DNA microarray and analysis of metabolic control

By Shilpa Sharma

DNA MICROARRAYS

DNA microarrays are solid supports, usually of glass or silicon, upon which DNA is attached in an organized grid fashion. Each spot of DNA, called a probe, represents a single gene.

There are several synonyms of DNA microarrays such as DNA chips, gene chips, DNA arrays, gene arrays and biochips.

Microarray technology evolved from Southern blotting, where fragmented DNA is attached to a substrate and then probed with a known DNA sequence.

The use of miniaturized microarrays for gene expression profiling was first reported in 1995, and a complete eukaryotic genome (Saccharomyces cerevisiae) on a microarray was published in 1997

Principle

The principle of DNA microarrays lies on the hybridization between the nucleotide. Using this technology the presence of one genomic or cDNA sequence in 1,00,000 or more sequences can be screened in a single hybridization.

The property of complementary nucleic acid sequences is to specifically pair with each other by forming hydrogen bonds

between complementary nucleotide base pairs.

Design of a DNA Microarray System

Types of DNA chips

1. cDNA based microarray 2. Oligonucleotide

based microaaray

Microarray Data Analysis

• The goal of microarray image analysis is to extract intensity descriptors from each spot that represent gene expression levels and input features for further analysis. Biological conclusions are then drawn based on the results from data mining and statistical analysis of all extracted features. Components of DNA Microarray image analysis are:

• Grid Alignment Problem• Foreground Separation• Quality Assurance• Quantification • Normalization

Microarray Data analysis

Input: Laser image scans (data) and underlying experiment hypotheses or experiment designs .

Output: Conclusions about statistical behaviour of measurements and thus the test of the hypotheses or knowledge. The results are derived automatically from data for subsequent model fitting.

Microarray data processing workflow

Fluorescent DNA microarray images obtained from laser scanners containing a 2D array of dots with two channels of 532nm (red) and 632nm (green) wavelengths.

DNA microarray analysis of gene expression in response to physiological and genetic

changes that affect tryptophan metabolism in Escherichia coli.

• E. coli can synthesize, transport, and degrade tryptophan

• we used DNA microarrays to measure transcript levels corresponding to almost every translated gene of E. Coli.

• Every gene responding transcriptionally should show increased or decreased mRNA levels.

• Expression also was examined in strains with mutations that affect expression of the genes of tryptophan metabolism.

Following questions were addressed:

• Which genes exhibit expression patterns indicating that their expression is influenced by changes in tryptophan availability?

• Which genes are transcriptionally repressed when trp repressor is active, and transcriptionally active when trp repressor is inactive?

• Do quantitative estimates of gene expression provided by microarray analyses agree with previous estimates of gene expression based on measurements of specific protein levels?

Known genes of tryptophan metabolism in E.coli

Materials and Methods

• Strains Used and Growth Condition Examined Vogel and Bonner minimal medium (17)+0.2%

glucose was used throughout. It was supplemented with L-tryptophan (50 mg/ml) or indole acrylic acid (10 or 15 mg/ml), as indicated. After growth to about 2–3 3 108 cell/ml, sodium azide was added to each culture and the culture was chilled and centrifuged. Each cell pellet was stored at 280°C until its RNA was extracted.

• Our principal objective is to identify all of the protein-encoding genes of E. coli whose

transcripts become more or less abundant when the growth medium or genetic background of the strains are change.

Data Selection and Analysis

• Data were collected by using microarrays using spots whose intensities were reproducibly higher than the background level.

• We measured relative mRNA abundance under appropriate conditions in 19 comparisons. These were divided into the following categories:

1) Growth with and without added trp --- (+TRP) 5 comparisons2) Growth with and without trp starvation ---(-TRP) 9 comparisons3) Growth of strains with and without trp repressor ---(trpR) 5

comparisons

Growth condition examined and strains compared

Minimal medium vs. excess tryptophan1. trpR+ (Min) vs. trpR+ (Min + Trp) Nonstarved vs. tryptophan-starved1. trpR+ (Min) vs. trpR+ (Min + 10 mg/ml indole acrylate)2. trpR+ (Min) vs. trpR+ (Min + 15 mg/ml indole acrylate)3. trpR+ tnaA2 (Min) vs. trpR+ trpA46PR9 tnaA2 (Min) trpR+ vs. trpR2 (repressor minus)1. trpR+ (Min) vs. trpR2 (Min)2. trpR+(Min) vs. trpR2 (Min + Trp)3. trpR+ (Min + Trp) vs. trpR2 (Min + Trp)4. trpR+ tnaA2 (Min + Trp) vs. trpR2 tnaA2 (Min + Trp)5. trpR+ DtrpEA2 (Min + Trp) vs. trpR2 DtrpEA2 (Min + Trp)

3 Different conditions have different effects on trp metabolism

1) Excess trp was added to cultures growing in minimal medium (+TRP):- Transcription termination occur

2) Cultures were partially starved of tryptophan (-TRP):- starvation imposed in either two ways : >By addition of indole acrylate to growing culture :- it has two

effects ---Prevent the trp repressor from acting --- Inhibits the charging of tRNATrp by tryptophanyl-tRNA

synthetase >By using a trp bradytroph,strain trpA46PR9 :- The bradytroph

used grows at only 80% the rate of the wild type strain in min medium because its mutant TrpA protein is only slightly active ---

--- this defect results in overexpression of the trp operon as the cell attempts to provide sufficient tryptophan to support rapid growth.

3) Inactivation of Trp repressor(trpR2) :- ---The mutant allele used trpR2, has a frameshift mutation in

trpR that eliminates the production of a functional trp repressor.

Estimated Trp protein ratios compared with trpmRNA ratios calculated from microarray data.

WtGrowth in min vs.

trp

tyrpR2 vs. Wt, growth in min

Brady vs. Wt,

growth in min

Wt, growth in IA vs. min

Gene Protein mRNA Protein mRNA mRNA Protein mRNA

trpE 10 5.0 +-0.2 7.7 6.3 11.4 46 81+-3

trpD 10 5.2+-0.7 7.7 3.7 8.0 46 43+-0.5

trpC 3.7 2.2+-0.5 4.8 4.4 8.7 29 30+-9

trpB 3.7 2.4+-0.2 4.8 4.1 6.9 29 17+-4

trpA 3.7 2.4+-0.2 4.8 3.8 9.3 29 15+-2

Dynamic changes in mRNA levels for the genes

Average Expression ProfilesTRP

ExcessTRP

StarvationtrpR

inactivationNumber of

GenesMember genes/Function

↓ - ↑ 1 b1172

↓ - ↓ 1 fliA

↑ - ↑ 1 tnaA

- ↓ - 41 N-metabolism/motility

- - ↑ 40 IS5 copies and unknown

- ↑ - 35 yi21/22 copies and unknown

- - ↓ 24 Transport/intermed. metblsm

↓ - - 13 Aromatic AA biosynthesis

↑ - - 6 tnaB, artJ, malE and unknown

↓ ↑ ↑ 7 trpR regulon

- - - 522 N/A

36* 79* 82* 691

Conclusion

• Results demonstrate both quantitatively and qualitatively that only 3 operons trp, mtr, and aroH, constitute the core,highly responsive trp repressor regulon.

• mRNA levels for a group of genes concerned with aromatic amino acid biosynthesis decreased when tryptophan was in excess

• Only one operon, containing two genes, tnaA-tnaB, was up-regulated on tryptophan addition

References

• Arkady B. Khodursky*, Brian J. Peter†, Nicholas R. Cozzarelli†, David Botstein‡, Patrick O. Brown*§, and Charles Yanofsky, DNA microarray analysis of gene expression in response to physiological and genetic changes that affect tryptophan metabolism in Escherichia col, August 29, 2000.

• http://genome.genetics.duke.edu/STAT_talk_301.

• MANJULA KURELLA, LI-LI HSIAO,* TAKUMI YOSHIDA, JEFFREY D. RANDALL, GARY CHOW, SATINDER S. SARANG, RODERICK V. JENSEN, and STEVEN R. GULLANS, DNA Microarray Analysis of Complex Biologic Processes, J Am Soc Nephrol 12: 1072–1078, 2001.