1. Application of Molecular Biotechnologies to Remediation
Shu-Chi Chang, Ph.D., P.E., P.A.
Assistant Professor1 and Division Chief2
1Department of Environmental Engineering
2Division of Occupational Safety and Health,
Center for Environmental Protection and Occupational Safety and Health
National Chung Hsing University
Wednesday, June 13, 2007

2. Categories Molecular biological methods Biochemical methods
Microbiological methods

3. Molecular biological methods
PCR based
A PCR animation from “Molecular Biology of the Cell”
Probe hybridization

4. PCR based
ARDRA (amplified ribosomal DNA restriction analysis): Separates amplified 16S molecules by restriction patterns
DGGE (denaturing gradient gel electrophoresis): Separates amplified 16S molecules by %G-C content
TGGE (temperature gradient gel electrophoresis): Separates amplified 16S molecules by %G-C content;
T-RFLP (terminal-restriction fragment length polymorphism): Separates amplified 16S molecules by restriction patterns
LH-PCR (length heterogeneity polymerase chain reaction): Separates amplified 16S molecules by length
RISA (ribosomal intergenic spacer analysis): Separates amplified 16S-23S intergenic region by length
SSCP (single-strand conformation polymorphism): Separates amplified 16S ssDNA by sequence-dependent higher order structure
RAPD (randomly amplified polymorphic DNA): Sequence-independent profiling based on random PCR priming,
Sequencing of cultured isolates: Sequencing of PCR amplicons derived from cultured isolates
Functional PCR: Several PCR-based analyses using amplified catabolic genes; indirect functional assay
Direct cloning and sequencing: Direct sequencing of isolated and cloned fragments

5. ARDRA Amplify community rDNA Add combinations of restriction enzymes
Assumption: if right enzymes were used, each species will have a unique pattern (fingerprint). However, it is hard to differentiate from each other. Usually only one fingerprint for one community
BY incorporating probe hybridization, more detail information can be obtained
Disadvantage: need optimized combination of restriction enzymes.
Advantage: fast and cost-effective

6. DGGE
Different G-C contents render different mobility in DNA-denaturing gel which is prepared to have a concentration gradient of denaturant.
Probably most widely applied method for community characterization.
Limitation
Need to optimize the gradient and electrophoresis duration
DNA fragment < 500bp
Need large quantity of DNA
Statistical method may help to resolve some problems associated with DGGE.

7. T-RFLP Modified form of ARDRA using fluorescent PCR primers
Limitation of database (only prokaryotic)
Can only observe 50 or so populations
Sensitivity ~0.5%
Potential bias from PCR
Probably more quantitative than other methods

8. RISA Ribosomal intergenic region
Utilizing natual variability of rrl operon in rRNA
Can be used to distinguish different strains and closely related species
Rapid and simple but biases from PCR and secondary structure.

9. RAPD Is able to generate a unique set of amplicons for each species.
random short PCR primer
Usually 5~15 sets per species
Cannot be complemented by other method

10. Comparison of methods

11. Probe hybridization
General probe hybridization: Identifies presence of desired sequences using labeled probes
DNA microarrays: Extremely high-throughput multiple probe hybridization

12. Probe hybridization Purposes Type Presence of various taxanomic groups
Measure relative abundance
Determine their spatial distribution
Type
FISH
CISH
CARD-FISH
MAR-FISH

13. Probe hybridization Advantages Disadvantages Great flexibility
Rapid and low cost
Good specificity, usually
Can aim at multiple targets
Disadvantages
Probe design ->mismatch
Sensitivity

14. DNA microarray

15. Microarray data analysis

16. Microarray Related areas Notable companies
Bioinformatics : Online Services : Gene Expression and Regulation at the Open Directory Project
Gene Expression : Databases at the Open Directory Project
Gene Expression : Software at the Open Directory Project
Data Mining : Tool Vendors at the Open Directory Project
Notable companies
Affymetrix
Agilent Technologies
CombiMatrix
Eppendorf
Nanogen

17. Biochemical methods DNA composition and kinetics assays
DNA reassociation kinetics: Estimates sample diversity based on rate of reassociation of denatured DNA
Bisbenzimidazole-CsCl-gradient fractionation: DNA fractionnation based on %GC content
Community DNA hybridization: Estimates relative similarity of two communities by cross hybridization kinetics
Metabolic assays
Metabolomics: Emerging technique to profile total metabolites produced by a community
Lipid analyses
Quinone profiling: Culture-independent community profile based on distribution of quinones
PLFA (phospholipids fatty acids) + FAME (fatty acid methyl esters): Culture-independent community profile based on distribution of various membrane lipids

18. Metabolomics
Systematic study of the unique chemical fingerprints that specific cellular processes leave behind
mRNA gene expression data and proteomic analyses do not tell the whole story of what might be happening in a cell, metabolic profiling can give an instantaneous snapshot of the physiology of that cell.

19. PLFA

20. PLFA

21. PLFA

22. Microbiological methods
Metabolic assay
CLPP (community-level physiological profiling): Creates a profile of substrates metabolized by the microbial community
Cell counting techniques
Direct cell counting: Microscopic counting of stained cells
Indirect cell counting: Counting of a culturable subset of the microbial community
Morphological counting: Microscopic identification and enumeration of the morphotypes in an environmental sample
Flow cytometry and cell sorting: Physically separates microbial assemblages on the basis of measurable properties,

23. CLPP
BiologTM

24. Basics of flow cytometry
Light
source
Side scatter light
Forward scatter light
Forward scatter : Blue
Fluorescence 3: Red
Fluorescence 4: Dark red
Fluorescence 2: Yellow
Side Scatter : Blue
Fluorescence 1: Green
Flow cytometry is not like a microscope which allows you to examine each cell by your eyes or camera. Then, how do you get the cellular phenotypic information. Here, I show you a very simple figure explaining how it works. First, we need a laser light, which has a narrow band of wavelengths and comes in from the left hand side of this picture. Then, it hits on a particle. If the particle is small, you got more light passing through without hitting it. Therefore, smaller particle, higher forward scatter light intensity. Flow cytometer also have several detectors at the side direction. This side scatter light is proportional to the internal complexity and granularity. More interanlly complex particle will reflect or deflect the lights more. So, particle which is transparent will exhibit very low side scatter light intensity and opaque one very high. At the side direction, fluorescent lights which have wavelengths longer than the laser are also collected and those are emitted from the fluorescently labeled particles.

25. Basics of flow cytometry
No.
FSC
SSC
FL1
FL2
FL3
FL4
Fluorescence 1
Side Scatter 1
0.50
1.20
2.23
0.31
0.54
0.33
530/30
Fluorescence 2 2
3.11
1.22
0.45
0.39
0.51
3.33 3
0.27
3.20
0.38
1.24
3.61
3.44 4
0.06
0.01
1.14
0.71
1.67
0.69 5
1.27
1.92
2.30
3.07
2.74 6
3.14
1.18
0.16 7
3.13
3.28
0.55
0.21
2.55 8
3.88
0.84
3.37
2.94
0.52 9
0.88
0.43
1.51
1.85
2.86 10
2.07
1.64
0.92
1.12
1.83
488/10
Fluorescence 4
Use same title from previous slide
Spell out the acronyms in the figure, take out the animation that flashes, it is not helpful, label the second figure that shows up with appropriate text (also take out the moving of this figure, it is not helpful). You can’t see the cells, just pay more attention to every detail in the figure. Ask yourself why is it there, should I spell it out, should I label it, etc.
I am not sure why you have the bullet with microfluidics etc. What is the point you are trying to make with that?
The method has to be fast in order to address the needs of effective mycobacteria management. Currently, one of the fastest particle counting instrument is flow cytometry. It has multiple color detection capability. It can easily detect 100, 000 particles per second. Each detected particle will have six values registered in computer memory, one from forward direction and five from side direction. Forward scatter and side scatter light detector will pick up the signal at the same wavelength as the first laser. The othe four detectors pick up only certain wavelengths, or color of light, due to the optical arrangement. For example, fluorescent light 1 detector, it picks up green light and fluorescent light 4 detector picks up the bright red color.
Here let me show you what happens when the particle is passing through the detection zone in this flow cell. Sample is introduced from the back of the picture to coming out the picture.
Click
Each time, when a particle passes through the detection zone, the signal will be picked up. Six values are stored from six different detectors for each particle. But, keep in mind, not only fluorescently labeled bacterial cell will emit fluorescent light, some other particles may also exhibit fluorescent light, which is unwanted noise.
A very key module of this instrument is its microfluidic part. If we observe from the side of the flow cell following the direction from the bottom to the top of this picture. We will see a structure like this.
The scale here is usually less than 1000 micrometer, about 10 times of a human hair. When this yellowish liquid sample is introduced into the detection zone surrounded by the sheath fluid, it will be hydrodynamically focused due to the velocity difference and the laminar flow characteristics in such a tiny channel. Therefore, each particle will pass through the detection zone one by one.
Now, I can observe fluorescent particle in a dark background and I got four detectors to see different colors. It is kind of like the vision.
585/42
661/16
Fluorescence 3
670LP
488nm
Blue Laser
FSC
635nm
Red Laser
488/10
Three major modules: Optics, Electronics, and Microfluidics.

26. Flow cytometry output R2 R1 High FL1: Green Fluorescence Low
Light
source
Side scatter light
Forward
scatter
light
FSC
FL4
FL3
FL2
SSC
FL1
Flow cytometry output
High R2
If we take two values out of the six of each particles. For example, we take green fluorescence versus side scatter light to form a dot plot. Here, the s-axis is the side scatter light intensity. If the particle is transparent, the light intensity will be low. If opaque, it will be high. On the y-axis, if the particle emits high green fluorescence, the fluorescence 1 intensity will be high and if it is dim, it will be low.
Now, let me show you what we would see on a dot plot. If, in a very clean sample, we stain the bacterial cell with green fluorescent dyes specific to double stranded DNA, deoxyribonucleic acid, we will expect the biological particle with intact double stranded DNA will have higher green fluorescence intensity than other kind of particles. Here I show you the first five events with various different light intensities. Some particles may have exactly the same or very similar green light intensities. within a seconds, you may get thousands of particles, and two different populations emerge here. If you use a latex microsphere intensively stained by a green fluorophore, you can see a separate population here.
Click
It may show up at upper-right corner. Again, here, we only used 2 values out of the six values from each particle. Now, we have multiple samples and therefore, multiple files to compare. Usually, we apply different gating windows on dot plots. Once we draw the region on one dot plot, the software will do the apply the same gating region to other files. Here, I just show you how it works. Therefore, different colors on a dot plot do not mean anything but differentiating populations.
Here, we can see that two-dimensional dot plot can help us to differentiate two populations with similar side-scatter light intensities due to their difference on green fluorescent light. Then, how about different bacteria, like mycobacteria and other bacteria, they may have very similar green fluorescence intensity and side scatter light intensity. In this case, we will need a mycobacteria-specific antibody to label only mycobacteria with a color other than green. So, by adding one more dimension, we should be able to differentiate mycobacteria from other bacteria. R1
FL1: Green Fluorescence
Low
Side scatter light
Transparent
Opaque