Comparative analysis between zebrafish and an automated live-cell assay to classify developmental neurotoxicant chemicals.

Modern toxicology's throughput has dramatically increased due to alternative models, laboratory automation, and machine learning. This has enabled comparative studies across species and assays to prioritize chemical hazard potential and to understand how different model systems might complement one another. However, such comparative studies of high-throughput data are still in their infancy, with more groundwork needed to firmly establish the approach. Therefore, this study aimed to compare the bioactivity of the NIEHS Division of Translational Toxicology's (DTT) 87-compound developmental neurotoxicant (DNT) library in zebrafish and an in vitro high-throughput cell culture system. The early life-stage zebrafish provided a whole animal approach to developmental toxicity assessment. Chemical hits for abnormalities in embryonic zebrafish morphology, mortality, and behavior (ZBEscreen™) were compared with chemicals classified as high-risk by the Cell Health Index (CHI™), which is an outcome class probability from a machine learning classifier using 12 parameters from the SYSTEMETRIC® Cell Health Screen (CHS). The CHS was developed to assess human toxicity risk using supervised machine learning to classify acute cell stress phenotypes in a human leukemia cell line (HL60 cells) following a 4-h exposure to a chemical of interest. Due to the design of the screen, the zebrafish assays were more exhaustive, yielding 86 total bioactive hits, whereas the SYSTEMETRIC® CHS focusing on acute toxicity identified 20 chemicals as potentially toxic. The zebrafish embryonic and larval photomotor response assays (EPR and LPR, respectively) detected 40 of the 47 chemicals not found by the zebrafish morphological screen and CHS. Collectively, these results illustrate the advantages of using two alternative models in tandem for rapid hazard assessment and chemical prioritization and the effectiveness of CHI™ in identifying toxicity within a single multiparametric assay.

IL-4 promotes stromal cell expansion and is critical for development of a type-2, but not a type 1 immune response.

IL-4 is critical for differentiation of Th2 cells and antibody isotype switching, but our work demonstrated that it is produced in the peripheral LN under both Type 2, and Type 1 conditions, raising the possibility of other functions. We found that IL-4 is vital for proper positioning of hematopoietic and stromal cells in steady state, and the lack of IL-4 or IL-4Rα correlates with disarrangement of both follicular dendritic cells and CD31+ endothelial cells. We observed a marked disorganization of B cells in these mice, suggesting that the lymphocyte-stromal cell axis is maintained by the IL-4 signaling pathway. This study showed that absence of IL-4 correlates with significant downregulation of Lymphotoxin alpha (LTα) and Lymphotoxin beta (LTß), critical lymphokines for the development and maintenance of lymphoid organs. Moreover, immunization of IL-4 deficient mice with Type 2 antigens failed to induce lymphotoxin production, LN reorganization, or germinal center formation, while this process is IL-4 independent following Type 1 immunization. Additionally, we found that Type 1 antigen mediated LN reorganization is dependent on IFN-γ in the absence of IL-4. Our findings reveal a role of IL-4 in the maintenance of peripheral lymphoid organ microenvironments during homeostasis and antigenic challenge.

Schistosoma mansoni Infection-Induced Transcriptional Changes in Hepatic Macrophage Metabolism Correlate With an Athero-Protective Phenotype.

Hepatic macrophages play an essential role in the granulomatous response to infection with the parasitic helminth Schistosoma mansoni, but the transcriptional changes that underlie this effect are poorly understood. To explore this, we sorted the two previously recognized hepatic macrophage populations (perivascular and Kupffer cells) from naïve and S. mansoni-infected male mice and performed microarray analysis as part of the Immunological Genome Project. The two hepatic macrophage populations exhibited remarkably different genomic profiles. However, this diversity was substantially reduced following infection with S. mansoni, and in fact, both populations demonstrated increases in transcripts of the monocyte lineage, suggesting that both populations may be replenished by monocytes following infection. Pathway analysis showed a profound alteration in global metabolic pathways, including changes to phospholipid and cholesterol metabolism, as well as amino acid biosynthesis and glucagon signaling. These changes suggest a possible mechanism for the previously reported athero-protective effects of S. mansoni infection. Indeed, we find that male ApoE null mice fed a high-fat diet in combination with S. mansoni infection have reduced plaque area and increased glucose tolerance as compared to control mice. Transcript analysis of infected and control high-fat diet fed ApoE-/- mice confirm that ApoC1, Psat1, and Gys1 are all altered by infection, suggesting that altered hepatic macrophage metabolism is associated with S. mansoni- induced protection from hyperlipidemia, atherosclerosis, and glucose intolerance. These results suggest a previously unknown and unreported role of hepatic macrophages in the modulation of whole body lipid and glucose metabolism during infection and provide a template for examining the role of immunomodulation on the long-term metabolism of the host.

A Chemogenomic Screening Platform Used to Identify Chemotypes Perturbing HSP90 Pathways.

Compounds that modulate the heat shock protein (HSP) network have potential in a broad range of research applications and diseases. A yeast-based liquid culture assay that measured time-dependent turbidity enabled the high-throughput screening of different Saccharomyces cerevisae strains to identify HSP modulators with unique molecular mechanisms. A focused set of four strains, with differing sensitivities to Hsp90 inhibitors, was used to screen a compound library of 3680 compounds. Computed turbidity curve functions were used to classify strain responses and sensitivity to chemical effects across the compound library. Filtering based on single-strain selectivity identified nine compounds as potential heat shock modulators, including the known Hsp90 inhibitor macbecin. Haploid yeast deletion strains (360), mined from previous Hsp90 inhibitor yeast screens and heat shock protein interaction data, were screened for differential sensitivities to known N-terminal ATP site-directed Hsp90 inhibitors to reveal functional distinctions. Strains demonstrating differential sensitivity (13) to Hsp90 inhibitors were used to prioritize primary screen hit compounds, with NSC145366 emerging as the lead hit. Our follow-up biochemical and functional studies show that NSC145366 directly interacts and inhibits the C-terminus of Hsp90, validating the platform as a powerful approach for early-stage identification of bioactive modulators of heat shock-dependent pathways.

Automated Assessment of Disease Progression in Acute Myeloid Leukemia by Probabilistic Analysis of Flow Cytometry Data.

OBJECTIVE: Flow cytometry (FC) is a widely acknowledged technology in diagnosis of acute myeloid leukemia (AML) and has been indispensable in determining progression of the disease. Although FC plays a key role as a posttherapy prognosticator and evaluator of therapeutic efficacy, the manual analysis of cytometry data is a barrier to optimization of reproducibility and objectivity. This study investigates the utility of our recently introduced nonparametric Bayesian framework in accurately predicting the direction of change in disease progression in AML patients using FC data. METHODS: The highly flexible nonparametric Bayesian model based on the infinite mixture of infinite Gaussian mixtures is used for jointly modeling data from multiple FC samples to automatically identify functionally distinct cell populations and their local realizations. Phenotype vectors are obtained by characterizing each sample by the proportions of recovered cell populations, which are, in turn, used to predict the direction of change in disease progression for each patient. RESULTS: We used 200 diseased and nondiseased immunophenotypic panels for training and tested the system with 36 additional AML cases collected at multiple time points. The proposed framework identified the change in direction of disease progression with accuracies of 90% (nine out of ten) for relapsing cases and 100% (26 out of 26) for the remaining cases. CONCLUSIONS: We believe that these promising results are an important first step toward the development of automated predictive systems for disease monitoring and continuous response evaluation. SIGNIFICANCE: Automated measurement and monitoring of therapeutic response is critical not only for objective evaluation of disease status prognosis but also for timely assessment of treatment strategies.

Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples.

We describe algorithms for discovering immunophenotypes from large collections of flow cytometry samples and using them to organize the samples into a hierarchy based on phenotypic similarity. The hierarchical organization is helpful for effective and robust cytometry data mining, including the creation of collections of cell populations' characteristic of different classes of samples, robust classification, and anomaly detection. We summarize a set of samples belonging to a biological class or category with a statistically derived template for the class. Whereas individual samples are represented in terms of their cell populations (clusters), a template consists of generic meta-populations (a group of homogeneous cell populations obtained from the samples in a class) that describe key phenotypes shared among all those samples. We organize an FC data collection in a hierarchical data structure that supports the identification of immunophenotypes relevant to clinical diagnosis. A robust template-based classification scheme is also developed, but our primary focus is in the discovery of phenotypic signatures and inter-sample relationships in an FC data collection. This collective analysis approach is more efficient and robust since templates describe phenotypic signatures common to cell populations in several samples while ignoring noise and small sample-specific variations. We have applied the template-based scheme to analyze several datasets, including one representing a healthy immune system and one of acute myeloid leukemia (AML) samples. The last task is challenging due to the phenotypic heterogeneity of the several subtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML and were able to distinguish acute promyelocytic leukemia (APL) samples with the markers provided. Clinically, this is helpful since APL has a different treatment regimen from other subtypes of AML. Core algorithms used in our data analysis are available in the flowMatch package at www.bioconductor.org. It has been downloaded nearly 6,000 times since 2014.

Point-of-care test for cervical cancer in LMICs.

Cervical cancer screening using Papanicolaou's smear test has been highly effective in reducing death from this disease. However, this test is unaffordable in low- and middle-income countries, and its complexity has limited wide-scale uptake. Alternative tests, such as visual inspection with acetic acid or Lugol's iodine and human papillomavirus DNA, are sub-optimal in terms of specificity and sensitivity, thus sensitive and affordable tests with high specificity for on-site reporting are needed. Using proteomics and bioinformatics, we have identified valosin-containing protein (VCP) as differentially expressed between normal specimens and those with cervical intra-epithelial neoplasia grade 2/3 (CIN2/CIN3+) or worse. VCP-specific immunohistochemical staining (validated by a point-of-care technology) provided sensitive (93%) and specific (88%) identification of CIN2/CIN3+ and may serve as a critical biomarker for cervical-cancer screening. Future efforts will focus on further refinements to enhance analytic sensitivity and specificity of our proposed test, as well as on prototype development.

A double blinded, placebo-controlled pilot study to examine reduction of CD34 +/CD117 +/CD133 + lymphoma progenitor cells and duration of remission induced by neoadjuvant valspodar in dogs with large B-cell lymphoma.

We previously described a population of lymphoid progenitor cells (LPCs) in canine B-cell lymphoma defined by retention of the early progenitor markers CD34 and CD117 and "slow proliferation" molecular signatures that persist in the xenotransplantation setting. We examined whether valspodar, a selective inhibitor of the ATP binding cassette B1 transporter (ABCB1, a.k.a., p-glycoprotein/multidrug resistance protein-1) used in the neoadjuvant setting would sensitize LPCs to doxorubicin and extend the length of remission in dogs with therapy naïve large B-cell lymphoma. Twenty dogs were enrolled into a double-blinded, placebo controlled study where experimental and control groups received oral valspodar (7.5 mg/kg) or placebo, respectively, twice daily for five days followed by five treatments with doxorubicin 21 days apart with a reduction in the first dose to mitigate the potential side effects of ABCB1 inhibition. Lymph node and blood LPCs were quantified at diagnosis, on the fourth day of neoadjuvant period, and 1-week after the first chemotherapy dose. Valspodar therapy was well tolerated. There were no differences between groups in total LPCs in lymph nodes or peripheral blood, nor in event-free survival or overall survival. Overall, we conclude that valspodar can be administered safely in the neoadjuvant setting for canine B-cell lymphoma; however, its use to attenuate ABCB1 + cells does not alter the composition of lymph node or blood LPCs, and it does not appear to be sufficient to prolong doxorubicin-dependent remissions in this setting.

A non-parametric Bayesian model for joint cell clustering and cluster matching: identification of anomalous sample phenotypes with random effects.

BACKGROUND: Flow cytometry (FC)-based computer-aided diagnostics is an emerging technique utilizing modern multiparametric cytometry systems.The major difficulty in using machine-learning approaches for classification of FC data arises from limited access to a wide variety of anomalous samples for training. In consequence, any learning with an abundance of normal cases and a limited set of specific anomalous cases is biased towards the types of anomalies represented in the training set. Such models do not accurately identify anomalies, whether previously known or unknown, that may exist in future samples tested. Although one-class classifiers trained using only normal cases would avoid such a bias, robust sample characterization is critical for a generalizable model. Owing to sample heterogeneity and instrumental variability, arbitrary characterization of samples usually introduces feature noise that may lead to poor predictive performance. Herein, we present a non-parametric Bayesian algorithm called ASPIRE (anomalous sample phenotype identification with random effects) that identifies phenotypic differences across a batch of samples in the presence of random effects. Our approach involves simultaneous clustering of cellular measurements in individual samples and matching of discovered clusters across all samples in order to recover global clusters using probabilistic sampling techniques in a systematic way. RESULTS: We demonstrate the performance of the proposed method in identifying anomalous samples in two different FC data sets, one of which represents a set of samples including acute myeloid leukemia (AML) cases, and the other a generic 5-parameter peripheral-blood immunophenotyping. Results are evaluated in terms of the area under the receiver operating characteristics curve (AUC). ASPIRE achieved AUCs of 0.99 and 1.0 on the AML and generic blood immunophenotyping data sets, respectively. CONCLUSIONS: These results demonstrate that anomalous samples can be identified by ASPIRE with almost perfect accuracy without a priori access to samples of anomalous subtypes in the training set. The ASPIRE approach is unique in its ability to form generalizations regarding normal and anomalous states given only very weak assumptions regarding sample characteristics and origin. Thus, ASPIRE could become highly instrumental in providing unique insights about observed biological phenomena in the absence of full information about the investigated samples.

An excitation wavelength-scanning spectral imaging system for preclinical imaging.

Small-animal fluorescence imaging is a rapidly growing field, driven by applications in cancer detection and pharmaceutical therapies. However, the practical use of this imaging technology is limited by image-quality issues related to autofluorescence background from animal tissues, as well as attenuation of the fluorescence signal due to scatter and absorption. To combat these problems, spectral imaging and analysis techniques are being employed to separate the fluorescence signal from background autofluorescence. To date, these technologies have focused on detecting the fluorescence emission spectrum at a fixed excitation wavelength. We present an alternative to this technique, an imaging spectrometer that detects the fluorescence excitation spectrum at a fixed emission wavelength. The advantages of this approach include increased available information for discrimination of fluorescent dyes, decreased optical radiation dose to the animal, and ability to scan a continuous wavelength range instead of discrete wavelength sampling. This excitation-scanning imager utilizes an acousto-optic tunable filter (AOTF), with supporting optics, to scan the excitation spectrum. Advanced image acquisition and analysis software has also been developed for classification and unmixing of the spectral image sets. Filtering has been implemented in a single-pass configuration with a bandwidth (full width at half maximum) of 16 nm at 550 nm central diffracted wavelength. We have characterized AOTF filtering over a wide range of incident light angles, much wider than has been previously reported in the literature, and we show how changes in incident light angle can be used to attenuate AOTF side lobes and alter bandwidth. A new parameter, in-band to out-of-band ratio, was defined to assess the quality of the filtered excitation light. Additional parameters were measured to allow objective characterization of the AOTF and the imager as a whole. This is necessary for comparing the excitation-scanning imager to other spectral and fluorescence imaging technologies. The effectiveness of the hyperspectral imager was tested by imaging and analysis of mice with injected fluorescent dyes. Finally, a discussion of the optimization of spectral fluorescence imagers is given, relating the effects of filter quality on fluorescence images collected and the analysis outcome.

The SH3 domain of Lck modulates T-cell receptor-dependent activation of extracellular signal-regulated kinase through activation of Raf-1.

Engagement of the T-cell antigen receptor (TCR) results in the proximal activation of the Src family tyrosine kinase Lck. The activation of Lck leads to the downstream activation of the Ras/Raf/MEK/ERK signaling pathway (where ERK is extracellular signal-related kinase). Under conditions of weak, but not strong, stimulation through the TCR, a version of Lck that contains a single point mutation in the SH3 (Src homology 3) domain (W97ALck) fails to support the activation of ERK, despite initiating signaling through the TCR, as demonstrated by the robust activation of ZAP-70, PLC-gamma, and Ras. We determined that the signaling lesion in W97ALck-expressing cells lies at the level of Raf-1 activation and is dependent on the presence of tyrosines 340/341 in the Raf-1 sequence. These data demonstrate a second function for Lck in TCR-mediated signaling to ERK. Additionally, we found that a significant fraction of Lck is localized to the Golgi apparatus and that, compared with wild-type Lck, W97ALck displays aberrant Golgi membrane localization. Our results support a model where under conditions of weak stimulation through the TCR, in addition to activated Ras, Golgi apparatus-localized Lck is needed for the full activation of Raf-1.

Single- and two-photon spectral imaging of intrinsic fluorescence of transformed human hepatocytes.

Autofluorescence (AF) originating from the cytoplasmic region of mammalian cells has been thoroughly investigated; however, AF from plasma membranes of viable intact cells is less well known, and has been mentioned only in a few older publications. Herein, we report results describing single- and two-photon spectral properties of a strong yellowish-green AF confined to the plasma-membrane region of transformed human hepatocytes (HepG2) grown in vitro as small three-dimensional aggregates or as monolayers. The excitation-emission characteristics of the membrane AF indicate that it may originate from a flavin derivative. Furthermore, the AF was closely associated with the plasma membranes of HepG2 cells, and its presence and intensity were dependent on cell metabolic state, membrane integrity and presence of reducing agents. This AF could be detected both in live intact cells and in formaldehyde-fixed cells.

Actin cytoskeleton in Arabidopsis thaliana under blue and red light.

BACKGROUND INFORMATION: Actin cytoskeleton is the basis of chloroplast-orientation movements. These movements are activated by blue light in the leaves of terrestrial angiosperms. Red light has been shown to affect the spatial reorganization of F-actin in water plants, where chloroplast movements are closely connected with cytoplasmic streaming. The aim of the present study was to determine whether blue light, which triggers characteristic responses of chloroplasts, i.e. avoidance and accumulation, also influences F-actin organization in the mesophyll cells of Arabidopsis thaliana. Actin filaments in fixed mesophyll tissue were labelled with Alexa Fluor 488-conjugated phalloidin. The configuration of actin filaments, expressed as a form factor (4 pi x area/perimeter(2)), was determined for all actin formations which were measured in fluorescence confocal images. RESULTS: In the present study, we compare form-factor distributions and the median form factors for strong and weak, blue- and red-irradiated tissues. Spatial organization of the F-actin network did not undergo any changes which could be attributed specifically to blue light. Actin patterns were similar in blue-irradiated wild-type plants and phot2 (phototropin 2) mutants which lack the avoidance response of chloroplasts. However, significant differences in the shape and distribution of F-actin formations were observed between mesophyll cells of phot2 mutants irradiated with strong and weak red light. These differences were absent in wild-type leaves. CONCLUSIONS: Actin does not appear to be the main target for the blue-light chloroplast-orientation signal. The modes of actin involvement in chloroplast translocations are different in water and terrestrial angiosperms. The results suggest that co-operation occurs between blue- and red-light photoreceptors in the control of the actin cytoskeleton architecture in Arabidopsis.

DPI induces mitochondrial superoxide-mediated apoptosis.

The iodonium compounds diphenyleneiodonium (DPI) and diphenyliodonium (IDP) are well-known phagocyte NAD(P)H oxidase inhibitors. However, it has been shown that at high concentrations they can inhibit the mitochondrial respiratory chain as well. Since inhibition of the mitochondrial respiratory chain has been shown to induce superoxide production and apoptosis, we investigated the effect of iodonium compounds on mitochondria-derived superoxide and apoptosis. Mitochondrial superoxide production was measured on both cultured cells and isolated rat-heart submitochondrial particles. Mitochondria function was examined by monitoring mitochondrial membrane potential. Apoptotic pathways were studied by measuring cytochrome c release and caspase 3 activation. Apoptosis was characterized by detecting DNA fragmentation on agarose gel and measuring propidium iodide- (PI-) stained subdiploid cells using flow cytometry. Our results showed that DPI could induce mitochondrial superoxide production. The same concentration of DPI induced apoptosis by decreasing mitochondrial membrane potential and releasing cytochrome c. Addition of antioxidants or overexpression of MnSOD significantly reduced DPI-induced mitochondrial damage, cytochrome c release, caspase activation, and apoptosis. These observations suggest that DPI can induce apoptosis via induction of mitochondrial superoxide. DPI-induced mitochondrial superoxide production may prove to be a useful model to study the signaling pathways of mitochondrial superoxide.