Physics of nano-motors: Physics of nano-motors: from cargo transport to gene from cargo transport to gene expression expression Debashish Chowdhury Physics Department, Indian Institute of Technology, Kanpur Home page: http://home.iitk.ac.in/~debch/profile_DC.ht ml
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Physics of nano-motors: from cargo transport to gene expression
Physics of nano-motors: from cargo transport to gene expression. Debashish Chowdhury Physics Department, Indian Institute of Technology, Kanpur. Home page: http://home.iitk.ac.in/~debch/profile_DC.html. - PowerPoint PPT Presentation
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Physics of nano-motors: Physics of nano-motors:
from cargo transport to gene from cargo transport to gene expressionexpression
Debashish Chowdhury
Physics Department,
Indian Institute of Technology,
Kanpur
Home page: http://home.iitk.ac.in/~debch/profile_DC.html
Motor Transport System = Motor + Track + Fuel
(A) Properties of single-motor:
(i) Composition and structure (inventory of parts and architectural design)
Fundamental questions:
(B) Collective properties:
(i) Machines within machines, e.g., replisome (DNA replication factory):
(ii) Collective phenomena: coordination, cooperation and competition
(iii) Control systems and regulators of operation.
(ii) Structural/conformational and bio-chemical dynamics (operational mechanism driven by mechano-chemical cycles):
power-stroke or Brownian ratchet?
(iii) Effects of steric interactions on the spatio-temporal organization
Power-stroke versus Brownian ratchet
Joe Howard, Curr. Biol. 16, R517 (2006).
The operational mechanism of a real molecular motor may involve a combination of power stroke and Brownian ratchet
Brownian ratchetPower Stroke
Input energy drives the motor forward
Random Brownian force tends to move motor both forward and backward.
Input energy merely rectifies backward movements.
Mechanisms of energy transduction by molecular motors
A Brownian motor operates by converting random thermal energy of the surrounding medium into mechanical work!! Such systems are far from thermodynamic equilibrium and, therefore, do NOT violate second law of thermodynamics.
Simplest Model of Interacting Self-Driven Particles in 1-d
A particle moves forward, with probability q, iff the target site is empty.
q
Totally Asymmetric Simple Exclusion Process (TASEP)
Discretized position, discrete velocity (0 or 1) and discrete time
Steric interactions of the motors are often captured in the theoretical models by appropriate extensions of
We plot phase diagrams in planes spanned by exprimentally accessible parameters.
2. Brief overview of the motors of our current interest
4. Ribosome traffic on mRNA track
5. RNA polymerase traffic on DNA
1. Introduction
6. Summary and conclusion
Outline of the talk
3. Single-headed motor traffic on microtubule track
Brief overview of molecular motors of our
current interest
Cytoskeletal Molecular Motors: Cargo transport
Porters
Animated cartoon: MCRI, U.K.
Kinesin-1 on Microtubule
Myosin-V on F-actin
Ribbon diagram of the two heads of kinesin-1 (also called conventional kinesin)
Distribution of Step sizes of KIF1A Okada et al. Nature (2003)
(1) +Ve and –Ve steps sizes, i.e., both forward and backward steps.
(2) Step sizes are distributed around multiples of 8 nm
Not all kinesins have two-heads.
KIF1A kinesins are single-headed (“lame” porters);
These motors are physical realizations of Brownian ratchets
Okada and Hirokawa, PNAS (2000)
Experiments on a series of KIF1A mutants with different number of lysines in the K-loop and with E-hook digested microtubules
Molecular mechanism of processivity of KIF1A
Processivity depends on the K-loop; the larger the number of lysines, the higher is the processivity.
KIF1A becomes practically non-processive on E-hook-digested MT
Both +vely charged K-loop of KIF1A and the –vely charged E-hook of MT
are essential for the processive movement of KIF1A.
(Diffusive)
K KT KDP KD K
ATP P ADP
State 1 State 2
Strongly Attached to MT
Weakly Attached to MT
Brownian ratchet mechanism of movement of single KIF1A
In the weakly-attached state, because of the electrostatic attraction between E-hook of the microtubule and the K-loop of the kinesin, the motor remains tethered while executing Brownian motion along its track. This corresponds to the diffusive part of the dynamics of a Brownian ratchet.
KIF1A (Red) MT (Green)
10 pM
100 pM
1000pM
2 mM of ATP2 mNishinari, Okada, Schadschneider and Chowdhury, Phys. Rev. Lett. 95, 118101 (2005)
Greulich, Garai, Nishinari, Schadschneider, Chowdhury, Phys. Rev. E, 77, 041905 (2007)Chowdhury, Garai and Wang, Phys. Rev. E (Rapid Commun.), 77, 050902(R) (2008)
Many motors are moving simultaneously on the same track;
similarity with traffic
Model of interacting KIF1A on a single MT protofilament
Govindan, Gopalakrishnan and Chowdhury, Europhys. Lett. 83, 40006 (2008)
Dependence of MT-length distribution on depolymerase concentration
Not all motors move on tracks made of filamentous proteins
Track
Filamentous Protein Nucleic Acid strand
DNA RNA
Example: DNA helicase that unzips a double-stranded DNA and translocates on one of the single strands.
Garai, Chowdhury and Betterton, Phys. Rev. E 77, 061910 (2008).
Microtubule F-actin
But, today I’ll talk about the “real engines of creation”, the motors which also polymerize the macromecules of life (e.g., RNA and proteins), from the respective templates which also serve as the corresponding tracks.
Motor traffic on Nucleic Acid Tracks
(RNA polymerase)
Translation
(Ribosome)
DNA
RNA
Protein
Transcription
Central dogma of Molecular Biology and assemblersSimultaneous Transcription and Translation in bacteria
Rob Phillips and Stephen R. Quake, Phys. Today, May 2006.
Many motors move on the same track; similarity with traffic
In prokaryotes, unbinding and binding of transcription
repressor molecules
In eukaryotes, chromatin remodeling enzymes
Such a universal feature indicates a generic mechanism
Tripathi and Chowdhury, Europhys. Lett. (in press) (2008)
A Generic model: Transcriptional burst caused by gene switching
“ON”
“OFF”
A typical time series in our model
Sort the events into separate bursts: members of the same burst are separated from the immediate preceding and succeeding events by time gaps smaller than t while the time gap between any pair of successive bursts is at least t. Two choices: t = 0.5 min. and 2.5 min.
Distr. Of burst duration and intervals depend only on the rates of switching
Burst Size
P(n)exp(- off /keff)] exp(-noff/keff)wherekeff = eff/l, and eff = 12 21
f/(12 + 21
f)
Burst-size Distribution
Burst-size distribution depends on the rate constants in the elongation cycle.
Summary and Conclusion
(1)We have developed models for template-dictated polymerization of macromolecules of life by incorporating
mechano-chemistry of individual machines + steric interactions
between the machines. These efforts go beyond the earlier works on single-machine modeling and models of “ribosome traffic” (TASEP for hard rods).
(2) We have not only calculated the average rate of polymerization and
average density profile, but also studied
transcriptional and translational noise.
Our models account for transcriptional “bursts” observed in single-cell experiments. These models go beyond the earlier models of noise in gene expression (at the single gene level) as the roles of the machinery are captured explicitly.
Thank You
Acknowledgements
Collaborators (Last 4 years):
On Ribosome: Aakash Basu*, Ashok Garai, T.V. Ramakrishnan (IITK/IISc/BHU).
On RNA Polymerase: Tripti Tripathi, Prasanjit Prakash.
On Helicase: Ashok Garai, Meredith D. Betterton (Phys., Colorado).
On Chromatin-remodeling enzymes: Ashok Garai, Jesrael Mani.
On KIF1A: Ashok Garai, Philip Greulich (Th. Phys., Univ. of Koln), Andreas Schadschneider (Th. Phys., Univ. of Koln), Katsuhiro Nishinari (Engg, Univ. of Tokyo), Yasushi Okada (Med., Univ. of Tokyo), Jian-Sheng Wang (Phys., NUS).
On MCAK & Kip3p: Manoj Gopalakrishnan (HRI), Bindu Govindan (HRI).
Funding: CSIR (India), MPI-PKS (Germany).
Now at Stanford University
Support: IITK-TIFR MoU, IITK-NUS MoU.
Shaw, Zia, Lee, PRE (2003)
Coverage density = N l/L
Main steps of ribosome in the mechano-chemical cycle in the elongation stage
tRNA selection
Peptide bond formation
translocation
Mechano-chemical cycle of ribosome during polypeptide elongation
Basu and Chowdhury, Phys. Rev. E 75, 021902 (2007)E P A