Advanced cellular analytics
Inside every cell is a complex, dynamic and sometimes mysterious environment. The Biocompute Lab is developing advanced biometrology approaches based on emerging technologies like nanopore sequencing and high-throughput fluorescence activated cell sorting to "see" and "measure" the inner workings of this typically hidden world.
When you can measure what you are speaking about, and express it in numbers, you know something about it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely, in your thoughts advanced to the stage of science.
— Lord Kelvin
Core strands
Biometrology
Measurements of the natural world underpin science, yet in biology we are often hampered by a lack of numbers we trust and measurements in units that are only loosely connected to the physical quantities we are interested in. The Biocompute Lab is developing new high-throughput techniques to measure core cellular processes like transcription and translation, tracking the flows of RNA polymerase and ribomsomes within a cell, as well as the means to count the key molecules of life (DNA, RNA and proteins).
Standards development
Modern engineering and effective sharing of data for improved reproducibility relies on supporting standards. If no too bolts were ever the same size, how would we ever construct a bridge? And if every webpage was encoded in a different format the Internet would cease to exist! To do this, the Biocompute Lab is supporting open community-driven data standards for synthetic biology (e.g. SBOL) to aid the exchange of biological designs and associated data.
Nanopore sequencing
To enable the measurement of key cellular processes and components, the Biocompute Lab is harnessing the unique capabilities of nanopore sequencing. Unlike other sequencing approaches, nanopore sequencing is able to read full-length DNAs/RNAs as well as the base modifications present. We are keen to make access to this technology simpler and so are also creating robust bioinformatics tools and lab automation systems to ensure more equitable access to our developments.
Whole-cell modelling
High-performance computing is transforming many aspects of how we do science and is central to the design processes used in mature engineering fields. The Biocompute Lab is exploring the possibility to create and use whole-cell models that can simulate in detail the many of the key cellular processes within a cell. We are exploring ways to use these models as a way of rapidly testing out biological designs without the need to build them in the lab, and narrow down the experiments that need to be performed. We are also using this complex models as a basis for learning simplified representations that are more efficient to simulate.
Selected publications
Transfer learning for cross-context prediction of protein expression from 5'UTR sequence
Gilliot P.A., Gorochowski T.E.
Nucleic Acids Research 52, e58, 2024.
Optimization of periodic treatment strategies for bacterial biofilms using an agent-based in silico approach
Blee J.A., Gorochowski T.E., Hauert S.
Journal of the Royal Society Interface 21, 20240078, 2024.
Effective design and inference for cell sorting and sequencing based massively parallel reporter assays
Gilliot P.A., Gorochowski T.E.
Bioinformatics 39, btad277, 2023.
Massively parallel characterisation of engineered transcript isoforms using direct RNA sequencing
Tarnowski M.J., Gorochowski T.E.
Nature Communications 13, 434, 2022.
Sequencing enabling design and learning in synthetic biology
Gilliot P.A., Gorochowski T.E.
Current Opinion in Chemical Biology 58, 54-62, 2020.
Communicating Structure and Function in Synthetic Biology Diagrams
Beal J., Nguyen T., Gorochowski T.E., Goñi-Moreno A., Scott-Brown J., McLaughlin J.A., Madsen C., Aleritsch B., Bartley B., Bhatia S., Bissell M., Castillo-Hair S., Clancy K., Luna A., Le Novére N., Palchick Z., Pocock M., Sauro H., Sexton J.T., Tabor J.J., Voigt C.A., Zundel Z., Myers C., Wipat A.
ACS Synthetic Biology 8, 1818-1825, 2019.
Absolute quantification of translational regulation and burden using combined sequencing approaches
Gorochowski T.E., Chelysheva I., Eriksen M., Nair P., Pedersen S., Ignatova Z.
Molecular Systems Biology 15, e8719, 2019.
Genetic circuit characterization and debugging using RNA-seq
Gorochowski T.E., Espah Borujeni A., Park Y., Nielsen A.A.K., Zhang J., Der B.S., Gordon D.B., Voigt C.A.
Molecular Systems Biology 13, 952, 2017.
A standard-enabled workflow for synthetic biology
Myers C.J., Beal J., Gorochowski T.E., Kuwahara H., Madsen C., McLaughlin J.A., Mısırlı G., Nguyen T., Oberortner E., Samineni M., Wipat A., Zhang M., Zundel Z.
Biochemical Society Transactions 45, 793-803, 2017.
DNAplotlib: programmable visualization of genetic designs and associated data
Der B.S., Glassey E., Bartley B.A., Enghuus C., Goodman D.B., Gordon D.B., Voigt C.A., Gorochowski T.E.
ACS Synthetic Biology 6, 1115-1119, 2017.
