Post-doctoral Research Scholar in the Developmental Studies Hybridoma Bank; Dr. David Soll’s laboratory in the Department of Biology at the University of Iowa

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Post-doctoral Research Scholar in the Developmental Studies Hybridoma Bank; Dr. David Soll’s laboratory in the Department of Biology at the University of Iowa

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Post-doctoral Research Scholar in the Developmental Studies Hybridoma Bank; Dr. David Soll’s laboratory in the Department of Biology at the University of Iowa
100% time position  - Salary is commensurate with prior research experience and NIH guidelines.
Position Description: The Developmental Studies Hybridoma Bank (DSHB) (http://dshb.biology.uiowa.edu/) housed in the Department of Biology at the University of Iowa and directed by David R. Soll invites applications for a post-doctoral research scholar. Using unique 4D reconstruction software and 4D imaging capabilities developed in our W.M. Keck Dynamic Image Analysis Facility laboratory (https://biology.uiowa.edu/keck) [1-4], we have analyzed cells embedded in a 3D Matrigel matrix [6,7,9,10] and discovered that tumorigenic cell lines as well as cells isolated from patient tumors undergo coalescence to form model tumors mediated by specialized cells [6,7,10]. Non-tumorigenic cells and cells derived from normal tissue do not undergo coalescence [6,7,10]. We have observed coalescence in every tumor tissue and tumorigenic cell line so far examined and have identified coalescence in histological preparations of melanoma [10]. Hence, coalescence may be a heretofore unrecognized mechanism of tumor growth and an underlying cause of tumor heterogeneity. We have begun to exploit the commonality of coalescence as a characteristic of cancer cells to screen for potential anti-tumorigenic mAbs [10], using the extensive collection of close to 6,000 mAbs available through the DSHB.  We have already identified several potential candidates. We are expanding our model to test mAbs within the tumor microenvironment in order to identify additional mAbs with potential for cancer therapy. The position will broadly focus on analysis of interactions between cancer cells, stromal cells and immune cells within the microenvironment in 3D co-cultures using 3D and 4D imaging systems, animal models and molecular biology technologies. The successful applicant will also work with a team to generate high quality mAbs [5,8] against tumorigenesis targets. Stages of production will include designing peptides, injecting mice, performing B cell/myeloma cell fusions, selecting positive clones and characterizing the mAb.

Required Qualifications:
Ph.D in Biology or a related field.
Prior experience in cell biology, immunostaining, confocal and multi-photon microscopy, digital videomicroscopy, and image analysis, and familiarity with molecular biology techniques
Documented record of publications
Written and verbal communication skills

Desirable Qualifications:
Previous experience with monoclonal antibody (mAb) techniques, immunology, FACS, molecular biology and cancer biology, including the use of mammalian models.

To apply for this position, requisition number 2782, go to http://jobs.uiowa.edu/
The University of Iowa is an equal opportunity/affirmative action employer. All qualified applicants are encouraged to apply and will receive consideration for employment free from discrimination on the basis of race, creed, color, national origin, age, sex, pregnancy, sexual orientation, gender identity, genetic information, religion, associational preference, status as a qualified individual with a disability, or status as a protected veteran.

References:
1.  Soll D, Voss E. Two and three dimensional computer systems for analyzing how cells crawl. In: Soll D, Wessels D, editors. Motion Analysis of Living Cells: John Wiley, Inc 1998. p. 25-52.
2.  Soll DR, Wessels D, Voss E, Johnson O. 2001. Computer-assisted systems for the analysis of amoeboid cell motility. Meth. Molec. Biol. 161:45-58. PubMed PMID: 11190516.
3.  Soll DR, Wessels D, Heid PJ, Voss E. 2003. Computer-assisted reconstruction and motion analysis of the three-dimensional cell. Sci. World J. 3:827-41. doi: 10.1100/tsw.2003.70.
4.  Soll DR, Voss E, Wessels D, Kuhl S. 2007. Computer-Assisted systems for Dynamic 3D Reconstruction and Motion Analysis of Living Cells. In: Shorte S, Frischknecht F, editors. Imaging Cellular and Molecular Biological Functions. Principles and Practice: Springer Berlin Heidelberg. p. 365-84.
5.   Sanchez P, Daniels KJ, Park YN, Soll DR. 2014. Generating a battery of monoclonal antibodies against native green fluorescent protein for immunostaining, FACS, IP, and ChIP using a unique adjuvant. Monoclonal antibodies in immunodiagnosis and immunotherapy. 33(2):80-8. doi: 10.1089/mab.2013.0089.
6.  Scherer A, Kuhl S, Wessels D, Lusche DF, Hanson B, Ambrose J, et al. 2015. A computer-assisted 3D model for analyzing the aggregation of tumorigenic cells reveals specialized behaviors and unique cell types that facilitate aggregate coalescence. PLoS ONE. 10(3):e0118628. doi: 10.1371/journal.pone.0118628.
7.  Ambrose J, Livitz M, Wessels D, Kuhl S, Lusche DF, Scherer A, et al. 2015. Mediated coalescence: a possible mechanism for tumor cellular heterogeneity. Amer. J. Cancer Res. 5(11):3485-504. PubMed PMID: 26807328; PubMed Central PMCID: PMCPMC4697694.
8.  Park YN, Glover RA, Daniels KJ, Soll DR. 2016. Generation and validation of monoclonal antibodies against the maltose binding protein. Monoclonal Antibodies in Immunodiag. Immunother. 35(2):104-8. doi: 10.1089/mab.2015.0072. PubMed PMID: 26982821; PubMed Central PMCID: PMCPMC4845686.
9.  Kuhl S, Voss E, Scherer A, Lusche DF, Wessels D, Soll DR. 2016. 4D Tumorigenesis model for quantitating coalescence, quantitating directed cell motility and chemotaxis, identifying unique cell behaviors and testing anti-cancer drugs. In: Hereld D, Jin T, editors. Chemotaxis: Methods and Protocols: Springer.
10.  Wessels D, Lusche DF, Voss E, Kuhl S, Buchele EC, Klemme MR, et al. 2017. Melanoma cells undergo aggressive coalescence in a 3D Matrigel model that is repressed by anti-CD44. PLoS One. 12(3):e0173400. doi: 10.1371/journal.pone.0173400. PubMed PMID: 28264026; PubMed Central PMCID: PMCPMC5338862.



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