SLC38A10 Deficiency in Mice Affects Plasma Levels of Threonine and Histidine in Males but Not in Females: A Preliminary Characterization Study of SLC38A10-/- Mice.

Solute carriers belong to the biggest group of transporters in the human genome, but more knowledge is needed to fully understand their function and possible role as therapeutic targets. SLC38A10, a poorly characterized solute carrier, is preliminary characterized here. By using a knockout mouse model, we studied the biological effects of SLC38A10 deficiency in vivo. We performed a transcriptomic analysis of the whole brain and found seven differentially expressed genes in SLC38A10-deficient mice (Gm48159, Nr4a1, Tuba1c, Lrrc56, mt-Tp, Hbb-bt and Snord116/9). By measuring amino acids in plasma, we found lower levels of threonine and histidine in knockout males, whereas no amino acid levels were affected in females, suggesting that SLC38A10-/- might affect sexes differently. Using RT-qPCR, we investigated the effect of SLC38A10 deficiency on mRNA expression of other SLC38 members, Mtor and Rps6kb1 in the brain, liver, lung, muscle, and kidney, but no differences were found. Relative telomere length measurement was also taken, as a marker for cellular age, but no differences were found between the genotypes. We conclude that SLC38A10 might be important for keeping amino acid homeostasis in plasma, at least in males, but no major effects were seen on transcriptomic expression or telomere length in the whole brain.

Diacylglycerol, PKC and MAPK signaling initiate tubeworm metamorphosis in response to bacteria.

External environmental cues can have significant impacts on the timing and outcomes of animal development. For the swimming larvae of many marine invertebrates, the presence of specific surface-bound bacteria are important cues that help larvae identify a suitable location on the sea floor for metamorphosis and adult life. While metamorphosis in response to bacteria occurs in diverse animals from across the animal tree of life, we know little about the signal transduction cascades stimulated at the onset of metamorphosis upon their interaction with bacteria. The metamorphosis of a model tubeworm, Hydroides elegans, is triggered by the bacterium Pseudoalteromonas luteoviolacea which produces a stimulatory protein called Mif1. In this work, we define three key nodes in a signaling cascade promoting Hydroides metamorphosis in response to Mif1. Using metabolomic profiling, we find that the stimulation of Hydroides larvae by P. luteoviolacea leads to an increase in diacylglycerol during the initiation of metamorphosis, and that Mif1 is necessary for this upregulation. Genomic and pharmacological examination suggests that diacylglycerol triggers a phosphotransferase signaling cascade involving Protein Kinase C (PKC) and Mitogen-Activated Protein Kinase (MAPK), to induce Hydroides metamorphosis. Additionally, Mif1 activates the expression of two nuclear hormone receptors, HeNHR1 and HeNHR2 in the cerebral ganglia of Hydroides larvae. Our results define a post-translational signal transduction pathway mediating bacteria-stimulated metamorphosis in a model invertebrate animal.

Treatment with Bacterial Biologics Promotes Healthy Aging and Traumatic Brain Injury Responses in Adult Drosophila, Modeling the Gut-Brain Axis and Inflammation Responses.

Drosophila are widely used to study neural development, immunity, and inflammatory pathways and processes associated with the gut-brain axis. Here, we examine the response of adult Drosophila given an inactive bacteriologic (IAB; proprietary lysate preparation of Lactobacillus bulgaricus, ReseT®) and a probiotic (Lactobacillus rhamnosus, LGG). In vitro, the IAB activates a subset of conserved Toll-like receptor (TLR) and nucleotide-binding, oligomerization domain-containing protein (NOD) receptors in human cells, and oral administration slowed the age-related decline of adult Drosophila locomotor behaviors. On average, IAB-treated flies lived significantly longer (+23%) and had lower neural aggregate profiles. Different IAB dosages also improved locomotor function and longevity profiles after traumatic brain injury (TBI) exposure. Mechanistically, short-term IAB and LGG treatment altered baseline nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κß) signaling profiles in neural and abdominal tissues. Overall, at select dosages, IAB and LGG exposure has a positive impact on Drosophila longevity, neural aging, and mild traumatic brain injury (TBI)-related responses, with IAB showing greater benefit. This includes severe TBI (sTBI) responses, where IAB treatment was protective and LGG increased acute mortality profiles. This work shows that Drosophila are an effective model for testing bacterial-based biologics, that IAB and probiotic treatments promote neuronal health and influence inflammatory pathways in neural and immune tissues. Therefore, targeted IAB treatments are a novel strategy to promote the appropriate function of the gut-brain axis.

Differentiation of two human neuroblastoma cell lines alters SV2 expression patterns.

BACKGROUND: The synaptic vesicle glycoprotein 2 (SV2) family is essential to the synaptic machinery involved in neurotransmission and vesicle recycling. The isoforms SV2A, SV2B and SV2C are implicated in neurological diseases such as epilepsy, Alzheimer's and Parkinson's disease. Suitable cell systems for studying regulation of these proteins are essential. Here we present gene expression data of SV2A, SV2B and SV2C in two human neuroblastoma cell lines after differentiation. METHODS: Human neuroblastoma cell lines SiMa and IMR-32 were treated for seven days with growth supplements (B-27 and N-2), all-trans-retinoic acid (ATRA) or vasoactive intestinal peptide (VIP) and gene expression levels of SV2 and neuronal targets were analyzed. RESULTS: The two cell lines reacted differently to the treatments, and only one of the three SV2 isoforms was affected at a time. SV2B and choline O-acetyltransferase (CHAT) expression was changed in concert after growth supplement treatment, decreasing in SiMa cells while increasing in IMR-32. ATRA treatment resulted in no detected changes in SV2 expression in either cell line while VIP increased both SV2C and dopamine transporter (DAT) in IMR-32 cells. CONCLUSION: The synergistic expression patterns between SV2B and CHAT as well as between SV2C and DAT mirror the connectivity between these targets found in disease models and knock-out animals, although here no genetic alteration was made. These cell lines and differentiation treatments could possibly be used to study SV2 regulation and function.

Towards Predicting Gut Microbial Metabolism: Integration of Flux Balance Analysis and Untargeted Metabolomics.

Genomics-based metabolic models of microorganisms currently have no easy way of corroborating predicted biomass with the actual metabolites being produced. This study uses untargeted mass spectrometry-based metabolomics data to generate a list of accurate metabolite masses produced from the human commensal bacteria Citrobacter sedlakii grown in the presence of a simple glucose carbon source. A genomics-based flux balance metabolic model of this bacterium was previously generated using the bioinformatics tool PyFBA and phenotypic growth curve data. The high-resolution mass spectrometry data obtained through timed metabolic extractions were integrated with the predicted metabolic model through a program called MS_FBA. This program correlated untargeted metabolomics features from C. sedlakii with 218 of the 699 metabolites in the model using an exact mass match, with 51 metabolites further confirmed using predicted isotope ratios. Over 1400 metabolites were matched with additional metabolites in the ModelSEED database, indicating the need to incorporate more specific gene annotations into the predictive model through metabolomics-guided gap filling.

A Single δ9-Tetrahydrocannabinol (THC) Dose During Brain Development Affects Markers of Neurotrophy, Oxidative Stress, and Apoptosis.

δ9-tetrahydrocannabinol (THC) is one of the most used drugs during pregnancy and lactation and efficiently crosses the placental and blood-brain barriers. Despite the recent legalization initiatives worldwide, the adverse outcome pathway (AOP) of THC following exposure during brain development is incompletely understood. We have previously reported that a single injection of THC on postnatal day (PND) 10 altered adult spontaneous behavior and habituation rates in adult mice. Similar behavioral alterations have been reported following PND 10 exposure to the commonly used over-the-counter analgesic acetaminophen (AAP; also known as paracetamol); as both THC and AAP interact with the endocannabinoid system, we hypothesize that this system might be involved in the AOP of both these pharmaceuticals/drugs. Here, we report that a single THC dose on PND 10 decreased transcript levels of tropomyosin receptor kinase b (Trkb) 24 h after exposure in both the frontal and parietal cortex, and in the hippocampus in mice. An increase in the nuclear factor (erythroid-derived 2)-like 2 (Nrf2)/Kelch-like ECH-associated protein 1 (Keap1) ratio were also found in both the parietal cortex and hippocampus following neonatal exposure to THC. In addition, THC exposure increased transcript levels of cannabinoid receptor type 1 (Cb1r) in the parietal cortex and increased the apoptosis regulator BAX in the frontal cortex. This study is important for mainly 3 reasons: 1) we are starting to get information on the developmental neurotoxic AOP of PND 10 exposure to THC, where we suggest that transcriptional changes of the neurotrophic receptor Trkb are central, 2) our PND 10 exposure model provides information relevant to human exposure and 3) since PND 10 exposure to AAP also decreased Trkb transcript levels, we suggest THC and AAP may share key events in their respective AOP through endocannabinoid-mediated alterations of the brain-derived neurotrophic factor (BDNF)-TRKB signaling pathway.

A fiber-deprived diet disturbs the fine-scale spatial architecture of the murine colon microbiome.

Compartmentalization of the gut microbiota is thought to be important to system function, but the extent of spatial organization in the gut ecosystem remains poorly understood. Here, we profile the murine colonic microbiota along longitudinal and lateral axes using laser capture microdissection. We found fine-scale spatial structuring of the microbiota marked by gradients in composition and diversity along the length of the colon. Privation of fiber reduces the diversity of the microbiota and disrupts longitudinal and lateral gradients in microbiota composition. Both mucus-adjacent and luminal communities are influenced by the absence of dietary fiber, with the loss of a characteristic distal colon microbiota and a reduction in the mucosa-adjacent community, concomitant with depletion of the mucus layer. These results indicate that diet has not only global but also local effects on the composition of the gut microbiota, which may affect function and resilience differently depending on location.

Fluorinated Gold Nanoparticles for Nanostructure Imaging Mass Spectrometry.

Nanostructure imaging mass spectrometry (NIMS) with fluorinated gold nanoparticles (f-AuNPs) is a nanoparticle assisted laser desorption/ionization approach that requires low laser energy and has demonstrated high sensitivity. Here we describe NIMS with f-AuNPs for the comprehensive analysis of metabolites in biological tissues. F-AuNPs assist in desorption/ionization by laser-induced release of the fluorocarbon chains with minimal background noise. Since the energy barrier required to release the fluorocarbons from the AuNPs is minimal, the energy of the laser is maintained in the low µJ/pulse range, thus limiting metabolite in-source fragmentation. Electron microscopy analysis of tissue samples after f-AuNP NIMS shows a distinct "raising" of the surface as compared to matrix assisted laser desorption ionization ablation, indicative of a gentle desorption mechanism aiding in the generation of intact molecular ions. Moreover, the use of perfluorohexane to distribute the f-AuNPs on the tissue creates a hydrophobic environment minimizing metabolite solubilization and spatial dislocation. The transfer of the energy from the incident laser to the analytes through the release of the fluorocarbon chains similarly enhances the desorption/ionization of metabolites of different chemical nature, resulting in heterogeneous metabolome coverage. We performed the approach in a comparative study of the colon of mice exposed to three different diets. F-AuNP NIMS allows the direct detection of carbohydrates, lipids, bile acids, sulfur metabolites, amino acids, nucleotide precursors as well as other small molecules of varied biological origins. Ultimately, the diversified molecular coverage obtained provides a broad picture of a tissue's metabolic organization.

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online.

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LC)-mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5-10 min, depending on user experience; data processing typically takes 1-3 h, and data analysis takes ∼30 min.

Metabolomics Reveals that Dietary Xenoestrogens Alter Cellular Metabolism Induced by Palbociclib/Letrozole Combination Cancer Therapy.

Recently, the palbociclib/letrozole combination therapy was granted accelerated US FDA approval for the treatment of estrogen receptor (ER)-positive breast cancer. Since the underlying metabolic effects of these drugs are yet unknown, we investigated their synergism at the metabolome level in MCF-7 cells. As xenoestrogens interact with the ER, we additionally aimed at deciphering the impact of the phytoestrogen genistein and the estrogenic mycotoxin zearalenone. A global metabolomics approach was applied to unravel metabolite and pathway modifications. The results clearly showed that the combined effects of palbociclib and letrozole on cellular metabolism were far more pronounced than that of each agent alone and potently influenced by xenoestrogens. This behavior was confirmed in proliferation experiments and functional assays. Specifically, amino acids and central carbon metabolites were attenuated, while higher abundances were observed for fatty acids and most nucleic acid-related metabolites. Interestingly, exposure to model xenoestrogens appeared to counteract these effects.

Exposome-Scale Investigations Guided by Global Metabolomics, Pathway Analysis, and Cognitive Computing.

Concurrent exposure to a wide variety of xenobiotics and their combined toxic effects can play a pivotal role in health and disease, yet are largely unexplored. Investigating the totality of these exposures, i.e., the "exposome", and their specific biological effects constitutes a new paradigm for environmental health but still lacks high-throughput, user-friendly technology. We demonstrate the utility of mass spectrometry-based global exposure metabolomics combined with tailored database queries and cognitive computing for comprehensive exposure assessment and the straightforward elucidation of biological effects. The METLIN Exposome database has been redesigned to help identify environmental toxicants, food contaminants and supplements, drugs, and antibiotics as well as their biotransformation products, through its expansion with over 700 000 chemical structures to now include more than 950 000 unique small molecules. More importantly, we demonstrate how the XCMS/METLIN platform now allows for the readout of the biological effect of a toxicant through metabolomic-derived pathway analysis, and further, artificial intelligence provides a means of assessing the role of a potential toxicant. The presented workflow addresses many of the methodological challenges current exposomics research is facing and will serve to gain a deeper understanding of the impact of environmental exposures and combinatory toxic effects on human health.

Evaluation of the safety and immunomodulatory effects of sargramostim in a randomized, double-blind phase 1 clinical Parkinson's disease trial.

A potential therapeutic role for immune transformation in Parkinson's disease evolves from more than a decade of animal investigations demonstrating regulatory T cell (Treg) nigrostriatal neuroprotection. To bridge these results to human disease, we conducted a randomized, placebo-controlled double-blind phase 1 trial with a well-studied immune modulator, sargramostim (granulocyte-macrophage colony-stimulating factor). We enrolled 17 age-matched non-Parkinsonian subjects as non-treated controls and 20 Parkinson's disease patients. Both Parkinson's disease patients and controls were monitored for 2 months for baseline profiling. Parkinson's disease patients were then randomized into two equal groups to self-administer placebo (saline) or sargramostim subcutaneously at 6 µg/kg/day for 56 days. Adverse events for the sargramostim and placebo groups were 100% (10/10) and 80% (8/10), respectively. These included injection site reactions, increased total white cell counts, and upper extremity bone pain. One urticarial and one vasculitis reaction were found to be drug and benzyl alcohol related, respectively. An additional patient with a history of cerebrovascular disease suffered a stroke on study. Unified Parkinson's disease rating scale, Part III scores in the sargramostim group showed modest improvement after 6 and 8 weeks of treatment when compared with placebo. This paralleled improved magnetoencephalography-recorded cortical motor activities and Treg numbers and function compared with pretreated Parkinson's disease patients and non-Parkinsonian controls. Peripheral Treg transformation was linked to serum tryptophan metabolites, including L-kynurenine, quinolinic acid, and serotonin. These data offer a potential paradigm shift in modulating immune responses for potential therapeutic gain for Parkinson's disease. Confirmation of these early study results requires larger numbers of enrolled patients and further clinical investigation.

Data Streaming for Metabolomics: Accelerating Data Processing and Analysis from Days to Minutes.

The speed and throughput of analytical platforms has been a driving force in recent years in the "omics" technologies and while great strides have been accomplished in both chromatography and mass spectrometry, data analysis times have not benefited at the same pace. Even though personal computers have become more powerful, data transfer times still represent a bottleneck in data processing because of the increasingly complex data files and studies with a greater number of samples. To meet the demand of analyzing hundreds to thousands of samples within a given experiment, we have developed a data streaming platform, XCMS Stream, which capitalizes on the acquisition time to compress and stream recently acquired data files to data processing servers, mimicking just-in-time production strategies from the manufacturing industry. The utility of this XCMS Online-based technology is demonstrated here in the analysis of T cell metabolism and other large-scale metabolomic studies. A large scale example on a 1000 sample data set demonstrated a 10 000-fold time savings, reducing data analysis time from days to minutes. Further, XCMS Stream has the capability to increase the efficiency of downstream biochemical dependent data acquisition (BDDA) analysis by initiating data conversion and data processing on subsets of data acquired, expanding its application beyond data transfer to smart preliminary data decision-making prior to full acquisition.

Staying Alive: Measuring Intact Viable Microbes with Electrospray Ionization Mass Spectrometry.

Mass spectrometry has traditionally been the technology of choice for small molecule analysis, making significant inroads into metabolism, clinical diagnostics, and pharmacodynamics since the 1960s. In the mid-1980s, with the discovery of electrospray ionization (ESI) for biomolecule analysis, a new door opened for applications beyond small molecules. Initially, proteins were widely examined, followed by oligonucleotides and other nonvolatile molecules. Then in 1991, three intriguing studies reported using mass spectrometry to examine noncovalent protein complexes, results that have been expanded on for the last 25 years. Those experiments also raised the questions: How soft is ESI, and can it be used to examine even more complex interactions? Our lab addressed these questions with the analyses of viruses, which were initially tested for viability following electrospray ionization and their passage through a quadrupole mass analyzer by placing them on an active medium that would allow them to propagate. This observation has been replicated on multiple different systems, including experiments on an even bigger microbe, a spore. The question of analysis was also addressed in the early 2000s with charge detection mass spectrometry. This unique technology could simultaneously measure mass-to-charge and charge, allowing for the direct determination of the mass of a virus. More recent experiments on spores and enveloped viruses have given us insight into the range of mass spectrometry's capabilities (reaching 100 trillion Da), beginning to answer fundamental questions regarding the complexity of these organisms beyond proteins and genes, and how small molecules are integral to these supramolecular living structures. Graphical Abstract ᅟ.

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses.

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process. Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism.

Global Isotope Metabolomics Reveals Adaptive Strategies for Nitrogen Assimilation.

Nitrogen cycling is a microbial metabolic process essential for global ecological/agricultural balance. To investigate the link between the well-established ammonium and the alternative nitrate assimilation metabolic pathways, global isotope metabolomics was employed to examine three nitrate reducing bacteria using (15)NO3 as a nitrogen source. In contrast to a control (Pseudomonas stutzeri RCH2), the results show that two of the isolates from Oak Ridge, Tennessee (Pseudomonas N2A2 and N2E2) utilize nitrate and ammonia for assimilation concurrently with differential labeling observed across multiple classes of metabolites including amino acids and nucleotides. The data reveal that the N2A2 and N2E2 strains conserve nitrogen-containing metabolites, indicating that the nitrate assimilation pathway is a conservation mechanism for the assimilation of nitrogen. Co-utilization of nitrate and ammonia is likely an adaption to manage higher levels of nitrite since the denitrification pathways utilized by the N2A2 and N2E2 strains from the Oak Ridge site are predisposed to the accumulation of the toxic nitrite. The use of global isotope metabolomics allowed for this adaptive strategy to be investigated, which would otherwise not have been possible to decipher.

Bio-solid-phase extraction/tandem mass spectrometry for identification of bioactive compounds in mixtures.

We describe a two-step column-based bioassay method with tandem mass spectrometric detection for rapid identification of bioactive species in mixtures. The first step uses an immobilized enzyme reactor (IMER) column interfaced to an electrospray ionization mass spectrometer (ESI-MS) to identify mixtures containing bioactive compounds (i.e., enzyme inhibitors), while the second step uses bioselective solid-phase extraction (bioSPE) columns to isolate compounds from "hit" mixtures, which are then identified online by data-dependent ESI-MS. IMER columns were prepared by entrapment of adenosine deaminase (ADA) into sol-gel derived monolithic silica columns, and used to perform a primary IMER screen of mixtures prepared from a bioactive library, which resulted in four apparent hit compounds. Such columns did not provide sufficient binding site density to allow bioSPE, and thus a new column format was developed using ADA that was covalently immobilized to monolithic silica capillary columns, providing ∼500-fold more protein binding sites than were present in columns containing entrapped proteins. Using the covalently linked ADA columns, bioactive mixtures identified by IMER were infused until a maximum total ion current was achieved, followed by washing with a buffer to remove unbound compounds. A harsh wash with 3% acetic acid eluted the strongly bound ligands and the resulting peak triggered data dependent MS/MS to identify the ligand, showing that two of the apparent hits were true ADA inhibitors and demonstrating the ability of this method to rapidly identify bioactive compounds in mixtures.

Solid-phase biological assays for drug discovery.

In the past 30 years, there has been a significant growth in the use of solid-phase assays in the area of drug discovery, with a range of new assays being used for both soluble and membrane-bound targets. In this review, we provide some basic background to typical drug targets and immobilization protocols used in solid-phase biological assays (SPBAs) for drug discovery, with emphasis on particularly labile biomolecular targets such as kinases and membrane-bound receptors, and highlight some of the more recent approaches for producing protein microarrays, bioaffinity columns, and other devices that are central to small molecule screening by SPBA. We then discuss key applications of such assays to identify drug leads, with an emphasis on the screening of mixtures. We conclude by highlighting specific advantages and potential disadvantages of SPBAs, particularly as they relate to particular assay formats.

Continuous flow immobilized enzyme reactor-tandem mass spectrometry for screening of AChE inhibitors in complex mixtures.

A method is described for identifying bioactive compounds in complex mixtures based on the use of capillary-scale monolithic enzyme-reactor columns for rapid screening of enzyme activity. A two-channel nanoLC system was used to continuously infuse substrate coupled with automated injections of substrate/small molecule mixtures, optionally containing the chromogenic Ellman reagent, through sol-gel derived acetylcholinesterase (AChE) doped monolithic columns. This is the first report of AChE encapsulated in monolithic silica for use as an immobilized enzyme reactor (IMER), and the first use of such IMERs for mixture screening. AChE IMER columns were optimized to allow rapid functional screening of compound mixtures based on changes in the product absorbance or the ratio of mass spectrometric peaks for product and substrate ions in the eluent. The assay had robust performance and produced a Z' factor of 0.77 in the presence of 2% (v/v) DMSO. A series of 52 mixtures consisting of 1040 compounds from the Canadian Compound Collection of bioactives was screened and two known inhibitors, physostigmine and 9-aminoacridine, were identified from active mixtures by manual deconvolution. The activity of the compounds was confirmed using the enzyme reactor format, which allowed determination of both IC(50) and K(I) values. Screening results were found to correlate well with a recently published fluorescence-based microarray screening assay for AChE inhibitors.