Download The “silent” noise of bacterial genes…

INRA – AgroParisTech – CNRS – Inserm – Université Montpellier 2
Press release – Thursday, December 22, 2011
The “silent” noise of bacterial genes…
Research scientists from INRA, AgroParisTech, CNRS, INSERM and the University of
Montpellier have succeeded in observing the expression of bacterial genes with an
unprecedented accuracy. Using fluorescence-based techniques and microscopy, the
scientists were able to count the number of synthesized proteins to within one molecule,
and within each individual bacteria of a population. By observing an early stage in the gene
expression, they also succeeded in associating the fluctuations in gene expression from
one cell to another with the molecular mechanisms regulating the activity of the genes
being studied. This advance could be a step forward towards predicting the type of
mechanism regulating the expression of a gene, based on the fluctuation profile of its
expression. It also opens up an interesting perspective for synthetic biology1 since it
helps to better understand the random part of gene expression in synthetic constructions.
These results were published on December 22nd, 2011 in the on-line version of the PNAS.
The level of expression of most genes in a cell depends on the environment in which the cell is
placed. Numerous gene expression-regulating mechanisms adjust the expression of each gene to
the current environment, thus allowing the gene to adapt to this environment. However, even in a
stable environment, a given gene is not always expressed at the same level in each cell of a
population. This is because the gene expression mechanism is a largely stochastic 2 process
involving much noise. This means that it is not a regular, continuous, entirely determined process,
but rather a partly random process. At the scale of a single cell, only a small number of molecules
is involved: one single copy of the gene, a few gene regulating molecules, a few molecules to
transcribe this gene into messenger NRA, plus a few molecules to convert this messenger NRA
into protein, etc. Therefore in certain cases, the stochastic quality of gene expression can induce a
phenotypic heterogeneity within a population that is otherwise perfectly identical from a genetic
point of view: schematically speaking, one sub-population turns 'green’ while another turns 'red’
and yet they are genetically identical and placed in the same environment.
A team of microbiologists from INRA and AgroParisTech, working with a team of biophysicists from
the CNRS, INSERM, the University of Montpellier and a mathematician from the CNRS worked
together to develop a new method of measuring versus time the expression of a given gene, albeit
weak, in each bacterial cell of a population. And they did this without destroying the cells and by
counting directly and giving an absolute number of molecules produced. They concentrated on the
first stage of expression, the transcription of the gene into messenger NRA, with the aim of
determining the degree and characteristics of the random process inherent in each precise stage.
They studied a small group of cells involved in the breakdown and synthesis of glucose during a
precise environmental change in the model bacteria Bacillus subtilis after studying the molecular
gene regulating mechanisms. They built a mathematical model based on previous experience from
these mechanisms in order to analyze and interpret their impact on the random character of gene
expression in the genes studied, both in basal and induced states.
1
Synthetic biology: an overall approach to biological engineering and the synthesis of new biological
systems
2
Stochastic: governed both by chance and by probability
Recent work has demonstrated that gene expression takes place in ‘bursts’, separated by periods
of inactivity. The frequency and strength of these bursts characterize the expression of a given
gene at cell scale and help to better understand how the cells of this gene adapt to change. It is
particularly important to identify these characteristics when gene expression is at basal level, in
other words, when current conditions do not require gene expression - because stochasticity is
most marked at this point (in these conditions, the number of molecules involved in gene
expression is lower). This allows us to understand how natural selection has best “prepared” the
cell population to adapt to an environmental condition in which the given gene needs to be
expressed. We can use the metaphor of “basal respiration” of a basal gene in each cell to better
understand how the gene is subsequently induced at population level, when an environmental
change occurs. More generally, the research scientists were able to associate the characteristics
of the specific molecular mechanisms regulating the expression of each gene studied, with the
stochastic characteristics of expression from one cell to another.
Different levels of expression within a same gene in bacteria of a same population, shown by
different colors. © CNRS/CBS
This work led to the development of a powerful method of exploring the random part of gene
expression at bacterial cell level (that can also be used for eukaryotic cells). Using this type of
measurement helps to refine modeling of gene expression and hence to both understand and to
more accurately predict gene behavior depending on environmental conditions. Moreover, from a
synthetic biology point of view, it is important to be able to find the association between a given
gene expression-regulating mechanism and a variation profile of this expression between the
individual cells of a same clonal population, in other words, cells that carry exactly the same
genetic data.
References
Matthew L. Ferguson, Dominique Le Coq, Matthieu Jules, Stéphane Aymerich, Ovidiu Radulescu ; Nathalie
Declerck & Catherine A. Royer. Reconciling molecular regulating mechanisms with noise patterns of
bacterial metabolic promoters in induced and repressed states. PNAS, December 22nd, 2011,
DOI:10.1073/pnas.1110541108
Scientific contacts:
Stéphane Aymerich
01 30 81 54 49 - [email protected]
MICrobiologie de l'ALImentation au service de la Santé -Micalis
Département scientifique « Microbiologie et chaîne alimentaire »
Centre Inra de Jouy-en-Josas
Catherine A. Royer
04 67 41 79 02 - [email protected]
Centre de Biochimie Structurale (INSERM/CNRS/Université de Montpellier)