative analysis of cellular and sub-cellular morphologies in live animals. These isogenic nematodes have a rapid life cycle and transparent body, making high-throughput imaging and evaluation of fluorescently tagged neurons possible. However, the current state-of-the-art method for quantifying dopaminergic degeneration requires researchers to manually examine images and score dendrites into groups of varying levels of neurodegeneration severity, which is time consuming, subject to bias, and limited in data sensitivity. We aim to overcome the pitfalls of manual neuron scoring by developing an automated, unbiased image processing algorithm to quantify dopaminergic neurodegeneration in C. elegans. The algorithm can be used on images acquired with different microscopy setups and only requires two inputs: a maximum projection image of the four cephalic neurons in the C. elegans head and the pixel size of the user's camera. We validate the platform by detecting and quantifying neurodegeneration in nematodes exposed to rotenone, cold shock, and 6-hydroxydopamine using 63x epifluorescence, 63x confocal, and 40x epifluorescence microscopy, respectively. Analysis of tubby mutant worms with altered fat storage showed that, contrary to our hypothesis, increased adiposity did not sensitize to stressor-induced neurodegeneration. We further verify the accuracy of the algorithm by comparing code-generated, categorical degeneration results with manually scored dendrites of the same experiments. The platform, which detects 20 different metrics of neurodegeneration, can provide comparative insight into how each exposure affects dopaminergic neurodegeneration patterns.

Laminin switches terminal differentiation fate of human trophoblast stem cells under chemically defined culture conditions.

Human trophoblast stem cells (hTSCs) have emerged as a powerful tool to model early placental development in vitro. Analogous to the epithelial cytotrophoblast in the placenta, hTSCs can differentiate into cells of the extravillous trophoblast (EVT) lineage or the multinucleate syncytiotrophoblast (STB). Here we present a chemically defined culture system for STB and EVT differentiation of hTSCs. Notably, in contrast to current approaches, we neither utilize forskolin for STB formation nor transforming growth factor-beta (TGFß) inhibitors or a passage step for EVT differentiation. Strikingly, the presence of a single additional extracellular cue-laminin-111-switched the terminal differentiation of hTSCs from STB to the EVT lineage under these conditions. In the absence of laminin-111, STB formation occurred, with cell fusion comparable to that obtained with differentiation mediated by forskolin; however, in the presence of laminin-111, hTSCs differentiated to the EVT lineage. Protein expression of nuclear hypoxia-inducible factors (HIF1α and HIF2α) was upregulated during EVT differentiation mediated by laminin-111 exposure. A heterogeneous mixture of Notch1+ EVTs in colonies and HLA-G+ single-cell EVTs were obtained without a passage step, reminiscent of heterogeneity in vivo. Further analysis showed that inhibition of TGFß signaling affected both STB and EVT differentiation mediated by laminin-111 exposure. TGFß inhibition during EVT differentiation resulted in decreased HLA-G expression and increased Notch1 expression. On the other hand, TGFß inhibition prevented STB formation. The chemically defined culture system for hTSC differentiation established herein facilitates quantitative analysis of heterogeneity that arises during hTSC differentiation and will enable mechanistic studies in vitro.

An unbiased, automated platform for scoring dopaminergic neurodegeneration in C. elegans.

Caenorhabditis elegans ( C. elegans ) has served as a simple model organism to study dopaminergic neurodegeneration, as it enables quantitative analysis of cellular and sub-cellular morphologies in live animals. These isogenic nematodes have a rapid life cycle and transparent body, making high-throughput imaging and evaluation of fluorescently tagged neurons possible. However, the current state-of-the-art method for quantifying dopaminergic degeneration requires researchers to manually examine images and score dendrites into groups of varying levels of neurodegeneration severity, which is time consuming, subject to bias, and limited in data sensitivity. We aim to overcome the pitfalls of manual neuron scoring by developing an automated, unbiased image processing algorithm to quantify dopaminergic neurodegeneration in C. elegans . The algorithm can be used on images acquired with different microscopy setups and only requires two inputs: a maximum projection image of the four cephalic neurons in the C. elegans head and the pixel size of the user’s camera. We validate the platform by detecting and quantifying neurodegeneration in nematodes exposed to rotenone, cold shock, and 6-hydroxydopamine using 63x epifluorescence, 63x confocal, and 40x epifluorescence microscopy, respectively. Analysis of tubby mutant worms with altered fat storage showed that, contrary to our hypothesis, increased adiposity did not sensitize to stressor-induced neurodegeneration. We further verify the accuracy of the algorithm by comparing code-generated, categorical degeneration results with manually scored dendrites of the same experiments. The platform, which detects 19 different metrics of neurodegeneration, can provide comparative insight into how each exposure affects dopaminergic neurodegeneration patterns.

Endogenous DAF-16 spatiotemporal activity quantitatively predicts lifespan extension induced by dietary restriction.

In many organisms, dietary restriction (DR) leads to lifespan extension through the activation of cell protection and pro-longevity gene expression programs. In the nematode C. elegans, the DAF-16 transcription factor is a key aging regulator that governs the Insulin/IGF-1 signaling pathway and undergoes translocation from the cytoplasm to the nucleus of cells when animals are exposed to food limitation. However, how large is the influence of DR on DAF-16 activity, and its subsequent impact on lifespan has not been quantitatively determined. In this work, we assess the endogenous activity of DAF-16 under various DR regimes by coupling CRISPR/Cas9-enabled fluorescent tagging of DAF-16 with quantitative image analysis and machine learning. Our results indicate that DR regimes induce strong endogenous DAF-16 activity, although DAF-16 is less responsive in aged individuals. DAF-16 activity is in turn a robust predictor of mean lifespan in C. elegans, accounting for 78% of its variability under DR. Analysis of tissue-specific expression aided by a machine learning tissue classifier reveals that, under DR, the largest contribution to DAF-16 nuclear intensity originates from the intestine and neurons. DR also drives DAF-16 activity in unexpected locations such as the germline and intestinal nucleoli.

Identifying C. elegans lifespan mutants by screening for early-onset protein aggregation.

Genetic screens are widely used to identify genes that control specific biological functions. In Caenorhabditis elegans, forward genetic screens rely on the isolation of reproductively active mutants that can self-propagate clonal populations. Screens that target post-reproductive phenotypes, such as lifespan, are thus challenging. We combine microfluidic technologies and image processing to perform high-throughput automated screening for short-lived mutants using protein aggregation as a marker for aging. We take advantage of microfluidics for maintaining a reproductively active adult mutagenized population and for performing serial high-throughput analysis and sorting of animals with increased protein aggregation, using fluorescently-labeled PAB-1 as a readout. We demonstrate that lifespan mutants can be identified by screening for accelerated protein aggregation through quantitative analysis of fluorescently labeled aggregates while avoiding conditional sterilization or manual separation of parental and progeny populations. We also show that aged wildtypes and premature aggregation mutants differ in aggregate morphology, suggesting aggregate growth is time-dependent.

A bioinspired, passive microfluidic lobe filtration system.

Size-based microfluidic filtration systems can be affected by clogging, which prevents their use in high-throughput and continuous applications. To address these concerns, we have developed two microfluidic lobe filters bioinspired by the filtration mechanism of two species of manta ray. These chips enable filtration of particles around 10-30 µm with precise control and high throughput by using two arrays of equally spaced filter lobes. For each filter design, we investigated multiple inlet flow rates and particle sizes to identify successful operational parameters. Filtration efficiency increases with fluid flow rate, suggesting that particle inertial effects play a key role in lobe filter separation. Microparticle filtration efficiencies up to 99% were obtainable with inlet flow rates of 20 mL min-1. Each filter design successfully increased microparticle concentrations by a factor of two or greater at different inlet flow rates ranging from 6-16 mL min-1. At higher inlet flow rates, ANSYS Fluent simulations of each device revealed a complex velocity profile that contains three local maxima and two inflection points. Ultimately, we show that distances from the lobe array to the closest local maxima and inflection point of the velocity profile can be used to successfully estimate lobe filtration efficiency at each operational flow rate.

Optogenetics gets the worm.

Analysis of Caenorhabditis elegans natural movement and optogenetic control of its muscle cells enable controlled locomotion.

Two distinct trophectoderm lineage stem cells from human pluripotent stem cells.

The trophectoderm layer of the blastocyst-stage embryo is the precursor for all trophoblast cells in the placenta. Human trophoblast stem (TS) cells have emerged as an attractive tool for studies on early trophoblast development. However, the use of TS cell models is constrained by the limited genetic diversity of existing TS cell lines and restrictions on using human fetal tissue or embryos needed to generate additional lines. Here we report the derivation of two distinct stem cell types of the trophectoderm lineage from human pluripotent stem cells. Analogous to villous cytotrophoblasts in vivo, the first is a CDX2- stem cell comparable with placenta-derived TS cells-they both exhibit identical expression of key markers, are maintained in culture and differentiate under similar conditions, and share high transcriptome similarity. The second is a CDX2+ stem cell with distinct cell culture requirements, and differences in gene expression and differentiation, relative to CDX2- stem cells. Derivation of TS cells from pluripotent stem cells will significantly enable construction of in vitro models for normal and pathological placental development.

Deep learning-enabled analysis reveals distinct neuronal phenotypes induced by aging and cold-shock.

BACKGROUND: Access to quantitative information is crucial to obtain a deeper understanding of biological systems. In addition to being low-throughput, traditional image-based analysis is mostly limited to error-prone qualitative or semi-quantitative assessment of phenotypes, particularly for complex subcellular morphologies. The PVD neuron in Caenorhabditis elegans, which is responsible for harsh touch and thermosensation, undergoes structural degeneration as nematodes age characterized by the appearance of dendritic protrusions. Analysis of these neurodegenerative patterns is labor-intensive and limited to qualitative assessment. RESULTS: In this work, we apply deep learning to perform quantitative image-based analysis of complex neurodegeneration patterns exhibited by the PVD neuron in C. elegans. We apply a convolutional neural network algorithm (Mask R-CNN) to identify neurodegenerative subcellular protrusions that appear after cold-shock or as a result of aging. A multiparametric phenotypic profile captures the unique morphological changes induced by each perturbation. We identify that acute cold-shock-induced neurodegeneration is reversible and depends on rearing temperature and, importantly, that aging and cold-shock induce distinct neuronal beading patterns. CONCLUSION: The results of this work indicate that implementing deep learning for challenging image segmentation of PVD neurodegeneration enables quantitatively tracking subtle morphological changes in an unbiased manner. This analysis revealed that distinct patterns of morphological alteration are induced by aging and cold-shock, suggesting different mechanisms at play. This approach can be used to identify the molecular components involved in orchestrating neurodegeneration and to characterize the effect of other stressors on PVD degeneration.

An inexpensive programmable optogenetic platform for controlled neuronal activation regimens in C. elegans.

In Caenorhabditis elegans, optogenetic stimulation has been widely used to assess neuronal function, control animal movement, or assay circuit responses to controlled stimuli. Most studies are performed on single animals and require high-end components such as lasers and shutters. We present an accessible platform that enables controlled optogenetic stimulation of C. elegans in two modes: single animal stimulation with locomotion tracking and entire population stimulation for neuronal exercise regimens. The system consists of accessible electronic components: a high-power light-emitting diode, Arduino board, and relay are integrated with MATLAB to enable programmable optogenetic stimulation regimens. This system provides flexibility in optogenetic stimulation in freely moving animals while providing quantitative information of optogenetic-driven locomotion responses. We show the applicability of this platform in single animals by stimulation of cholinergic motor neurons in C. elegans and quantitative assessment of contractile responses. In addition, we tested synaptic plasticity by coupling the entire-population stimulation mode with measurements of synaptic strength using an aldicarb assay, where clear changes in synaptic strength were observed after regimens of neuronal exercise. This platform is composed of inexpensive components, while providing the illumination strength of high-end systems, which require expensive lasers, shutters, or automated stages. This platform requires no moving parts but provides flexibility in stimulation regimens.

Discovery and Evaluation of Peptide Ligands for Selective Adsorption and Release of Cas9 Nuclease on Solid Substrates.

The rapid expansion of CRISPR in biotechnology, medicine, and bioprocessing poses an urgent need for advanced manufacturing of Cas nucleases. The lack of Cas-targeting ligands, however, prevents the development of platform processes for purifying this class of molecules. This work represents the first effort at developing short synthetic Cas9-binding peptides and demonstrates their applicability as affinity ligands for the purification of a Cas nuclease. Candidate Cas9-targeting peptides were initially identified by screening a solid-phase peptide library against a model mixture of Streptococcus pyogenes Cas9 spiked in Escherichia coli cell lysate. An ensemble of homologous sequences was identified, conjugated on Toyopearl resin, and evaluated by Cas9 binding studies to identify sequences providing selective Cas9 capture and efficient release. In silico docking studies were also performed to evaluate the binding energy and site of the various peptides on Cas9. Notably, sequences GYYRYSEY and YYHRHGLQ were shown to target the RecII domain of Cas9, which is not involved in nuclease activity and was targeted as an ideal binding site. The peptide ligands were validated by purifying Cas9 from the E. coli lysate in dynamic conditions and through measurements of binding capacity and strength (Qmax and KD). The resulting values of Qmax = 4-5 mg Cas9 per mL of resin and KD ∼ 0.1-0.3 µM, product recovery (86-89%), and purity (91%-93%) indicate that both peptides, and YYHRHGLQ in particular, can serve as capture ligands in a platform purification process of Cas9.

Microfluidic Technologies for High Throughput Screening Through Sorting and On-Chip Culture of C. elegans.

The nematode Caenorhabditis elegans is a powerful model organism that has been widely used to study molecular biology, cell development, neurobiology, and aging. Despite their use for the past several decades, the conventional techniques for growth, imaging, and behavioral analysis of C. elegans can be cumbersome, and acquiring large data sets in a high-throughput manner can be challenging. Developments in microfluidic "lab-on-a-chip" technologies have improved studies of C. elegans by increasing experimental control and throughput. Microfluidic features such as on-chip control layers, immobilization channels, and chamber arrays have been incorporated to develop increasingly complex platforms that make experimental techniques more powerful. Genetic and chemical screens are performed on C. elegans to determine gene function and phenotypic outcomes of perturbations, to test the effect that chemicals have on health and behavior, and to find drug candidates. In this review, we will discuss microfluidic technologies that have been used to increase the throughput of genetic and chemical screens in C. elegans. We will discuss screens for neurobiology, aging, development, behavior, and many other biological processes. We will also discuss robotic technologies that assist in microfluidic screens, as well as alternate platforms that perform functions similar to microfluidics.

Affordable Microfluidic Bead-Sorting Platform for Automated Selection of Porous Particles Functionalized with Bioactive Compounds.

The ability to rapidly and accurately evaluate bioactive compounds immobilized on porous particles is crucial in the discovery of drugs, diagnostic reagents, ligands, and catalysts. Existing options for solid phase screening of bioactive compounds, while highly effective and well established, can be cost-prohibitive for proof-of-concept and early stage work, limiting its applicability and flexibility in new research areas. Here, we present a low-cost microfluidics-based platform enabling automated screening of small porous beads from solid-phase peptide libraries with high sensitivity and specificity, to identify leads with high binding affinity for a biological target. The integration of unbiased computer assisted image processing and analysis tools, provided the platform with the flexibility of sorting through beads with distinct fluorescence patterns. The customized design of the microfluidic device helped with handling beads with different diameters (~100-300 µm). As a microfluidic device, this portable novel platform can be integrated with a variety of analytical instruments to perform screening. In this study, the system utilizes fluorescence microscopy and unsupervised image analysis, and can operate at a sorting speed of up to 125 beads/hr (~3.5 times faster than a trained operator) providing >90% yield and >90% bead sorting accuracy. Notably, the device has proven successful in screening a model solid-phase peptide library by showing the ability to select beads carrying peptides binding a target protein (human IgG).

A microfluidic platform for lifelong high-resolution and high throughput imaging of subtle aging phenotypes in C. elegans.

Aging produces a number of changes in the neuronal structure and function throughout a variety of organisms. These aging-induced changes encompass a wide range of phenotypes, from loss of locomotion ability to defective production of synaptic vesicles. C. elegans is one of the primary systems used to elucidate phenotypes associated with aging processes. Conventional aging studies in C. elegans are typically labor-intensive, low-throughput, and incorporate fluorodeoxyuridine (FUdR) as a sterilizing agent to keep the population age-synchronized throughout the assay. However, FUdR exposure induces lifespan extension, and can potentially mask the phenotypes associated with the natural aging process. In addition, studying cellular or subcellular structures requires anesthetics or adhesives to immobilize nematodes while acquiring high-resolution images. In this platform, we are able to maintain a population (∼1000 worms) age-synchronized throughout its lifespan and perform a series of high-resolution microscopy studies in a drug-free environment. The device is composed of two main interconnected sections, one with the purpose of filtering progeny while keeping the parent population intact, and one for trapping nematodes in individual compartments for microscopy. Immobilization is carried out by decreasing the temperature of the device where nematodes are trapped by placing a heat sink on top of the chip. We were able to perform periodic high-resolution microscopy of fluorescently tagged synapses located at the dorsal side of the nematode's tail throughout the worms' lifespan. To characterize the subtle phenotypes that emerge as nematodes age, computer vision was implemented to perform automated unbiased detection of synapses and quantitative analysis of aging-induced synaptic changes.

Deep phenotyping unveils hidden traits and genetic relations in subtle mutants.

Discovering mechanistic insights from phenotypic information is critical for the understanding of biological processes. For model organisms, unlike in cell culture, this is currently bottlenecked by the non-quantitative nature and perceptive biases of human observations, and the limited number of reporters that can be simultaneously incorporated in live animals. An additional challenge is that isogenic populations exhibit significant phenotypic heterogeneity. These difficulties limit genetic approaches to many biological questions. To overcome these bottlenecks, we developed tools to extract complex phenotypic traits from images of fluorescently labelled subcellular landmarks, using C. elegans synapses as a test case. By population-wide comparisons, we identified subtle but relevant differences inaccessible to subjective conceptualization. Furthermore, the models generated testable hypotheses of how individual alleles relate to known mechanisms or belong to new pathways. We show that our model not only recapitulates current knowledge in synaptic patterning but also identifies novel alleles overlooked by traditional methods.

Widespread macromolecular interaction perturbations in human genetic disorders.

How disease-associated mutations impair protein activities in the context of biological networks remains mostly undetermined. Although a few renowned alleles are well characterized, functional information is missing for over 100,000 disease-associated variants. Here we functionally profile several thousand missense mutations across a spectrum of Mendelian disorders using various interaction assays. The majority of disease-associated alleles exhibit wild-type chaperone binding profiles, suggesting they preserve protein folding or stability. While common variants from healthy individuals rarely affect interactions, two-thirds of disease-associated alleles perturb protein-protein interactions, with half corresponding to "edgetic" alleles affecting only a subset of interactions while leaving most other interactions unperturbed. With transcription factors, many alleles that leave protein-protein interactions intact affect DNA binding. Different mutations in the same gene leading to different interaction profiles often result in distinct disease phenotypes. Thus disease-associated alleles that perturb distinct protein activities rather than grossly affecting folding and stability are relatively widespread.

An automated programmable platform enabling multiplex dynamic stimuli delivery and cellular response monitoring for high-throughput suspension single-cell signaling studies.

Cell signaling events are orchestrated by dynamic external biochemical cues. By rapidly perturbing cells with dynamic inputs and examining the output from these systems, one could study the structure and dynamic properties of a cellular signaling network. Conventional experimental techniques limit the implementation of these systematic approaches due to the lack of sophistication in manipulating individual cells and the fluid microenvironment around them; existing microfluidic technologies thus far are mainly targeting adherent cells. In this paper we present an automated platform to interrogate suspension cells with dynamic stimuli while simultaneously monitoring cellular responses in a high-throughput manner at single-cell resolution. We demonstrate the use of this platform in an experiment to measure Jurkat T cells in response to distinct dynamic patterns of stimuli; we find cells exhibit highly heterogeneous responses under each stimulation condition. More interestingly, these cells act as low-pass filters, only entrained to the low frequency stimulus signals. We also demonstrate that this platform can be easily programmed to actively generate arbitrary dynamic signals. We envision our platform to be useful in other contexts to study cellular signaling dynamics, which may be difficult using conventional experimental methods.