Laboratory of Biosystem Dynamics (LBD)

Home

People

Research

Publications

Laboratory

Funding

Software

Teaching

Open Positions

About us

The Laboratory of Biosystem Dynamics (LBD), led by Associate Prof. Andre S. Ribeiro of the Biomeditech Institute at Tampere University of Technology (TUT), studies the in vivo dynamics and regulatory mechanisms of bacterial gene expression and genetic circuits at the single-cell, single-molecule level using time-lapse microscopy, stochastic models, single-cell signal processing, and synthetic gene engineering. This research aims to understand how genes and genetic circuits are regulated and unravel their range of functionalities, thereby assisting in the comprehensive engineering of synthetic circuits for regulating cellular processes.


Our team (stuck in the office) in December 2016

Recent highlights

  • The Journal of Neuroscience has published a work by Leonard Khiroug and Sergei Kirov teams in which we also collaborated for.
  • The Biophysical Journal has accepted our study on the role of the nucleoid in the polar localization of the Serine Chemoreceptors of Escherichia coli. (pre-print here)
  • We published a new paper (review) on stochastic models of genetic circuits: AS Ribeiro (2016) Delays as regulators of the dynamics of genetic circuits. Markov Processes and Related Fields 22, 573-594. PDF
  • Our detailed work on the measurements and detailed dissection of the dynamics of RNA production at various temperatures in E. coli has been accepted and published in PLOS Computational Biology. Warm thanks to our former team member and now collaborator Antti Hakkinen. PDF
  • The LBD has been granted the "Key project funding: Forging ahead with research" grant by the Academy of Finland (01.10.2016 - 30.09.2018) for more research and applications of ongoing research in gene expression and genetic circuits!
  • Mohamed Bahrudeen has joined our group !
  • Eero Lihavainen has completed his PhD at the LBD and will now pursue new adventures! Best wishes to him from all of us!
  • Jarno Mäkelä has completed his PhD at the LBD and will now work as a Post-Doctoral Fellow at Oxford! Best wishes from all of us!
  • We recently published a work on the effects σ factor competition on the in vivo kinetics of transcription initiation in E. coli: VK Kandavalli, H Tran, and AS Ribeiro (2016) Effects of σ factor competition on the in vivo kinetics of transcription initiation in Escherichia coli. BBA Gene Regulatory Mechanisms 1859 (2016) 1281–1288. PDF
  • The Academy of Finland has granted the LBD with a new grant (01.09.2016 - 31.08.2020) for a project on studies of transcription dynamics!
  • Huy Tran and Antti Häkkinen have completed their PhD studies at the LBD, and have now move forward for Post-doctoral positions in Paris and Helsinki, respectively. We wish them all the best in their new challenges.

A little history...

The LBD was established in January 2009, as part of the Computational Systems Biology Research Group of the DSP. In 2015, it became an independent group of the DSP, TUT. In 2016, it joined Biomeditech (Institute of Biosciences and Medical Technologies of Tampere, Finland). Since 2017, the group has been entirely moved to the Biomeditech Institute, TUT.

At first, we performed studies using computational and theoretical biology methods alone. In 2011, we setup a Cell and Molecular Biology Laboratory, specialized in live, single-cell, single-molecule imaging. This allowed us to combine theory and measurements. Currently, we conduct live single-cell, single-molecule microscopy measurements to study gene expression and genetic circuits dynamics, as well as other intracellular processes. For this, we perform and also develop methods in image and data analysis, and design detailed stochastic models and simulators of genetic circuits dynamics. For this, we have assembled and maintain a highly multi-disciplinary group that includes backgrounds in physics, theoretical biology, molecular and cell biology, biotechnology, biomedical engineering, signal processing, and computer science.

A detail description of some of our recent projects is available here.

Cells_nucleoids            Spots            Clod_cells

Above are movies obtained in our lab, by microscopy, which we make use of to study cellular processes ranging from transcription dynamics to segregation of protein aggregates to the cell poles. (Left) Here, we image nucleoids (red) and FtsZ proteins (green) associated with the formation of the cell wall in cell division. (Center) Here we observe RNAs production, one at a time (bright spots), in a single cell. (Right) Here we observe the spatial distribution of MS2-GFP-RNA spots in live cells at 10 C, to assess how lower temperatures affect the dynamics of segregation of protein aggregates.

WorkFig

This image illustrates the methodology used in several of our studies, which consist of measurements of RNA production dynamics using state-of-the-art signal and image processing techniques, which are used to test or design a model of the processes responsible for the RNA production.

MULTI-BAM - Multi-scaled biodata analysis and modelling Research Community

The Multi-scaled biodata analysis and modelling (MultiBAM) is a recently formed (2016) research community composed of the Laboratory of Biosystem Dynamics (LBD) of the DSP (TUT) led by Andre Ribeiro (chair of MultiBAM), the Biological Physics and Soft Matter (BIO) Group led by Ilpo Vattulainen (TUT), the Computational Biology Group (CB) of BioMediTech (UTA) led by Matti Nykter, and the Protein Dynamics Group (PD) (UTA) led by Vesa Hytönen. All these groups study, at different scales, how cells sense and respond to the environment and how information flows and is processed inside them. The new community for multi-scaled biodata analysis and modelling (MultiBAM) will combine knowledge, methods, and tools used by its groups to handle biodata at different scales of observation and from different phenomena. The goal is to study and understand dynamical processes in cells in a broad sense and to produce new computational tools and models that, by being applicable to multiple scales, can provide new comprehensive understanding of biological systems.