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Development of a Screening Informa3cs System at the UNM Center for Molecular Discovery
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Jeremy Yang, Oleg Ursu, Stephen Mathias, Cristian Bologa, Anna Waller, Annette Evangelisti, Gergely Záhoransky-Köhalmi, and Tudor Oprea University of New Mexico, Albuquerque, New Mexico, USA
ACS National Meeting, San Diego, March 25-29, 2012
Intro to Flow Cytometry at UNMCMD
References: 1. Flow Cytometry Shi8ing Gears, Gene=c Eng & Biotech News, Nov 15, 2011 (Vol. 31, No. 20) , hJp://www.genengnews.com/gen-‐ar=cles/flow-‐cytometry-‐shi8ing-‐gears/3913.
2. Edwards BS, Young SM, Saunders MJ, Bologa C, Oprea TI, Ye RD, Prossnitz ER, Graves SW, Sklar LA. High-‐throughput flow cytometry for drug discovery. Expert Opin. Drug Discov. 2, 685-‐696, 2007.
3. Haynes MK, Strouse JJ, Waller A, Leitão A, Curpan RF, Bologa C, Oprea TI, Prossnitz ER, Edwards BS, Sklar LA, Thompson TA. Detec=on of intracellular granularity induc=on in prostate cancer cell lines by small molecules using the HyperCyt® high throughput flow cytometry system. J. Biomol. Screening, 14, 596-‐609, 2009
4. The NIH's Molecular Libraries Program -‐ What's Next? | SLAS Electronic Laboratory Neighborhood, hJp://www.eln.slas.org/story/1/52-‐the-‐nihs-‐molecular-‐libraries-‐program-‐whats-‐next.
Mul=plexed!
One of the primary mo=va=ons for cheminforma=cs has been drug discovery which involves bioassay screening and increasingly, high-‐throughput screening (HTS).
What is screening informa3cs? • Informa=cs in support of screening for biomolecular discovery, usually pharma discovery: Acquisi=on, processing and storage of bioassay data for use during projects and for retrospec=ve analyses. • Searching over molecules, assays, ac=vi=es, targets, etc. I/O & integra=on in conformance with contractual, legal/regulatory, business, and scien=fic requirements. • Applica=ons and interfaces suited to trans-‐disciplinary audience (biology, chemistry, pharmacology, medicine, etc.).
Screening Informa3cs ≠ Cheminforma3cs !! Cheminforma=cs is a key part of screening informa=cs but biology is primary. Plates, wells, samples, and measurements are physically real and informa=cally authorita=ve while structure data is a model which may be incorrect or imprecise. Chem-‐ and bio-‐ contexts must be integrated for successful system. E.g. EC50 = 1.7µM is about a sample, a well, a plate, an assay, a biological system… eventually we hope about a lead compound.
Why screening informa3cs?
Major challenges • New methodology, such as high-‐content and mul=plex bioassays • More data, internal and external • New privacy and collabora=on models • Advances in cheminforma=cs and bioinforma=cs methodology • Development concurrent with ongoing projects and deadlines requiring con=nually opera=onal system.
No shrink-‐wrapped solu3ons Due to the complexity of modern screening informa=cs, and in par=cular our novel, highly versa=le mul=plex flow-‐cytometry plasorm (patented, and commercialized as HyperCyt), there cannot be a shrink-‐wrapped solu=on providing all needed func=onality for all possible experiments.
Solu3on: hybrid, agile system of apps & APIs Heterogeneous so8ware components from (1) commercial vendors, (2) open source projects, and (3) custom code developed at UNM.
AEI & Pipeline Pilot & customiza3on A8er licensing the Accelrys Accord Enterprise Informa=cs (AEI) and Pipeline Pilot (PP) so8ware in 2009, efforts began to configure and customize AEI/PP. Accelrys-‐UNMCMD consulta=on, customiza=on and training, revealed (1) what components could be used with minor configura=on efforts, and (2) scope of required custom coding. This experience was essen=al and decisive in the evolu=onary design process.
UNMCMD specialized for flow cytometry
Automa3ng when every assay is special Flow cytometry generates mul=ple fluorescence measurements per sample and per target, where mul=plex = mul=-‐target. Even “singleplex” assays may employ mul=ple posi=ve and nega=ve control targets. Assays can differ greatly in raw data outputs and analysis protocols to calculate a “response” represen=ng a biological outcome (e.g. binding to a target). In some cases, it may seem more appropriate to conceive an API (programming interface) to recode each assay analysis rather than an informa=cs system, flexible but generally constant, and in fact, our solu=on combines elements of both.
Custom code: Using the right tools for the tasks Custom so8ware development has included: Oracle SQL w/ AEI, Excel macros, Perl, Java, Python, NCBI EntrezU=ls apps, custom PP protocols, Prism batch code, and more. Interfaces include command line apps, web apps, and in-‐house APIs for rapid development.
Conclusion The good news is that advances in so8ware and informa=cs provide choices of solu=ons and opportuni=es to effec=vely manage screening. The complexity of the so8ware landscape is truly both a challenge and opportunity. It is hoped that our experiences will be helpful to others similarly tasked with designing and implemen=ng a screening informa=cs system.
c/o Anna Waller, UNMCMD HyperViewSession_20110603
Accurate data acquisi3on key pre-‐requisite
Excel remains an important tool for scien=fic data processing, analysis and visualiza=on, at UNMCMD and elsewhere. But it has fundamental limita=ons and drawbacks, esp. data and code access and version control.
E.g. Bcl-‐2 assay analysis worksheets, UNMCMD,
2007 (PubChem AID=1693).
MicroSoP Excel, not going away soon
Screening informa=cs depends on accurate measurements with addi=onal informa=cs challenges, such as “binning”, i.e. correla=ng fluorescence data to wells and substances.
AEVA (Assay Explora3on, Viewing & Analysis) web app
PP protocol, via WebPort, to generate PubChem compliant depositor upload.
Hit Defini3on: various assays, various methods • Response: >(ac=va=on) or <(inhibi=on) cutoff • SD: >(ac=va=on) or <(inhibi=on) cutoff SDs from plate mean. • Custom: custom func=on specified for assays with "special needs“. Custom may include counter-‐targets, mul=ple +/-‐ controls, etc., etc.