NIH / NIGMS Perspective

Karin A. Remington, Ph.D., NIGMS

NCSA Strategic Planning MeetingApril 20, 2010

First Genome Sequenced 1995Haemophilus influenzae

1.8 million basepairs

Meta-GenomicsPilot Study:

The Sargasso Sea

Described in: Venter et al. Environmental Genome Shotgun

Sequencing of the Sargasso Sea, Science 304, 66-74 (2004)

Sorcerer ll ExpeditionSampling Sites

Sorcerer GOS Expedition34 sites, baseline of 150,000 sequences site

Just outside Canadian waterBrowns bankOutside HalifaxBedford BasinBay of FundeeTransit outside of MaineNewport Harbor, Rhode IslandBlock IslandCape MayNext To Nuke Power Plant in Delaware BayChesapeake Bay near Annapollis11.3 miles off of Nags Head N.C.South of Charleston S.COff Dry TortugasNorthwest of western most CubaYucatan Channel, MexicoCarribean Sea 30 nm of Rosario bank, Honduras80 nm north of Panama Canal

Borro de Colorado at STRI, Panama35 miles off of Panama City250 miles from Panama Canal30 miles from Coco's Island, EcuadorDirty Rock Coco's Island, EcuadorDevil's Crown Off of Floreana, GalapagosOff theCoast of Floreana, GalapagosEspumilla Beach, Santigo Island, GalapagosThermal Vent Roca Redonda, GalapagosOff Fernandina Island, Galapagos Floreana Flamingo Pond, GalapagosNorth Seamore Island, GalapagosWolf Island, GalapagosCabo Marshall, Isabella Island Galapagos

http://www.genomenewsnetwork.org/resources/sequenced_genomes/genome_guide_p1.shtml

Challenges Scalability (both memory and I/O) Flexible components, with incremental,

fault tolerant design Standardization so that studies can build

upon one another Changing definitions over time Visualization and usability

Comparative analyses of assemblies

GS05 GS04 GS06 GS02 GS03 GS08 GS07 GS09 GS10 GS00 GS14 GS25 GS01 GS31 GS16 GS15 GS34 GS29 GS27 GS30 GS21 GS22 GS19 GS17 GS23

North Atlantic

Comparative analyses of assemblies

Flamingo Pond (Galapagos)

Eastern US Seaboard

Galapagos

North AtlanticSargasso Sea andYucatan Channel, Mexico

Gulf Stream

Panama Canal

Comparative analyses of gene variationExample: proteorhodopsin

Plus 23 additional pages….

Comparative analyses of gene variationExample: proteorhodopsin

2 R01 GM 76667 5

http://www.genomenewsnetwork.org/resources/sequenced_genomes/genome_guide_p1.shtml

Revolutionary and rapid changes in Science Increasing breadth of mission and growth Complex organization with many units

(27 institutes and centers, multiple program offices, e.g., OWHR, OAR, ORD, ...)

Structured by Disease, Organ, Life stage, Disciplines ….

Rapid Convergence of Science

21st Century Challenges for NIH

NIH: Many Compute Intensive Programs:

NIGMS Systems Biology Centers NCI Integrative Cancer Biology Program National Centers for Biomedical Computing (“Roadmap”) Intramural Systems Biology – NIAID, e.g. Coordinated Clinical Research Opportunities (via CTSAs, e.gg.) Various other programs…

decentralized, nascent, constantly in review

Models of Infectious Disease Agent Study

Computational and mathematical investigations of: Dynamics of emergence and spread of pathogens and

their products Identification and surveillance of infectious diseases Effectiveness and consequences of intervention

strategies Host/pathogen interactions Ecological, climatic, and evolutionary dimensions of

infectious diseases outbreaks.

Development of cutting edge computer science Translation of this computer science into biomedical

computation, i.e., effective algorithms and environments for solving real biological problems Enable the analysis, modeling, understanding, and

prediction of dynamic and complex biomedical systems across time and distance scales

Allow the integration of biomedical and behavioral data and knowledge at all levels of organization

National Centers for Biomedical Computing

(NCBCs)

Some NCBC Grand Challenges: Automated shape analysis Knowledge resources that enhance

experimentation Integration of bioinformatics data and tools High-throughput sample acquisition, analysis

and identification Relationship between genomic and clinical data Multi-body dynamic simulation, modeling and

structural analysis

See detailed center information at http://ncbcs.org

NIGMS

Multiscale ModelingSpanning scales from molecular to population, designed to illuminate biological processes and further the predictive capability in biological, biomedical and environmental systems. Multi-scale modeling encompasses concepts of space, time and state space.

Genes Cellstructure-function

Tissue structure-function

Clinicalmedicine

Organ structure-function

ProteinsLipids

Carbohydrates

mRNA

…

30,000+genes

100,000+proteins

12 organsystems

1body

200+ celltypes

4 tissuetypes

Courtesy of Peter Hunter

Biological Scales

IMAG Multiscale Modeling (MSM) Consortium Working Groups

WG1 - Filament Dynamics and Simulation (FDS) WG2 - Cardiac and Skeletal Muscle Physiology WG3 - Macro-To-Micro Scale Transport in Human Systems WG4 - Cell Level Modeling WG5 - High Performance Computing, Computational Issues

and Algorithms WG6 - Tissue Mechanics WG7 - Multiscale Imaging WG8 – Theoretical Methods WG9 – Nano-modeling WG10 – Model Sharing

The CHALLENGES of finding funding at the NIH

NIGMS

A portrait of NIH Study Sections, when it comes to interdisciplinary teams and emerging areas:

To encourage fair review of the desired collaborations:

Special Emphasis Panels, for targeted FOAs Multiple PI applications Encouragement of “New” Investigators, with IC-

level policies to boost likelihood of funding “Enhancing Peer-Review” effort underway

NIH: some recent activities

NIH-wide IT infrastructure assessment NHGRI Cloud Computing workshop NCI/NIGMS Synthetic Biology workshop NHGRI Informatics and Analysis strategic planning National Centers for Biomedical Computing competitive renewal

Sequencing Bioinformatics

Eric Green account:

Enabling biology:We really need: to carefully design, document, and scrutinize

experiments to test hypotheses and avoid misinterpreting collected data

to rely less on automated annotation, and more on focused studies, and then create tools to assist

to integrate intra-organism and intra-community systems biology as well as hypothesis-generating and hypthothesis-testing systems biology

Human polymorphism