almaden may 6th 2014 gilbert
DESCRIPTION
My 10 minute Talk at IBM Almalden's Sequencing the City on the Chicago Sequencing initiative.TRANSCRIPT
Sequencing Chicago: Mapping Urban
Metabolism
Jack A Gilbert
@gilbertjacka
www.americangut.org
www.microbial-models.com
www.homemicrobiome.com
www.earthmicrobiome.org
www.hospitalmicrobiome.com
400million city dwellers
China will add
221Chinese cities will have 1M or more people.
And by 2030...
Rapid Urbanization in Developing Economies
of Chinese people will live in cities with 1M or more people.
In 2025:
70%....requiring the
construction of one New York City every year for
several decades
Source: Foreign Policy Magazine, Sep/Oct
2010, “Megacities,” Richard Dobbs (McKinsey Global Institute)
Landsat images of the Pearl River Delta in 1980 and 2005, illustrating the impact of urbanization on the planet.
Between now and 2020, the Guangdong province will invest $229B in 202 ongoing and 258 new transport infrastructure
projects to create a single 50M person city.
Produced by: S. Jiang, J. Ferreira, M. Gonzalez (2011) | Data Source: CMAP Travel Tracker Data, 2008.Reference: Jiang, S., J. Ferreira, and M. González. 2012. Clustering Daily Patterns of Human Activities in the City. Data Mining and Knowledge Discovery. Volume 25, Number 3, Pages 478-510
Mapping Megadata for Human Activity Patterns: survey data for 10,000
Chicago households on two weekdays in 2008
Crowd Funded Human Microbiome – American Gut
4
>$800,000
8450 56
www.americangut.org
House 1 Dynamic Bayesian Network
Predicting Interactions between people and
surfaces
Adding dogs into the mix make the interaction
space more complex.
US-EC Workshop on Marine Genomics: Next Generation Scientists for Next Generation Sequencing
House 4 Dynamic Bayesian Network
We can forensically identify physical
connections between people
Young Couple living with a lodger - you can identify the ‘relationship’ from the microbiome- you can also tell which parts of the house the lodger uses.
A young family (parents with 2 young boys) shows no such delineation.
University of Chicago: Kim Handley, Simon Lax, Daniel Smith, Kristen Starkey, John Alverdy, Emily Landon, Jack Gilbert, etc.Illinois Institute of Technology: Tiffanie Ramos, Brent Stephens University of Toronto: Jeff Siegel
Building science data summary
• 84 variables measured continuously every 5 minutes
• 100,000+ data points per variable
• 8.4 million+ data points collected
• over 8500+ hours of active data collection per variable
Microbial Community Analysis
• Bacterial, Fungal diversity and function over
12,000 samples
• Patients, Staff, Air, Water, Surfaces
Patient Records
• Age, Sex, disease burden, antibiotics, admission,
stay, blood tests, surgery, anesthesia, etc.
The Hospital Microbiome shifts towards a human
microbiome following arrival of patients and staff
-3 -2 -1 0 1 2
-2-1
01
2
CCA1
CC
A2
-10
1
F
DO
ALKALINITY
w_102
w_36
w_73
w_96
W_36, W_73
W_112, W_96Chicago Area Waterways Project
112 36 96 73
0%
10%
20%
30%
40%
50%
60%
70%fish mucus
human feces
Goose feces
Bird associated
Cat feces
mammal feces
animal skin
May June july Aug. Sept. May June July Aug. Sept. May Aug. Sept. May June July Aug. Sept.
Some samples were dominated by goose, human and animal fecal microbiota
• City Municipal Water reclamation Department Study
• $4M over 7 years• Tracking sources of
impact• Tracking impact of
water management strategies
Mapping human and building microbiota
US-EC Workshop on Marine Genomics: Next Generation Scientists for Next Generation Sequencing
Mapping human and building microbiota
US-EC Workshop on Marine Genomics: Next Generation Scientists for Next Generation Sequencing
Homes,Offices,
Hospitals,Public Restrooms
Gyms,Sports Stadiums,
Retail
Mapping air, water and green-site microbiota
US-EC Workshop on Marine Genomics: Next Generation Scientists for Next Generation Sequencing
Mapping air, water and green-site microbiota
US-EC Workshop on Marine Genomics: Next Generation Scientists for Next Generation Sequencing
Array of
Things
Array of Things – Air Microbiome
TemperatureHumidityLightSoundCO2IRMotionUltrasonic (proximity)PrecipitationAnemometer...
Array of Things – Air Microbiome
TemperatureHumidityLightSoundCO2IRMotionUltrasonic (proximity)PrecipitationAnemometer...
Microbial communityTemperatureCarbon DioxideCarbon MonoxideNOxHumidityWeather eventsWind speedWind directionBluetooth signalsVisibilityNoise levelAir qualityAir densityLocal tweet mining
Current 30 node prototype
A 30-node prototype is being developed for deployment in summer 2014 with internal funding from Argonne National Laboratory.
Business and Tourism
Dense
Commercial
Neighborhood
s and
recreational corridors
Vision for 2015*
* Funding Permitting
Vision for 2016*
Neighborhood
s and
recreational corridors
Business and Tourism
Dense
Commercial
* Even More Funding Permitting
Within 5 years: Automated Air Microbiome Detection
Rapid detection of:• Pathogens• Microbial imbalance• Allergens• Pollution
Influence policy:• Urban planning• Threat response• Medical surveillance• Pollution management
In all Environments:• Air• Water (rivers, lakes)• Soil (parks, agriculture)• Human bodies
Predicting the microbiome across all cities
Josh Ladau, Katie Pollard
23
Predicting Historical Changes in the Microbiome:
Facilitating Forecasting
Haiyen Chu, Josh Ladau
Research TeamInvesting Partners(engineering team)
Charlie Catlett, Rob Jacob, Raj Sankaran, Cristina Negri, Julian Gordon, Syed Hashsham,
Aaron Packman, etc.