Metrology for Mammalian Synthetic
Modularity is one of the fundamental tenets of synthetic biology: the
notion that we can effectively engineer biological organisms by
combining or modifying known biological components, such as DNA, RNA,
Putting this vision into practice, however, has been hampered by a lack
of quantitative models capable of making accurate predictions about
what components will do when combined to form novel biological
circuits, except in a few particular narrow domains.
The problem may be understood as one of metrology: effective
engineering requires a system of measurements that are focused on
delivering the specific types of information needed for design of
functional systems. Consider, for example, the use in mechanical
engineering of properties such as stiffness, stress and strain, and
rigidity. These sorts of quantities are precisely focused on
questions that need to be answered by designers of physical structures
and are measurable through well-defined and standardized experiments.
In synthetic biology, despite the excellent work done by many
researchers, the field has not yet converged on an appropriate system
of measurements that can support the needs of biological circuit
designers. Until it does, the engineering of complex circuits
will tend to be a black art requiring much costly trial and error.
With recent improvements in tools for measurement, analysis, and
modeling, however, the time is ripe to revisit the question of
metrology for synthetic biology. This is particularly true for
work in mammalian cells, which are relatively robust to the
introduction of engineered circuits and where large libraries of
orthogonal components are beginning to emerge.
The goal of this workshop is to bring together both producers and
consumers of synthetic biology component models, with the aim of laying
out a roadmap for metrology in mammalian synthetic biology.
Participants will be invited to contribute to a whitepaper to be
produced after the workshop, summarizing the conclusions of the
workshop and recommendations for metrology investigations that will
advance synthetic biology.
Agenda for Discussion:
- Why do we need quantitative measurements?
The use that measurements are put to
will dictate what it makes sense to measure, and how we know whether we
are measuring the right things with high enough precision and accuracy.
- What measurements should be taken?
Fluorescence? PoPS? RiPS? Single
element (e.g. terminator, 5'UTR) or "device" complex (e.g, rtTA +
pTRE)? When are population measurements sufficient and when are
single cell measurements necessary? What model priors should be assumed?
What types of context are important?
- How can we distinguish values, variations, and error?
When data has an unexpected form, do we
debug our models or our experiments or our materials? How much do
duplicate sample points matter? What resolution of sampling is
necessary to determine variation? How do we decide when to throw data
away? When is it time to think we've discovered a new
phenomenon? Can we learn anything
systematic about biology?
- What techniques are most effective for measurement?
Fluorimetry? Optical imaging? Flow
cytometry, HCS microscopy? HT mass spec? Others?
- What needs to happen to establish community standards for
How do we share data, with a lab, or
with our peers, or publicly? How do we represent it? How do we
Schedule and Location:
Patil/Kiva Seminar Room (32-G449)
MIT Stata Center (Building 32)
32 Vassar Street
Sunday, May 12th, 2013, 1-5pm
- 1:00pm - 1:15pm: Introduction
- 1:15pm - 2:00pm: Consumers of Quantitative Measurement
- 2:00pm - 2:45pm: What Should Be Measured?
- Break from 2:45pm - 3:15pm
- 3:15pm - 4:00pm: Protocols and Interpretation
- 4:00pm - 4:45pm: Exchanging Measurement Data
- 4:45pm - 5:00pm: Wrapup and Future Plans
Dial-in participation will be provided via GoToMeeting:
- Use your microphone and speakers (VoIP) - a headset is recommended.Or,
call in using your telephone.
- Dial +1 (805) 309-0010
- Access Code: 336-632-202
- Audio PIN: Shown after joining the meeting
- Meeting ID: 336-632-202
Registration is free.
To register, email: email@example.com
Bio-Design Automation Consortium