Lecture notes for evolution III
For Nov. 21, 2001
Last modified Nov. 20, 2000 1PM
David Nelson
Comparative Genetics and Human Evolution, What Makes Us Human
Humans and chimpanzees have DNA sequences that are 98.74% identical (over 3 million bases).
When one considers that our DNA is 3 billion base pairs, that means that only 38
million bases differ between humans and chimps. According to the Feb 15 2001 Nature only 1.1%
of our genome is exons (however the gene count estimates have almost doubled since then, so
assume 2% is exons) The other 98% is non-coding sometimes called junk DNA, then the number of
base pairs that differ in genes is about 756,000. If we have 70,000 genes (this gene count
estimate seems to the current best guess) that is about 11 base differences per gene. Most
genes are not going to be seriously changed by a handful of base changes. In fact, most of
these changes are probably going to be silent and result in the same amino acid sequence, or a
very conservative change like arginine for lysine. It is very unlikely that the function of a
protein will be changed by these small conservative differences. Hemoglobin will still be
hemoglobin.
So what are the differences that make us different from chimps? These will probably be
very small changes, perhaps only a single base difference in genes that make a difference in
development. An article in Science 281, 1432-1434 1998 (Sept. 4), discusses this
question. The suggestion is made that small changes in proteins like transcription factors
could have large effects. For example, a transcription factor that controlled the length of
time that the brain was able to grow would have a large effect on brain complexity and the
number of synapses that could form. One biochemical difference that has been discovered
is a defect in a human gene that modifies sialic acid. Humans do not have a functional copy of
this gene because it has a 92 bp deletion. The result is a change in the cell surfaces where
glycoproteins are expressed. (A structural difference between the cell surfaces of humans and
the great apes. Am J Phys Anthropol. 1998 Oct;107(2):187-98) (A mutation in human CMP-sialic
acid hydroxylase occurred after the Homo-Pan divergence. Proc Natl Acad Sci U S A. 1998
95(20):11751-6).
One of the FAQs (Frequently Asked Questions) that was asked on the Research Genetics
site for the GeneFilters was can you do a cross-species hybridization with the filters.
The answer was yes you could and if the genes were more than 70% identical good signals
could be detected under selected conditions of hybridization. Since the two genomes of
humans and chimps are so similar, it would not even matter that they were different
species. DNA microarray analysis of 60,000 human genes (5 Affymetrix chips) between chimps and
humans could be done right now to look for expression level differences in specific tissues
or developmental stages. It is likely that very few genes would show significant differences
in gene expression and these would be the ones that would make the best candidates for those
genes that make us human. Svante Paabo reports his group is doing this now "We have furthermore
studied the relative levels of expression of 20,000 genes in humans, chimpanzees and macaques.
A number of genes that differ significantly in their expression levels between humans and
chimpanzees have been identified." From an abstract at the meeting: Evolutionary Genomics
New Paradigm of Biology in the 21st Century, November 4-6, 2001 Atami Korakuen Hotel, Atami,
Japan.
Nature from July 6, 2000 reports a Japanese project to compare humans
and chimps. The Silver Project
It is called silver for the chemical symbol of silver Ag which is also short for Ape genome.
For more discussion see
this link>
Comparative Genetics and Human Races
Studies of human populations from around the world have shown that 85% of all the variation
in our DNA can be found in any small population no matter where it is on earth (Science 286,
451-453 1999). That means that 85% of all the variation there is in humans occurred before
the migration from Africa. Another 6% of the total variation is seen from within different
groups on the same continent. That only leaves 9% of the observed variation in our DNA that
is linked to differences in continents. This means the idea that human races are genetically
separate from one another is wrong. So why do races look so different? The case of
differences in skin color has been linked to a hormone receptor named MC1R for melanocortin-
stimulating hormone receptor 1. Skin color is largely determined by the ratio and
concentrations of different melanin pigments made in melaoncytes. This gene MC1R has
been shown to have multiple alleles (DNA sequence variants) in humans. These occur in the
1st and 7th transmembrane segments of the protein and the first extracellular domain.
Certain alleles are seen in 80% of people with red hair and skin that burns rather than tans.
These same alleles are seen in less than 4% of caucasian people who tan rather than burn.
These particular alleles are never seen in Africans. Different alleles are found in Asians,
some in as high as 70% of the sampled group. (Genetics 151, 1547-57 1999) The red hair
alleles show a loss of function when expressed in COS cells and assayed for cAMP production
upon addition of hormone (Biochem Biophys Res Commun 260, 488-91 1999) The variation at
this site is probably an adaptation to different sun exposure levels in these different
populations. It is expected that differences in hair color and texture, differences in
facial structure and other features of human races will be controlled by alleles of one or a
small number of genes that affect these superficial visible differences. The true
differences between human races will be minor sequence variations in receptors or some
equivalent genes and these have nothing to do with our humanity.
Genomics approaches to metabolic pathways and more on evolution
The era of studying one gene at a time to define biochemical pathways and functions is
being displaced by new methods called Genomics approaches. These methods examine the
effect of some controlled condition on the expression of hundreds or thousands of genes.
The condition may be something simple like changing nutrients in media, such as switching
yeast cells from glycerol to glucose. This will cause a large number of genes to be
repressed under the new conditions, and other genes will be activated. Whole pathways
may be turned on or shut down.
This area is changing very rapidly so much of what was here last year is obsolete. I have left
some of this information in place to emphasize the rate at which change is occurring. Notes
will indicate old and obsolete sections.
Research Genetics offers nylon filters that contain 6144 yeast genes in a defined grid.
These filters cost $1345. RNA preparations from yeast can be transcribed to cDNA and
hybridized to the filters and the intensity of the hybridized spots can be measured by a
Phosphor Imager. There are many ways this technology can be used. For instance, if a
gene knockout can be made that deletes a transcription factor gene, all the genes that this
factor controls will not be turned on or off as in the wild type cells. The concentration of
the RNA levels for all these genes will be affected.
The genes are arrayed in 32 8X24 sections plus control lanes (see figure). The Research
Genetics filters can be analyzed by hand, one spot at a time, [or for $6700 a software package
called PATHWAYS can be used that will automatically read the intensity of all 6144 spots and
enter this data into an array that can be manipulated. Two sets of filter data can be
compared by color overlay or subtraction and the results displayed as a color coded picture
of the grid pattern. ] Bracketed section is obsolote. Pathways software has gone through a
major revision so it can handle all spot formats and is more general. The price also went
through a major revision and it is now $15,500 for the Pathways 4 software.
This next section marked off by ********** is true for the old Pathways software. The new
software can be expected to do much more sophisticated analysis than this.
************
Pathways allows you to compare GENEFILTER images in two different ways:
1.Red/Green Overlay- This overlay uses one image as a red channel and the other as a
green channel, then maps their ratio. The resulting color is based on the ratio of the
intensities of both images. This method maintains the correct intensity of all spots while
still allowing a comparison of the filters.
All Red / minimal Green = Red
minimal Red / All Green = Green
All Red / All Green = All Yellow
minimal Red / minimal Green = Black
2. Red/Blue Overlay- Subtracts the intensities of one image from the other. Positive values
are shaded Red, while negative values are shaded blue.
All GENEFILTER 1 - No GENEFILTER 2 = Red
No GENEFILTER 1 - All GENEFILTER 2 = Blue
No GENEFILTER 1 - No GENEFILTER 2 = White
This color scheme immediately identifies those RNAs that decreased or increased their
expression levels under the two different conditions (wild type vs knockout), (30C vs
37C), (sporulation vs vegetative growth), (G1 vs S phase of the cell cycle) etc. Once a
spot has been identified, you can identify the gene by its position on the grid. If you have
the software, the computer will identify it for you just by clicking on it.
************
There is stiff competition for the microarray analysis software market. Two other companies
Genespring and Spotfire specialize in selling this software. Their product is by subscription
at about $3000 per subscription per year. You never own it. You only have a license to use it
for a year and this must be renewed.
A paper in the Dec 97 Nature Biotechnology 15, 1359-1367 describes the results of
experiments with an array of yeast genes comparing growth in rich and minimal media.
Figure 5 shows the pattern of expression for all the genes in a histogram plot. Lines above
the center indicate RNA is more abundant in rich medium, below the line RNA is more
abundant in minimal medium. About 20 genes are affected in a significant way (greater
than a 10-15 fold difference). Some of these make sense such as heat shock genes being
turned on in minimal medium which is a form of cell stress. However, some of these
genes are of unknown function.
Similar filters(9 different ones) are available from Research Genetics for a total 0f 46,656
human genes at 5184 genes per filter. (about 75% of the 62,193 human gene clusters in UNIGENE
with two or more ESTs in build 143 Oct 29, 2001). These 5 filters cost $980 each and they can
be stripped and reprobed about 5 times. There is competition in this market. Research Genetics
is also offering tissue specific filters from sources like breast, prostate, skin, bone, ovary,
colon ($1460 each). There are now three rat filters (about 15,000 genes) and one mouse filter
available.
This next paragraph is obsolete because Genome Systems is now part of Incyte Genomics.
Genome Systems also sells filters with human clone DNA attached. They offer
Genome Discovery Arrays (GDAs) with 46,000 different human clones from the IMAGE consortium.
These come as three different filters that cost $995 each or $1395 for a single filter set (I
think they mean two identical filters). These arrays are made by growing bacteria on the
nylon filters to 0.4mm in size, lysing the bacteria and UV crosslinking the DNA to the nylon
filters. Research Genetics claims its GeneFilters are better because they spot pure DNA
(about 1000bp of DNA from the 3 prime end of clone inserts) on the filters rather than
growing bacteria on the filters. The GDAs are being discontinued and replaced by LifeGrid
filters with pure DNA spotted as from Reserach Genetics (7075 genes on one filter)
Incyte Genomics also makes arrays of clones on glass to be labeled with fluorescent
cDNA. Up to 10,000 spots can be arrayed on one slide. They offer five different
microarrays with a total of 45,512 genes spotted. Once the DNA is bonded to the
glass, the DNA strands are treated to make the majority of them single stranded so they can
bind complementary DNA added during a hybridization. The mRNA isolated from cells
under two different conditions are transcribed into cDNA labeled with two different color
fluorescent dyes, then both are hybridized to the glass at the same time. The ratio of one
dye color to the other reflects the ratio in the hybridization mix. Spots with no dye bound
did not have any mRNA for that clone in the sample. Spots with only one dye color were
only expressed under one condition, but not the other. Spots with both dye colors were
expressed under both conditions. These GEM arrays are scanned and analyzed in house.
The prices for these GEM arrays are $4000 to analyze two RNA samples. You better be
sure that you want to know this information and that your RNA samples are perfect at
$4000 a shot. You can also buy the software to analyze your own data, but it is a bit pricey
at $7800.
NOTE: AS OF OCT 24, 2001 INCYTE GENOMICS WILL NO LONGER TAKE ORDERS FOR MICROARRAY SERVICES OR
LifeArray DNA CHIPS (They are getting out of this business).
Genetic MicroSystems Inc. is another company that offers intruments for making and
reading filters (arrayers and scanners). They have been bought up by Affymetrix as of 2000
and this of course reduces the competition.
Affymetrix seems to be beating the competition with its gene chips.
The GeneChip Human Genome U95 Set contains the most comprehensive transcript coverage of the
human genome enabling you to study the expression level of more than 60,000 human genes and ESTs
using quantitative microarray technology. The first array in the set, the Human Genome U95Av2
Array (HG-U95Av2), contains all full-length genes. This single array represents ~12,000
sequences previously characterized in terms of function or disease association.
Arrays B, C, D and E of the Human Genome U95 Set (HG-U95B, HG-U95C, HG-U95D, and HG-U95E)
contain probes interogating ~50,000 UNIGENE clusters comprised solely of EST sequences.
These are about $1000 per chip and to do an experiment with duplicates and controls would cost
about $6000. (Note this set represents almost complete coverage of the human UNIGENE clusters
with two or more ESTs).
Mapping of microarray data onto the KEGG maps is possible to see if intensity changes
correspond to whole pathways. It is also possible to calibrate the RNA intensity levels
with the absolute number of RNA molecules per cell, based on measurements of known
genes. Then the number of copies of RNA molecules per cell can be plotted on the KEGG
maps to see what pathways are coded by highly expressed genes and what pathways may
be totally unexpressed in a given condition. Filter methods are able to measure about 5
copies of an RNA per cell and detect about 5 fold changes in expression above the noise
level. The glass slide (DNA chip) methods are more sensitive at about 1 RNA per cell and
1.7 fold changes in expression levels above background noise.
De Risi, Iyer and Brown at Stanford published a paper in Science 278, 680-686
(1997) exploring the metabolic and genetic control of gene expression on a genomic scale.
They made their own microarrays and measured RNA concentrations at high glucose
(1.9%) and 9.5 hours later (0.2% glucose) as the yeast were going through a shift from
fermentation to respiration. This is called the diauxic shift. As glucose is depleted and the
ethanol concentration rises, the yeast shuts down many genes needed in the fermentation
pathways and induces the genes needed in respiration. By looking at all the genes in yeast
at once, it was possible to see these changes in mRNA levels.
The paper is posted at Patrick Browns web site,
along with all the data and microarray figures. One of the most dramatic figures is the
TCA cycle and glycolysis pathways showing the changes in gene expression in these two
pathways. TCA and glycolysis pathway map,
The induced genes are red and the repressed genes are green. It is clear
to see that the glycolysis genes from hexokinase to pyruvate kinase are repressed while the
genes of ethanol metabolism, the TCA cycle and the glyoxylate cycle are induced.
These authors went on to test the effects of gene deletion of TUP1. TUP1 is a corepressor
required for glucose repression of transcription, so its deletion should prevent glucose
repression from being efficient. Based on this hypothesis, many of the same genes that
were induced by a switch to respiration should also be induced in the TUP1 deletion strain
since they should not be repressed by glucose. 34 genes were found that were induced
under both the diauxic shift conditions and in the TUP1 deletion.
The authors discussed the use of these arrays to test the effects of drugs on a target. If a
drug is specific for a single target and it is effective at inhibiting that target, then the
expression profile of the cells mRNA should be identical when the drug is given and when
the target is knocked out. If additional genes are affected, then the drug will perhaps have
unwanted side effects. This problem is addressed in a paper in the Nov. issue of Nature
Medicine 4, 1293-1301 1998. They did expression profiling of yeast exposed to FK506.
The primary target of FK506 is calcineurin, a phosphatase involved in signal transduction.
They compared the yeast with FK506 and the calcineurin knockout strain and found that
two additional pathways were affected by the drug that were not affected by the knockout.
These kinds of studies could lead to understanding the side effects of drugs and to
preventing clinical trials of drugs that create undesired changes in gene expression.
It should be emphasized that this technology cannot detect changes on enzyme activity
caused by other methods of regulation like phosphorylation or feedback inhibition. The
technology is very powerful, but it cannot address every question.
Pathway Analysis in Whole Genomes
In addition to examining RNA levels to study gene expression, whole genomes can be
analyzed for their pathway uniqueness. The KEGG site in Japan has compared many of
the pathways from different bacteria to see what differences might be detected. They have
found that the TCA cycle is incomplete in some whole genomes. It is missing the top half
of the cycle in Haemophilus influenzae and missing the bottom half in Helicobacter pylori.
The genes from these different sectors of the cycle appear to be clustered in two different
operons, at least in some bacteria. This suggests that the TCA cycle evolved as two
separate linear pathways that became functionally joined in a cycle.
Pathway Engineering
The Blue Rose Project
Florigene, a company based in Australia is interested in expressing proteins in
flowers, not to make the protein, but to engineer in a pathway for flower pigments. For
centuries, a blue rose has been the subject of fiction. It was mentioned in the Arabian
Nights. There is no such thing as a blue rose however, because the key enzyme in the
pathway to blue or purplish pigments is lacking in the rose family. This enzyme is a
flavonoid 3'5' hydroxylase. This enzyme acts on anthocyanins that are already
hydroxylated at the 3' and 4' positions to add a third hydroxyl at the 5' position of the
anthocyanin B ring. This pigment is bluish or purplish in color and its specific absorption
properties can be modified by pH, metal ions and copigments.
Excerpt from the public information sheet on PR-35: Planned release of transgenic
rose. (This is part of an Australian regulatory agency impact statement)
"The flower colour modification gene is the 'blue' gene from petunia. It encodes an
enzyme, flavonoid 3'5' hydroxylase, which is required for synthesis of a class of pigments
called delphinidins. Only plants containing delphinidin are able to produce blue flowers,
and rose plants do not naturally synthesise delphinidin. The expectation is that the
transgenic rose will have an altered flower colour, such as blue, violet, purple or lilac."
Florigene has developed methods to transform genes into carnations,
chrysanthemums and roses. They have cloned the genes for flavonoid 3'5' hydroxylase
from petunia flower petals and expressed these genes in carnations. This has led to
purplish colored carnations. They have not got all the additional factors worked out yet to
get a true blue color expressed, but they are working on it. In addition, they are
transforming the genes into chrysanthemums and roses. The estimated world wide market
for a blue rose is in the 3-5 billion dollar a year range, so it is worth the initial trouble to
engineer this pathway into roses. Quote from a web page from March of 1998 "Dr. Steve Chandler
of Florigene said recently that they expect a prototype of a true blue rose to be developed in
1998 or 1999." Link to page
But another site dated May 21, 1999 says:
But hopes of a blue rose have been thwarted because, it seems, rose petals are naturally
acidic and this prevents the blue pigment being expressed.
The company hopes to sidestep the problem - either by finding a conventional rose variety
that is less acidic, or genetically-altering the plants to become more alkaline.
Florigene.com web site
In 2001, the company still has not given up on the blue rose, but it is elusive.
Now we are going to talk about some examples of pathway engineering in yeast. Before
we do, I would like to share this quote from a book by Issac Asimov who held a Ph.D. in
biochemistry from Columbia University which he earned in 1947.
excerpt from I, Robot (1950)
"In the first place, by far the largest crop we deal with ...is yeast. We have upward
of two thousand strains of yeast in production and new strains are added monthly. ...these
strains of yeast have each their peculiar properties. The beef steak you thought you ate
today was yeast. The frozen fruit confection you had for dessert was iced yeast. We have
filtered yeast juice with the taste, appearance, and all the food value of milk."
Steroids in Yeast, Adrenocortical Yeast
When we talked about the Blue Rose Project, we encountered the idea of gene expression
for the sake of engineering novel pathways into an organism. The concept of gene therapy
is based on restoring defective pathways to cure a genetic disease. Thus, pathway
engineering must be considered of at least equal importance to overproduction of a protein
for the sake of purification and study of that protein. We will talk now about an
example of pathway engineering in yeast rather than roses. This is a powerful idea that is
being commercially exploited by multiple companies. I have two more examples of
pathway engineering in yeast that illustrate the economic importance of this technology.
The pharmaceutical industry has traditionally manufactured drugs by chemical synthesis.
This frequently involves many steps with overall low yields. Competitors are always on
the lookout to reduce the number of steps in an important synthesis, or to improve yield.
Often one consideration is the cost of treating wastes produced in the process, especially if
they contain toxic chemicals or heavy metals. I heard a talk in October 1995 on
the case of industrial manufature of steroid hormones, specifically hydrocortisone. The
speaker was R. Spagnoli of the company Roussel Uclaf. He outlined the history of steroid
manufacture, with an account of the earliest synthesis that took about 40 steps. This was
slowly improved upon by more sophisticated chemical strategies to a much smaller number
of steps. He then introduced the concept of bioconversions, or getting microorganisms to
do some of the steps previously done by chemists. In the end the modern manufacture
method now requires 8 steps, including some bioconversions. Dr. Spagnoli's goal was to
engineer in yeast the pathway for direct biosynthesis of hydrocortisone from cholesterol.
In mammals this is done in the adrenocortex by five enzymes in two different
compartments, the ER and the mitochondria. Four of the five enzymes are cytochrome
P450s.
The pathway starts in the mitochondria with the cleavage of the lipid side chain to make
pregnenolone. This then moves to the ER where it is oxidized and hydroxylated by three
more enzymes to make 11-deoxycortisol. This moves back to the mitochondria to be
converted to hydrocortisone. To engineer this pathway into yeast would require expression
of five enzymes in the correct compartments and adrenodoxin and adrenodoxin reductase
needed in the mitochondria for electron transfer to the P450s. Also, yeast does not make
cholesterol. It makes ergosterol instead and it does not take up cholesterol from the
medium, so a way has to be found to get cholesterol into the yeast. This was a very
ambitious project, but the goal would be biosynthesis of a valuable steroid in one
bioconversion step, with no waste products except yeast.
For this process, the research team started at the last step and worked backwards.
As of the talk, they had expressed the last two P450s, one human microsomal enzyme C21
hydroxylase in the ER and one bovine enzyme 11 beta hydroxylase in the mitochondria
along with the two electron carriers adrenodoxin and adrenodoxin reductase (both bovine)
in the mitochondria. The engineered system could successfully convert 17 hydroxy
progesterone to hydrocortisone. This meant they had reconstituted the last two steps of the
pathway. (Eur J Biochem. 1996 Jun 1;238(2):495-504)
This is an incredible feat. They have expressed four mammalian proteins in this yeast
simultaneously and with correct targeting. These were all expressed off a single vector. It
should not be any more difficult to do the last three proteins.
Update on this story. A paper published in Nature Biotechnology 16, 186-189 1998 by the
same research group showed progress with engineering the first part of the pathway into
yeast. The native sterol made by yeast is ergosterol, not cholesterol that is used in animals.
Ergosterol has an extra double bond in the B ring at the 7,8 position. There is also a
methyl group on the 24 carbon that is not present in cholesterol. To eliminate the 7,8
double bond from ergosterol, an Arabidopsis gene for a delta 7 sterol reductase was added.
This enzyme reduced the 7,8 double bond.
One additional complication in yeast is a cytochrome P450 enzyme that creates a new
double bond at the 22,23 position in the tail. In normal yeast, sterols with both the 7,8 and
22,23 unsaturations are required, but there are suppressor strains that are viable when these
double bonds are absent. This strain of yeast has mutations in a gene called fen1. The
fen1 strain was used. In this genetic background the P450 that makes the 22,23 double
bond was deleted and the Arabidopsis delta 7 sterol reductase prevented the 7,8 double
bond. The product of sterol synthesis was very similar to cholesterol except for the 24
methyl group, and that gets cleaved off later, so it does not really matter.
With the substrate adjustment made so the steroid nucleus was like cholesterol and not
ergosterol, another P450, the side chain cleavage enzyme or CYP11A1 was added along
with the two needed electron transfer components adrenodoxin and adrenodoxin reductase.
These are all mitochondrial proteins. This strain was successfully able to make
pregnenolone by oxidatively removing the tail of the 24 methyl cholesterol substrate.
Addition of the human 3 beta hydroxysteroid dehydrogenase isomerase converted the
pregnenolone to progesterone. A side reaction converted some of the pregnenolone to
pregnenolone ester at the 3 OH position. The enzyme responsible for this reaction has been
identified as the yeast gene ATF2 and this has been deleted to block the formation of the
ester [Eur. J. Biochem. 261, 317-324 1999].
If we look at the synthesis of cortisol, the only missing step is the P450 17 alpha
hydroxylase to hydroxylate pregnenolone at the 17 position. Once this enzyme is added,
the formation of hydrocortisone should be possible by combining the two different
yeast constructs together to assemble the whole pathway. A paper in J. Steroid Biochem
Mol Biol 71, 239-246 1999 shows that the last enzyme has been successfully expressed in
yeast. Conditions were found to move in the pathway to 17 hydroxyprogesterone or toward
testosterone. Combination of this top half of the pathway with the bottom part already
engineered in another strain will complete the synthesis.
Polyester Yeast
In the April 1997 Scientific American, a two page ad (pp.18-19) from Dupont asks the
question in big bold letters: Use yeast to turn sugar into other molecules? Then they go on
to tell you they are not talking about alcohol, but about a polymer called polytrimethylene
terephthalate (3GT). This polymer is more versatile than traditional polyester abbreviated
(2GT) that is made from ethylene glycol (2G) [1,2 ethandiol, HO-CH2-CH2-OH]. The
process of making the two polymers is similar but the monomers that go into each are
different. One factor preventing the commercial production of 3GT is the cost of one of its
monomers, trimethylene glycol (3G) [1,3 propanediol, HO-CH2-CH2-CH2-OH]. 3G is
made by some bacteria starting from glycerol. Some naturally occurring yeasts can make
glycerol from sugar. However, no organism known does both. So in comes pathway
engineering. Dupont joined forces with a company called Genencor International to add the
bacterial genes for conversion of glycerol to 3G into yeast. They have done
it, and the process involves no heavy metals, petroleum or toxic chemicals.
The carbon source for the process is glucose.
Plastic Plants
Some bacteria have the enzymes needed to make a type of plastic called
polyhydroxybutyrate or PHB. This compound acts as a carbon reserve and can be broken
down by the same bacteria that make it, so it is biodegradable. This plastic is also a
thermoplastic that could be used in manufacture. It is costly to produce it from bacterial
fermentation, but it could be much less expensive if it could be manufactured by plants.
Early attempts to express the three genes needed to make this plastic in Arabidopsis showed
that it could be made in transgenic Arabidposis plants, but it was harmful to the plants. A
paper in PNAs 91, 12760-12764 1994 describes the modification of the three genes by
addition of a pea chloroplast transit peptide, a plant promoter and a poly A addition site.
The genes were successfully targeting into chloroplasts in Arabidopsis leaves and they did
produce the PHB in granules. The amount of plastic produced in the plants was up to 14%
of the dry weight and it was not harmful to the growth of the plants. The authors suggest
that the plastids have a mechanism to boost the synthesis of Acetyl CoA that is the
precursor for this synthesis, whereas the cytosol became depleted of Acetyl CoA leading to
stunted growth. I think I heard on the radio this summer that a similar strategy was used to
make a plastic in potatos, with a large percentage of the potato bulk being replaced by
plastic, but I could not find any references to this in Medline.
Engineering Malolactic Fermentation in Yeast
One of the major uses of yeast is found in making wine. One of the tasks of the winemaker
is to determine the proper time to harvest the grapes. A key factor in making this decision
is the acidity of the grape juice. Too much acid in the grapes will lead to too much acid in
the wine and the wine will not be enjoyable to drink. Many cooler grape growing regions
produce an excess of acid in the grapes mostly in the form of tartaric acid and malic acid.
Yeast used in wine making cannot take up the malic acid and convert it to pyruvate by malic
enzyme or to lactate. Wine makers sometimes add bacteria to their wine to reduce the levels
of malate by conversion to CO2 and lactate. This is performed by a malolactic enzyme not
present in yeast.
Yeast do have malic enzyme that converts malate to pyruvate, but the Km is too high so it
does not perform well. The major obstacle in this process is diffusion of malate into yeast
cells, since they do not have a malate permease. To get around these two blocks to
malolactic fermentation in yeast, two genes were introduced into yeast. One is from S.
pombe and is called mae1. It is a malate permease. The other is malolactic enzyme from
Lactococcus lactis (mleS). As an alternative to malolactic enzyme, the malic enzyme of S.
pombe was also used. This enzyme mae2 has a lower Km for malate and so it works better
in the conversion of malate to pyruvate.
Both of these strategies worked. The permease by itself was not effective. The mleS or
mae2 genes by themselves were also unable to reduce malate concentrations, but the
combination of the permease and either of the malate converting enzymes did the job. This
work was described in Nature Biotechnology 15, 224-225 and on pages 253-257 (1997).
The commentary on the paper states that "malolactic enzyme is unique in the biosphere,
found only in a few genera of lactic acid bacteria". So this work takes advantage of what
nature provides and combines all the enzymes into one organism to accomplish a desired
result.