Michael J Lombardi

Harvard University, Cambridge, Massachusetts, United States

Are you Michael J Lombardi?

Claim your profile

Publications (15)108.56 Total impact

  • Source
    Dataset: Figure S3
    [Show abstract] [Hide abstract]
    ABSTRACT: High throughput droplet patterning system, images of printed droplet array. One hundred droplets were inspected for target homogeneous droplet sorting. (a–d) droplet array was generated under four different conditions, (a) 1×105 cells/ml with 10% target cell concentration, (b) 1×105 cells/ml with 50% target cell concentration, (c) 2×105 cells/ml with 10% target cell concentration, (d) 2×105 cells/ml with 50% target cell concentration. Scale bar, 1 mm. (TIF)
    Preview · Dataset · Mar 2011
  • Source
    Dataset: Figure S1
    [Show abstract] [Hide abstract]
    ABSTRACT: Homogeneous single cell droplet sorting system. A computerized xyz stage was synchronized with a pulse controller, Labview™. The automated stage positioned the substrate with 5 µm spatial resolution. Two ejectors and a 10× camera permitted in-situ imaging and lysing of the droplets. Schematic of droplet ejector showed cells flowing into the valve driven by a controlled air pressure pulse (34 kPa for 55 µs). A heterogeneous sample, mixture of cells and media solution, was loaded into a reservoir. Each droplet was placed at a predetermined position. (TIF)
    Preview · Dataset · Mar 2011
  • Source
    Dataset: Figure S5
    [Show abstract] [Hide abstract]
    ABSTRACT: Probability of encapsulating a single target cell in a droplet was presented by probability distribution functions, P(X = Xsingle target cell). (a) The number of homogeneous droplets was modeled using Poisson distribution in a random variable space, i.e. number of target cells. The model was verified using a coefficient, λ, and experimental results. (b) According to four different cell loading concentrations and target cell concentrations, 16 Poisson distributions resulting from 4 cases of concentration times 4 cases of target cell mixture concentrations and their coefficients, λ, were obtained comparing to experimental results. As cell loading density increases, target cell concentration, λ values increase, λmax = 0.95 and λmin = 0.03. Based on the analysis, statistical models for 1.0×105 cells/ml with 10% target cell mixture were based on λ = 0.05. (TIF)
    Preview · Dataset · Mar 2011
  • Source
    Dataset: Figure S4
    [Show abstract] [Hide abstract]
    ABSTRACT: Pre- and post-patterning cell viability. (a) Normalized cell viability was obtained comparing the two viabilities. Average and standard deviation of normalized viability were 96.4±0.8%, 97.9±2.3%, 97.2±2.2%, and 96.0±2.4% from 0.5×105 to 2×105 cells/ml of cell loading concentrations (n = 3 sets left y-axis reference). (b) Pre-patterning (flask) viabilities were measured based on 200 cells in a 10 µl sample volume. Post-print cell viabilities were obtained from 2500 droplets for each cell loading concentration, i.e. 70 cells at 0.5×105 cells/ml and 575 cells at 2×105 cells/ml. Overall mean and standard deviation of pre- and post-printing cell viabilities were 96.7±0.5% and 93.8±1.1%, respectively (right hand y-axis). (TIF)
    Preview · Dataset · Mar 2011
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Technologies that rapidly isolate viable single cells from heterogeneous solutions have significantly contributed to the field of medical genomics. Challenges remain both to enable efficient extraction, isolation and patterning of single cells from heterogeneous solutions as well as to keep them alive during the process due to a limited degree of control over single cell manipulation. Here, we present a microdroplet based method to isolate and pattern single cells from heterogeneous cell suspensions (10% target cell mixture), preserve viability of the extracted cells (97.0±0.8%), and obtain genomic information from isolated cells compared to the non-patterned controls. The cell encapsulation process is both experimentally and theoretically analyzed. Using the isolated cells, we identified 11 stem cell markers among 1000 genes and compare to the controls. This automated platform enabling high-throughput cell manipulation for subsequent genomic analysis employs fewer handling steps compared to existing methods.
    Full-text · Article · Mar 2011 · PLoS ONE
  • Source
    Dataset: Figure S2
    [Show abstract] [Hide abstract]
    ABSTRACT: Controlling droplet size. Image and illustration of ejected droplet in air were shown. (a) Stroboscopic images of ejected droplets. When the valve opening time and the gas pressure is not optimized, we observed satellite droplets. The sequential images were taken every second. (b) Stable droplets, Dair = 245±12 µm (V≈7.7±1.2 nl), were generated during optimized ejection: i.e. 55 µs valve opening time, 34.4 kPa pressurized nitrogen gas, and 25 Hz ejection frequency. The droplet size was measured at 2.3 mm distance from the ejector. (c) Droplet size at bottom surface. After landing on the surface, the diameter of the ejected droplet was determined by the surface tension and droplet volume. Hdroplet = 68±2 µm, Ddroplet = 525±15 µm, (V≈7.6±0.6 nl). Scale bars are 1 mm in a and b, 100 µm in c, respectively. (TIF)
    Preview · Dataset · Mar 2011
  • Source
    Dataset: Table S1
    [Show abstract] [Hide abstract]
    ABSTRACT: Statistical modeling results for drop-on-demand target single cell encapsulation. (a) Randomness of process was verified by three variables, number of samples (n), tolerance (ε), and confidence level (1−α) using an inequality(**). Following the law of large numbers (LLN), minimum sample number was decided as 100 droplets for 90% confidence level and 15% tolerance. This sampling volume of a droplet represented (0.76 µl = 10×10×7.6 nl) 0.76% of the total volume of the ejection reservoir (0.1 mL). (b) Random processes have different probability distribution functions in accordance with their parameters, i.e. number of cell containing droplets (Xdrop), number of cells in a droplet (Xcell), number of target cells per droplet (Xtarget cell), and number of single target cell containing droplets (Xsingle target cell drop). These four different random variables are represented by three PDFs to statistically model the cell encapsulation process, i.e. binomial, Poisson, and normal distributions. We investigated probability values and parameters, λ, for each case with respect to the cell loading concentrations, cell volume fraction, and percentage of target cells. (c) In the case of simple random sampling (SRS) process, statistical characteristics of a small sampling volume could represent the characteristics of a large population based on the central limit theorem (CLT). In our experiments, the target cell fraction (F%) shows same concentration as the reservoir concentration for 10% to 50% at 1.0×105 cells/ml concentration (Copt) under conditions of 90% confidence level and 15% tolerance. (DOCX)
    Preview · Dataset · Mar 2011
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.
    Full-text · Article · Oct 2006 · Nature Biotechnology
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Over the last decade, gene expression microarrays have had a profound impact on biomedical research. The diversity of platforms and analytical methods available to researchers have made the comparison of data from multiple platforms challenging. In this study, we describe a framework for comparisons across platforms and laboratories. We have attempted to include nearly all the available commercial and 'in-house' platforms. Using probe sequences matched at the exon level improved consistency of measurements across the different microarray platforms compared to annotation-based matches. Generally, consistency was good for highly expressed genes, and variable for genes with lower expression values as confirmed by quantitative real-time (QRT)-PCR. Concordance of measurements was higher between laboratories on the same platform than across platforms. We demonstrate that, after stringent preprocessing, commercial arrays were more consistent than in-house arrays, and by most measures, one-dye platforms were more consistent than two-dye platforms.
    Full-text · Article · Aug 2006 · Nature Biotechnology
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The hypothesis tested in the study was that the effect of estrogen and progesterone on the lacrimal gland is mediated through specific receptors and that hormonal effects involve the regulation of gene expression and protein synthesis. Lacrimal glands were collected from young adult, ovariectomized mice, that were treated with 17beta-estradiol, progesterone, 17beta-estradiol plus progesterone or vehicle for 2 weeks. Glands were pooled according to treatment, processed for the isolation of RNA, and evaluated for differentially expressed mRNAs by using gene microarrays. Bioarray data were analyzed with sophisticated bioinformatics and statistical programs. The expression of selected genes was verified by using gene chips and quantitative real-time PCR methods. The results demonstrate that 17beta-estradiol, progesterone, or both hormones together significantly influences the expression of hundreds of genes in the mouse lacrimal gland. Sex steroid treatment led to numerous alterations in gene activities related to transcriptional control, cell growth and/or maintenance, cell communication, signal transduction, enzyme catalysis, immune expression, and the binding and metabolism of nucleic acids and proteins. A number of the 17beta-estradiol, progesterone or 17beta-estradiol plus progesterone effects on gene expression were similar, but most were unique to each treatment. Of particular interest was the finding that these hormones seem to contribute little to the known sex-related differences in gene expression of the lacrimal gland. These results support the hypothesis that estrogen's and progesterone's action on the lacrimal gland involves the regulation of numerous genes. However, these hormone effects do not appear to represent a major factor underlying the sexual dimorphism of gene expression in lacrimal tissue.
    Full-text · Article · Feb 2006 · Investigative Ophthalmology & Visual Science
  • [Show abstract] [Hide abstract]
    ABSTRACT: Significant, sex-associated differences exist in the physiology and pathophysiology of the lacrimal gland. We hypothesize that many of these differences are due to fundamental variations in gene expression. The purpose of this study was to determine the extent to which sex-related differences in gene expression are present in the lacrimal gland. Lacrimal glands were obtained from adult male and female BALB/c mice (n=5-10mice/sex/experiment), pooled according to sex and processed for the isolation of RNA. Samples were analyzed for differentially expressed mRNAs by using Atlas Mouse cDNA Expression Arrays, cDNA amplification techniques, GEM 1 and 2 gene chips, CodeLink bioarrays and quantitative real-time PCR (qPCR) procedures. Quantitative evaluation of Atlas Array gene expression was performed with an image analysis system developed in our laboratory, whereas gene chip data were analyzed with Rosetta Resolver and GeneSifter.Net software. Statistical significance was determined by using Student's t-test. Our results with CodeLink bioarrays show that sex has a significant influence on the expression of over 490 genes in the mouse lacrimal gland. These genes are involved in a wide range of biological processes, molecular functions and cellular components, including such activities as development, growth, transcription, metabolism, signal transduction, transport, receptor activity and protein and nucleic acid binding. The expression of selected genes was confirmed by the use of GEM gene chips and qPCR. Our findings also demonstrate that certain methodological approaches are less useful in attempting to assess the magnitude of sex-associated differences in the lacrimal gland. These results support our hypothesis that sex-related differences in gene expression play a role in the sexual dimorphism of the lacrimal gland.
    No preview · Article · Feb 2006 · Experimental Eye Research
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In prior work, it has been found that the meibomian gland is an androgen target organ, that androgens modulate lipid production within this tissue, and that androgen deficiency is associated with glandular dysfunction and evaporative dry eye. This study's purpose was to test the hypothesis that the androgen control of the meibomian gland involves the regulation of gene expression. Meibomian glands were obtained from orchiectomized mice that were treated with placebo or testosterone for 14 days. Tissues were processed for the analysis of differentially expressed mRNAs by using gene bioarrays, gene chips, and real-time PCR procedures. Bioarray data were analyzed with GeneSifter software (VizX Labs LLC, Seattle, WA). The results show that testosterone influenced the expression of more than 1590 genes in the mouse meibomian gland. This hormone action involved a significant upregulation of 1080 genes (e.g., neuromedin B), and a significant downregulation of 518 genes (e.g., small proline-rich protein 2A). Some of the most significant androgen effects were directed toward stimulation of genes associated with lipid metabolism, sterol biosynthesis, fatty acid metabolism, protein transport, oxidoreductase activity, and peroxisomes. These findings demonstrate that testosterone regulates the expression of numerous genes in the mouse meibomian gland and that many of these genes are involved in lipid metabolic pathways.
    Full-text · Article · Nov 2005 · Investigative Ophthalmology & Visual Science
  • [Show abstract] [Hide abstract]
    ABSTRACT: The objective of this study was to determine the nature and extent of androgen influence on gene expression in the lacrimal gland. Lacrimal glands were obtained from orchiectomized mice that had been treated with testosterone or vehicle for 2 weeks, as well as from testicular feminized mice and their Tabby controls. Samples were pooled according to experiment, processed for the isolation of RNA, and analyzed for differentially expressed mRNAs by using primarily CodeLink Bioarrays, GEM 1 and 2 gene chips and quantitative real-time PCR (qPCR) procedures. Gene chip data were analyzed with GeneSifter.Net software. Our results demonstrate that testosterone regulates the expression of over 2000 genes in the lacrimal gland. Gene ontologies most affected by androgen treatment included those related to cell growth, proliferation and metabolism, cell communication and transport, nucleic acid binding, signal transduction and receptor activities. Our findings also indicate that androgen action may be mediated, at least in part, through classical androgen receptors, and may contribute to the sex-related differences in gene expression of lacrimal tissue. Overall, these results support our working hypothesis that androgen action on the lacrimal gland is mediated primarily through a receptor-associated regulation of gene transcription.
    No preview · Article · Oct 2005 · The Journal of Steroid Biochemistry and Molecular Biology
  • [Show abstract] [Hide abstract]
    ABSTRACT: Sex-related differences exist in the structure and function of the major glands in a variety of species. Moreover, many of these variations appear to be unique to each tissue. We hypothesized that this sexual dimorphism is due, at least in part, to gland-specific differences in gene expression between males and females. Glands were collected from male and female BALB/c mice (n = 5/sex/experiment), and total RNA was isolated. Samples were analyzed for differentially expressed mRNAs with CodeLink microarrays, and data were evaluated by GeneSifter. Our results demonstrate that significant (P < 0.05) sex-related differences exist in the expression of numerous genes in the major salivary glands, and many of these differences were tissue-specific. These findings support our hypothesis that sex-related differences in the salivary glands are due, at least in part, to tissue-specific variations in gene expression.
    No preview · Article · Mar 2005 · Journal of Dental Research

  • No preview · Article · Jul 2004 · Neurobiology of Aging

Publication Stats

2k Citations
108.56 Total Impact Points

Institutions

  • 2011
    • Harvard University
      Cambridge, Massachusetts, United States
  • 2005-2006
    • Brigham and Women's Hospital
      • Center for Neurologic Diseases
      Boston, Massachusetts, United States
    • University of Massachusetts Boston
      • Department of Physics
      Boston, Massachusetts, United States