Johan Paulsson | |
---|---|
Born | |
Citizenship | Sweden |
Alma mater | Uppsala University (M.S., Ph.D.) |
Scientific career | |
Fields | Systems biology, Mathematical biology, Stochastic Process |
Institutions | Harvard |
Johan Paulsson is a Swedish mathematician and systems biologist at Harvard Medical School. He is a researcher in systems biology and stochastic processes, specializing in stochasticity in gene networks and plasmid reproduction.
Johan Paulsson was born in 1973, in Kristinehamn, a small city in the Swedish province of Värmland. He studied at Uppsala University, where he obtained a BSc in Mathematics in 1996, a Masters of Science in Molecular Biology in 1996, and a Ph.D. in Molecular Biology in 2000 on stochasticity in intracellular circuits, in particular in plasmid copy control, under the supervision of Profs. Mans Ehrenberg and Kurt Nordström. In 2000 he moved to Princeton University, where he was a Lewis-Thomas Fellow in Biophysics, where he did the research for his paper "Summing up the noise in genetic networks", which received wide attention because it gave a firm theoretical footing to the budding field of genetic noise. In 2003 he joined the Dept. of Applied Mathematics and Theoretical Physics at the University of Cambridge and was tenured the following year. In 2005 he moved to the recently created Department of Systems Biology at Harvard University, where he focused on the development of experimental techniques for counting plasmids in single cells and on theoretical results on control of fluctuations in gene expression.
He is married with two children.
Paulsson's lab has made contributions to the development of experimental techniques for counting plasmids, to extend his previous work on the mathematical aspects of plasmid replication [1] [2] [3] [4] [5] as well as theoretical work on the stochastic processes on gene expression and copy number control [6] [7] [8] [9] [10] and work on multi-level selection [11] by using experimental evolution.
A publication is the analysis of all previous noise data and interpretations in one unified framework, [12] [13] which later guided many experimental approaches. [14] [15] [16]
More recent results include the effects of partition in phenotypic variability, [17] the details of the stochastic processes that underlie gene expression noise and the limitations of the usual experimental approaches [18] [19] and the fundamental limits of feedback as a noise control mechanism. [20] This set of interests led Paulsson to examine the repressilator, a synthetic gene regulatory network that was designed from scratch to oscillate and reported in 2000 [21] by Michael Elowitz and Stanislas Leibler. Although the repressilator oscillated, and therefore demonstrated the potential of synthetic biology, the oscillations were noisy and quickly became incoherent on the single cell level. Using an understanding of the causes of noise in cellular networks, Paulsson's team was able to redesign the repressilator, retaining the basic design, to produce a new synthetic circuit that oscillated with some accuracy. [22]
Electroporation, or electropermeabilization, is a technique in which an electrical field is applied to cells in order to increase the permeability of the cell membrane. This may allow chemicals, drugs, electrode arrays or DNA to be introduced into the cell.
A generegulatory network (GRN) is a collection of molecular regulators that interact with each other and with other substances in the cell to govern the gene expression levels of mRNA and proteins which, in turn, determine the function of the cell. GRN also play a central role in morphogenesis, the creation of body structures, which in turn is central to evolutionary developmental biology (evo-devo).
Fluorescence correlation spectroscopy (FCS) is a statistical analysis, via time correlation, of stationary fluctuations of the fluorescence intensity. Its theoretical underpinning originated from L. Onsager's regression hypothesis. The analysis provides kinetic parameters of the physical processes underlying the fluctuations. One of the interesting applications of this is an analysis of the concentration fluctuations of fluorescent particles (molecules) in solution. In this application, the fluorescence emitted from a very tiny space in solution containing a small number of fluorescent particles (molecules) is observed. The fluorescence intensity is fluctuating due to Brownian motion of the particles. In other words, the number of the particles in the sub-space defined by the optical system is randomly changing around the average number. The analysis gives the average number of fluorescent particles and average diffusion time, when the particle is passing through the space. Eventually, both the concentration and size of the particle (molecule) are determined. Both parameters are important in biochemical research, biophysics, and chemistry.
Neuronal noise or neural noise refers to the random intrinsic electrical fluctuations within neuronal networks. These fluctuations are not associated with encoding a response to internal or external stimuli and can be from one to two orders of magnitude. Most noise commonly occurs below a voltage-threshold that is needed for an action potential to occur, but sometimes it can be present in the form of an action potential; for example, stochastic oscillations in pacemaker neurons in suprachiasmatic nucleus are partially responsible for the organization of circadian rhythms.
The repressilator is a genetic regulatory network consisting of at least one feedback loop with at least three genes, each expressing a protein that represses the next gene in the loop. In biological research, repressilators have been used to build cellular models and understand cell function. There are both artificial and naturally-occurring repressilators. Recently, the naturally-occurring repressilator clock gene circuit in Arabidopsis thaliana and mammalian systems have been studied.
James Joseph Collins is an American biomedical engineer and bioengineer who serves as the Termeer Professor of Medical Engineering & Science at the Massachusetts Institute of Technology (MIT), where he is also a director at the MIT Abdul Latif Jameel Clinic for Machine Learning in Health.
Carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) also known as CD66c, is a member of the carcinoembryonic antigen (CEA) gene family..
Eukaryotic translation initiation factor 6 (EIF6), also known as Integrin beta 4 binding protein (ITGB4BP), is a human gene.
Tropomodulin-1 is a protein that in humans is encoded by the TMOD1 gene.
Unconventional myosin-Ia is a protein that in humans is encoded by the MYO1A gene.
Developmental noise or stochastic noise is a concept within developmental biology in which the observable characteristics or traits (phenotype) varies between individuals even though both individuals share the same genetic code (genotypes) and the other environmental factors are completely the same. Factors that influence the effect include stochastic, or randomized, gene expression and other cellular noise.
Alexander van Oudenaarden is a Dutch biophysicist and systems biologist. He is a researcher in stem cell biology, specialising in single cell techniques. In 2012 he started as director of the Hubrecht Institute and was awarded three times an ERC Advanced Grant, in 2012, 2017, and 2022. He was awarded the Spinoza Prize in 2017.
Transcriptional bursting, also known as transcriptional pulsing, is a fundamental property of genes in which transcription from DNA to RNA can occur in "bursts" or "pulses", which has been observed in diverse organisms, from bacteria to mammals.
Transcriptional noise is a primary cause of the variability (noise) in gene expression occurring between cells in isogenic populations. A proposed source of transcriptional noise is transcriptional bursting although other sources of heterogeneity, such as unequal separation of cell contents at mitosis are also likely to contribute considerably. Bursting transcription, as opposed to simple probabilistic models of transcription, reflects multiple states of gene activity, with fluctuations between states separated by irregular intervals, generating uneven protein expression between cells. Noise in gene expression can have tremendous consequences on cell behaviour, and must be mitigated or integrated. In certain contexts, such as establishment of viral latency, the survival of microbes in rapidly changing stressful environments, or several types of scattered differentiation, the variability may be essential. Variability also impacts upon the effectiveness of clinical treatment, with resistance of bacteria and yeast to antibiotics demonstrably caused by non-genetic differences. Variability in gene expression may also contribute to resistance of sub-populations of cancer cells to chemotherapy and appears to be a barrier to curing HIV.
Michael B. Elowitz is a biologist and professor of Biology, Bioengineering, and Applied Physics at the California Institute of Technology, and investigator at the Howard Hughes Medical Institute. In 2007 he was the recipient of the Genius grant, better known as the MacArthur Fellows Program for the design of a synthetic gene regulatory network, the Repressilator, which helped initiate the field of synthetic biology. He was the first to show how inherently random effects, or 'noise', in gene expression could be detected and quantified in living cells, leading to a growing recognition of the many roles that noise plays in living cells. His work in Synthetic Biology and Noise represent two foundations of the field of Systems Biology. Since then, his laboratory has contributed to the development of synthetic biological circuits that perform a range of functions inside cells, and revealed biological circuit design principles underlying epigenetic memory, cell fate control, cell-cell communication, and multicellular behaviors.
In evolutionary biology, robustness of a biological system is the persistence of a certain characteristic or trait in a system under perturbations or conditions of uncertainty. Robustness in development is known as canalization. According to the kind of perturbation involved, robustness can be classified as mutational, environmental, recombinational, or behavioral robustness etc. Robustness is achieved through the combination of many genetic and molecular mechanisms and can evolve by either direct or indirect selection. Several model systems have been developed to experimentally study robustness and its evolutionary consequences.
Cellular noise is random variability in quantities arising in cellular biology. For example, cells which are genetically identical, even within the same tissue, are often observed to have different expression levels of proteins, different sizes and structures. These apparently random differences can have important biological and medical consequences.
Synthetic biological circuits are an application of synthetic biology where biological parts inside a cell are designed to perform logical functions mimicking those observed in electronic circuits. Typically, these circuits are categorized as either genetic circuits, RNA circuits, or protein circuits, depending on the types of biomolecule that interact to create the circuit's behavior. The applications of all three types of circuit range from simply inducing production to adding a measurable element, like green fluorescent protein, to an existing natural biological circuit, to implementing completely new systems of many parts.
Genetic regulatory circuits is a concept that evolved from the Operon Model discovered by François Jacob and Jacques Monod. They are functional clusters of genes that impact each other's expression through inducible transcription factors and cis-regulatory elements.
Intracellular delivery is the process of introducing external materials into living cells. Materials that are delivered into cells include nucleic acids, proteins, peptides, impermeable small molecules, synthetic nanomaterials, organelles, and micron-scale tracers, devices and objects. Such molecules and materials can be used to investigate cellular behavior, engineer cell operations or correct a pathological function.