ISSN: 0974-276X
Journal of Proteomics & Bioinformatics
Make the best use of Scientific Research and information from our 700+ peer reviewed, Open Access Journals that operates with the help of 50,000+ Editorial Board Members and esteemed reviewers and 1000+ Scientific associations in Medical, Clinical, Pharmaceutical, Engineering, Technology and Management Fields.
 
Meet Inspiring Speakers and Experts at our 3000+ Global Conferenceseries Events with over 600+ Conferences, 1200+ Symposiums and 1200+ Workshops on
Medical, Pharma, Engineering, Science, Technology and Business

Imaging Mass Spectrometry and Its Methodological Application to Murine Tissue

J.O.R. Gustafsson1, S. R. McColl2, P. Hoffmann1*
1Adelaide Proteomics Centre, School of Molecular and Biomedical Science, University of Adelaide, Adelaide,
  South Australia 5005
2Chemokine Laboratory, School of Molecular and Biomedical Science, University of Adelaide, Adelaide,
  South Australia 5005
Corresponding Author : Dr. Peter Hoffmann, Adelaide Proteomics Centre,
Gate 8 Victoria Drive, Molecular Life Sciences Building Rm 1.49,
University of Adelaide, Adelaide, South Australia 5005,
Tel   : (08) 8303 7521
Received September 09, 2008; Accepted November 02, 2008; Published December 05, 2008
Citation: Gustafsson JOR, McColl SR, Hoffmann P (2008) Imaging Mass Spectrometry and Its Methodological Application to Murine Tissue. J Proteomics Bioinform 1:458-463. doi:10.4172/jpb.1000053
Copyright: © 2008 Gustafsson JOR, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Related article at
DownloadPubmed DownloadScholar Google

Visit for more related articles at Journal of Proteomics & Bioinformatics

Abstract

Imaging mass spectrometry (IMS) is an emerging technology, pioneered by Prof. Richard Caprioli’s group starting more than a decade ago. In this study we have demonstrated the simplicity of initial technological set up for IMS experiments with commercially available automated matrix deposition, MALDI-TOF mass spectrometry instrumentation and data handling software for image generation. We have applied two different concepts of automated matrix deposition on Murine brain sections and discussed their different features and capabilities in IMS.

Keywords
MALDI; Mass spectrometry; Imaging; Tissue; Methodology
Abbreviations
IMS: Imaging Mass Spectrometry
Introduction
Proteomics has seen the development of even more complex and labour intensive methodologies and technologies, with increased qualitative and quantitative analytical power (Schmidt et al., 2005; Vanrobaeys et al., 2005; Mitulovic and Mechtler, 2006). As the workhorses of proteomics, two-dimensional gels and high performance liquid chromatography (HPLC) allow exquisite protein/peptide separation and thus in depth proteome analysis in high throughput formats (Vanrobaeys, et al., 2005). Such classical proteomics, however, require protein/ peptide sample solubilisation and treatment (E.g. precipitation, purification, labelling) prior to separation and downstream analysis by mass spectrometry [MS] (Schmidt et al., 2005; Vanrobaeys et al. 2005). Furthermore, studies seeking diagnostic markers typically use bodily fluids as the basis for investigation, raising the possibility of multiple high abundance species complicating analysis. Spatial information is also lost when solubilisation and protein separation are applied to tissue samples. In this light, it is not surprising that almost a decade ago direct MS analysis on tissue sections was pioneered by Caprioli et al (Caprioli et al., 1997; Chaurand et al., 2006). MS is now regularly being applied to in situ tissue analysis (Schwartz et al., 2003; Seeley et al., 2008; Stauber et al., 2008). Typically, tissue sections are washed in alcohol, dried and either a homogeneous layer or droplet array of matrix is applied (Schwartz et al., 2003). Direct MS desorption from the matrix cocrystallised tissue surface is then performed: predominantly with Matrix Assisted Laser Desorption/Ionisation (MALDI) sources (Seeley et al., 2008; Stauber et al., 2008). Prior knowledge of tissue composition is not necessary, hundreds if not thousands of masses can be measured rapidly and spatial distribution information is maintained (Chaurand et al., 2006). To date, IMS has been applied in several biological systems including rodent (Schwartz et al., 2003; Baluya et al., 2007; Groseclose et al., 2007) and crustacean brain (Dekeyser et al., 2007), rodent spinal cord (Monroe et al., 2008), liver (Seeley et al., 2008), testes, kidney (Herring et al., 2007) and skin (Bunch et al., 2004). Due to its relative infancy, IMS still requires optimisation of many of its component protocols, including those for section washing, effective and reproducible matrix deposition and processing the large volumes of data generated. Thus, although great progress has been made by several groups no standard IMS methodology has been defined.
With this is mind it was the objective to develop an IMS platform in our laboratory, focused on the imaging aspects of an IMS experiment prior to profiling applications for statistical model generation and potential diagnostic applications (Lemaire et al., 2007; Stauber et al., 2008). One of the most challenging aspects of IMS is the reproducible application of matrix on tissue sections. Three different commercial systems are currently available for automated matrix deposition, including the ImagePrep station (Bruker Daltonics), the CHIP-1000 printer (Shimadzu Biotechnology) and the Portrait 630 printer (Labcyte). The ImagePrep station uses vibrational vaporization to generate a matrix aerosol, which gently settles onto tissue samples. The CHIP-1000 and Portrait 630 are both picolitre range droplet printers capable of generating discrete matrix arrays on tissue sections. However, while the CHIP-1000 uses piezoelectric technology to forcefully eject droplets from a printer head, the Portrait 630 uses acoustic ejection of droplets from a liquid surface. We were able to successfully apply IMS to murine brain sections using both the CHIP- 1000 and the ImagePrep in conjunction with a ALDITOF- MS instrument and image generation software. Under these conditions a comparison between the two instruments using similar sagittal murine brain sections is provided in this communication. Continued optimisation of key methodological steps is still needed, including maintenance of tissue integrity, section washes, matrix solvent composition and matrix deposition strategy. However, we have shown that the technology can be implemented with commercially available instrumentation in a relatively short timeframe. The potential of this technology for future application in biomarker discovery and diagnostics looks extremely promising.
Experimental Methods Experimental Tissues and Solvents
Murine brain tissue was scavenged from on going experiments in the Chemokine laboratory at the University of Adelaide. All source experiments had full ethics approval from the University of Adelaide Ethics Committee. Solvents, acetonitrile (ACN) and methanol (MeOH) were HPLC grade (Merck, Damstadt, Germany). Ethanol (EtOH) and isopropanol (IPA) were analytical grade or higher (Merck). Trifluoroacetic acid (TFA) was purchased from Applied Biosystems (Foster City, CA). Sinapinic acid (SA) and peptide/ protein standards (ClinProT standards, Bruker Daltonics) used to calibrate the Ultra Flex III MALDI-TOF/ TOF mass spectrometer were purchased from Bruker Daltonics (Bremen, Germany).
Sample Preparation
Mice were sacrificed by carbon dioxide asphyxiation and tissues of interest were excised within ten minutes of sacrifice. Tissues were slow frozen in foil floated on liquid nitrogen (N2(l)) and transferred on dry ice to a -80°C freezer. Tissues were equilibrated to -20°C, followed by sectioning at -20°C (brain) or -18°C (other organs). Tissue was sectioned at a thickness of 10 μm with 35 x 80 mm blades in a Shandon cryotome (Thermo Electron, Pittsburgh, PA). Sections were mounted onto pre-chilled Indium Tin Oxide (ITO) slides (Bruker Daltonics) using heat from the operators hand applied underneath the slide. Mounted sections were desiccated for 45 minutes prior to washes for 60 seconds in 100ml of 70% EtOH or IPA followed by 60 seconds submerged in 100ml of 100% EtOH or IPA. Following washes sections were desiccated for 15 minutes. Use of IPA in washes was an alteration to protocols due to published data (Seeley et al., 2008).
Matrix Deposition – CHIP-1000
The CHIP-1000 piezo electric printer (Shimadzu Biotechnology, Kyoto, Japan) was operated as per manufacturer’s instructions to deposit 250 μm centre to centre arrays of SA matrix directly onto tissue sections. Dwell voltage and dwell time were modulated as necessary to maintain the quality of droplets for deposition. Prior to printing the piezo printer head was flushed with several volumes of 50% IPA. Following printing the piezo printer head was flushed with 200μl of 50% IPA and the outside rinsed with 50% IPA (3x), 100% MeOH (3x) and 100% ultra pure water (Resistivity 18.2 MW-cm, TOC < 1ppb) (3x). SA matrix at 10 mg/ml concentration in 50% ACN, 44.8% ultra pure water, 5% IPA and 0.2% TFA was used. Number of droplets and layers was variable.
Matrix Deposition – ImagePrep
The ImagePrep station (Bruker Daltonics) was operated as per manufacturer’s instructions to deposit homogeneous matrix layers onto tissue sections. SA at concentrations of 6, 8 and 10 mg/ml in 50% ACN, 5% IPA and 0.2% TFA were deposited using the default SA ImagePrep method (Bruker Daltonics). Microscopic slide images were captured using a Nikon pathology microscope connected to a digital camera.
MALDI-TOF Imaging Mass Spectrometry and Data Analysis
Slides for automated MALDI-TOF analysis were scanned at 1200 dpi using a Powerbook III PrePress Digital colour scanner (Amersham Biosciences, Soeborg, Denmark) controlled by Magic Scan software (version 4.6, UMAX). Slides were fitted into a Slide Adapter II MALDI target (Bruker Daltonics). An Ultra Flex III MALDITOF/ TOF mass spectrometer (Bruker Daltonics) operating in linear mode was used for IMS acquisition. Scanned slide images were loaded into Flex Imaging software (version 2.0, Bruker Daltonics), which was used to generate an auto execute sequence and set teach points for each individual IMS experiment. Homogeneous matrix layers generated by the ImagePrep were analysed at a raster suited to the quality of the preparation. Droplet arrays generated by the CHIP-1000 were analysed at a raster of the same size as the centre to centre droplet distance (250 μm). Auto execute parameters were set by Flex Control software (version 3.0, Bruker Daltonics) and a fixed laser power was selected by the operator. Results from IMS acquisition were observed in Flex Imaging and Flex Analysis software (version 3.0, Bruker Daltonics).
Results and Discussion
Stability of Imaging Mass Spectrometry Instrumentation Allows Successful Application
The IMS methodology is rather straightforward in that it involves use of tissue sections mounted on a conductive surface, which are washed in alcohol to fix protein and wash away contaminants, coated in matrix and analysed by MALDI-TOF MS. Established tissue washes were used for our applications, including simple washes in 70% EtOH or IPA and 100% EtOH or IPA (Schwartz et al., 2003; Seeley et al., 2008). The difference in terms of EtOH and IPA is marginal, but as demonstrated previously, IPA generates slightly better spectral data (Seeley et al., 2008). IMS requires automated matrix deposition: stability at this stage is critical to ensure reproducibility and prevent protein/peptide delocalisation due to matrix pooling on the section. The two automated systems, the Shimadzu CHIP-1000 Piezoelectric printer and the Bruker Daltonics ImagePrep station, were chosen for their availability and demonstration of applicability, both in the literature (Groseclose et al., 2007) and in practical terms. The CHIP-1000 has been utilised for experiments on Murine brain, as shown in Figure 1. The SA matrix crystals in Figure 1a were arranged in a 250 ìm centre to centre array coating the coronal Murine brain section and these array foci appeared as discrete, dark spots on the section surface. Printer stability was paramount, as instability leads to dispensing of droplets in multiple directions, interrupting the grid pattern, but more importantly, potentially causing random delocalisation of proteins and peptides. However, with fine modulation of piezoelectric voltage during printing, large droplet arrays, as shown in Figure 1a, were consistently deposited. Proper printer function was also found to be dependent on the stability of pressure lines feeding into the piezo unit and the condition/cleanliness of the external portions of the print head. These operations were also considered during fine tuning of the printing process and add to the complexity of the instrument. Furthermore, the matrix itself can generate problems in that SA, for example, can cause significant blockages of the piezo printing orifice at concentrations above 10 mg/ml. The ImagePrep station, which generates homogeneous matrix layers, maintains stability dependent on instrument specific methods, the condition of the piezo controlled nebulizer membrane as well as matrix concentration. In a trial of the instrument it was found that while 6 mg/ml SA can generate a homogeneous field of discrete matrix crystals, 10 mg/ml SA in an identical solvent mixture generates larger matrix foci, decreasing the possible resolution of the homogeneous spray preparation (Figure 1B and 1C respectively). Matrix blockages caused by crystallisation of SA on the nebulizer membrane do not have dramatic effects on spray quality until a significant portion (>50%) of the membrane surface is covered. Resolution, while limited in these examples to arrays of 250 μm or more using a CHIP-1000 printer (Figure 1a, 2A-D), was reduced to 70 ìm with the ImagePrep automated spray system (Figure 2e). Pending further experiments, however, it is unclear how comparable the two systems are in terms of reproducibility.
Imaging the Murine Brain at the Protein Level with the CHIP-1000 and ImagePrep
Rodent and in particular the Murine brain, was a logical start point for IMS experiments due to its well characterized symmetrical structure and ease of handling once frozen. From a single acquisition point in an IMS experiment anywhere from 100-400 masses can be observed with typical array spectra showing high signal to noise (S/N) values for numerous masses in the range of 5-30 kDa (Chaurand et al., 2006). And as shown in figures 2AD, masses analysed correlate to internal section structure. Similar results are generated for homogeneous matrix layers, but these are generally more difficult to reproduce because control over droplet deposition is lost (data not shown). With proper modulation of instrument settings for both the CHIP-1000 and ImagePrep station, ion intensity maps resulting from multiple successful MALDI-TOF tissue acquisitions were generated as shown in figures 2F and 2G respectively. These results are key proofs of principle: currently these experiments show potential biological significance, which can be verified with future experimental determination of mass/protein identity by LC-MS/MS.
Importantly, it is worth considering that the CHIP-1000 and ImagePrep, as a result of generating different crystal structures, become well suited to different modes of IMS. Droplet arrays are suited to low resolution protein profiling: where different tissue areas are rapidly scanned for identification of a tissue signature based upon molecular ion determinants (Yanagisawa et al., 2003). Homogeneous matrix layers on the other hand are suited to pure imaging experiments where high resolution tracking of a defined ion or initial tissue overview is needed. Figure 2f shows the ion maps corresponding to three different m/z-s and their spatial distribution across the tissue following acquisition from a printed droplet array. Compared to the ImagePrep data in Figure 2G, the low resolution seems to be a drawback of the CHIP-1000 matrix array. While high resolution is obtainable with the ImagePrep with a hands free automated system, the CHIP-1000 allows rapid deposition of multiple droplets in an array or single point format. Combined with histology, the printer systems are extremely well suited to rapid tissue profiling to provide molecular identification which complements classical pathology. Furthermore, the MS acquisition time for droplet arrays is far less than the high resolution spray preparations. A typical array coating a coronal Murine brain section at a raster of 250 μm (Figure 1a) takes approximately one hour to analyse by MALDITOFMS, where as a similar experiment using a 70 ìm raster or lower can take in excess of four hours. This limits high resolution IMS to the research laboratory until such a time when MALDI laser frequencies have increased by at least two fold.
Conclusion
IMS technology, although in its infancy compared to established proteomic methods, including HPLC and two dimensional gels, has shown and continues to show its extreme potential through numerous applications in biological systems. Our laboratory has set up and begun the process of evaluating the methodology for performing high quality IMS experiments using automated systems such as the CHIP-1000 printer and ImagePrep station for matrix deposition. As a result we have observed that both systems can be confidently applied to Murine brain tissue for the purpose of imaging, at both rapid medium resolution (CHIP- 1000) and high resolution (ImagePrep).
Acknowledgements
The authors would like to acknowledge Prof. Deon Venter at the Mater Hospital in Brisbane and Bruker Daltonics for use of the ImagePrep station. We would also like to thank Prof. Mark Baker at the Australian Proteome Analysis Facility (APAF) for arranging a loan of their CHIP-1000 instrument and Shimadzu Biotechnology for their application support with the instrument.
References
  1. Baluya DL, Garrett TJ, Yost RA (2007) Automated MALDI matrix deposition method with inkjet printing for imaging mass spectrometry. Anal Chem 79: 6862-7. » CrossRef   » PubMed   »  Google Scholar
  2. Bunch J, Clench MR, Richards DS (2004) Determination of pharmaceutical compounds in skin by imaging matrix-assisted laser desorption/ionisation mass spectrometry. Rapid Commun Mass Spectrom 18: 3051-60. » CrossRef   » PubMed   »  Google Scholar

  3. Caprioli RM, Farmer TB, Gile J (1997) Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS. Anal Chem 69: 4751-60. » CrossRef   » PubMed   »  Google Scholar
  4. Chaurand P, Norris JL, Cornett DS, Mobley JA, Caprioli RM (2006) New developments in profiling and imaging of proteins from tissue sections by MALDI mass spectrometry. J Proteome Res 5: 2889- 900. » CrossRef   » PubMed   »  Google Scholar
  5. Dekeyser SS, Kutz NKK, Schmidt JJ, Barrett-Wilt GA, Li L (2007) Imaging mass spectrometry of neuropeptides in decapod crustacean neuronal tissues. J Proteome Res 6: 1782-91. » CrossRef   » PubMed   »  Google Scholar
  6. Groseclose MR, Andersson M, Hardesty WM, Caprioli RM (2007) Identification of proteins directly from tissue: in situ tryptic digestions coupled with imaging mass spectrometry. J Mass Spectrom 42: 254-62. » CrossRef   » PubMed   »  Google Scholar
  7. Herring KD, Oppenheimer SR, et al. (2007) Direct issue analysis by matrixassisted laser desorption ionization mass spectrometry: application to kidney biology. Semin Nephrol 27: 597-608. » CrossRef   » PubMed   »  Google Scholar
  8. Lemaire R, Menguellet SA, Stauber J, Marchaudon V, Lucot JP, et al. (2007) Specific MALDI imaging and profiling for biomarker hunting and validation: fragment of the 11S proteasome activator complex, Reg alpha fragment, is a new potential ovary cancer biomarker. J Proteome Res 6: 4127-34. » CrossRef   » PubMed   »  Google Scholar
  9. Mitulovic G, Mechtler K (2006) HPLC techniques for proteomics analysis-a short overview of latest developments. Brief Funct Genomic Proteomic 5: 249-60. » CrossRef   » PubMed   »  Google Scholar
  10. Monroe EB, Annangudi SP, Hatcher NG, Gutstein HB, Rubakhin SS, et al. (2008) SIMS and MALDI MS imaging of the spinal cord. Proteomics 8: 1-9. » CrossRef   » PubMed   »  Google Scholar
  11. Schmidt A, Kellermann J, Lottspeich F (2005) A novel strategy for quantitative proteomics using isotope-coded protein labels. Proteomics 5: 4-15. » CrossRef   » PubMed   »  Google Scholar
  12. Schwartz SA, Reyzer ML, Caprioli RM (2003) Direct tissue analysis using matrix-assisted laser desorption/ionization mass spectrometry: practical aspects of sample preparation. J Mass Spectrom 38: 699-708. » CrossRef   » PubMed   »  Google Scholar
  13. Seeley EH, Oppenheimer SR, Mi D, Chaurand P, Caprioli RM (2008) Enhancement of Protein Sensitivity for MALDI Imaging Mass Spectrometry After Chemical Treatment of Tissue Sections. J Am Soc Mass Spectrom. » CrossRef   » PubMed   »  Google Scholar
  14. Stauber J, Lemaire R, Franck J, Bonnel D, Croix D, et al. (2008) MALDI Imaging of Formalin-Fixed Paraffin-Embedded Tissues: Application to Model Animals of Parkinson Disease for Biomarker Hunting. J Proteome Res. » CrossRef   » PubMed   »  Google Scholar
  15. Vanrobaeys F, Van Coster R, Dhondt G, Devreese B, Van Beeumen J (2005) Profiling of myelin proteins by 2D-gel electrophoresis and multidimensional liquid chromatography coupled to MALDI TOF-TOF mass spectrometry. J Proteome Res 4: 2283- 93. » CrossRef   » PubMed   »  Google Scholar
  16. Yanagisawa K, Shyr Y, Xu BJ, Massion PP, Larsen PH, et al. (2003) Proteomic patterns of tumour subsets in nonsmall-cell lung cancer. Lancet 362: 433-9. » CrossRef   » PubMed   »  Google Scholar
Select your language of interest to view the total content in your interested language
 
Share This Article
   
 
   
 
Relevant Topics
Disc Applications of Bioinformatics
Disc Bacterial transcriptome
Disc Bioinformatics Algorithms
Disc Bioinformatics Databases
Disc Bioinformatics Tools
Disc Cancer Pharmacogenomics
Disc Cancer Proteomics
Disc Clinical Pharmacogenomics
Disc Clinical Proteomics
Disc Cluster analysis
Disc Comparative genomics
Disc Comparative proteomics
Disc Comparative transcriptomics
Disc Computational drug design
Disc Current Proteomics
Disc Data algorithms
Disc Data mining applications in genomics
Disc Data mining applications in proteomics
Disc Data mining in drug discovery
Disc Data mining tools
Disc Data modelling and intellegence
Disc Data warehousing
Disc Drug Dosage Formulations
Disc Drug Toxicity and Efficacy
Disc Epigenetics
Disc Epigenomic studies
Disc Gene Expression profiling
Disc Gene polymorphism
Disc Genome annotation
Disc Genomic Targets
Disc Genomic data mining
Disc Genomic data warehousing
Disc Glycome
Disc Human Proteome Project Applications
Disc Immune Disorders
Disc Individualized Medicine
Disc Mapping of genomes
Disc Mass Spectrometry in Proteomics
Disc Meta genomics
Disc Metabolome
Disc Microarray
Disc Microarray Proteomics
Disc Molecular and Cellular Proteomics
Disc Mouse transcriptome
Disc Non coding MRNA
Disc Personalized Medicine Studies
Disc Pharmacoeconomics in Drug Development
Disc Pharmacogenetics
Disc Pharmacogenomic Biomarker
Disc Pharmacogenomics Applications
Disc Pharmacogenomics Future Medicine
Disc Pharmacogenomics and Personalized Medicine
Disc Pharmacogenomics for Patient Care
Disc Pharmacoproteomics in Drug development
Disc Profiling
Disc Protein Sequence Analysis
Disc Protein engineering
Disc Proteogenomics
Disc Proteome
Disc Proteome Profiling
Disc Proteomic Analysis
Disc Proteomic Biomarkers
Disc Proteomics Clinical Applications
Disc Proteomics Research
Disc Proteomics Science
Disc Proteomics and Pharmacodynamics
Disc Proteomics data warehousing
Disc Python for Bioinformatics
Disc Quantitative Proteomics
Disc RNA sequencing
Disc RNA sequencing and analysis
Disc Sequencing
Disc Small RNA Sequencing
Disc Statistical data mining
Disc Transcripotme
Disc Transcriptional Attenuation
Disc Transcriptional Regulation
Disc Transcriptome analysis
Disc Translational Medicine
 
Recommended Journals
Disc Transcriptomics Journal
Disc Pharmacogenomics Journal
Disc Data Mining Journal
  View More»
 
Recommended Conferences
Disc 6th Bioinformatics Conference
August 22-23, 2016 Philadelphia, Pennsylvania, USA
Disc 7th International Conference and Expo on Proteomics
October 24-26, 2016 Rome, Italy
View More»
 
Article Tools
Disc Export citation
Disc Share/Blog this article
 
Article usage
  Total views: 11166
  [From(publication date):
December-2008 - May 27, 2016]
  Breakdown by view type
  HTML page views : 7433
  PDF downloads :3733
 
 

Post your comment

captcha   Reload  Can't read the image? click here to refresh

 
OMICS International Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
 
 
OMICS International Conferences 2016-17
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings
 
 

Contact Us

Agri, Food, Aqua and Veterinary Science Journals

Dr. Krish

agrifoodaquavet@omicsinc.com

1-702-714-7001 Extn: 9040

Clinical and Biochemistry Journals

Datta A

clinical_biochem@omicsinc.com

1-702-714-7001Extn: 9037

Business & Management Journals

Ronald

business@omicsinc.com

1-702-714-7001Extn: 9042

Chemical Engineering and Chemistry Journals

Gabriel Shaw

chemicaleng_chemistry@omicsinc.com

1-702-714-7001 Extn: 9040

Earth & Environmental Sciences

Katie Wilson

environmentalsci@omicsinc.com

1-702-714-7001Extn: 9042

Engineering Journals

James Franklin

engineering@omicsinc.com

1-702-714-7001Extn: 9042

General Science and Health care Journals

Andrea Jason

generalsci_healthcare@omicsinc.com

1-702-714-7001Extn: 9043

Genetics and Molecular Biology Journals

Anna Melissa

genetics_molbio@omicsinc.com

1-702-714-7001 Extn: 9006

Immunology & Microbiology Journals

David Gorantl

immuno_microbio@omicsinc.com

1-702-714-7001Extn: 9014

Informatics Journals

Stephanie Skinner

omics@omicsinc.com

1-702-714-7001Extn: 9039

Material Sciences Journals

Rachle Green

materialsci@omicsinc.com

1-702-714-7001Extn: 9039

Mathematics and Physics Journals

Jim Willison

mathematics_physics@omicsinc.com

1-702-714-7001 Extn: 9042

Medical Journals

Nimmi Anna

medical@omicsinc.com

1-702-714-7001 Extn: 9038

Neuroscience & Psychology Journals

Nathan T

neuro_psychology@omicsinc.com

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

John Behannon

pharma@omicsinc.com

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

social_politicalsci@omicsinc.com

1-702-714-7001 Extn: 9042

 
© 2008-2016 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version