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Model-based Inference of Gene Expression Dynamics from Sequence Information

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Biotechnology for the Future

Part of the book series: Advances in Biochemical Engineering/Biotechnology ((ABE,volume 100))

Abstract

A dynamic model of prokaryotic gene expression is developed that makes considerable use of gene sequence information. The main contribution arises from the fact that the combined gene expression model allows us to access the impact of altering a nucleotide sequence on the dynamics of gene expression rates mechanistically. The high level of detail of the mathematical model is considered as an important step towards bringing together the tremendous amount of biological in-depth knowledge that has been accumulated at the molecular level, using a systems level analysis (in the sense of a bottom-up, inductive approach). This enables to the model to provide highly detailed insights into the various steps of the protein expression process and it allows us to access possible targets for model-based design. Taken as a whole, the mathematical gene expression model presented in this study provides a comprehensive framework for a thorough analysis of sequence-related effects on the stages of mRNA synthesis, mRNA degradation and ribosomal translation, as well as their nonlinear interconnectedness. Therefore, it may be useful in the rational design of recombinant bacterial protein synthesis systems, the modulation of enzyme activities in pathway design, in vitro protein biosynthesis, and RNA-based vaccination.

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Abbreviations

a i :

number of codons representing a particular amino acid i

A:

number of naturally occurring amino acids

c:

codon usage

C:

metabolite concentration (μM)

d:

spacing between ribosomes and degradosomes, and between SD sequence and translational start codons

D:

promoter contained on DNA template

f:

fraction of single-stranded bases within the 23 bases subsequent to the Shine-Dalgarno sequence

f j,i :

relative portion of base j contained in transcript i (%)

G :

free energy (kJ/mol)

J :

number of base triplets of a mRNA

k i :

respective rate constant

K :

last codon of a coding region

K a :

association constant

K d :

dissociation constant

K I :

inhibition constant for respective metabolite (μM)

K M :

Michaelis-Menten constant for respective substrate (μM)

L j :

physical diameter of a ribosome and degradosome, respectively

m :

mass (g)

m i :

ratio of RNA species i to total measured RNA (g/g)

m i,j :

element of matrix M

m j :

reference state of a ribosome and a degradosome, respectively

M :

mRNA

M :

number of mRNA molecules

M :

mRNA matrix

n :

number

n i :

transcript length for RNA species i (kb)

n cod :

number of base triplets used to denote a state

N :

number of ribonucleic bases

N A :

Avogadro number

R :

number of RNA species synthesized from a given DNA template

S :

number of segments

t :

time (min)

T :

number of tRNA species

T :

temperature (K)

T :

time (s)

V :

reaction rate (μM/min)

V :

volume (μl)

V P :

relative protein expression rate (%)

X :

measured radioactivity (dpm/μL)

z :

position of endonucleolytic cleavage site

Z :

number of fragments of a mRNA obtained by endonucleolytic cleavage

η:

fractional codon usage

μ:

specific growth rate (h−1)

Φ:

efficiency factor

ϕ:

T7 transcription terminator

ϕ10:

T7 promoter

φ:

energy charge

aq:

aqueous

avg:

average

cell:

referring to a single cell

CR:

catabolite repression

d:

degradation

D:

refers to promoter sequence of a DNA

D0:

refers to a degradosome association site

dto:

ditto

eff:

effective

eq:

thermodynamic equilibrium

exp:

experimentally determined

f:

formyl-

f:

forward reaction

i :

count index

in:

entering equilibrium computation

I:

induction

j :

count index

k :

count index

m:

methionine

NTP:

nucleoside triphosphate

out:

outcome of equilibrium computation

qss:

quasi-stationary state

r:

reverse reaction

R0:

refers to a ribosome binding site

s :

count index

sim:

predicted from simulation

t:

denotes total concentration

un:

unbound

′:

refers to new codon grid representation

0:

initial condition

0:

standard condition

A:

refers to the A-site of a ribosome

D:

degradosome

M:

mRNA

M:

methionine

max:

maximum value

P:

refers to the P-site of a ribosome

R:

ribosome

R* :

ribosome bound to the initiation codon prior to IF2-dissociation

30S:

small prokaryotic ribosomal subunit

30SIC:

30S initiation complex

50S:

large prokaryotic ribosomal subunit

70S:

free, undissociated prokaryotic ribosome

70SIC:

70S initiation complex

A:

adenine

aa:

amino acid(s)

aa-tRNA:

aminoacyl-tRNA

Ac:

acetate

Ack:

acetate kinase

AcP:

acetyl phosphate

ACSL:

Advanced Continuous Simulation Language

Adk:

adenylate kinase

ADP:

adenosine diphosphate

Ala:

alanine

AMP:

adenosine monophosphate

Arg:

arginine

ARS:

aminoacyl-tRNA-synthetase

Asn:

asparagine

Asp:

aspartic acid

ass:

association

ATP:

adenosine triphosphate

AUG:

translational start codon

bp:

base pairs

BSA:

bovine serum albumin

C:

cytosine

CDP:

cytosine diphosphate

CMP:

cytosine monophosphate

CTP:

cytosine triphosphate

Cys:

cysteine

DNA:

deoxyribonucleic acid

E:

enzyme

EC:

Enzyme Commission

EF:

translational elongation factor

EMBL:

European Molecular Biology Laboratory

endo:

endonucleolytic

exo:

exonucleolytic

F:

folded conformation of the ribosome binding site

fMet-tRNA f M :

N-formylmethionyl-tRNA

Frag:

mRNA fragment

G:

guanine

GDP:

guanosine diphosphate

GFP:

green fluorescent protein

Gln:

glutamine

Glu:

glutamic acid

Gly:

glycine

GMP:

guanosine monophosphate

GTP:

guanosine triphosphate

h:

hour

His:

histidine

IC:

initiation complex

IF:

translational initiation factor

IF2D:

IF2-dependent GTP hydrolysis

Ile:

isoleucine

K:

Kelvin

kb:

kilobases

kDa:

kiloDalton (1 Da ≙ 1 g/mol)

kJ:

kiloJoule

Leu:

leucine

Lys:

lysine

Met:

methionine

min:

minute

mRNA:

messenger RNA

mv:

degradosome movement

Ndk:

nucleoside diphosphate kinase

NDP:

nucleoside diphosphate

Nmk:

nucleoside monophosphate kinase

NMP:

nucleoside monophosphate

nt:

nucleotide(s)

NTP:

nucleoside triphosphate

P:

promoter

PAGE:

polyacryl amide gel electrophoresis

PAP I:

poly-adenylate phosphorylase

pelB:

pelB leader sequence

Phe:

phenylalanine

Pi:

inorganic phosphate

PNPase:

polynucleotide phosphorylase

PPi:

inorganic pyrophosphate

PPK:

polyphosphate kinase

Pro:

proline

RBS:

ribosome binding site

rDNA:

recombinant DNA

RF:

translational termination factor

RFH:

a particular translational termination factor

RNA:

ribonucleic acid

RNAP:

DNA-dependent RNA polymerase

RNase:

ribonuclease

RP:

ribosomal protein

RRF:

ribosome release factor

rRNA:

ribosomal RNA

s:

second

S1:

ribosomal protein S1 (contained in 30S ribosomal subunit)

Ser:

serine

SNP:

single-nucleotide polymorphism

ssRNA:

single-stranded RNA

T:

terminator

T:

thymine

T:

tRNA

T3:

ternary complex (consists of one copy of EFTu, GTP, and aa-tRNA)

TC:

transcription

TCA:

tricarboxylic acid

TCE:

transcription elongation

TCI:

transcription initiation

TCT:

transcription termination

TE:

termination efficiency

THF:

H4-folate

Thr:

threonine

TL:

translation

TLE:

translation elongation

TLI:

translation initiation

TLT:

translation termination

tmRNA:

transfer-messenger RNA

Tris:

tris(hydroxymethyl)aminomethane

tRNA:

transfer RNA

Trp:

tryptophan

Tyr:

tyrosine

U:

unit

U:

uracil

UDP:

uracil diphosphate

UMP:

uracil monophosphate

UTP:

uracil triphosphate

Val:

valine

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Author information

Authors and Affiliations

  1. Biotechnology R&D, DSM Nutritional Products Ltd., Bldg. 203/113A, 4002, Basel, Switzerland

    Sabine Arnold

  2. University of Stuttgart, Institute of Biochemical Engineering, Allmandring 31, 70569, Stuttgart, Germany

    Martin Siemann-Herzberg, Joachim Schmid & Matthias Reuss

Authors
  1. Sabine Arnold
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  2. Martin Siemann-Herzberg
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  3. Joachim Schmid
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  4. Matthias Reuss
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Correspondence to Matthias Reuss .

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J. Nielsen

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Arnold, S., Siemann-Herzberg, M., Schmid, J., Reuss, M. Model-based Inference of Gene Expression Dynamics from Sequence Information. In: Nielsen, J. (eds) Biotechnology for the Future. Advances in Biochemical Engineering/Biotechnology, vol 100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/b136414

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