Belugas and Llamas: Living in Thin Air

Genetics of Adaptation Graduate Seminar

Author: Sunita Yadav

One normally does not think of llamas and beluga whales in the same sentence; they look very different and one lives in the ocean whereas the other in the Andes Mountains. Nonetheless, they have adapted to low-oxygen environments in much the same fashion. Llamas belong to the camel family and are divided into 4 species, llama, alpaca, guanaco, and vicuña, all in the genusLama. They live at altitudes above 5000 feet where atmospheric pressure is lower and therefore less available oxygen. The Beluga Whale, Delphinapterus leucas, is ghostly white with a circumpolar distribution in frigid waters around the Arctic Sea. It is one of two members in the toothed order Monodontidae, the other species being the Narwhal. Beluga whales have been known to dive to depths of 500 m, also an oxygen deficient (hypoxic) habitat, and for periods that can exceed 15 minutes at a time in a dive. A third type of hypoxic habitat would be underground environments inhabited by mole rats. The work to date reflects that there are multiple mechanisms that underlie various physiological responses to hypoxic environments.

                 

Mammals employ different physiological adaptations to survive in low-oxygen environments such as: high oxygen affinity to hemoglobin (the respiratory pigment), a reduced heart rate, a lower metabolic rate, a higher blood volume percentage, higher myoglobin content (a protein that stores oxygen in muscle tissue and allows muscle tissue to be active for prolonged periods), and altered distribution of blood flow to tissues.

A first question to ask is why there is less oxygen in deep oceans and high mountains. With increasing altitude, atmospheric pressure is lower resulting in what is generally called ‘thin air’. Basically this means there are less oxygen molecules available per unit of air. In contrast, oxygen in oceans is incorporated by surficial mixing; deep ocean water simply does not mix at the surface very often and therefore is hypoxic. When mammals are exposed to such habitats, their normal oxygen transport does not work well (the reason why we hyperventilate when mountain climbing).

So what happens when a beluga whale dives? If it were not adapted to its deep sea lifestyle, at some point during the dive, the amount of carbon dioxide (CO2) in it’s blood would increase leading to lower pH, reduced oxygen binding in blood (due to reduced oxygen binding to hemoglobin) and probable death because of oxygen starvation. Since beluga whales are not extinct, they have found a way to survive during their deep diving. The question is how?

Under normal pressures, most mammals in a resting state have excess oxygen releasing only about 25% oxygen to tissues. Under active conditions when cells need more oxygen, hemoglobin quickly unloads oxygen to the active cells. Typically, an oxygen disassociation curve is used to describe percent saturation of hemoglobin with oxygen at different atmospheric pressures. Since one hemoglobin molecule can attach 4 oxygen molecules, a 50% saturation (referred to as p50) value is commonly used for comparison. Temperature, pH and other organic molecules affect how quickly an individual reaches the p50 value.

Since belugas and llamas have been living in hypoxic environments for thousands of years, their bodies have adapted to efficiently use lower oxygen amounts. One way they accomplish this is to modulate blood chemistry to make oxygen more attracted to the hemoglobin molecule (this would be a left shift on the oxygen dissociation curve depicted above).

The balance of CO2 and oxygen maintains blood pH. At low pH, hemoglobin has lower affinity for oxygen(curve shifts to the right) whereas at higher pH, hemoglobin has a higher affinity for oxygen (curve shifts to the left). An increase in CO2 reduces pH and restricts binding of oxygen to hemoglobin. Reduced pH occurs because CO2 is converted to carbonic acid by a group of enzymes known as carbonic anhydrases (CA). They form carbonic acid from CO2 at different rates. One form of the CA enzymes is CA II which is 10x to 100x faster than CA I or CA III in forming carbonic acid. The hypothesis is that mammals (like the beluga) living in hypoxic environments would show reduced levels of CA II to maintain pH balance in blood thereby maintaining high oxygen attraction for hemoglobin.

By comparing the expression levels (quantities) of CAs in different species, researchers have begun to explain the underlying physiological adaptations that beluga whales and other mammals employ. One research group (H. Yang and colleagues) used blood samples from the dromedary camel, domestic llamas, and beluga whales to separate and quantify CAs. Remember that CA II was the fastest in converting CO2 to carbonic acid; not good if you are a beluga whale or llama. Well, what did they find? CA II was not detected in red cells of beluga whales and reduced levels were found in llamas. Camels though closely related to llamas displayed a typical mammalian ratio with greater CA I levels in relation to CA II. In studies of mole rats (underground lifestyle), CA II was also deficient in red blood cells.

Storz and colleagues used deer mice (Peromyscus maniculatus) that live at different elevations to study adaptation to altitude. Genetic studies comparing mice populations at various elevation zones revealed differences in allelic forms (version of a gene) of α and β globin genes (type of protein) that code for hemoglobin structure. Mice that live at higher elevations show a higher prevalence of the genetic code for the version of the gene that ultimately leads to a destabilized hemoglobin molecule. What does this mean? An unstable hemoglobin molecule shows a higher attraction for oxygen. Mice in lowlands had a different β –globin (more stable hemoglobin) than mice in highlands (unstable hemoglobin, i.e. higher affinity to oxygen). This implies some sort of divergent selection based on habitat locations of deer mice.

             

More recent work on humans living on the Tibetan plateau by Xan Yi and colleagues shows a strong positive selection on a different pathway. Exomes (coding regions in the DNA) of 50 Tibetan individuals were sequenced. Differences were found at a single location (single nucleotide polymorphism or SNP) on the genome for a gene called EPAS1 between highland Tibetan and lowland Han populations. EPAS1 is a transcription factor gene involved in hemoglobin concentration in red blood cells. Most humans react to low oxygen levels by producing more hemoglobin which can make blood more viscous (and also lead to altitude sickness), Tibetans, however, have relatively low hemoglobin concentrations. Therefore, Tibetans avoid the symptoms of altitude sickness. How they actually get enough oxygen is yet to be decoded. If you have ever wondered why Ethiopian and Kenyan athletes frequently win marathons, you will not be surprised to learn that the runners all come from highland areas in those countries. Their adaptation to high altitude allows them to use oxygen more efficiently.

Researchers are also actively studying different species such as, plateau pika, mountain sheep, and orca whales to study variation in adaptation to hypoxic habitats across species. The earlier studies in llamas and beluga whales have not been repeated to verify DNA sequence level differences in gene expression (amount of a gene that is produced to make a certain number of protein molecules) or regulation (whether a gene is activated or not). Thus far, the research in llamas, belugas, deer mice, and humans suggests that there are multiple pathways for adaptation to low oxygen habitats.

References

Storz, J.F., Runck, A.M., Sabatino, S.J., Kelly, J.K., Ferrand, N., Moriyama, H., Weber, R.E. and A. Fago, 2009, Evolutionary and functional insights into the mechanism underlying high-altitude adaptation of deer mouse hemoglobin, PNAS, Vol. 106(34): 14450-14455.

Yang, H., Hewett-Emmett,D. and Richard E. Tashian, 2000, Absence or Reduction of Carbonic Anhydrase II in the Red Cells of the Beluga Whale and Llama: Implications for Adaptation to Hypoxia, Biochemical Genetics, Vol. 38(7/8):241-252.

Yi, Xan et al., 2010, Science, Vol. 329(5987): 75-78.

http://www.ncbi.nlm.nih.gov/pubmed/11950136

http://www.seaworld.org

http://i.telegraph.co.uk

http://www.latintravelmall.com

http://share3.esd105.wednet.edu/rsandelin/NWnature/Photos

http://www.tibettrip.com

http://www.acbrown.com/lung/

http://footpro.com.au/images/news_image

Searching for the genetic basis of adaptation in Bees

Genetics of Adaptation Graduate Seminar

Author: Priya Date

It is a common view among scientists who study human evolution that humans originated on the African continent and then migrated. Isn’t it surprising how different people from different parts of the world look? Not only do we look different, but also we can have very different styles of living. One important question is, if these differences are culturally transmitted, or genetically heritable, i.e., we pass them down to our kids through our genes (DNA). However, because of our long life spans, late age of reproduction and difficulty to conduct genetic experiments in humans, it is very difficult to study these kinds of questions. This is when other organisms like the little buzzing critter ‘the honey bee’ can come to our rescue.

The honeybees also originated in Africa and have then expanded in range to Asia and Europe due to introduction by humans. These bees are thus now living in different parts of the planet (thanks to us !) and show region-specific adaptations in how they look or behave. Bees in Europe that had genes that helped them to survive in the cold climate reproduced and thus passed on the heritable component of their DNA for cold survival to the next generation. The same is true for why the bees from Europe look different from the African bees. Even though we have some indication that some genes are involved in adapting to new environments, we still don’t know what regions of the whole genome of any organism are important for these adaptations. In this study by Zayed and Whitfield (PNAS article, 2008) scientists have taken the opportunity to take advantage of the sequenced genome of honeybees to look for signature of selection. By signature of selection we mean whether changes in certain parts of the genome are increasing in frequency in the population in a geographic location specific manner. This would then indicate that those genomic regions have some adaptive value to increase the bee’s fitness or survival in any given environment.

Before we delve into the details of this study lets take a few moments to refresh our basics of molecular biology. The genome of any organism is a huge string of DNA. The DNA sequence is made up of four bases which are read as A, T, G and C. As we make words by putting together certain alphabets in the right sequence, the DNA sequence when put in the right order makes genes, which encode proteins. And just like changing the sequence of alphabets in a word will make it meaningless, changing the sequence of DNA makes different proteins that might be non-sense proteins. Very rarely, these changed or damaged proteins in turn may result in changing how we look or behave. We only store the changes that are beneficial and generally get rid of those which are harmful. However, genes form only a small proportion of the whole genome, sometimes as little as 1% in certain organisms: much of it may code for nothing but is important for regulating the expression of the coding region. However, in this study the authors focus on only the coding regions. Thus if we want to find out if certain regions of the genome have changed to suit the environmental needs we can compare the ancestral genome with the derived or newer genome and screen for signatures of selection.

Zayed and Whitfield have compared certain genomic regions of the African, Asian, East and West European bees for changes in the DNA sequence. To do such comparison researchers have developed very complicated statistic called ‘Fst’. In simple words, it goes from 0 to 1 where 0 indicates no genetic differences between if two DNA sequences and 1 indicate a lot of differences in the DNA. Thus, if the derived genome were to be very similar to the ancestral genome its Fst would be 0 and if it were diverged the Fst would be 1. In the bee study, the authors found that the West European population of bees was significantly diverged from its ancestral African population, but the other two populations, however, do not show any evidence for divergence at this stage (Figure 1). This may be due to the fact that the Asian and East European environment is somewhat similar to the African environment. This data suggest that the vast differences seen in the West European and African bees has a strong genetic basis and more functional studies relating the two should be performed. 

Finally, turning back to the questions we started with to understand how the we look different, studies like this can provide some common rules or generic principles which will hold true anywhere. As the bees, which originated on the African continent when moved to the colder climate of West Europe changed in order to survive in the new environment, humans have also evolved several adaptations. For example, a study shows genome-wide signatures of selection acting on certain pigment related genes in Asian, European and African people (Genetics-of-human-pigmentation). This can be explained as the people inhabiting the tropical regions have darker skin pigment to gain protection from the uv radiation and thus have diverged in skin color from their European counterparts. Not only skin color but several such examples leading to difference in our height, stature, behavior, etc. can be found which probably have similar genetics and animal models like the honey bees can be used to understand these genetic mechanisms.

Give a Hoot Don’t Pollute!

Genetics of Adaptation Graduate Seminar

By Lindsay Chaney

Woodsy the Owl (US Forest Service icon circa 1970) is not the only owl concerned with the environment.  Recently the tawny owl of Europe is calling out hoots to scientists about global climate change.  Over the past 48 years there has been an increased number of brown tawny owls across Finland, likely as a direct result of milder winters.

The tawny owl (Strix aluco) is found across temperate regions of Europe.  It can be heard calling hu ..... hu-hooooo as it hunts through the night for voles and other small rodents.  There are two colors of the tawny owl, grey and brown (Fig 1).  Feather color is determined by level of the reddish-brown pigment pheomelanin present in feathers at birth.  The tawny owl remains this color throughout its life, regardless of age or sex.  Scientists have found that the grey color is dominant over the brown color, meaning there would most likely be more grey colored tawny owls than brown in a population (Fig 2). 

In southern Finland, scientists have monitored 250km² of land and tawny owl nests for over 33 years.  Year after year researchers have observed these owl populations through counting, color identification, and behavioral studies of the owls.  Recently, they have seen an increase in the number of brown owls.  From 1961 to 2009, over 3,239 tawny owls had been observed and the frequency of the brown owl has increased by about 2.5% per year.  Why was this? 

One possibility is that the owls have a color preference for mates. This occurs for many bird species, such as the peacock.  Females prefer male peacocks with the biggest, most ornate tail feathers.  When they preferably choose the big tail males, their sons have big tails as well, and there is an increase in the number of big tailed male peacocks.  This is an example of sexual selection, natural selection taking place due to preference in mate.  So, do the tawny owls prefer the brown owls as mates?  This is not the case.  Through studies of the owls, there has not been indication of any mate preference.

Another possible explanation is immigration.  If additional brown owls joined our study population, there would be an increase of the number of brown owls in the study population.  In these studies, the researchers catch the owls, take measurements and attach a harmless metal bracelet around their legs with an identification number. This provides critical information on every bird, and which members are new to the group.  By doing so, scientists have ruled out immigration as a key influencing factor. 

If not mating preference or immigration, what has caused this change?  Scientist began turning to the climate.  They developed five different prediction models to determine what accounts for the increasing prevalence of the brown tawny owl.  They noticed that the snow depth in the area has been steadily decreasing for the past 30 years.  Is this the key that is changing the color compositions of the owls?  Data showed that there is a difference in survival based on owl color.  When there are high snow years, the brown owl is not as likely to survive (Fig 3).  The model confirmed this idea with 99.4% accuracy.

Researchers offer three possible explanations for why brown owls would increase with the milder winters. One, the brown owl is a target of prey.  The larger eagle owl preys on the tawny owl.  In snowy conditions the brown tawny owl would be more contrasted against the white snow, while the grey tawny owl would be camouflaged.  If there is less snow, due to climate change, that would mean less brown owls being eaten.  This seemed likely until it was discovered that the eagle owl does not hunt by vision. 

A second scenario is that the brown owl has different energy requirements than the grey owl.  This would require the brown owl to hunt and eat more food, such as voles.  With the vole population in decline, this would be difficult in high snow years, causing the brown owl to decrease survivorship. 

The third potential explanation is that feather color is genetically linked to genes that provide a better immune system.  With milder winters, this would allow brown owls to survive more successfully, allowing their numbers to increase. 

Regardless of the specific cause of change, it is clear that the brown tawny owl is becoming more common throughout Europe.  In 1960, brown owls made up 11-15% of the population. In 2010, their frequency increased to nearly 50%.  The change in the population of tawny owls is an example of modern day evolution taking place as result of the change in climate.  This is one of the clearest examples we have seen thus far of nature responding to climate change impact. As global warming takes place it causes a domino effect.  The environment changes, resulting in changes in animal survival (natural selection).  This, in turn, causes a change in the genetic composition of the animals and which traits are passed on to the next generation.  This leads to the animal becoming better suited to the new environment (adaptation).  Thus, climate change does have a significant impact, even on the animals in our own backyard. 

Woodsy the Owl had wise counsel for us when he said, “Give a Hoot, Don’t Pollute!”  By following his advice, we may be able to stop or mitigate the trend of our warming planet. And next time you see a grey tawny owl in the wild, pull out your camera.  If climate change continues we may only have the brown owls left.

Source: Karell, P. et al. Climate change drives microevolution in a wild bird. Nat. Commun. 2:208 doi: 10.1038/ncomms1213 (2011).

African Cichlids Perfect the Evolutionary Moonwalk

Genetics of Adaptation Graduate Seminar
Author: Brian Carlson


Marines know the value of making a “strategic advance to the rear,” and this begs the question: Can evolution do the same? In fact, it can and it does. The best-known examples of such so-called “reverse evolution” include the return of sexually dimorphic species to monomorphism and the loss and recovery of wings in stick insects (Nagai et al. 2010).


With nature providing such interesting examples of the apparent action of reverse evolution, what is the missing piece? Why does the investigation of this phenomenon remain relevant and interesting? The answer is actually quite simple: While many examples can be cited which suggest the action of reverse evolution, very little is known about the mechanism that drives such evolutionary backtracking. 


Previously, the only published study that attempted to address this topic on a genetic level was the work of Kitano et al. (2008), in which it was demonstrated that the reoccurrence of armor plates in stickleback fish was the result of a reverse shift in allele frequencies from the derived (mutant) allele to the ancestral allele. Even this important study left questions regarding the mechanism(s) by which reverse evolution is accomplished, however, as the derived allele had never become fixed. As a result, the published body of work on the topic has failed to shed any light on how a new trait could arise, become fixed in the population and later be replaced by the fixation of a “new” mutation, restoring the ancestral phenotype… until now.


Recent work by Nagai et al. (2010) has finally provided an example of reverse evolution in which the genetic changes underpinning the re-emergence and fixation of ancestral traits can be confidently demonstrated. Their study, conducted in African cichlid species from Lake Tanganyika, reveals several substitution events and subsequent reversals of the amino acid at position 292 in the RH1 rod-opsin photopigment, together with their inferred evolutionary impacts.


Before moving any further, it is important to first understand the mechanism of such change and its functional effects. In brief, the authors compiled sequence data for the RH1 gene in 293 individuals, representing 67 cichlid species from four tribes (“tribe” being a secondary taxonomic rank, referring to a closely-related group of genera) native to Lake Tanganyika. Analysis of sequence data revealed that all fish examined possessed either an alanine (292A) or a serine (292S) amino acid residue at position 292 in the RH1 proteins for which they encode. Further, it was observed that, at this position, alanine was always coded for using the GCC codon in the inferred mRNA transcript sequence. Similarly, serine was always coded for using UCC. This is an important point: it indicates that a single nucleotide substitution in the RH1 gene can result in a change from one protein form to another. Analysis of the absorbance spectra for both forms of RH1 opsin showed a difference in the maximum absorbance (λmax), with RH1 proteins containing 292S showing maximum absorbance at shorter wavelengths (488-494 nm) than those containing 292A (497-504 nm).


So, why is this single nucleotide change important? The peptide sequence differences between the two forms of the RH1 protein found in these cichlids are significant for two main reasons: First, expression of each form of this visual photopigment is believed to be advantageous in certain habitats. In shallower waters that tend to be blue-green, maximum absorbance at a longer wavelength (i.e. expression of RH1 with 292A) is believed to confer an advantage in light-dark discrimination and, by extension, such things as feeding, mate choice, predator avoidance, etc (Nagai et al. 2010). Conversely, in the bluer waters of deeper habitats, absorbance at shorter wavelengths (i.e. expression of RH1 with 292S) is likely advantageous. Second, the data collected indicates that either one form of RH1 or the other tends to be found in each population, with only one population examined possessing both forms (Fig. 1). This suggests that natural selection is likely acting on this trait.

Figure 1. Distribution by depth (in meters) of the sampled species (numbered columns) in the Cyprichromini (A), Perissodini (B), Lamprologini (C) and Ectodini (D) tribes. Bars represent the depth ranges at which species are found and bar color indicates whether the ancestral 292A allele (gray) or the derived 292S allele (black) is fixed in that species. Maximum RH1 absorbance values are indicated for the given species, where available (Nagai et al. 2010, Fig. 3).


Alright, things are getting a little more interesting, but I promised you a compelling example of reverse evolution, which, so far, I have yet to deliver. I am not one to disappoint, so lets add a few broad strokes of phylogenetics (phylogenetics being the study of the evolutionary relationships among species) and finish the picture we’re painting here.


Using a variety of techniques, Nagai et al. (2010) inferred the evolutionary history of the RH1 gene in the species studied. The phylogeny that they generated reveals several important facts. First, the species generally clustered with other members of their tribe, suggesting genetic similarity across the region of the genome that was sequenced in this study. Second, the ancestral form of the RH1 protein likely contained 292A. Third, the derived form (292S) of the protein has been acquired at least four different times as the result of a single nucleotide substitution. Subsequently, the ancestral (292A) phenotype has been reacquired in at least three distinct lineages by reversing the original substitution (Fig. 2).

Figure 2. Neighbor-joining tree based on RH1 sequence data. Capital letters represent the allele known (for existing species) or predicted (for ancestral species) to be fixed in a species or lineage. Species with shallow (including depths <20 meters), deep (including depths >50 meters) and wide (including depths <20 and >60 meters) distributions are highlighted in orange, blue and green, respectively. Portions of the tree highlighted in yellow represent inferred shallow lineages and portions highlighted in blue represent inferred deep lineages. Maximum RH1 absorbance values are indicated for the given species, where available (Nagai et al. 2010, Fig. 4).


When data relative to the respective habitats of the species examined and the natural history of the lake is considered, the following picture of cichlid evolutionary history emerges: The common ancestor of these species carried the 292A form of the RH1 protein and likely lived in a shallow habitat. Later in evolutionary history, a single-nucleotide substitution resulted in the expression of the derived 292S form of RH1, which conferred a visual advantage in bluer water, allowing some species to colonize deeper habitats. In some lineages, subsequent reacquisition of the ancestral trait either led to, or resulted from, recolonization of shallow habitats.


There you have it! You have witnessed science take its first real steps in understanding the genetic underpinnings of reverse evolution, which represents real, forward progress in our understanding of how Earth’s myriad species came to be the way that they are. Hopefully, such exciting research will encourage us to continually sharpen and redefine our understanding of evolution and the way that we communicate the concept to others. Evolutionarily speaking, “forward” progress is made by selecting for traits that confer some advantage, whether novel or ancestral; sometimes natural selection simply orders, “About face, double time!”




References
Kitano J, Bolnick DI, Beauchamp DA, Mazur MM, Mori S, Nakano T, Peichel CL. 2008. Reverse evolution of armor plates in the threespine stickleback. Curr. Biol. 18: 769–774.
Nagai H, Terai Y, Sugawara T, Imai H, Nishihara H, Hori M, Okada N. 2010. Reverse evolution in RH1 for adaptation of cichlids to water depth in Lake Tanganyika. Mol. Biol. Evol. Advance online publication. doi:10.1093/molbev/msq344.

Host-parasite system in microbial life

Genetics of Adaptation Graduate Seminar
Author: AA


Plants and their pollinators, predator and prey, host and parasite, and viruses and the organisms they live in are only several examples of coevolutionary associations: over time, the interactions between organisms can result in mutual adaptations during their evolution. But how can they coevolve, and what does coevolution mean?


According to one of the first definitions, coevolution is "the change of a biological object triggered by the change of a related object" (Futuyma & Slatkin, 1983). Coevolution can occur at different levels of the life of an organization; it can be biochemical processes, changes in cell structure and shape, behavioral responses, or even changes in population sizes.  Coevolutionary processes are often complicated and involve both genetic mechanisms and morphological/behaviorial adaptations.

             
Host-parasite system is a good model to study coevolution. There are many “popular” host-parasite interactions that are studied very well: mammals and tapeworms, snails and flatworms, human and bacteria, human and insects and so on. Some parasites can use only one host (tightly specific) and these organisms, therefore, evolve together (or co-evolve). Other parasites can develop in a variety of hosts (universally adapted).


Evolutionary studies on host-parasite interactions often focus on two sides of this system: the defensive mechanisms of hosts, and the potential for adaptation of the parasites. Authors of the paper “The effect of migration on local adaptation in a coevolving host–parasite system” (Morgan et al. 2005, Nature) considered the latter.


Parasite adaptation is a controversial topic; there are studies that support the local adaptation of parasites to their hosts, and studies that report no evidence of parasite adaptation.


However, this study is somewhat unique in that the host was bacteria, an organism that we generally think more often as the parasite rather than the host. The authors had good reason for choosing this model, as its use allowed for (1) a large population size, (2) short generation times, and (3) an antagonistic nature of the interaction with the parasite. All those things, according to the authors, were favorable for evolution.           


Specifically, the researchers used the bacteria Pseudomonas fluorescens (Fig. 1) as the host, and the bacteriophage (lytic DNA phage SBW25f2) as the parasite. The members of the Pseudomonas genus are widespread in nature, inhabiting soil, water, plants, and animals (including humans). Most of them are pathogens. For example, Pseudomonas syringae can act as plant pathogen; whereas Pseudomonas aeruginosa is the most common human pathogen which can cause nosocomial infections such as pneumonia, urinary tract infections, and bacteremia (= the presence of bacteria in the blood).

Fig.1. Pseudomonas. Source

Fig. 2. Bacteriophage (on the left, Source) and bacteriophages attached to a bacterial cell (on the right, Source).

A bacteriophage (“phage” means “to eat” from Greek) is one of a number of viruses that infect bacteria (Fig.2). Phages are widely distributed and can be found in all reservoirs populated by bacterial hosts, such as soil or the intestines of animals. Sea water is one of the densest natural sources for phages; there are up to 9×10⁸ phages per milliliter and up to 70% of marine bacteria may be infected by phages (Wommack and Colwell,  2000).


Although we already know that host and parasite behavior are very important for this interaction, we don’t understand the impact of host and parasite migration, that seems to have no primary effect on the adaptation of any organism. Nevertheless, migration between populations is very important in terms of genetic variation; beneficial genes can be introduced from one population to another. Many experimental studies have demonstrated the role of migration in coevolutionary processes. However,  whether migration rates of hosts or parasites have an effect on their local adaptation, remains poorly investigated. The authors’ prediction was that parasites were locally adapted if they migrated more than their hosts, whereas hosts were locally adapted if they migrated more than their parasites.


The experimental design of this work was impressive. The main idea was to grow the necessary amount of bacteria populations and particles of phages (“particle” – because they act as viruses), and then, to perform several cultures with different ratios of migration either bacteria, or phage. The authors cultured 6 populations with 10 ⁸ cells of bacteria (that is approximately the population of both North and Latin America) and 10⁵  particles of phage, and perform 5 treatments: control; 10% bacteria migration, 0% phage migration; 0.1% bacteria migration, 0% phage migration; 0% bacteria migration, 10% phage migration; and 0% bacteria migration, 0.1% phage migration. Author performed the migration as the removal of a certain amount of either bacteria, or phage from the culture.


After allowing for migration, the authors measured the local adaptation of host and parasite—they assayed this as either resistance on the part of the bacteria, or conversely the ability of the phage to infect the bacteria. In practice, it looked like any visible inhibition of bacterial growth when exposed to the phage.

And here are the results:

Figure 3. Mean local adaptation of parasites. Data are averaged over six populations and six time points for different migration treatments. Results are means ± s.e.m. across populations. P, phage migration; B, bacterial migration (Morgan et al., 2005).

The results of the experiments in this paper confirmed, once again, that the local adaptation of parasites exists, and that the migration has an effect on this adaptation. What they found was that phage migration increased phage local adaptation, whereas bacterial migration had little effect.


They also observed that the effect of migration was asymmetric: parasite migration increased parasite local adaptation relative to unmigrated populations; whereas host migration did not decrease parasite adaptation (its migration just had no any effect on parasites). The authors explained that by the following: “parasites are locally maladapted in the absence of any migration, and host migration is unable to increase parasite local maladaptation any further”.


These results might have important implications. Since the authors demonstrated that parasite migration could result in parasite local adaptation through their evolutionary advantage in a host-parasite coevolution, it can be addressed to global interactions, for examples, in human-parasite system. Parasites have inhabited humans since the beginning of life; their interactions may increase both parasite transmission and their infectivity to their local hosts, and therefore, that might facilitate the development and spreading of human diseases.


References:

Morgan, A. D., S. Gandon, et al. (2005). "The effect of migration on local adaptation in a coevolving host–parasite system." Nature 437(7056): 253-256.

Futuyma, D. J. and M. Slatkin (editors). (1983). “Coevolution”. Sunderland, Massachusetts: Sinauer Associates,555 pp.

Wommack, K. E.; Colwell, R. R. (2000). “Viroplankton: viruses in auquatic ecosystems”. Microbiology and Molecular Biology Reviews 64 (1): 69.

In defense of a “theory of everything” in ecology

Genetics of Adaptation Graduate Seminar

Author: Francis Cartieri*

The beginning of the modern scientific era arguably began when Isaac Newton was able to explain the diverse phenomena of ocean tides, projectile motion, the movement of the moon and planets, and the seemingly chaotic oscillations in the trajectories of the stars… all with one cohesive set of mathematical formulas. It was the first great “theory of everything,” and since then, scientists and philosophers have endeavored to reproduce new and better general theories to account for groups of phenomena within the diverse array of disciplines that make up humanity’s knowledge‐gathering enterprise.

Some disciplines, namely the physical sciences such as theoretical physics and thermodynamics, are more amenable to highly general theories. The objects and relations they study are more uniform than those studied by the life sciences. As a result, thinkers have had more difficulty establishing the existence of “theories of everything” that regularly apply to such complex things as living organisms and their relations to complex ecosystems over time. A major difficulty has been providing theories that are predictive, rather than descriptive. That is, the general tenets of evolutionary science do not allow one to make a wide range of predictions about how a given ecosystem will look six million years from now. General theories in physics are composed of law‐like relations that do allow for long‐range predictions of future states, given the present state of a physical system.

It comes as quite a surprise, then, that a theory of everything of the predictive sort has been put forward, and has been convincingly defended, in ecology‐‐that discipline of boundless living complexity and contingency. The name of that theory is the Metabolic Theory of Ecology, or MTE, and it is a kind of master equation based on a set of bio‐physical principles, as well as the assumption that organisms evolve by natural selection to use resources efficiently. The applications of MTE are startlingly wide—the theory is purported to account for such diverse phenomena as individual plant and animal structure and function, the design of circulatory systems, migration patterns (be they birds or mega‐fauna), the storage of nutrients in ecosystems, and population growth rates. Incredibly, this list is far from exhaustive. “If the theory is right, it's one of the most significant in biology for a long time,” says ecologist David Robinson of the University of Aberdeen. “It would provide a common functional basis for all biodiversity.”

To say the reception of the Metabolic Theory of Ecology has been stormy would be an understatement. Many critics actually think it does damage to the study of ecology. “If they're not right, they'll have done a disservice to ecology,” says Jan Kozlowski, of Jagiellonian University, Krakow. Others are ecstatic, believing MTE represents a massive leap forward in how we can account for the frustratingly complex world of environment‐organism and organism‐organism interactions. “I've never been more excited in my life,” says Stephan Hubbell of the University of

Georgia. “Ecology now is like quantum mechanics in the 1930s—we're on the cusp of some major rearrangements and syntheses. I'm having a lot of fun.”

But the most common reaction is, perhaps understandably, cautious excitement. After all, the Metabolic Theory is only about ten years old, and it is not quite clear how one should go about testing it. Because the Theory is so abstract, one cannot conclusively claim that it is “correct” or “incorrect.” Instead, the question is whether or not the Theory is useful, whether or not it can be correctly applied, and where it can be usefully applied.

The Theory was born out of a longstanding mystery: why is the relationship between the rate an organism processes energy (base metabolic rate) and the size of an organism (biomass) more or less conserved across much of the tree of life? For the most part, there is a constant mathematical relationship between size and metabolism that holds for everything from apples to elephants. Why is this so?

The Metabolic Theory of Ecology answers that question by supposing that what matters in building a living thing is how energy is transferred; that there is an optimal way to get energy from one place to another, and that natural selection pushes living things to move energy around in the optimal way. The founders of the Theory used elegant mathematical engines called fractals to generate models of optimal energy transfer networks—networks that any living thing must use to move energy from where it is released to where it is needed.

In focusing on energy transfer, the founders of the Metabolic Theory had made a eureka insight—it turns out that their fractal mathematics produced ideal models of energy transfer systems that a huge variety of living things tend to approximate. If one knows the metabolic rate of an organism, one can use the Theory to determine when that organism will die, how many offspring it is likely to have, and how large it is or may become. Since the same equations govern energy transfer and organism growth across different species, predictions can be made using MTE for a whole community of different organisms, or a whole ecosystem of different communities. In fact, MTE can be used to make predictions about future states of living systems, as well as model how evolution has gotten a given species or group of species to their present state.

One of the things that make the Metabolic Theory of Ecology a potential “theory of everything,” is the extent to which researchers are able to add on extensional models. Extensional models are tools that allow researchers to translate the mathematics of the general Theory into the language of their particular area of interest. Say you are interested in bird migration. MTE is very abstract and says nothing about birds. But researchers have been able to translate the general things MTE predicts about mass‐metabolism relations into terms that the ornithologist can understand and make us of. In this way, MTE has been extended to a great number of research areas.

Of course, all this generality comes at a price. While the Theory is useful for predicting central tendencies of form and function (such as: what is the relationship between size and abundance in this population of water‐lilies?), its predictions are only approximate. If a researcher is interested in very specific questions about a given organism and its ecosystem, then more fine‐grained tools are necessary. Additionally, tension has been building between those thinkers who try to explain natural systems using the Theory as a substitute for fieldwork, and those researchers who believe that ecosystems are too complicated to understand without direct observation and intervention. Some even worry that MTE will lead to “armchair ecology” akin to the empirically disreputable “armchair philosophy.”

Whether the Metabolic Theory of Ecology is recognized to be a “theory of everything” or not will be the subject of great debate in the coming years. What is undoubtedly true, however, is that the Theory represents a powerful new tool in our attempts to understand the endless complexity of living, changing systems here on earth.

*Francis is a graduate student in the Dept of Philosophy, and because he was excited about the Metabolic Theory of Ecology, we agreed to let him write a on a slightly different blog topic than the other students

Genetics of Adaptation blog posts coming soon!

Josh Gross and I have been teaching a graduate-level Genetics of Adaptation course this quarter. It has been an extremely fun class--students present a seminar-style lecture on a recent paper, followed by a discussion--and the discussions have been excellent. The students appeared to enjoy the reading and the discussion never really faltered throughout.

Along with being graded on their presentations, and the discussion following the presentation, the students are required to write a blog post about a topic that covers, broadly, the genetics of adaptation. We have given them very little restrictions over their blog topic, but we have asked them to write their posts for the general public. There are a few reasons we went this route rather than having them write a term paper. First, just as it takes training to write scientifically, it also takes training to write to a general audience. We figured they should begin to learn how to do this sooner rather than later, because, practically speaking, they will have people outside of their field critically evaluate their writing at some point--whether for a grant, a job, etc etc. It makes sense to begin developing this skill now. Second, one of the very important tasks that we do as scientists is outreach, again, to the general public. For example, some scientists will get involved with the local community and give general topics lectures to gardening or naturalist clubs. Some people work with local non-profits, some with local school-age kids and science fairs: it's all in the name of making a difference, promoting change, or just being a good citizen and contributing. I can get behind that. Thus the blog posts that we require from our students is an exercise both in writing and in contributing their knowledge of evolutionary biology, the cornerstone of biology, to the general public.

I will be posting these blog entries here at Science in Cinci over the next week or so, and will indicate when an entry was from the course along with the student's name. Please check in often, and leave comments!