Identification of compounds that enhance the anti-lymphoma activity of rituximab using flow cytometric high-content screening

Obinutuzumab-Based Drug-Free Macromolecular Therapeutics Synergizes with Topoisomerase Inhibitors

Drug-free macromolecular therapeutics (DFMT) utilizes modified monoclonal antibodies (or antibody fragments) to generate antigen-crosslinking-induced apoptosis in target cells. DFMT is a two-component system containing a morpholino oligonucleotide (MORF1) modified antibody (Ab-MORF1) and human serum albumin conjugated with multiple copies of complementary morpholino oligonucleotide (MORF2), (HSA-(MORF2)x ). The two components recognize each other via the Watson-Crick base pairing complementation of their respective MORFs. One HSA-(MORF2)x molecule can hybridize with multiple Ab-MORF1 molecules on the cell surface, thus serving as the therapeutic crosslink-inducing mechanism of action. Herein, various anti-neoplastic agents in combination with the anti-CD20 Obinutuzumab (OBN)-based DFMT system are examined. Three different classes of chemotherapies are examined: DNA alkylating agents; proliferation pathway inhibitors; and DNA replication inhibitors. Chou-Talalay combination index mathematics is utilized to determine which drugs engaged synergistically with OBN-based DFMT. It is determined that OBN-based DFMT synergizes with topoisomerase inhibitors and DNA nucleotide analogs but is antagonistic with proliferation pathway inhibitors. Cell mechanism experiments are performed to analyze points of synergism or antagonism by investigating Ca2+ influx, mitochondrial health, lysosomal stability, and cell cycle arrest. Finally, the synergistic drug combinatorial effects of OBN-based DFMT with etoposide in vivo are demonstrated using a human xenograft non-Hodgkin's lymphoma mouse model.

Leukemia Cell Cycle Chemical Profiling Identifies the G2-Phase Leukemia Specific Inhibitor Leusin-1

Targeting the leukemia proliferation cycle has been a successful approach to developing antileukemic therapies. However, drug screening efforts to identify novel antileukemic agents have been hampered by the lack of a suitable high-throughput screening platform for suspension cells that does not rely on flow-cytometry analyses. We report the development of a novel leukemia cell-based high-throughput chemical screening platform for the discovery of cell cycle phase specific inhibitors that utilizes chemical cell cycle profiling. We have used this approach to analyze the cell cycle response of acute lymphoblastic leukemia CCRF-CEM cells to each of 181420 druglike compounds. This approach yielded cell cycle phase specific inhibitors of leukemia cell proliferation. Further analyses of the top G2-phase and M-phase inhibitors identified the leukemia specific inhibitor 1 (Leusin-1). Leusin-1 arrests cells in G2 phase and triggers an apoptotic cell death. Most importantly, Leusin-1 was more active in acute lymphoblastic leukemia cells than other types of leukemias, non-blood cancers, or normal cells and represents a lead molecule for developing antileukemic drugs.

GRP78/BIP/HSPA5 as a Therapeutic Target in Models of Parkinson's Disease: A Mini Review

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by selective loss of dopamine neurons in the substantia nigra pars compacta of the midbrain. Reports from postmortem studies in the human PD brain, and experimental PD models reveal that endoplasmic reticulum (ER) stress is implicated in the pathogenesis of PD. In times of stress, the unfolded or misfolded proteins overload the folding capacity of the ER to induce a condition generally known as ER stress. During ER stress, cells activate the unfolded protein response (UPR) to handle increasing amounts of abnormal proteins, and recent evidence has demonstrated the activation of the ER chaperone GRP78/BiP (78 kDa glucose-regulated protein/binding immunoglobulin protein), which is important for proper folding of newly synthesized and partly folded proteins to maintain protein homeostasis. Although the activation of this protein is essential for the initiation of the UPR in PD, there are inconsistent reports on its expression in various PD models. Consequently, this review article aims to summarize current knowledge on neuroprotective agents targeting the expression of GRP78/BiP in the regulation of ER stress in experimental PD models.

Low ferroportin expression in AML is correlated with good risk cytogenetics, improved outcomes and increased sensitivity to chemotherapy

Iron metabolism is altered in a variety of cancers; however, little is known about the role of iron metabolism in the biology and response to therapy of acute myeloid leukemia (AML). Here we show that SLC40A1, the gene encoding the iron exporter ferroportin (FPN), is variably expressed among primary AMLs and that low levels are associated with good prognosis and improved outcomes. In particular, core binding factor (CBF) AMLs, which are associated with good outcomes with chemotherapy, consistently have low level of SLC40A1 expression. AML cell lines that expressed relatively low levels of FPN endogenously, or were engineered via gene knockdown, had an increased sensitivity to chemotherapy relative to controls expressing high levels of FPN. Primary FPN^low AML bulk cells also had increased sensitivity to Ara-C treatment, iron treatment and the combination of Ara-C and iron relative to FPN^high cells. FPN^low leukemic stem cells (LSCs) had decreased viability following addition of iron alone and in combination with Ara-C treatment relative to FPN^high LSCs. Together these observations suggest a model where FPN mediated iron metabolism may play a role in chemosensitivity and outcome to therapy in AML.

Candidiasis and the impact of flow cytometry on antifungal drug discovery

INTRODUCTION

Invasive candidiasis continues to be associated with significant morbidity and mortality as well as substantial health care costs nationally and globally. One of the contributing factors is the development of resistance to antifungal agents that are already in clinical use. Moreover, there are known treatment limitations with all of the available antifungal agents. Since traditional techniques in novel drug discovery are time consuming, high-throughput screening using flow cytometry presents as a potential tool to identify new antifungal agents that would be useful in the management of these patients. Areas covered: In this review, the authors discuss the use of automated high-throughput screening assays based upon flow cytometry to identify potential antifungals from a library comprised of a large number of bioactive compounds. They also review studies that employed the use of this research methodology that has identified compounds with antifungal activity. Expert opinion: High-throughput screening using flow cytometry has substantially decreased the processing time necessary for screening thousands of compounds, and has helped enhance our understanding of fungal pathogenesis. Indeed, the authors see this technology as a powerful tool to help scientists identify new antifungal agents that can be added to the clinician's arsenal in their fight against invasive candidiasis.

Aldehyde dehydrogenase 1B1: a novel immunohistological marker for colorectal cancer

Background:

Aldehyde dehydrogenase (ALDH) 1A1 is an immunohistological biomarker of various solid tumours, but has not been successfully proved as a colorectal cancer (CRC) marker. We recently reported that ALDH1B1, which has functional roles in tumourigenesis, may be a better CRC marker than ALDH1A1.

Methods:

Human CRC explants and cell lines were analysed to identify candidate CRC markers from eight ALDH isozymes including ALDH1A1 and ALDH1B1. A tissue microarray, including paired specimens of normal and tumour tissues, was subsequently analysed to determine if candidate ALDHs could distinguish CRC from normal tissue.

Results:

Based on mRNA analysis, ALDH1B1 and ALDH2 were selected as suitable candidates. These were strongly and regularly expressed in tumour tissue and cell lines, including highly tumourigenic cell populations (ALDH⁺CD44⁺ cells), while other ALDHs, including ALDH1A1, showed differential or low expression. No genetic alteration of ALDH1B1 in CRC was suggested by the relationships between mRNA and protein levels/enzymatic activities, and cDNA sequences of CRC cell lines. Tissue microarray findings showed that ALDH1B1, but not ALDH2, could distinguish CRC from normal tissue. Furthermore, ratios of ALDH1B1 to ALDH1A1 or ALDH2 were found to be powerful CRC indicators.

Conclusions:

These results suggest that ALDH1B1 is a novel human CRC biomarker.

Targeted therapy for a subset of acute myeloid leukemias that lack expression of aldehyde dehydrogenase 1A1

Aldehyde dehydrogenase 1A1 (ALDH1A1) activity is high in hematopoietic stem cells and functions in part to protect stem cells from reactive aldehydes and other toxic compounds. In contrast, we found that approximately 25% of all acute myeloid leukemias expressed low or undetectable levels of ALDH1A1 and that this ALDH1A1⁻ subset of leukemias correlates with good prognosis cytogenetics. ALDH1A1⁻ cell lines as well as primary leukemia cells were found to be sensitive to treatment with compounds that directly and indirectly generate toxic ALDH substrates including 4-hydroxynonenal and the clinically relevant compounds arsenic trioxide and 4-hydroperoxycyclophosphamide. In contrast, normal hematopoietic stem cells were relatively resistant to these compounds. Using a murine xenotransplant model to emulate a clinical treatment strategy, established ALDH1A1⁻ leukemias were also sensitive to in vivo treatment with cyclophosphamide combined with arsenic trioxide. These results demonstrate that targeting ALDH1A1⁻ leukemic cells with toxic ALDH1A1 substrates such as arsenic and cyclophosphamide may be a novel targeted therapeutic strategy for this subset of acute myeloid leukemias.

Salubrinal protects against Clostridium difficile toxin B-induced CT26 cell death

Clostridium difficile (C. difficile) is considered to be the major cause of the antibiotic-associated diarrhea and pseudomembranous colitis in animals and humans. The prevalence of C. difficile infections (CDI) has been increasing since 2000. Two exotoxins of C. difficile, Toxin A (TcdA) and Toxin B (TcdB), are the main virulence factors of CDI, which can induce glucosylation of Rho GTPases in host cytosol, leading to cell morphological changes, cell apoptosis, and cell death. The mechanism of TcdB-induced cell death has been investigated for decades, but it is still not completely understood. It has been reported that TcdB induces endoplasmic reticulum stress via PERK-eIF2α signaling pathway in CT26 cell line (BALB/C mouse colon tumor cells). In this study, we found that salubrinal, a selective inhibitor of eIF2α dephosphorylation, efficiently protects CT26 cell line against TcdB-induced cell death and tried to explore the mechanism underlying in this protective effect. Our results demonstrated that salubrinal protects CT26 cells from TcdB-mediated cytotoxic and cytopathic effect, inhibits apoptosis and death of the toxin-exposed cells via caspase-9-dependent pathway, eIF2α signaling pathway, and autophagy. These findings will be helpful for the development of CDI therapies.

High-content screening identifies inhibitors of the nuclear translocation of ATF6

Activating transcription factor 6 (ATF6) is a transmembrane protein that consists of a cytoplasmic domain and an endoplasmic reticulum (ER) luminal domain. As unfolded protein levels arise in the ER, the ER cytoplasmic domain of ATF6 moves to the nucleus, where it activates the transcription of a range of genes, including those involved in apoptosis. As ATF6 only becomes functional once it has moved to the nucleus, compounds that inhibit its re-localization are of therapeutic interest. The aim of the present study was to rapidly and accurately identify such compounds using a novel image‑based, high‑content screening (HCS) technique. The results from the HCS analysis were then confirmed by luciferase reporter assays, western blot analysis and the measurement of cell viability. We found that HCS identified compounds which inhibited ATF6 nuclear translocation with high specificity, as confirmed by the luciferase reporter assay and western blot analysis. Moreover, we demonstrated that 3 of the 80 identified compounds impaired ATF6-mediated induced cell death. The data from this study support the theory that HCS is a novel, high throughput method which can be used for accurate and rapid compound screening.

Salubrinal protects cardiomyocytes against apoptosis in a rat myocardial infarction model via suppressing the dephosphorylation of eukaryotic translation initiation factor 2α

The aim of the present study was to examine the role of eIF2α in cardiomyocyte apoptosis and evaluate the cardioprotective role of salubrinal in a rat myocardial infarction (MI) model. Rat left anterior descending coronary arteries were ligated and the classical proteins involved in the endoplasmic reticulum stress (ERS)-induced apoptotic pathway were analyzed using quantitative polymerase chain reaction and western blot analysis. Salubrinal was administered to the rats and cardiomyocyte apoptosis and infarct size were evaluated by a specific staining method. Compared with the sham surgery group, the rate of cardiomyocyte apoptosis in the MI group was increased with the development of the disease. It was also demonstrated that the mRNA and protein levels of GRP78, caspase-12, CHOP and the protein expression of p-eIF2α were increased in the MI group. Furthermore, the results showed that treatment with salubrinal can decrease cardiomyocyte apoptosis and infarct size by increasing eIF2α phosphorylation and decreasing the expression of caspase-12 and CHOP. The present study suggests that salubrinal protects against ER stress-induced rat cadiomyocyte apoptosis via suppressing the dephosphorylation of eIF2α in the ERS-associated pathway.

Inhibition of serine/threonine protein phosphatase PP1 protects cardiomyocytes from tunicamycin-induced apoptosis and I/R through the upregulation of p-eIF2α

The serine/threonine protein phosphatase PP1 mediates the dephosphorylation of phosphorylated eukaryotic translation initiation factor 2 subunit α (p-eIF2α), which is a central regulator of protein synthesis. In the present study, we examined the protective effects of PP1-12 (an inhibitor of the serine/threonine protein phosphatase PP1) against tunicamycin (TM)-induced apoptosis in cultured cardiomyocytes in vitro, as well as in an in vivo model of ischemia/reperfusion (I/R) injury in rat hearts. Neonatal cardiomyocytes cultured from the ventricles of the hearts of 1-day-old Wistar rats were exposed to various concentrations of PP1-12 (0.3, 1 and 3 µmol/l) for 30 min, followed by treatment with TM for 36 h. Cell viability was assessed by adenosine triphosphate (ATP) bioluminescence, and the results revealed that pre-treatment with PP1-12 protected cell viability. Western blot analysis revealed that PP1-12 induced eIF2α phosphorylation and immuncytochemistry indicated that PP1-12 downregulated the expression of C/EBP homologous protein (CHOP), which is related to apoptosis. PP1-12 suppressed cell apoptosis, with maximum protective effects displayed at the concentration of 3 µmol/l. For the in vivo experiments, male Sprague-Dawley rats were randomly divided into 5 groups: i) sham-operated; ii) vehicle (I/R + DMSO); iii) I/R + 1 mg/kg/day PP1-12; iv) I/R + 3 mg/kg/day PP1-12; and v) I/R + 10 mg/kg/day PP1-12. PP1-12 reduced the expression of cleaved caspase-12 and increased the phosphorylation of eIF2α, as revealed by western blot analysis. By calculating the apoptotic index (AI), we found that 10 mg/kg/day PP1-12 exerted the most pronounced anti-apoptotic effect. The infarction area was significantly decreased following treatment with this concentration of PP1-12, as revealed by 2,3,5-triphenyltetrazolium chloride (TTC) staining. Taken together, these data suggest that PP1-12 protects cardiomyocytes from TM- and I/R-induced apoptosis, and this effect is achieved at least in part through the inhibition of cell apoptosis and the induction of eIF2α phosphorylation.

Salubrinal protects against tunicamycin and hypoxia induced cardiomyocyte apoptosis via the PERK-eIF2α signaling pathway

Objectives

This study examined the protective effect of salubrinal and the mechanism underlying this protection against tunicamycin (TM)- and hypoxia-induced apoptosis in rat cardiomyocytes.

Methods

Neonatal rat cardiomyocytes were cultured from the ventricles of 1-day-old Wistar rats. Cells were exposed to different concentrations of salubrinal (10, 20, and 40 µmol/L) for 30 min followed by TM treatment or hypoxia for 36 h. Apoptosis was measured by a multiparameter HCS (high content screening) apoptosis assay, TUNEL assay and flow cytometry. The phosphorylation of eukaryotic translation initiation factor 2 subunit alpha (eIF2α) and the expression of cleaved caspase-12 were determined by Western blotting. C/EBP homologous protein (CHOP) was detected by immunocytochemistry.

Results

HCS, TUNEL assays and flow cytometry showed that salubrinal protected cardiomyocytes against apoptosis induced by TM or hypoxia. Western blotting showed that salubrinal protected cardiomyocytes against apoptosis by inducing eIF2α phosphorylation and down-regulating the expression of the endoplasmic reticulum stress-mediated apoptotic proteins, CHOP and cleaved caspase-12.

Conclusions

Our study suggests that salubrinal protects rat cardiomyocytes against TM- or hypoxia-associated apoptosis via a mechanism involving the inhibition of ER stress-mediated apoptosis.

Multiparametric assessment of Cd²+ cytotoxicity using MTT-based microfluidic image cytometry

A modified MTT protocol-based microfluidic image cytometry (μFIC) was performed to assess Cd(2+) induced cytotoxicity. The expanded capabilities of μFIC, such as in situ measurement, high-throughput, and multiparametric analysis of adherent cells under precisely controlled chemical environments of microfluidic channels, were demonstrated in this study. Multiparametric analysis of μFIC data has enabled us to categorize the progress of cell death into at least four different subgroups based on their morphology and metabolic activity. These advantages of the MTT-based μFIC as a simpler, cheaper, and faster in vitro cell-based assay tool have many implications in biomedical, pharmaceutical, toxicological, and biological application areas, and we propose this technique as a future high throughput-high content screening (HT-HCS) platform for cytotoxicity assays and drug screening.

Varying levels of aldehyde dehydrogenase activity in adult murine marrow hematopoietic stem cells are associated with engraftment and cell cycle status

Aldehyde dehydrogenase (ALDH) activity is a widely used marker for human hematopoietic stem cells (HSCs), yet its relevance and role in murine HSCs remain unclear. We found that murine marrow cells with a high level of ALDH activity as measured by Aldefluor staining (ALDH(br) cells) do not contain known HSCs or progenitors. In contrast, highly enriched murine HSCs defined by the CD48(-)EPCR(+) and other phenotypes contain two subpopulations, one that stains dimly with Aldefluor (ALDH(dim)) and one that stains at intermediate levels (ALDH(int)). The CD48(-)EPCR(+)ALDH(dim) cells are virtually all in G(0) and yield high levels of engraftment via both intravenous and intrabone routes. In contrast the CD48(-)EPCR(+)ALDH(int) cells are virtually all in G(1), have little intravenous engraftment potential, and yet can engraft long-term after intrabone transplantation. These data demonstrate that Aldefluor staining of unfractionated murine marrow does not identify known HSCs or progenitors. However, varying levels of Aldefluor staining when combined with CD48 and EPCR detection can identify novel populations in murine marrow including a highly enriched population of resting HSCs and a previously unknown HSC population in G(1) with an intravenous engraftment defect.

flowPeaks: a fast unsupervised clustering for flow cytometry data via K-means and density peak finding

MOTIVATION

For flow cytometry data, there are two common approaches to the unsupervised clustering problem: one is based on the finite mixture model and the other on spatial exploration of the histograms. The former is computationally slow and has difficulty to identify clusters of irregular shapes. The latter approach cannot be applied directly to high-dimensional data as the computational time and memory become unmanageable and the estimated histogram is unreliable. An algorithm without these two problems would be very useful.

RESULTS

In this article, we combine ideas from the finite mixture model and histogram spatial exploration. This new algorithm, which we call flowPeaks, can be applied directly to high-dimensional data and identify irregular shape clusters. The algorithm first uses K-means algorithm with a large K to partition the cell population into many small clusters. These partitioned data allow the generation of a smoothed density function using the finite mixture model. All local peaks are exhaustively searched by exploring the density function and the cells are clustered by the associated local peak. The algorithm flowPeaks is automatic, fast and reliable and robust to cluster shape and outliers. This algorithm has been applied to flow cytometry data and it has been compared with state of the art algorithms, including Misty Mountain, FLOCK, flowMeans, flowMerge and FLAME.

AVAILABILITY

The R package flowPeaks is available at https://github.com/yongchao/flowPeaks.

CONTACT

yongchao.ge@mssm.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Aldehyde dehydrogenases are regulators of hematopoietic stem cell numbers and B-cell development

High levels of the aldehyde dehydrogenase isoform ALDH1A1 are expressed in hematopoietic stem cells (HSCs); however, its importance in these cells remains unclear. Consistent with an earlier report, we find that loss of ALDH1A1 does not affect HSCs. Intriguingly, however, we find that ALDH1A1 deficiency is associated with increased expression of the ALDH3A1 isoform, suggesting its potential to compensate for ALDH1A1. Mice deficient in ALDH3A1 have a block in B-cell development as well as abnormalities in cell cycling, intracellular signaling, and gene expression. Early B cells from these mice exhibit excess reactive oxygen species and reduced metabolism of reactive aldehydes. Mice deficient in both ALDH3A1 and ALDH1A1 have reduced numbers of HSCs as well as aberrant cell cycle distribution, increased reactive oxygen species levels, p38 mitogen-activated protein kinase activity and sensitivity to DNA damage. These findings demonstrate that ALDH3A1 can compensate for ALDH1A1 in bone marrow and is important in B-cell development, both ALDH1A1 and 3A1 are important in HSC biology; and these effects may be due, in part, to changes in metabolism of reactive oxygen species and reactive aldehydes.

The curvHDR method for gating flow cytometry samples

Background

High-throughput flow cytometry experiments produce hundreds of large multivariate samples of cellular characteristics. These samples require specialized processing to obtain clinically meaningful measurements. A major component of this processing is a form of cell subsetting known as gating. Manual gating is time-consuming and subjective. Good automatic and semi-automatic gating algorithms are very beneficial to high-throughput flow cytometry.

Results

We develop a statistical procedure, named curvHDR, for automatic and semi-automatic gating. The method combines the notions of significant high negative curvature regions and highest density regions and has the ability to adapt well to human-perceived gates. The underlying principles apply to dimension of arbitrary size, although we focus on dimensions up to three. Accompanying software, compatible with contemporary flow cytometry infor-matics, is developed.

Conclusion

The method is seen to adapt well to nuances in the data and, to a reasonable extent, match human perception of useful gates. It offers big savings in human labour when processing high-throughput flow cytometry data whilst retaining a good degree of efficacy.

Analysis of High-Throughput Flow Cytometry Data Using plateCore

Flow cytometry (FCM) software packages from R/Bioconductor, such as flowCore and flowViz, serve as an open platform for development of new analysis tools and methods. We created plateCore, a new package that extends the functionality in these core packages to enable automated negative control-based gating and make the processing and analysis of plate-based data sets from high-throughput FCM screening experiments easier. plateCore was used to analyze data from a BD FACS CAP screening experiment where five Peripheral Blood Mononucleocyte Cell (PBMC) samples were assayed for 189 different human cell surface markers. This same data set was also manually analyzed by a cytometry expert using the FlowJo data analysis software package (TreeStar, USA). We show that the expression values for markers characterized using the automated approach in plateCore are in good agreement with those from FlowJo, and that using plateCore allows for more reproducible analyses of FCM screening data.

Overcoming Problems of Compound Storage in DMSO: Solvent and Process Alternatives

The common practice of preparing storage libraries of compounds in 100% DMSO solution well in advance of bioassay brings with it difficulties that affect the accuracy of the data obtained. This publication presents a series of studies done on a subset of compounds that are difficult to bioassay because they precipitate from DMSO solution. These compounds are members of a frequently used, diverse compound library of the sort commonly used in the high-throughput screening (HTS) environment. Experiments were performed to determine the concentration of drug in solution above the precipitate, observe the time course and effect of various mixtures of solvents upon precipitation, measure the viscosity of cosolvents to determine compatibility with HTS, determine water absorption rates for various solvent combinations, and investigate resolubilization techniques to ensure proper drug solution for HTS. Recommendations are made on how to best maximize the probability that problem compounds will remain in solution, be accurately transferred during assay plate production, and, as a result, be accurately bioassayed at the specified molar concentration. ( Journal of Biomolecular Screening 2009:708-715)

flowCore: a Bioconductor package for high throughput flow cytometry

Background

Recent advances in automation technologies have enabled the use of flow cytometry for high throughput screening, generating large complex data sets often in clinical trials or drug discovery settings. However, data management and data analysis methods have not advanced sufficiently far from the initial small-scale studies to support modeling in the presence of multiple covariates.

Results

We developed a set of flexible open source computational tools in the R package flowCore to facilitate the analysis of these complex data. A key component of which is having suitable data structures that support the application of similar operations to a collection of samples or a clinical cohort. In addition, our software constitutes a shared and extensible research platform that enables collaboration between bioinformaticians, computer scientists, statisticians, biologists and clinicians. This platform will foster the development of novel analytic methods for flow cytometry.

Conclusion

The software has been applied in the analysis of various data sets and its data structures have proven to be highly efficient in capturing and organizing the analytic work flow. Finally, a number of additional Bioconductor packages successfully build on the infrastructure provided by flowCore, open new avenues for flow data analysis.

MIFlowCyt: the minimum information about a Flow Cytometry Experiment

A fundamental tenet of scientific research is that published results are open to independent validation and refutation. Minimum data standards aid data providers, users, and publishers by providing a specification of what is required to unambiguously interpret experimental findings. Here, we present the Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) standard, stating the minimum information required to report flow cytometry (FCM) experiments. We brought together a cross-disciplinary international collaborative group of bioinformaticians, computational statisticians, software developers, instrument manufacturers, and clinical and basic research scientists to develop the standard. The standard was subsequently vetted by the International Society for Advancement of Cytometry (ISAC) Data Standards Task Force, Standards Committee, membership, and Council. The MIFlowCyt standard includes recommendations about descriptions of the specimens and reagents included in the FCM experiment, the configuration of the instrument used to perform the assays, and the data processing approaches used to interpret the primary output data. MIFlowCyt has been adopted as a standard by ISAC, representing the FCM scientific community including scientists as well as software and hardware manufacturers. Adoptionof MIFlowCyt by the scientific and publishing communities will facilitate third-party understanding and reuse of FCM data.

Gating-ML: XML-based gating descriptions in flow cytometry

The lack of software interoperability with respect to gating due to lack of a standardized mechanism for data exchange has traditionally been a bottleneck, preventing reproducibility of flow cytometry (FCM) data analysis and the usage of multiple analytical tools. To facilitate interoperability among FCM data analysis tools, members of the International Society for the Advancement of Cytometry (ISAC) Data Standards Task Force (DSTF) have developed an XML-based mechanism to formally describe gates (Gating-ML). Gating-ML, an open specification for encoding gating, data transformations and compensation, has been adopted by the ISAC DSTF as a Candidate Recommendation. Gating-ML can facilitate exchange of gating descriptions the same way that FCS facilitated for exchange of raw FCM data. Its adoption will open new collaborative opportunities as well as possibilities for advanced analyses and methods development. The ISAC DSTF is satisfied that the standard addresses the requirements for a gating exchange standard.

Automated gating of flow cytometry data via robust model-based clustering

The capability of flow cytometry to offer rapid quantification of multidimensional characteristics for millions of cells has made this technology indispensable for health research, medical diagnosis, and treatment. However, the lack of statistical and bioinformatics tools to parallel recent high-throughput technological advancements has hindered this technology from reaching its full potential. We propose a flexible statistical model-based clustering approach for identifying cell populations in flow cytometry data based on t-mixture models with a Box-Cox transformation. This approach generalizes the popular Gaussian mixture models to account for outliers and allow for nonelliptical clusters. We describe an Expectation-Maximization (EM) algorithm to simultaneously handle parameter estimation and transformation selection. Using two publicly available datasets, we demonstrate that our proposed methodology provides enough flexibility and robustness to mimic manual gating results performed by an expert researcher. In addition, we present results from a simulation study, which show that this new clustering framework gives better results in terms of robustness to model misspecification and estimation of the number of clusters, compared to the popular mixture models. The proposed clustering methodology is well adapted to automated analysis of flow cytometry data. It tends to give more reproducible results, and helps reduce the significant subjectivity and human time cost encountered in manual gating analysis.

Data standards for flow cytometry

Flow cytometry (FCM) is an analytical tool widely used for cancer and HIV/AIDS research, and treatment, stem cell manipulation and detecting microorganisms in environmental samples. Current data standards do not capture the full scope of FCM experiments and there is a demand for software tools that can assist in the exploration and analysis of large FCM datasets. We are implementing a standardized approach to capturing, analyzing, and disseminating FCM data that will facilitate both more complex analyses and analysis of datasets that could not previously be efficiently studied. Initial work has focused on developing a community-based guideline for recording and reporting the details of FCM experiments. Open source software tools that implement this standard are being created, with an emphasis on facilitating reproducible and extensible data analyses. As well, tools for electronic collaboration will assist the integrated access and comprehension of experiments to empower users to collaborate on FCM analyses. This coordinated, joint development of bioinformatics standards and software tools for FCM data analysis has the potential to greatly facilitate both basic and clinical research--impacting a notably diverse range of medical and environmental research areas.

Data quality assessment of ungated flow cytometry data in high throughput experiments

BACKGROUND

The recent development of semiautomated techniques for staining and analyzing flow cytometry samples has presented new challenges. Quality control and quality assessment are critical when developing new high throughput technologies and their associated information services. Our experience suggests that significant bottlenecks remain in the development of high throughput flow cytometry methods for data analysis and display. Especially, data quality control and quality assessment are crucial steps in processing and analyzing high throughput flow cytometry data.

METHODS

We propose a variety of graphical exploratory data analytic tools for exploring ungated flow cytometry data. We have implemented a number of specialized functions and methods in the Bioconductor package rflowcyt. We demonstrate the use of these approaches by investigating two independent sets of high throughput flow cytometry data.

RESULTS

We found that graphical representations can reveal substantial nonbiological differences in samples. Empirical Cumulative Distribution Function and summary scatterplots were especially useful in the rapid identification of problems not identified by manual review.

CONCLUSIONS

Graphical exploratory data analytic tools are quick and useful means of assessing data quality. We propose that the described visualizations should be used as quality assessment tools and where possible, be used for quality control.

High-content flow cytometry and temporal data analysis for defining a cellular signature of graft-versus-host disease

Acute graft-versus-host disease (GVHD) is diagnosed by clinical and histologic criteria that are often nonspecific and typically apparent only after the disease is well established. Because GvHD is mediated by donor T cells and other immune effector cells, we sought to determine whether changes within a wide array of peripheral blood lymphocyte populations could predict the development of GvHD. Peripheral blood samples from 31 patients undergoing allogeneic blood and marrow transplant were analyzed for the proportion of 121 different subpopulations defined by 4-color combinations of lymphocyte phenotypic and activation markers at progressive time points posttransplant. Samples were processed using a newly developed high content flow cytometry technique and subjected to a spline- and functional linear discriminant analysis (FLDA)-based temporal analysis technique. This strategy identified a consistent posttransplant increase in the proportion and extent of fluctuation of CD3+CD4+CD8beta+ cells in patients who developed GVHD compared to those that did not. Although larger prospective clinical studies will be necessary to validate these results, this study demonstrates that high-content flow cytometry coupled with temporal analysis is a powerful approach for developing new diagnostic tools, and may be useful for developing a sensitive and specific predictive test for GVHD.

Discovery of protein phosphatase 2C inhibitors by virtual screening

Protein phosphatase 2C (PP2C) is an archetype of the PPM Ser/Thr phosphatases, characterized by dependence on divalent magnesium or manganese cofactors, absence of known regulatory proteins, and resistance to all known Ser/Thr phosphatase inhibitors. We have used virtual ligand screening with the AutoDock method and the National Cancer Institute Diversity Set to identify small-molecule inhibitors of PP2Calpha activity at a protein substrate. These inhibitors are active in the micromolar range and represent the first non-phosphate-based molecules found to inhibit a type 2C phosphatase. The compounds docked to three recurrent binding sites near the PP2Calpha active site and displayed novel Ser/Thr phosphatase selectivity profiles. Common chemical features of these compounds may form the basis for development of a PP2C inhibitor pharmacophore and may facilitate investigation of PP2C control and cellular function.

Screening for apoptosis???classical and emerging techniques

There has been a rapid development of cell-based assays and screening methods to identify promising apoptosis-inducing drug candidates for the treatment of cancer. Distinguishing between the complex processes involved in apoptosis and other forms of cell death requires information on both biochemical and morphological processes in the cell. Traditionally, many assays have been limited to measuring, for example, caspase activity using fluorogenic substrates. However, these screening assays provide only limited information on the complex processes involved in apoptosis. In this review we describe some of the available apoptosis assays amenable to high-throughput screening. In particular, image-based high-content screening assays to evaluate multiple biochemical and morphological parameters in apoptotic cells are described. Through combining the imaging of cells in microtiter plates with powerful image analysis algorithms, one can acquire deeper knowledge on multiple biochemical or morphological pathways at the single-cell level at an early stage in the development of novel anti-cancer drugs.