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Biosciences Division

Small Worlds

Small Worlds is focused on developing a new multi-modal imaging capability for studying complex multi-agent processes in cells and systems of cells across spatial and temporal scales.
(left) X-ray tomography will aid identification of target organisms (center) Dynamic three-dimensional imaging will study molecular interactions to uncover process mechanics (right) Electron tomography will correlate detailed dynamics with high-resolution cellular structure

The Small Worlds experimental platform is comprised of integrated hardware, software, and molecular-scale reporters that will enable the study of systems biology problems that involve many parts and span spatial scales from nanometers to millimeters and temporal scales from subseconds to days.

Small Worlds will address the following challenges:

  • Need for multi-scale resolution from nanometers to millimeters
  • Need for rapidly capturing dynamics in 3-D volumes for live systems
  • Need for conducting 3-D measurements of biological matter and function in native environments, such as soil, which is opaque to most forms of electromagnetic radiation
  • Ability to identify specific features or functions in the individual elements of complex biological systems (i.e. in bacteria, in roots, etc.)
  • Need to understand the relationships between and interactions among the constitutive elements (organisms)


Small Worlds distills these challenges into three main technological thrusts at the cutting edge of technology (1) Imaging, (2) creating reporters” that allow gaining molecular-level insights into the function of individual elements and their interactions and that are compatible with the imaging modalities and (3) making the complex systems compatible with the specialized imaging capabilities.


Close integration of the instrumental aspects of the project with computational optics and computational imaging (see Figure 1) is essential to create new approaches and algorithms for deriving volumetric images from the large data sets generated. The computational aspects are an integral part, both in modeling the design of the imaging systems and in optimizing each imaging modality for maximal information extraction capability.


To validate the imaging technologies and illustrate their scientific impact, we are using an experimental rhizosphere system comprised of aspen seedlings, the fungus Laccaria, and rhizobacteria such as Pseudomonas fluorescens.  The experimental system is used as a model for the diverse symbiosis existing between fungi and bacteria in soils and the roots of many forest ecosystems.  Genomes of specific bacterial species (e.g. P. fluorescens SBW25 and P. protogens Pf5) in this work have been sequenced and allow environmentally-relevant genomic-based generation of hypotheses related to rhizosphere community structure and function.


  • Unprecedented combination of resolution and volumetric field of view for study of dynamic inter- and intra-cellular biological processes
  • Powerful new approaches to bridging imaging modalities thru reporter systems and computation
  • A means for imaging soft biological material and function in dense opaque media. These will entail new algorithms for optimal reconstruction of 3D structure from sparse data; computational support for bridging scales: primarily in the area of multi-modal volumetric registration; methods of inference from comparative analysis of multi-modal static and dynamic imagery; new multi-modal co-registration markers; analytical methods for 3D dynamics of molecular-scale objects; creation of novel non-perturbative reporters of biological process that function across imaging modalities; and unique application of microfluidic technology to enable real-time observation of biological response to environmental perturbation.