bu - wellesely igem 2011 world finals

Challenges

data

design deployment trial & error

time management

debugging

iterative design

com

ple

xity

manual error

standardization

sharing

automation

integration

specification high throughput

initial research

verification

speed

accuracy

Apply engineering principles to synthetic biology by utilizing user-centered design to build software tools that foster collaborative problem solving, support complex system design, and enable automation in the lab.

BU-Wellesley Software 2011

Our Vision

Workflow


User Centered Design


Preliminary User Studies

Position #

PIs 9

Postdocs 6

Industry Researchers 2

Student Researchers 12

Research Assistant 2

Master Student 1

Total 32

Goal Design requirements for synthetic biologists

Interview Procedure

1 hour interviews in laboratories

Interview Questions

Procedure walk-through Research goals Work practices Computational tools Future of the field

Data collection

Video Voice recordings Screenshots Observations

Qualitative Methods

• Affinity diagrams • Iterative coding

Institutions

• Boston University • Harvard Medical School • MIT • Wellesley College • Wyss Institute

Findings: User Study Results

BU - Wellesley Software

Findings: User Study Results

Alleviate Data Explosion

Integrate Workflow

Provide Multiple Forms of Evidence

Support from Novice to Expert

Facilitate Collaboration


“ ” By taking into account the collaborative process, tabletop software can help novices learn from

experts, making an invaluable impact on synthetic biology

-Natalie Kuldell, SynBERC


Optimus Primer

Multiplatform collaborative primer designer

Facilitates transition from novice to expert

Teaching Primer Design


Low-Fidelity Prototype


G-nome Surfer Pro & Optimus Primer


Evaluation


1. Usability of concrete interaction techniques 12 users

2. Usefulness for collaborative learning 20 users

3. Impact of an end-to-end solution iGEM 2012 wet lab team Advanced Biology seminar in Wellesley College

Evaluating Usefulness


Intermediate College-level Neuroscience Lab &

Synthetic Biology Lab at BU

Results

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NASA TLX & Engagement

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Collaborative Learning

G-nome Surfer Pro reduces subjective workload, improves collaboration, encourages reflection, and facilitates intuitive interaction.

Findings


Using Gnome Surfer in the Lab

Gnome Surfer Pro Pubmed research on Tuberculosis Gene selection from TB genome Sequence analysis Tuberculosis Genes

Rv2324 Rv3574 Rv3574 promoter Rv0324 Other genes Smeg6038 Smeg6042 Cre Dre Flp

Designing Primers

Optimus Primer Designed primers to amplify TB genes and generate BioBricks A subset of our primers is listed below

Genes Forward Primers Reverse Primers

RV2324 CGGCCGCTTCTAGATGGACCGCCTGGATGACACC CGGCCTACTAGTACTAGGGCGGCATGCGGTCG

Smeg6038 CGCCCGCTTCTAGAGCGGGGTGACCCTTTCTCTTC CCGCTACTAGTATGAATTGCCTCCCGGATCG

RV3574 GGCCGCTTCTAGAGCTTGCAGACCTCCGCGTCGA GGCCGCTACTAGTATTTCATGACCGCGCGAGGTG

RV0324 CGCGCGCTTCTAGATGGCTGGACAGTCCGATCG CGCCTGTAGATTCGCCGATGCCGTGGATA

RV3574 CGCCCGCTTCTAGATGGCGGTACTTGCCGAGTC TCGATGCGGCTGAACTCCCGACCCAGCGCCGAC

Smeg_6042 CGCGCTTCTAGATGACCAACGTGGCGGTTCTC CGATGCGTTCGAACTCGCGTCCGAGTGCCGAG


Synbio: General outlook • Biology is...

• Want to investigate complex interactions between genes

• Avoid large number of constructs

• Create sophisticated genetic circuits

• Generate a large state space


Trumpet: Configurable constructs • Can we build a configurable biological construct?

• Prior work

• Ham et al. five-state machine (2009)

• Friedland et al. three-state counter (2008)

• Our goal: a fully permutable construct

• Results:

• Two algorithms for designing such constructs

Part

Part

Invertase


Invertases

Trumpet: Configurable constructs • Two design algorithms:

• Pancake and Linksort

• Pancake operations

• Bring to head (BtH)

• Push into place (PiP)

• Complexity

• invertases, operations

• Implemented with nested invertase sites

• BtH: One site per part

• PiP: N sites per part

Trumpet generated designs


Link Sort

Pancake


Trumpet

Trumpet produces a permutable design using invertases

Trumpet


Invertase –sites Flp – frt

Dre – rox Cre – lox

Trumpet Generated a reconfigurable circuit with 2 TB genes and 3 invertase sites

Generating a Circuit Design with Trumpet

PuppetShow:

• 10 part BioBrick using current

software:

•200 lines of code

• 10 part Biobrickusing

PuppetShow:

•~ 20 lines


Define protocols Call function Robot moves

PuppetShow: features


• Define protocols and assembly programs

• Generates Puppeteer code automatically

• Optimizes labware allocation

• Saves samples and protocol history to database

• Maintains Puppeteer Protocol Repository


PuppetShow: Workflow Spec

Plan

Protocol

Macro

Instruction

Action

Robot #1 Ligation

volume: 17µL Colonies: 300+

Robot #2 Ligation

volume: 16.7µL Colonies: 300+

Manual Side-by-Side

Ligation Volume: 20µL Colonies: 300+

eLabNotebook


PuppetShow & eLabNotebook


Assembling DNA with PuppetShow

Puppet Show Run protocols for the DNA assembly of the genetic circuit using a liquid handling robot

Manual Lab Work Do the protocols manually to build the genetic circuit

M: MW Ladder 1: Uncut BioBrick 2: Manual trial 3-5: Robot trials

Future Work & Conclusion


Impact • Feasible to streamline experimental process through a suite of tools

• Facilitates collaborative learning support of novice users

• Developed and automated 2 different algorithms which place invertase sites through Clotho.

• Created user-friendly interface for automating protocols to a robot

• Successfully tested in the wet lab


The user interface is limiting in many fields. Designing software for synthetic biology with collaborative and

educational capabilities will help attract new blood to the field and provide those in the field with vital new design

perspectives. -George M. Church,

Harvard Medical School

“ ”

Acknowledgements BU: Daniel Dwyer, Jim Collins, and the Collins Lab, Andrew Krueger, James Galagan, and the Galagan Lab, Gretchen

Fougere, Assistant Dean of Outreach and Diversity

BBN Technologies: Aaron Aadler

JBEI: Josh Gilmore

JHU: Jef Boeke, Noah Young

MIT: Jonathan Babb and the Weiss Lab, Tiffany Huang, Louis Lamia and the MIT iGEM Team, Joy, Leanna, Paul, Shawn, and Shirley of the MIT iGEM team of 2010

Somerville High School: Chris Angelli

UC Berkeley: J. Christopher Anderson

Wellesley College: Catherine Summa, Wellesley College Science Center Summer Research, Yui Suzuki and the

Suzuki Lab

Wyss Institute: Avi Robinson-Mosher

Surface

Strengths

• Facilitates collaboration

• Promotes hands-on learning

• Education

• Tangible interface facilitates spatial organization of information

• Interface geared for novice researchers

Weaknesses

• Low-resolution display limits visualization capabilities

• Expensive

• Large footprint


Evaluating Problem Solving

• Quantitative measures

– Number and value of insights

– time per activity

– subjective workload

– attitude

– physical and verbal participation

– equality of participation

• Qualitative indicators

– collaboration style

– problem-solving strategy

– nature of discussion


Feedback from Users


Our discussions were able to get further with the help of the G-nome Surfer.

G-nome Surfer contributed most to my satisfaction because while I usually prefer to work alone, the teamwork felt effortless, natural, and fun.

G-nome Surfer really helped in examining the strengths and weaknesses of your own hypothesis with those of others in the group. Being able to see and compare researched data side-by-side was particularly useful.

It was very helpful in the sense that information was very easy to find and could be organized into places that are easily seen and used.

G-nome Surfer vs GSP
