Download Overview of research in Biophysics Institute, NCU

• Overview of research in Biophysics
Institute @NCU. 中央大學生物物理所
• From DNA to collective behavior of
organisms
http://www.phy.ncu.edu.tw/~ibp/
Graduate Institute of BioPhysics at NCU
國立中央大學 生物物理所
Life Science
生命科學系
Inst. Systems Biology & Bioinformatics
系統生物與生物資訊所
Institute of Phys.,
Academia Sinica
中研院物理所
Biophysics
Brain Research Center,UST
聯合大學腦科學中心
Soft Condensed
Matter
Physics Dept.
Center for Complex Systems
複雜系統中心
What is Biophysics?
Biophysical Society defines as: "that branch of knowledge that applies the
principles of physics and chemistry and the methods of mathematical
analysis and computer modeling to understand how the mechanisms of
biological systems work” .
• Why BioPhysics ?
• Material Nature of Bio-substances affect
Biological properties. (Evolution made use
of the physical properties of bio-materials)
• Physical principles & Laws holds from
microscopic level  macroscopic level
• Traditional Biology is descriptive, nonquantitative
Why BioPhysics ?
• Physics is universal.
• Rise of molecular biology: DNA, RNA, protein
are universal in all living matters
• Universality in Central Dogma:
DNARNAproteinBiological functions…
• New, interesting, exciting & useful.
• Lots of unsolved important problems.
• Techniques & Methodology in physics can probe
the fundamental principles in bio-systems of a
wide spectrum of scales in a quantitative way.
Physics is vital in breakthrough in life sciences
• Breakthrough in physical instrument: optical microscope (Hooke, 1665),
amplifier, X-ray, electron microscope, MRI, SPM, mass spectrometer,
Single molecule microscopy,….
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Nobel laureates in physiology/medicine
that were physicists/had physics training:
Georg von Békésy (physical mechanism of the cochlea, 1961)
Francis Crick (DNA, 1962)
Alan Hodgkin (nerve cell ,1963)
Haldan Hartline (visual processes in the eye, 1967)
Max Delbrück (bacteriophage l, 1969)
Rosalyn Yalow (radio-immunoassays of peptide hormones, 1977)
Werner Arber (restriction enzymes , 1978)
Erwin Neher (single ion channels in cells ,1991)
Peter Mansfield (NMR, 2003)……
Wide Spectrum
• Length Scales:
nm 
mm

mm 
cm 
DNA,RNA,protein, intracellular, virus, bacteria, Intercellular, collective motion, insects,
• Time Scales:
fs  ps

e transfer,H-bonding,water
 hr 
cell division
ms

DNA,RNA,protein rearrangement ,
day
Earth organisms ,
 year
animal migration
m
animals/plants,

km
migration
ms  s
protein folding
DNA transcription
 Byr
evolution
• Knowledge: Interdisciplinary 跨越各學科領域
MathematicsPhysicsChemistryBiologyMedical
• Biophysicist is a TRUE Scientist ! Explore to the
maximum freedom for doing science!
•需要物理與非物理背景人材加入!
國立中央大學 生物物理研究所
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Officially established in 2004(碩士班),博士班(2008)
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教授: 6 副教授: 1 助理教授 2
合聘教授: 3
合聘助理教授: 2
現有從事生物物理領域在學研究生(含物理所)
碩士班：23 博士班：7
博士後: 6
以物理之技術或方法去探討生物系統中存在之基本原
理，從而對生物過程提供深入及定量之了解。
「5年500億發展國際一流大學及頂尖研究中心計畫」
經費建立 生物物理共用核心設施
歡迎物理與非物理背景同學加入.中大及中研院提供獎
學金
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師資
職稱
伊林
教授
陳方玉
教授
黎璧賢
教授
王敏生
教授
高仲明
教授
陳培亮
教授
陳宣毅
副教授
薛雅薇
助理教授
李紀倫
助理教授
李弘謙
合聘教授(中大系生所)
陳志強
合聘教授(中研院物理所)
梁鈞泰
合聘教授(中研院物理所)
林耿慧
合聘助理教授(中研院物理所)
阮文滔
合聘助理教授(中研院物理所)
Ph.D
研究專長
Email Address
Rutgers University
複雜系統/生物物理 (實驗)
[email protected]
Rice University
生物物理/生物膜 (實驗)
U of Pittsburgh
生物物理/軟凝態物理/神經元網路/生物材料
(理論/實驗)
[email protected]
[email protected]
U of Pittsburgh
腦科學 (理論)
U of Arizona
Caltech
演化的模擬 (理論)
[email protected]
[email protected]
生物圖案形成/軟物質/生物力學 (理論/實驗)
[email protected]
軟凝態物理/生物物理 (理論)
[email protected]
U of Toronto
生物膜物理/核磁共振 (實驗)
[email protected]
SUNY Stony Brook
軟凝態物理/生物物理 (理論)
[email protected]
U of Pittsburgh
McGill University
計算生物/生物物理/生物訊息 (理論)
[email protected]
軟物質/生物物理/神經元網路 (實驗)
[email protected]
U of Pittsburgh
UC Santa Barbara
U of Pennsylvania
National Central U
統計物理與軟物質/生物集體行為(理論)
軟物質/生物材料 (實驗)
生物高分子/生物物理(實驗)
[email protected]
[email protected]
[email protected]
BioPhysics Theory Groups at NCU
Soft
matters
• 陳培亮 Peilong Chen: bio-hydrodynamics, mechanics of
propulsion in living organisms, pattern formation in biology
• 陳宣毅 Hsuen-Yi Chen: complex fluids, cell adhesion,
collective motion in flocks
• 黎璧賢 Pik-Yin Lai: DNA physics, biomolecular chain models,
neurons, biological networks
• 李紀倫 Chi-Lun Lee: protein folding, charged biomolecules
• 梁鈞泰 Kwan-tai Leung: self-propelling motion in organisms,
flocking, non-equilibrium bio-processes
• 高仲明 Chung-ming Ko: Evolution models, astrobiology
• 王敏生 Min-Sheng Wang: Neural Networks, brain wave &
MEG analysis
• 李弘謙 Hoong-Chien Lee: Bioinformatics, protein physics,
genome/DNA sequence analysis
Biophysics
BioPhysics Experimental Labs at NCU
• Bio-Soft Core Facilities Lab. : BioAFM, Confocal microscopy, Wet
Labs, Bio samples, fast imaging systems, fluorescence microscopy,
rheometer…
• Complex System Lab.伊林 Lin I: micro-motion of bio- and soft materials in
confined spots, dynamics of neuronal system, laser pulse-soft matter
interaction
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Biophysics Lab.陳方玉 Fang Yu Chen: Biomembrane, Membrane-active
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Peptides, Effect of peptide-forming pore on neuron function
Bio-membrane Lab.薛雅薇 Ya-Wei Hsueh: lipid rafts in cell membranes, NMR
spectroscopy, AFM measurement
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Bio-Soft Matters Lab.黎璧賢 Pik-Yin Lai, 陳志強 C.K. Chan:
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interactions in cells, neuronal networks, DNA mechanics & hydrodynamics,
biomaterials
Soft-condensed Matter Lab.陳培亮 Peilong Chen: bio-hydrodynamics,
mechanics of propulsion in living organisms
Soft-Matter Lab. 林耿慧 K.H.Lin, 阮文滔 W.T.Juan: bio-soft materials,
colloids, single-molecule DNA
E
Biophysics/Soft-matter
Theory & Experimental Group
Bio-Soft Matters Lab. & Simulational Physics Lab.
Principal Investigators: Pik-Yin Lai , C.K. Chan
Graduate Institute of BioPhysics & Center for Complex Systems, NCU
Bio-Soft Matters Lab. Recent experimental research topics include
single-molecule experiments on biomolecules、complex network of neuron/cardiac
cells、synchronized firing of neuronal networks、 dynamical/collective behavior of
cells、DNA under flow、molecular motors、ion-channels. Drag reduction 。
Biophysics/Soft-matter
Bio-Soft Matters Lab. & Simulational Physics Lab.
Principal Investigators: Pik-Yin Lai , C.K. Chan
Graduate Institute of BioPhysics & Center for Complex Systems, NCU
Simulational Physics Lab. Simulations & analytical studies
in close connection with expts. in Bio-Soft Matters Lab.
Biological networks、structure & dynamics of biomolecules 、DNA
elasticity/hydrodynamics、physics & topological interactions in knots、phase
transitions in polymeric systems、 grafted polymer layers、 polymer adsorption 、
charged polymers。
Play (Torture) with DNA
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DNA stretching, elasticity
DNA drag reduction
DNA thermo-phoresis
DNA condensation
DNA under external fields
DNA jamming
DNA fibers
………
B-form to S-form Transition under a Stretching force
Lai & Zhou, J. Chem. Physics 118, 11189 (2003)
Force Experiments
Stretching a single end-grafted DNA
S-form
B-form
•Abrupt increase of 1.7 times in contour length of dsDNA near
65pN.
•Thermal fluctuations unimportant near onset of transition.
DNA transcription by RNA polymerase
T7 DNA polymerase
•effect of template tension polymerase
activity
•Pausing & arrest during polymerase
•Mechanism of polymerization kinetics
•Tune rate of DNA replication with
external stresses
Classical mechanics approach
•(thermal effects can be neglected since the DNA is quite straight near
the onset of BS)
•All lengths in units of R, energy in units of k/R f=fz, dimensionless
2
force b=fR /2k, t=(sinqcosf,sinq,sinf,cosq)
Minimizing Ebs: Euler Lagrange eqns.
B.C.s:
First order phase transition at bt
First-order elongation:Stretch by untwisting
b=0.073
Untwisting upon stretching
b=0.075
Untwist per contour length from BS, DTw/Lo~-100 deg. /nm;
•Almost completely unwound ~ 34deg./bp
•Torque ~ 60 pN nm
Direct observation of DNA rotation during
transcription by Escherichia coli RNA
polymerase Harada et al., Nature 409 , 113 (2001)
•DNA motor: untwisting gives
rise to a torque
•BS transition provides a
switch for such a motor.
G > 5 pN nm from hydrodynamic drag estimate
DNA thermophoresis (Soret effect)
Migration of single DNA molecule
towards under temperature gradient.
Dyed DNA in micropipette channel (3mm~30mm)
IR laser
Soret effect in microchannel
•may be used in bio-microfluidics, DNA separation process
•Possible mechanism to achieve high DNA conc. for
pre-biotic life emergence in sea
DNA condensation & packing
Complex competition of DNA elasticity,
charge interactions, volume interactions,
solvent effects…..
DNA condensed by spermidine
Good turbulent drag Reducer
Poor Drag Reducer
Molecular Jamming of DNA in Gel Electrophoresis
- - - - - - - - DNA+SPD
E
DNA
0.7% agarose gel
+ + ++ ++ +++
Single-λ DNA with [SPD]=20mM jamming when
entering in 0.7% gel from 0.5X TBE buffer solution
E
DNA under external drive
DNA in gel under AC electric field 
DNA fibers by Electro-spinning
• DNA are negatively charged, SPD are added to
bind to DNA to form aggregate  fiber
• Understand how DNA can be packed into fibers
 biological relevant for the packing of DNA in
virus and nucleus
• DNA are negatively charged, SPD are added to
bind to DNA to form aggregate  fiber
• Produce DNA fibers of special mechanical,
electric, bio-chemical properties. Woven to DNA
sheets… Bio-materials
Expt6: DNA + SPD No PEO (1%wt, 1mM)
1Day later
Simple to Complex: emerging properties of
networks: Neurons & cardiac cells
Hodgkin-Huxley Model
(1952)
Signal across synapses
Neuron Cell does not divide: number of neurons non-increasing.
Complex behavior/function determined by neurons
connections/synaptic strength.
Complex neuronal Network:
•A single neuron in vertebrate cortex connects ~10000 neurons
•Mammalian brain contains > 10**10 interconnected neurons
•Signal & information convey via neuronal connections—coding
Coupled oscillator networks of Cardic cells:
nonlinear dynamics, spiral waves, spatiao-temporal patterns…
Hodgkin-Huxley model (1952)
Expts. On giant axon of squid:
time & voltage dependent Na, K ion channels
+ leakage current
I(t) = IC(t) +
Ik(t)
Ik = gNa m3h (u - ENa) + gK n4 (u - EK) + gL (u - EL).
gating variables:
a,
=
(u) (1 - m) -
(u) m
=
(u) (1 - n) -
(u) n
(u) (1 - h) =
b: empirical functions
(u) h
Experiments
Schematic procedures in preparing
the sample of neuron cells from
celebral cortex embryonic rats
Embryos of Wistar rats
E17~E18 breeding days
http://mouse.kribb.re.kr/mou
sehtml/kistwistar.htm
Growth of axon connection to form a network
Typical confocal microscope pictures of cultures used in our experiments.
Red: anti-MAP2 (neuronal marker); Green, anti-GFAP (glia marker). Black &white:
phase contrast image; Merge of the three images above.
Optical recording of fluorescence
signals from firing network
Firing of the network is monitored by the changes in intracellular
[Ca 2+] which is indicated by the fluorescence probe (Oregon
Green).
Non-synchronous Firing in early stage of growth
Synchronized Firing of Neuronal Network Culture
Spontaneous firing of the cultures are induced
by reducing [Mg2+] in the Buffered salt solution
Firing  the changes in intracellular [Ca 2+] indicated by the
fluorescence probe.
Synchronized Firing at later stage of growth
Time dependence of the SF frequency for a
growing network
Phys. Rev. Lett. 93 088101 (2004)
PRE (2006)
•Critical age for SF, tc
•SF freq. grows with time
f=fc+fo log(t/tc)
tc
Coupling between neurons
D
•P(D)=mean prob. that 2 neurons initially separated by D
will be connected
•Characteristic coupling length
• Dc ~ 0.33mm ~ 2 rc
Biological implications
• Active growth in early stage, retarded
once goal is achieved.
• Slowing down to maintain a long time
span for function: homeostasis
• Continuing fast growth used up energy
• Too much connections may exceed
information capacity for a single neuron
Many Spikes in one pulse: Bursting
Electrophysiology measurement
(whole-cell recording, current-clamp)
Glia and neuron mixed culture (8DIV, 5X105)
0
-60
Inter-burst synchronized , but intra-burst is NOT synchronized
2s
mV
Bursting: role of inhibitory element
• Continuous firing (over excited) is harmful-excitotoxicity
• Inhibitors (Glia) suppress over-excited neurons
• g=inhibitory field
• Mean-field model
• z=mean connectivity of a neuron to inhibitors
FitzHugh-Nagumo model for neurons
Network of neurons & inhibitors
Synchronized Bursting
Intra-burst NOT synchronized
Experimental/Theoretical students Wanted
• Experiments & Theories on bio-molecules, cells,
neuronal/Cardiac physics, biological networks, biocomplex systems.
• Non-physics background are welcome!
• Interface bio/living system/molecules with materials.
• Training on nano-bio-techniques
Please contact黎璧賢: [email protected]
Complex system Lab. 伊林 Lin I
Bio/soft matter systems:
• Micro-motion of bio- and soft materials in
confined spots
• dynamics of neuronal system
• laser pulse-soft/bio matter interaction
Dusty plasma liquids:
• effects of thermal excitation, external
shear, finite size confinement, etc. on the
micro-structure and micro-dynamics of
dusty plasma liquid at the kinetic level
Biophysics Lab.
Membrane-active Peptides (NSC project)
陳方玉 Fang Yu Chen
Anti-microbial peptides (AmP) is gene-encoded and is produced in innate
immune system as the first-line defender to invading microbes and bacteria.
There are three types of AmP -- -helix, b-sheet and q-ring. We have
successfully proved the killing mechanism of -helix AmP - - stretching the
target cell membrane to form pores on membrane, that leads the target cell to
the death.
We are now focusing at killing mechanism of those b-sheet and q-ring AMPs.
Effect of peptide-forming pore on neuron function
(UTS project)
Gramicidin A (GA) is a small peptide, capable of forming trans-membrane ion
channel which allows monovalent cations to pass. We are studying the effect of
such GA channel on neuorn function.
Ya-Wei Hsueh
• Physical properties of biomembranes
•Lipid-Protein interaction
•applying solid-state NMR techniques in biological systems
Important Issues
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The size of lipid rafts ?
Fraction of lipid rafts in cell membranes ?
The stability of lipid rafts ?
The origin of lipid rafts in cell membranes ?
protein
sphingolipid
phospholipid
●
Techniques:
protein
cholesterol
Nuclear magnetic resonance)
Atomic force microscopy (AFM)
Fluid Dynamics & Soft Matters
陳培亮 Peilong Chen
Statistical Mechanics of Electrolyte Solutions
Distribution of electrolytes near interface, e.g., the cell membrane
Fluid Dynamics in Soap Film
Measuring friction at air-film interface
Pattern Formation in Faraday Waves
Pattern and mean flow interaction
Block Copolymer Shear Alignment
Derive the diffusion-stress
coupled dynamics
Active membranes
Hsuan-Yi Chen
Pattern formation: inclusions in
different states dislike each other.
increasing activities
Computational Biology Laboratory
HC Lee
•Universality, Complexity & Self-Similarity in Complete
Genomes
•Molecular dynamics simulation of Protein Structure & Function
Wang, Min-Sheng (王敏生)
Inverse problem of MEG (magnetoencephalography)
Objective: To develop a method to determine the locations
and strengths of synchronously activated neurons in the
brain from the MEG data.
Method: The brain is divided into blocks and a certain
number of current dipoles are placed at the center of
each block to represent the collective effect of
synchronously activated neurons in that block.
Assuming that the firing strength of all the current
dipoles has the same Gaussian distribution of zero
mean and large width prior to the knowledge of MEG
data, the entropy of the whole system is minimized with
respect to this Gaussian distribution (maximum entropy)
under the constraint of MEG data.
BioPhysics Institute @NCU
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Officially established in 2004
Professors: 6 Assoc. Prof.: 1 Assist. Prof. 3
Adj. Prof.: 2
Adj. assist.prof.: 2
Graduate students working on areas in biophysics
M.S.：23 Ph. D.：8
Postdocs: 6
aims at achieving some quantitative description of
biological processes and search for the fundamental
principles buried in these highly complex biological
phenomena
「5 years 500B」grant to support research &
building of core facility labs.
Cross-disciplinary: researchers/students from
physics & non-physics background