Frontiers of Metrology in Biology 26 th CGPM 2018 Marc Salit Joint - PowerPoint PPT Presentation

Frontiers of Metrology in Biology 26 th CGPM 2018 Marc Salit Joint Initiative for Metrology in Biology NIST, Stanford University and SLAC

Frontiers of Metrology in Biology 26 th CGPM 2018 Marc Salit Joint Initiative for Metrology in Biology NIST, Stanford University and SLAC

There are 10 13 cells in a human (human cells). There are 10 14 microbial cells in a human. There are ~10 10 carbon atoms in a human cell. This is a 192 x 128 grid at 18 droplets per cm. It contains 7212 droplet transfers of 2.5 nl/droplet. Each droplet contained about 1000 cells. Cells were grown for ~24h.

Derived units SI BASE UNITS SI DERIVED UNITS WITH SPECIAL NAMES AND SYMBOLS without special names Solid lines indicate multiplication, broken lines indicate division kilogram kg (kg·m/s 2 ) (N/m 2 ) newton pascal gray (J/kg) sievert (J/kg) N Pa Gy Sv m 3 https://physics.nist.gov/cuu/Units/SIdiagram.html MASS FORCE PRESSURE, ABSORBED DOSE VOLUME STRESS DOSE EQUIVALENT meter m m 2 joule (N·m) watt (J/s) becquerel (1/s) hertz (1/s) LENGTH J W Bq Hz AREA ENERGY, WORK, POWER, FREQUENCY ACTIVITY second QUANTITY OF HEAT HEAT FLOW RATE (OF A RADIONUCLIDE) s m/s VELOCITY TIME (Wb/m 2 ) katal (mol/s) weber (V·s) henry (Wb/A) tesla H T kat Wb mole m/s 2 CATALYTIC MAGNETIC INDUCTANCE MAGNETIC mol ACTIVITY FLUX FLUX DENSITY ACCELERATION AMOUNT OF SUBSTANCE coulomb (A·s) volt (W/A) C V ampere A POTENTIAL, ELECTRIC ELECTROMOTIVE CHARGE ELECTRIC CURRENT FORCE degree (K) farad (C/V) ohm (V/A) siemens (1/ W ) kelvin Celsius W ° C F S K CONDUCTANCE CELSIUS RESISTANCE CAPACITANCE THERMODYNAMIC TEMPERATURE TEMPERATURE t / ° C = T / K – 273.15 candela steradian radian (lm/m 2 ) cd lux lumen (cd·sr) (m 2 /m 2 = 1) (m/m = 1) lx sr rad lm LUMINOUS INTENSITY ILLUMINANCE SOLID ANGLE PLANE ANGLE LUMINOUS FLUX

Derived units SI BASE UNITS SI DERIVED UNITS WITH SPECIAL NAMES AND SYMBOLS without special names The Subway Solid lines indicate multiplication, broken lines indicate division (in Paris, The kilogram kg (kg·m/s 2 ) (N/m 2 ) newton pascal gray (J/kg) sievert (J/kg) N Pa Gy Sv m 3 Metro ) MASS FORCE PRESSURE, ABSORBED DOSE VOLUME STRESS DOSE EQUIVALENT meter m Diagram m 2 joule (N·m) watt (J/s) becquerel (1/s) hertz (1/s) LENGTH J W Bq Hz AREA ENERGY, WORK, POWER, FREQUENCY ACTIVITY second QUANTITY OF HEAT HEAT FLOW RATE (OF A RADIONUCLIDE) s m/s “Wait… there’s TIME VELOCITY (Wb/m 2 ) katal (mol/s) weber (V·s) henry (Wb/A) tesla H T kat Wb mole m/s 2 CATALYTIC MAGNETIC INDUCTANCE MAGNETIC mol no stop for ACTIVITY FLUX FLUX DENSITY ACCELERATION AMOUNT OF SUBSTANCE coulomb (A·s) volt (W/A) Biology?!?” C V ampere A POTENTIAL, ELECTRIC ELECTROMOTIVE CHARGE ELECTRIC CURRENT FORCE degree (K) farad (C/V) ohm (V/A) siemens (1/ W ) kelvin Celsius W ° C F S K CONDUCTANCE CELSIUS RESISTANCE CAPACITANCE THERMODYNAMIC TEMPERATURE TEMPERATURE t / ° C = T / K – 273.15 candela steradian radian cd (lm/m 2 ) lux lumen (cd·sr) (m 2 /m 2 = 1) (m/m = 1) lx sr rad lm LUMINOUS INTENSITY ILLUMINANCE PLANE ANGLE LUMINOUS SOLID ANGLE FLUX

JIMB focusing on Operational Mastery of Living Matter JIMB is focused on Operational Mastery of living matter at the cellular level. • Organizing principle: “ Measure, Model, Make ” • Through Genomics and Synthetic Biology • measure everything inside the cell… Not focusing on metrology of biomaterials properties, medical diagnostics, biotherapeutics, regenerative medicine, diagnostic imaging…

What’s different about metrology in biology? Characterizing living matter requires Genome measuring massively multiplexed DNA measurands of heterogeneous systems with complex dynamics and interactions. Transcriptome RNA • A living cell is a dance of interacting chemical systems governed by biophysics. Proteome Protein • The cell is the atom of biology.

There was a revolution in measuring biology in 2006. Accurate Multiplex Polony Sequencing of an Evolved Bacterial Genome Jay Shendure, 1 * . Gregory J. Porreca, 1 * . Nikos B. Reppas, 1 Xiaoxia Lin, 1 John P. McCutcheon, 2,3 Abraham M. Rosenbaum, 1 Michael D. Wang, 1 Kun Zhang, 1 Robi D. Mitra, 2 George M. Church 1 We describe a DNA sequencing technology in which a commonly available, inexpensive epifluorescence microscope is converted to rapid nonelectrophoretic DNA sequencing automation. We apply this technology to resequence an evolved strain of Escherichia coli at less than one error per million consensus bases. A cell-free, mate-paired library provided single DNA molecules that were amplified in parallel to 1-micrometer beads by emulsion polymerase chain reaction. Millions of beads were immobilized in a polyacrylamide gel and subjected to automated cycles of sequencing by ligation and four-color imaging. Cost per base was roughly one-ninth as much as that of conventional sequencing. Our protocols were implemented with off-the-shelf instrumentation and reagents. The ubiquity and longevity of Sanger sequenc- trophoretic methods may be reaching their lim- ing ( 1 ) are remarkable. Analogous to semicon- its. Meeting the challenge of the $1000 human ductors, measures of cost and production have genome requires a paradigm shift in our under- followed exponential trends ( 2 ). High-throughput lying approach to the DNA polymer ( 3 ). centers generate data at a speed of 20 raw bases Cyclic array methods, an attractive class per instrument-second and a cost of $1.00 per of alternative technologies, are B multiplex [ in raw kilobase. Nonetheless, optimizations of elec- that they leverage a single reagent volume to enzymatically manipulate thousands to mil- Shendure, J., Porreca, G. J., Reppas, N. B., Lin, X., McCutcheon, J. P., Rosenbaum, A. M., … Church, G. M. (2005). Accurate multiplex polony sequencing of an evolved bacterial genome. Science , 309 (5741), 1728–1732. https://doi.org/10.1126/science.1117389

You can scan the landscape to frame a roadmap. … System Sy Organism Or Tissue Ti Cell Ce Organelle Or Genome Ge We’re pretty good at sequencing, but sampling there’s work to do to roadmap our measurement capabilities. It’s more granular than this – presents challenges. Regulation Transcriptom Re Lots of methods, reasonably characterized Pretty good at RNA-Seq, reasonably characterized, sampling challenges. ome Re A couple of methods, Reg. still emerging Pr Proteome Variety of methods, technically challenging Re Reg. Enzyme activity measures, not ‘omics? Me Metabolome Variety of methods, still emerging

Community is reaching out for Standards. • Protocols • Data Representation • Data Exchange • Requirements /Specifications • Calibration Materials • Validation/Benchmark Materials • Validation/Benchmark Data from https://www.encodeproject.org based on an image from Darryl Leja (NHGRI), Ian Dunham (EBI), Michael Pazin (NHGRI)

This 2012 Nature Comment triggered recognition of a “ Re Reproducibility Crisis ” in biomedical science…

Taking a cue from Chemical Metrology… Reference Materials can work in Biology • Both RMs depicted Transcriptome Spike-ins ERCC Controls were created in consortium Quantitative partnerships • Both are widely adopted • Both address needs in GIAB Genomes Human Genomes Genome-Scale e v Measurements i t a t i l a u Q

Use the ERCC Reference Material plasmid library to make controls SRM 2374 Plasmid Pools with known RNA transcripts DNA Library abundance ratios in vitro … Pooling transcription

Design of Ambion ERCC Spike-In Ratio Mixtures e c n a d n u b a 23 Controls per n g e i g s n e D a r l o 2 20 o p b s n u a S p h s c a Subpool e n i h t i w

erccdashboard gives standard measures of technical performance • Technology-independent ratio performance measures • Shows differences in performance across Munro, S. A. et al. Nat. Commun. 5:5125 • Experiments doi: 10.1038/ncomms6125 (2014). • Laboratories • Measurement processes

Evaluate Dynamic Evaluate Diagnostic Range Performance Performance – “ROC Curve” Evaluate Ratio Establish Lower Performance – Limit of Detection for “MA Plot” Differential Expression Detection – “LODR”

Good Lab

Bad Lab

Genome in a Bottle Consortium is making and disseminating human genome reference materials. • create shared reference samples Sample genome sequencing measurement process • validation materials to evaluate, gDNA isolation demonstrate, refine, optimize technologies Library Prep • red light/yellow light… Sequencing • developed benchmarking dashboard with stakeholders @ GA4GH Alignment/Mapping • meeting needs for technology Variant Calling developers, regulators, clinical Confidence Estimates research teams Downstream Analysis

GIAB “Open Science” Virtuous Cycle Reference data Method development, • phased variant calls across 7 Users optimization, and analyze demonstration human genomes GIAB Samples • ~ 4M small variants • ~20,000 larger “structural New Benchmark variants” benchmark vs. GIAB data data GIAB/NIST All data available immediately expands to more Part of assay without embargo difficult regions validation • consistent with Integrate Critical transparency and metrology new feedback methods to GIAB