As we seek to recognize the opportunities of advanced aerospace technologies and spaceflight, it is increasingly important to understand the impacts of hypergravity, defined as gravitational forces greater than those present on the earth's surface. The nematode Caenorhabditis elegans has been established as a powerful model to study the effects of altered gravity regimens and has displayed remarkable resilience to space travel. In this study, we investigate the effects of short-term and defined hypergravity exposure on C. elegans motility, brood size, pharyngeal pumping rates, and lifespan. The results from this study advance our understanding of the effects of shorter durations of exposure to increased gravitational forces on C. elegans, and also contribute to the growing body of literature on the impacts of altered gravity regimens on earth's life forms. less

Neuronal modeling of patch-clamp data is based on approximations which are valid under specific assumptions regarding cell properties and morphology. Certain cells, which show a biexponential capacitance transient decay, can be modeled with a two-compartment model. However, for parameter-extraction in such a model, approximations are required regarding the relative sizes of the various model parameters. These approximations apply to certain cell types or experimental conditions and are not valid in the general case. In this paper, we present a general method for the extraction of the parameters in a two-compartment model without assumptions regarding the relative size of the parameters. All the passive electrical parameters of the two-compartment model are derived in terms of the available experimental data. The experimental data is obtained from a DC measurement (where the command potential is a hyperpolarizing DC voltage) and an AC measurement (where the command potential is a sinusoidal stimulus on a hyperpolarized DC potential) performed on the cell under test. Computer simulations are performed with a circuit simulator, XSPICE, to observe the effects of varying the two-compartment model parameters on the capacitive transients of the current response. Our general solution for the parameter-estimation of a two-compartment model may be used to model any neuron, which has a biexponential capacitive current decay. In addition, our model avoids the need for simplifying and perhaps erroneous approximations. Our equations may be easily implemented in hardware/software compensation schemes to correct the recorded currents for any series resistance or capacitive transient errors. Our general solution reduces to the results of previous researchers under their approximations. less

We report a nematode electrotactic-response valve (NERV) to control the locomotion of Caenorhabditis elegans (C. elegans) in microfluidic devices. This nonmechanical, unidirectional valve is based on creating a confined region of lateral electric field that is switchable and reversible. We observed that C. elegans do not prefer to pass through this region if the field lines are incident to its forward movement. Upon reaching the boundary of the NERV, the incident worms partially penetrate the field region, pull back, and turn around. The NERV is tested on three C. elegans mutants: wild-type (N2), lev-8, and acr-16. less

This paper describes a new microfluidic platform for screening drugs and their dose response on the locomotion behavior of free living nematodes and parasitic nematodes. The system offers a higher sensitivity drug screening chip which employs a combination of existing and newly developed methods. Real-time observation of the entire drug application process (i.e. the innate pre-exposure locomotion, the transient response during drug exposure and the time-resolved, post-exposure behavior) at a single worm resolution is made possible. The chip enables the monitoring of four nematode parameters (number of worms responsive, number of worms leaving the drug well, average worm velocity and time until unresponsiveness). Each parameter generates an inherently different dose response; allowing for a higher resolution when screening for resistance. We expect this worm chip could be used as a robust cross species, cross drug platform. Existing nematode motility and migration assays do not offer this level of sophistication. The device comprises two principal components: behavioral microchannels to study nematode motility and a drug well for administering the dose and observing drug effects as a function of exposure time. The drug screening experiment can be described by three main steps: (i) 'pre-exposure study' - worms are inserted into the behavioral channels and their locomotion is characterized, (ii) 'dose exposure' - worms are guided from the behavioral microchannels into the drug well and held for a predefined time, during which time their transient response to the dose is characterized and (iii) 'post-exposure study' - worms are guided back into the behavioral microchannels where their locomotion (i.e. their time-resolved response to the dose) is characterized and compared to pre-exposure motility. The direction of nematodes' movement is reliably controlled by the application of an electric field within a defined range. Control experiments (e.g. in the absence of any drug) confirm that the applied electric fields do not affect the worms' motility or viability. We demonstrate the workability of the microfluidic platform on free living Caenorhabditis elegans (wild-type N2 and levamisole resistant ZZ15 lev-8) and parasitic Oesophagotomum dentatum (levamisole-sensitive, SENS and levamisole-resistant, LEVR) using levamisole (a well-studied anthelmintic) as the test drug. The proposed scheme of drug screening on a microfluidic device is expected to significantly improve the resolution, sensitivity and data throughput of in vivo testing, while offering new details on the transient and time-resolved exposure effects of new and existing anthelmintics. less

We present a movement-based assay to observe adaptability in Caenorhabditis elegans locomotion behavior. The assay comprises a series of sinusoidal microchannels with a fixed wavelength and modulating (increasing or decreasing) amplitude. The channel width is comparable to the body diameter of the organism. Worms are allowed to enter the channel from the input port and migrate toward the output port. Within channel sections that closely match the worm’s natural undulations, the worm movement is relatively quick and steady. As the channel amplitude increases or decreases along the device, the worm faces difficulty in generating the propulsive thrust, begins to slow down and eventually fails to move forward. A set of locomotion parameters (i.e., average forward velocity, number and duration of stops, range of contact angle, and cut-off region) is defined for worm locomotion in modulated sinusoidal channels and extracted from the recorded videos. The device is tested on wild-type C. elegans (N2) and two mutants (lev-8 and unc-38). We anticipate this passive, movement-based assay can be used to screen nematodes showing difference in locomotion phenotype. ACKNOWLEDGMENT less

The ability to study bacteria at the single cell level has advanced our insights into microbial physiology and genetics in ways not attainable by studying large populations using more traditional culturing methods. To improve methods to characterize bacteria at the cellular level, we developed a new microfluidic platform that enables cells to be exposed to metabolites in a gradient of concentrations. By designing low-cost, three-dimensional devices with adhesive tapes and tailoring them for bacterial imaging, we avoided the complexities of silicon and polymeric microfabrication. The incorporation of an agarose membrane as the resting substrate, along with a temperature-controlled environmental chamber, allows the culturing of bacterial cells for over 10 h under stable growth or inhibition conditions. Incorporation of an autofocusing module helped the uninterrupted, high-resolution observation of bacteria at the single-cell and at low density population levels. We used the microfluidic platform to record morphological changes in Escherichia coli during ampicillin exposure and to quantify the minimum inhibitory concentration of the antibiotic. We further demonstrated the potential of finely-tuned, incremental gene regulation in a concentration gradient utilizing CRISPR interference (CRISPRi). These low-cost engineering tools, when implemented in combination with genetic approaches such as CRISPRi, should prove useful to uncover new genetic determinants of antibiotic susceptibility and evaluate the long-term effectiveness of antibiotics in bacterial cultures. less

The soybean cyst nematode (SCN), Heterodera glycines, is the most damaging pathogen of soybeans in the United States. To assess the severity of nematode infestations in the field, SCN egg population densities are determined. Cysts (dead females) of the nematode must be extracted from soil samples and then ground to extract the eggs within. Sucrose centrifugation commonly is used to separate debris from suspensions of extracted nematode eggs. We present a method using OptiPrep as a density gradient medium with improved separation and recovery of extracted eggs compared to the sucrose centrifugation technique. Also, computerized methods were developed to automate the identification and counting of nematode eggs from the processed samples. In one approach, a high-resolution scanner was used to take static images of extracted eggs and debris on filter papers, and a deep learning network was trained to identify and count the eggs among the debris. In the second approach, a lensless imaging setup was developed using off-the-shelf components, and the processed egg samples were passed through a microfluidic flow chip made from double-sided adhesive tape. Holographic videos were recorded of the passing eggs and debris, and the videos were reconstructed and processed by custom software program to obtain egg counts. The performance of the software programs for egg counting was characterized with SCN-infested soil collected from two farms, and the results using these methods were compared with those obtained through manual counting. https://doi.org/10.1371/journal.pone.0223386 less

With increasing resistance to anti-parasitic drugs, it has become more important to detect and recognize phenotypes of resistant isolates. Molecular methods of detecting resistant isolates are limited at present. Here, we introduce a microfluidic bioassay to measure phenotype using parameters of nematode locomotion. We illustrate the technique on larvae of an animal parasite Oesophagostomum dentatum. Parameters of sinusoidal motion such as propagation velocity, wavelength, wave amplitude, and oscillation frequency depended on the levamisole-sensitivity of the isolate of parasitic nematode. The levamisole-sensitive isolate (SENS) had a mean wave amplitude of 135 μm, which was larger than 123 μm of the levamisole-resistant isolate (LEVR). SENS had a mean wavelength of 373 μm, which was less than 393 μm of LEVR. The mean propagation velocity of SENS, 149 μm s-1, was similar to LEVR, 143 μm s-1. The propagation velocity of the isolates was inhibited by levamisole in a concentration-dependent manner above 0.5 μm. The EC50 for SENS was 3 μm and the EC50 for LEVR was 10 μm. This microfluidic technology advances present-day nematode migration assays and provides a better quantification and increased drug sensitivity. It is anticipated that the bioassay will facilitate study of resistance to other anthelmintic drugs that affect locomotion. Figures less

Precision swine production can benefit from autonomous, noninvasive, and affordable devices that conduct frequent checks on the well-being status of pigs. Here, we present a remote monitoring tool for the objective measurement of some behavioral indicators that may help in assessing the health and welfare status—namely, posture, gait, vocalization, and external temperature. The multiparameter electronic sensor board is characterized by laboratory measurements and by animal tests. Relevant behavioral health indicators are discussed for implementing machine learning algorithms and decision support tools to detect animal lameness, lethargy, pain, injury, and distress. The roadmap for technology adoption is also discussed, along with challenges and the path forward. The presented technology can potentially lead to efficient management of farm animals, targeted focus on sick animals, medical cost savings, and less use of antibiotics. less

Neuronal modeling of patch-clamp data is based on approximations which are valid under specific assumptions regarding cell properties and morphology. Certain cells, which show a biexponential capacitance transient decay, can be modeled with a two-compartment model. However, for parameter-extraction in such a model, approximations are required regarding the relative sizes of the various model parameters. These approximations apply to certain cell types or experimental conditions and are not valid in the general case. In this paper, we present a general method for the extraction of the parameters in a two-compartment model without assumptions regarding the relative size of the parameters. All the passive electrical parameters of the two-compartment model are derived in terms of the available experimental data. The experimental data is obtained from a DC measurement (where the command potential is a hyperpolarizing DC voltage) and an AC measurement (where the command potential is a sinusoidal stimulus on a hyperpolarized DC potential) performed on the cell under test. Computer simulations are performed with a circuit simulator, XSPICE, to observe the effects of varying the two-compartment model parameters on the capacitive transients of the current response. Our general solution for the parameter-estimation of a two-compartment model may be used to model any neuron, which has a biexponential capacitive current decay. In addition, our model avoids the need for simplifying and perhaps erroneous approximations. Our equations may be easily implemented in hardware/software compensation schemes to correct the recorded currents for any series resistance or capacitive transient errors. Our general solution reduces to the results of previous researchers under their approximations. less

Published literature has shown conflicting results regarding the effects of magnetic fields on the fermentation kinetics or cellular growth of various Saccharomyces cerevisiae strains. Here, two sets of experiments were conducted to characterize the role of magnetic fields on cell growth and ethanol production during fermentation. The first experiment was completed for 25 h at a 2% dextrose loading rate under influence of homogeneous and non-homogeneous static magnetic fields on the order of 100 and 200 mT, respectively. The second experiment was completed for 30 h at a 6% dextrose loading rate under the influence of a non-homogeneous static magnetic field on the order of 200 mT. It was found that homogeneous magnetic fields have no significant effect on the yeast cell growth, while non-homogeneous static magnetic fields produced an increase (~ 8% over the control) in peak ethanol concentration with 2% dextrose loading. less

Today, the area of point-of-care diagnostics is synonymous with paper microfluidics where cheap, disposable, and on-the-spot detection toolkits are being developed for a variety of chemical tests. In this work, we present a novel application of microfluidic paper-based analytical devices (microPADs) to study the behavior of a small model nematode, Caenorhabditis elegans. We describe schemes of microPAD fabrication on paper and plastic substrates where membranes are created in agarose and Pluronic gel. Methods are demonstrated for loading, visualizing, and transferring single and multiple nematodes. Using an anthelmintic drug, levamisole, we show that chemical testing on C. elegans is easily performed because of the open device structure. A custom program is written to automatically recognize individual worms on the microPADs and extract locomotion parameters in real-time. The combination of microPADs and the nematode tracking program provides a relatively low-cost, simple-to-fabricate imaging and screening assay (compared to standard agarose plates or polymeric microfluidic devices) for non-microfluidic, nematode laboratories. less

A hallmark of bacterial populations cultured in vitro is their homogeneity of growth, where the majority of cells display identical growth rate, cell size and content. Recent insights, however, have revealed that even cells growing in exponential growth phase can be heterogeneous with respect to variables typically used to measure cell growth. Bacterial heterogeneity has important implications for how bacteria respond to environmental stresses, such as antibiotics. The phenomenon of antimicrobial persistence, for example, has been linked to a small subpopulation of cells that have entered into a state of dormancy where antibiotics are no longer effective. While methods have been developed for identifying individual non-growing cells in bacterial cultures, there has been less attention paid to how these cells may influence growth in colonies on a solid surface. In response, we have developed a low-cost, open-source platform to perform automated image capture and image analysis of bacterial colony growth on multiple nutrient agar plates simultaneously. The descriptions of the hardware and software are included, along with details about the temperature-controlled growth chamber, high-resolution scanner, and graphical interface to extract and plot the colony lag time and growth kinetics. Experiments were conducted using a wild type strain of Escherichia coli K12 to demonstrate the feasibility and operation of our setup. By automated tracking of bacterial growth kinetics in colonies, the system holds the potential to reveal new insights into understanding the impact of microbial heterogeneity on antibiotic resistance and persistence. Pandey S, Park Y, Ankita A, Phillips GJ. Scan4CFU: Low-cost, open-source bacterial colony tracking over large areas and extended incubation times. HardwareX. 2021 Nov 25;10:e00249. doi: 10.1016/j.ohx.2021.e00249. PMID: 35607694; PMCID: PMC9123444. less

Soybeans are an important crop for global food security. Every year, soybean yields are reduced by numerous soybean diseases, particularly the soybean cyst nematode (SCN). It is difficult to visually identify the presence of SCN in the field, let alone its population densities or numbers, as there are no obvious aboveground disease symptoms. The only definitive way to assess SCN population densities is to directly extract the SCN cysts from soil and then extract the eggs from cysts and count them. Extraction is typically conducted in commercial soil analysis laboratories and university plant diagnostic clinics and involves repeated steps of sieving, washing, collecting, grinding, and cleaning. Here we present a robotic instrument to reproduce and automate the functions of the conventional methods to extract nematode cysts from soil and subsequently extract eggs from the recovered nematode cysts. We incorporated mechanisms to actuate the stage system, manipulate positions of individual sieves using the gripper, recover cysts and cyst-sized objects from soil suspended in water, and grind the cysts to release their eggs. All system functions are controlled and operated by a touchscreen interface software. The performance of the robotic instrument is evaluated using soil samples infested with SCN from two farms at different locations and results were comparable to the conventional technique. Our new technology brings the benefits of automation to SCN soil diagnostics, a step towards long-term integrated pest management of this serious soybean pest. less

Environmental toxicants influence development, behavior, and ultimately survival. The nematode Caenorhabditis elegans has proven to be an exceptionally powerful model for toxicological studies. Here, we develop novel technologies to describe the effects of cyanide toxicity with high spatiotemporal resolution. Importantly, we use these methods to examine the genetic underpinnings of cyanide resistance. Caenorhabditis elegans that lack the EGL-9 oxygen sensing enzyme have been shown to be resistant to hydrogen cyanide (HCN) gas produced by the pathogen Pseudomonas aeruginosa PAO1. We demonstrate that the cyanide resistance exhibited by egl-9 mutants is completely dependent on the HIF-1 hypoxiainducible factor and is mediated by the cysl-2 cysteine synthase, which likely functions in metabolic pathways that inactivate cyanide. Further, the expression of cysl-2 correlates with the degree of cyanide resistance exhibited in each genetic background. We find that each mutant exhibits similar relative resistance to HCN gas on plates or to aqueous potassium cyanide in microfluidic chambers. The design of the microfluidic devices, in combination with real-time imaging, addresses a series of challenges presented by mutant phenotypes and by the chemical nature of the toxicant. The microfluidic assay produces a set of behavioral parameters with increased resolution that describe cyanide toxicity and resistance in C. elegans, and this is particularly useful in analyzing subtle phenotypes. These multiparameter analyses of C. elegans behavior hold great potential as a means to monitor the effects of toxicants or chemical interventions in real time and to study the biological networks that underpin toxicant resistance. © The Author 2013. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. less

New combinations of existing antibiotics are being investigated to combat bacterial resilience. This requires detection technologies with reasonable cost, accuracy, resolution, and throughput. Here, we present a multi -drug screening platform for bacterial cultures by combining droplet microfluidics, search algorithms, and imaging with a wide field of view. We remotely alter the chemical microenvironment around cells and test 12 combinations of resistant cell types and chemicals. Fluorescence intensity readouts allow us to infer bacterial resistance to specific antibiotics within 8 hours. The platform has potential to detect and identify parameters of bacterial resilience in cell cultures, biofilms, and microbial aggregates. https://doi.org/10.1109/Transducers50396.2021.9495667 less

Infections from parasitic nematodes (or roundworms) contribute to a significant disease burden and productivity losses for humans and livestock. The limited number of anthelmintics (or antinematode drugs) available today to treat these infections are rapidly losing their efficacy as multidrug resistance in parasites becomes a global health challenge. We propose an engineering approach to discover an anthelmintic drug combination that is more potent at killing wild-type Caenorhabditis elegans worms than four individual drugs. In the experiment, freely swimming single worms are enclosed in microfluidic drug environments to assess the centroid velocity and track curvature of worm movements. After analyzing the behavioral data in every iteration, the feedback system control (FSC) scheme is used to predict new drug combinations to test. Through a differential evolutionary search, the winning drug combination is reached that produces minimal centroid velocity and high track curvature, while requiring each drug in less than their EC50 concentrations. The FSC approach is model-less and does not need any information on the drug pharmacology, signaling pathways, or animal biology. Toward combating multidrug resistance, the method presented here is applicable to the discovery of new potent combinations of available anthelmintics on C. elegans, parasitic nematodes, and other small model organisms. https://doi.org/10.1126/sciadv.aao1254 less