Microelectrode Arrays Measure Blocking of Voltage-Gated Calcium Ion Channels on Supported Lipid Bilayers Derived from Primary Neurons.

Drug studies targeting neuronal ion channels are crucial to understand neuronal function and develop therapies for neurological diseases. The traditional method to study neuronal ion-channel activities heavily relies on the whole-cell patch clamp as the industry standard. However, this technique is both technically challenging and labour-intensive, while involving the complexity of keeping cells alive with low throughput. Therefore, the shortcomings are limiting the efficiency of ion-channel-related neuroscience research and drug testing. Here, this work reports a new system of integrating neuron membranes with organic microelectrode arrays (OMEAs) for ion-channel-related drug studies. This work demonstrates that the supported lipid bilayers (SLBs) derived from both neuron-like (neuroblastoma) cells and primary neurons are integrated with OMEAs for the first time. The increased expression of voltage-gated calcium (CaV) ion channels on differentiated SH-SY5Y SLBs  compared to non-differentiated ones is sensed electrically. Also, dose-response of the CaV ion-channel blocking effect on primary cortical neuronal SLBs from rats is monitored. The dose range causing ion channel blocking is comparable to literature. This system overcomes the major challenges from traditional methods (e.g., patch clamp) and showcases an easy-to-test, rapid, ultra-sensitive, cell-free, and high-throughput platform to monitor dose-dependent ion-channel blocking effects on native neuronal membranes.

High-throughput functional trait testing for bacterial pathogens.

Functional traits are characteristics that affect the fitness and metabolic function of a microorganism. There is growing interest in using high-throughput methods to characterize bacterial pathogens based on functional virulence traits. Traditional methods that phenotype a single organism for a single virulence trait can be time consuming and labor intensive. Alternatively, machine learning of whole-genome sequences (WGS) has shown some success in predicting virulence. However, relying solely on WGS can miss functional traits, particularly for organisms lacking classical virulence factors. We propose that high-throughput assays for functional virulence trait identification should become a prominent method of characterizing bacterial pathogens on a population scale. This work is critical as we move from compiling lists of bacterial species associated with disease to pathogen-agnostic approaches capable of detecting novel microbes. We discuss six key areas of functional trait testing and how advancing high-throughput methods could provide a greater understanding of pathogens.

Engineering Citrobacter freundii using CRISPR/Cas9 system.

The CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR associated proteins) system is a useful tool to edit genomes quickly and efficiently. However, the use of CRISPR/Cas9 to edit bacterial genomes has been limited to select microbial chassis primarily used for bioproduction of high value products. Thus, expansion of CRISPR/Cas9 tools to other microbial organisms is needed. Here, our aim was to assess the suitability of CRISPR/Cas9 for genome editing of the Citrobacter freundii type strain ATCC 8090. We evaluated the commonly used two plasmid pCas/pTargetF system to enable gene deletions and insertions in C. freundii and determined editing efficiency. The CRISPR/Cas9 based method enabled high editing efficiency (~91%) for deletion of galactokinase (galk) and enabled deletion with various single guide RNA (sgRNA) sequences. To assess the ability of CRISPR/Cas9 tools to insert genes, we used the fluorescent reporter mNeonGreen, an endopeptidase (yebA), and a transcriptional regulator (xylS) and found successful insertion with high efficiency (81-100%) of each gene individually. These results strengthen and expand the use of CRISPR/Cas9 genome editing to C. freundii as an additional microbial chassis.

Engineered Cell Line Imaging Assay Differentiates Pathogenic from Non-Pathogenic Bacteria.

Cell culture systems have greatly expanded our understanding of how bacterial pathogens target signaling pathways to manipulate the host and cause infection. Advances in genetic engineering have allowed for the creation of fluorescent protein readouts within signaling pathways, but these techniques have been underutilized in pathogen biology. Here, we genetically engineered a lung cell line with fluorescent reporters for extracellular signal-related kinase (ERK) and the downstream transcription factor FOS-related antigen 1 (Fra1) and evaluated signaling after inoculation with pathogenic and non-pathogenic bacteria. Cells were inoculated with 100 colony-forming units of Acinetobacter baylyi, Klebsiella pneumoniae, Pseudomonas aeruginosa, Streptococcus agalactiae, or Staphylococcus epidermidis and imaged in a multi-mode reader. The alamarBlue cell viability assay was used as a reference test and showed that pathogenic P. aeruginosa induced significant (p < 0.05) cell death after 8 h in both wild-type and engineered cell lines compared to non-pathogenic S. epidermidis. In engineered cells, we found that Fra1 signaling was disrupted in as little as 4 h after inoculation with bacterial pathogens compared to delayed disruption in signaling by non-pathogenic S. epidermidis. Overall, we demonstrate that low levels of pathogenic versus non-pathogenic bacteria can be rapidly and sensitively screened based on ERK-Fra1 signaling.

Complete Genome Sequence of the Citrobacter freundii Type Strain.

Citrobacter freundii is a species of facultative anaerobic Gram-negative bacteria of the family Enterobacteriaceae The complete genome is composed of a single chromosomal circle of 4,957,773 bp with a G+C content of 52%.

A proteome-wide assessment of the oxidative stress paradigm for metal and metal-oxide nanomaterials in human macrophages.

Responsible implementation of engineered nanomaterials (ENMs) into commercial applications is an important societal issue, driving demand for new approaches for rapid and comprehensive evaluation of their bioactivity and safety. An essential part of any research focused on identifying potential hazards of ENMs is the appropriate selection of biological endpoints to evaluate. Herein, we use a tiered strategy employing both targeted biological assays and untargeted quantitative proteomics to elucidate the biological responses of human THP-1 derived macrophages across a library of metal/metal oxide ENMs, raised as priority ENMs for investigation by NIEHS's Nanomaterial Health Implications Research (NHIR) program. Our results show that quantitative cellular proteome profiles readily distinguish ENM types based on their cytotoxic potential according to induction of biological processes and pathways involved in the cellular antioxidant response, TCA cycle, oxidative stress, endoplasmic reticulum stress, and immune responses as major processes impacted. Interestingly, bioinformatics analysis of differentially expressed proteins also revealed new biological processes that were influenced by all ENMs independent of their cytotoxic potential. These included biological processes that were previously implicated as mechanisms cells employ as adaptive responses to low levels of oxidative stress, including cell adhesion, protein translation and protein targeting. Unsupervised clustering revealed the most striking proteome changes that differentiated ENM classes highlight a small subset of proteins involved in the oxidative stress response (HMOX1), protein chaperone functions (HS71B, DNJB1), and autophagy (SQSTM), providing a potential new panel of markers of ENM-induced cellular stress. To our knowledge, the results represent the most comprehensive profiling of the biological responses to a library of ENMs conducted using quantitative mass spectrometry-based proteomics. The results provide a basis to identify the patterns of a diverse set of cellular pathways and biological processes impacted by ENM exposure in an important immune cell type, laying the foundation for multivariate, pathway-level structure activity assessments of ENMs in the future.

An integrated experimental-computational approach for predicting virulence in New Zealand white rabbits and humans following inhalation exposure to Bacillus anthracis spores.

Inhalation of Bacillus anthracis spores can lead to an anthrax infection that can be fatal. Previously published mathematical models have extrapolated kinetic rates associated with bacterial growth in New Zealand White (NZW) rabbits to humans, but to date, actual measurements of the underlying processes associated with anthrax virulence between species have not been conducted. To address this knowledge gap, we have quantified species-specific rate constants associated with germination, proliferation, and immune cell inactivation of B. anthracis Sterne using an in vitro test platform that includes primary lung epithelial and immune cells. The generated data was then used to develop a physiologically based biokinetic model (PBBK) which quantitatively compares bacterial growth and mean time to death under lethal conditions in rabbits and humans. Simulations based upon our in vitro data and previously published in vivo data from rabbits indicate that disease progression is likely to be faster in humans than in NZW rabbits under comparable total deposited dose conditions. With the computational framework established, PBBK parameters can now be refined using experimental data for lethal B. anthracis strains (e.g. Ames) under identical conditions in future studies. The PBBK model can also be linked to existing aerosol dosimetry models that account for species-specific differences in aerosol deposition patterns to further improve the human health risk assessment of inhalation anthrax.

Targeted Quantification of Phosphorylation Dynamics in the Context of EGFR-MAPK Pathway.

Large-scale phosphoproteomics with coverage of over 10,000 sites of phosphorylation have now been routinely achieved with advanced mass spectrometry (MS)-based workflows. However, accurate targeted MS-based quantification of phosphorylation dynamics, an important direction for gaining quantitative understanding of signaling pathways or networks, has been much less investigated. Herein, we report an assessment of the targeted workflow in the context of signal transduction pathways, using the epidermal growth factor receptor (EGFR)-mitogen-activated protein kinase (MAPK) pathway as our model. A total of 43 phosphopeptides from the EGFR-MAPK pathway were selected for the study. The recovery and sensitivity of two commonly used enrichment methods, immobilized metal affinity chromatography (IMAC) and titanium oxide (TiO2), combined with selected reaction monitoring (SRM)-MS were evaluated. The recovery of phosphopeptides by IMAC and TiO2 enrichment was quantified to be 38 ± 5% and 58 ± 20%, respectively, based on internal standards. Moreover, both enrichment methods provided comparable sensitivity from 1 to 100 µg starting peptides. Robust quantification was consistently achieved for most targeted phosphopeptides when starting with 25-100 µg peptides. However, the numbers of quantified targets significantly dropped when peptide samples were in the 1-25 µg range. Finally, IMAC-SRM was applied to quantify signaling dynamics of EGFR-MAPK pathway in Hs578T cells following 10 ng/mL EGF treatment. The kinetics of phosphorylation clearly revealed early and late phases of phosphorylation, even for very low abundance proteins. These results demonstrate the feasibility of robust targeted quantification of phosphorylation dynamics for specific pathways, even starting with relatively small amounts of protein.

Evaluating Composite Sampling Methods of Bacillus Spores at Low Concentrations.

Restoring all facility operations after the 2001 Amerithrax attacks took years to complete, highlighting the need to reduce remediation time. Some of the most time intensive tasks were environmental sampling and sample analyses. Composite sampling allows disparate samples to be combined, with only a single analysis needed, making it a promising method to reduce response times. We developed a statistical experimental design to test three different composite sampling methods: 1) single medium single pass composite (SM-SPC): a single cellulose sponge samples multiple coupons with a single pass across each coupon; 2) single medium multi-pass composite: a single cellulose sponge samples multiple coupons with multiple passes across each coupon (SM-MPC); and 3) multi-medium post-sample composite (MM-MPC): a single cellulose sponge samples a single surface, and then multiple sponges are combined during sample extraction. Five spore concentrations of Bacillus atrophaeus Nakamura spores were tested; concentrations ranged from 5 to 100 CFU/coupon (0.00775 to 0.155 CFU/cm2). Study variables included four clean surface materials (stainless steel, vinyl tile, ceramic tile, and painted dry wallboard) and three grime coated/dirty materials (stainless steel, vinyl tile, and ceramic tile). Analysis of variance for the clean study showed two significant factors: composite method (p< 0.0001) and coupon material (p = 0.0006). Recovery efficiency (RE) was higher overall using the MM-MPC method compared to the SM-SPC and SM-MPC methods. RE with the MM-MPC method for concentrations tested (10 to 100 CFU/coupon) was similar for ceramic tile, dry wall, and stainless steel for clean materials. RE was lowest for vinyl tile with both composite methods. Statistical tests for the dirty study showed RE was significantly higher for vinyl and stainless steel materials, but lower for ceramic tile. These results suggest post-sample compositing can be used to reduce sample analysis time when responding to a Bacillus anthracis contamination event of clean or dirty surfaces.

Coregulation of Terpenoid Pathway Genes and Prediction of Isoprene Production in Bacillus subtilis Using Transcriptomics.

The isoprenoid pathway converts pyruvate to isoprene and related isoprenoid compounds in plants and some bacteria. Currently, this pathway is of great interest because of the critical role that isoprenoids play in basic cellular processes, as well as the industrial value of metabolites such as isoprene. Although the regulation of several pathway genes has been described, there is a paucity of information regarding system level regulation and control of the pathway. To address these limitations, we examined Bacillus subtilis grown under multiple conditions and determined the relationship between altered isoprene production and gene expression patterns. We found that with respect to the amount of isoprene produced, terpenoid genes fall into two distinct subsets with opposing correlations. The group whose expression levels positively correlated with isoprene production included dxs, which is responsible for the commitment step in the pathway, ispD, and two genes that participate in the mevalonate pathway, yhfS and pksG. The subset of terpenoid genes that inversely correlated with isoprene production included ispH, ispF, hepS, uppS, ispE, and dxr. A genome-wide partial least squares regression model was created to identify other genes or pathways that contribute to isoprene production. These analyses showed that a subset of 213 regulated genes was sufficient to create a predictive model of isoprene production under different conditions and showed correlations at the transcriptional level. We conclude that gene expression levels alone are sufficiently informative about the metabolic state of a cell that produces increased isoprene and can be used to build a model that accurately predicts production of this secondary metabolite across many simulated environmental conditions.