Genome Sequencing: Using Models to Predict Who's Next

0001 The recent discovery of a Hobbit-like hominid on the Indonesian island of Flores was startling in some respects—its rather modern existence, for one—but it represents a classic case of Darwinian evolution. For reasons that are not entirely clear, when animals make their way to isolated islands, they tend to evolve relatively quickly toward an outsized or pint-sized version of their mainland counterpart. Following this evolutionary script, the Flores woman, presumably a downsized version of Homo erectus, appears to have shared her island home with dwarf elephants and giant rats. Perhaps the most famous example of an island giant—and, sadly, of species extinction—is the dodo, once found on the Indian Ocean island of Mauritius. When the dodo’s ancestor (thought to be a migratory pigeon) settled on this island with abundant food, no competition from terrestrial mammals, and no predators, it could survive without fl ying, and thus was freed from the energetic and size constraints of fl ight. New Zealand also had avian giants, now extinct, including the fl ightless moa, an ostrich-like bird, and Haast’s eagle (Harpagornis moorei), which had a wingspan up to 3 meters. Though Haast’s eagle could fl y—and presumably used its wings to launch brutal attacks on the hapless moa—its body mass (10–14 kilograms) pushed the limits for self-propelled fl ight. As extreme evolutionary examples, these island birds can offer insights into the forces and events shaping evolutionary change. In a new study, Michael Bunce et al. compared ancient mitochondrial DNA extracted from Haast’s eagle bones with DNA sequences of 16 living eagle species to better characterize the evolutionary history of the extinct giant raptor. Their results suggest the extinct raptor underwent a rapid evolutionary transformation that belies its kinship to some of the world’s smallest eagle species. The authors characterized the rates of sequence evolution within mitochondrial DNA to establish the evolutionary relationships between the different eagle species. Their analysis places Haast’s eagle in the same evolutionary lineage as a group of small eagle species in the genus Hieraaetus. Surprisingly, the genetic distance separating the giant eagle and its more diminutive Hieraaetus cousins from their last common ancestor is relatively small. Without the fossils to directly determine divergence times, Bunce et al. relied on molecular dating techniques that use the rate of sequence evolution in the genes studied to establish the relative evolutionary ages of the eagles. Proposing a divergence date of roughly 0.7–1.8 million years ago, the authors acknowledge that while this is the “best available approximation of the ‘true’ date,” additional molecular data could help refi ne the estimate. Whatever the date of divergence, the extinct giant eagle is clearly an anomaly among the eagles studied here. The increase in body size—by at least an order of magnitude in less than 2 million years—is particularly remarkable, Bunce et al. argue, since it occurred in a species still capable of fl ight. The absence of mammalian competitors facilitated the evolution of much larger eagles and owls on Cuba and may have likewise precipitated the rapid morphological shift seen here. Haast’s eagle, the authors write, “represents an extreme example of how freedom from competition on island ecosystems can rapidly infl uence morphological adaptation and speciation.” Given its similarity to the smaller Hieraaetus species, the authors recommend reclassifying the New Zealand giant as Hieraaetus moorei. This study shows how quickly morphological changes can occur in vertebrate lineages within island ecosystems. Could it be that anthropologists might some day uncover evidence of a giant version of the Flores woman?

The recent discovery of a Hobbit-like hominid on the Indonesian island of Flores was startling in some respects-its rather modern existence, for one-but it represents a classic case of Darwinian evolution. For reasons that are not entirely clear, when animals make their way to isolated islands, they tend to evolve relatively quickly toward an outsized or pint-sized version of their mainland counterpart. Following this evolutionary script, the Flores woman, presumably a downsized version of Homo erectus, appears to have shared her island home with dwarf elephants and giant rats.
Perhaps the most famous example of an island giant-and, sadly, of species extinction-is the dodo, once found on the Indian Ocean island of Mauritius. When the dodo's ancestor (thought to be a migratory pigeon) settled on this island with abundant food, no competition from terrestrial mammals, and no predators, it could survive without fl ying, and thus was freed from the energetic and size constraints of fl ight. New Zealand also had avian giants, now extinct, including the fl ightless moa, an ostrich-like bird, and Haast's eagle (Harpagornis moorei), which had a wingspan up to 3 meters. Though Haast's eagle could fl y-and presumably used its wings to launch brutal attacks on the hapless moa-its body mass (10-14 kilograms) pushed the limits for self-propelled fl ight.
As extreme evolutionary examples, these island birds can offer insights into the forces and events shaping evolutionary change. In a new study, Michael Bunce et al. compared ancient mitochondrial DNA extracted from Haast's eagle bones with DNA sequences of 16 living eagle species to better characterize the evolutionary history of the extinct giant raptor. Their results suggest the extinct raptor underwent a rapid evolutionary transformation that belies its kinship to some of the world's smallest eagle species.
The authors characterized the rates of sequence evolution within mitochondrial DNA to establish the evolutionary relationships between the different eagle species. Their analysis places Haast's eagle in the same evolutionary lineage as a group of small eagle species in the genus Hieraaetus. Surprisingly, the genetic distance separating the giant eagle and its more diminutive Hieraaetus cousins from their last common ancestor is relatively small.
Without the fossils to directly determine divergence times, Bunce et al. relied on molecular dating techniques that use the rate of sequence evolution in the genes studied to establish the relative evolutionary ages of the eagles. Proposing a divergence date of roughly 0.7-1.8 million years ago, the authors acknowledge that while this is the "best available approximation of the 'true' date," additional molecular data could help refi ne the estimate. Whatever the date of divergence, the extinct giant eagle is clearly an anomaly among the eagles studied here. The increase in body size-by at least an order of magnitude in less than 2 million years-is particularly remarkable, Bunce et al. argue, since it occurred in a species still capable of fl ight.
The absence of mammalian competitors facilitated the evolution of much larger eagles and owls on Cuba and may have likewise precipitated the rapid morphological shift seen here. Haast's eagle, the authors write, "represents an extreme example of how freedom from competition on island ecosystems can rapidly infl uence morphological adaptation and speciation." Given its similarity to the smaller Hieraaetus species, the authors recommend reclassifying the New Zealand giant as Hieraaetus moorei. This study shows how quickly morphological changes can occur in vertebrate lineages within island ecosystems. Could it be that anthropologists might some day uncover evidence of a giant version of the Flores woman? After apprenticing at her mother's side for some eight years-the fi rst three clinging to her body-an orangutan is ready to make her own way in the forest canopy. The only great ape specializing in arboreal living, orangutans forage the treetops mostly for fruit, nuts, insects, leaves, and tree bark. They can recognize hundreds of species of edible fruit from trees and woody climbers and remember their location and fruiting season. Malay legend says orangutans (a variation on the Malay trope for "man of the woods") derived from humans who sought refuge from their species in the wilds of the forest. Today, with the last orangutan refuges shrinking drastically, the man of the woods has nowhere else to go.
Hundreds of thousands of orangutans once ranged throughout southeast Asia. Now just two orangutan species inhabit just two countries: Indonesia (Kalimantan, the southern part of Borneo and Sumatra Island) and Malaysia (Sabah and Sarawak, in northern Borneo). The Sumatran orangutan is listed as critically endangered; the Bornean, endangered. In Indonesian Borneo and Sumatra, logging operations clear an estimated 5 to 6 million forest acres a year, leaving the apes stranded in isolated stands of trees and the normally fi re-resistant rainforest at sudden risk. Another force driving orangutan extinction in Indonesia is the poaching and illegal killing (mothers do not give up their babies without a fi ght) that secures orangutan babies for the exotic pet trade. In Sabah, Malaysia, the primary threat comes from clearing the forest for agriculture.
Conservation efforts depend, among other things, on having reliable data on population size, density, and distribution, but estimates of orangutan numbers in Sabah-which range from 2,000 to 20,000-are outdated. In a new study, Marc Ancrenaz and colleagues report an innovative method of directly estimating orangutan numbers from the number of nests detected during aerial surveys. (Orangutans are tough to spot directly, so researchers count the nests they sleep in at night.) Their survey, which covered the entire orangutan range throughout Sabah, estimates a total population of 11,000 orangutans-a drop of 35% in the past 20 years, based on a 1988 World Wildlife Federation report.
Counting orangutans from the ground can be very timeconsuming, diffi cult work, especially when faced with the hip-deep muck and steep slopes of the rainforest fl oor. Though helicopters obviously cover greater distance and more remote territory than is possible by foot, they're generally used to survey animals in more open landscapes. By using ground survey data to refi ne their aerial survey results, Ancrenaz and colleagues could directly assess the distribution and size of orangutan populations throughout Sabah. (Sabah covers roughly 72,000 square kilometers.) Over the course of two years, ground surveys-requiring 1,100 hours of fi eld work-and aerial surveys-requiring just 72 hours-were conducted throughout all the major forests of Sabah. Commercial logging occurs in about 76% of all Sabah forests in commercial forest reserves. During the overfl ights, information was recorded on altitude, forest type, forest disturbance (on a scale from none to active exploitation), and signs of human activity.
The authors attribute the 35% decline in Sabah orangutan numbers primarily to habitat loss from agricultural development. The surveys revealed that lowland forests harbored the greatest density of nests and orangutans, with the densest populations found in several highly disturbed, fragmented forests along newly created palm oil plantations. These high orangutan densities could refl ect an infl ux of refugees from recently destroyed forest habitat into areas that are still forested. In logged forests, higher population densities were found in old exploited or sustainably logged forests than in conventionally logged reserves.
While the authors acknowledge the density estimates could be more precise-better measures of nest decay and construction rates are needed-their survey reveals crucial information on orangutan numbers and distribution. Most orangutans in Sabah, including those making up one of the largest unfragmented populations in Borneo, live outside protected areas, in commercially exploited forests. These results suggest that orangutans may adapt better to degraded forests than previously thought-provided illegal hunting and agricultural conversion are controlled.
More fi eld research will help quantify the impacts of human activity-from logging to stealing babies-on great ape ecology and survival, and determine whether exploited forests can support conservation. It may be, for example, that integrating agricultural fi elds with forested corridors could sustain orangutan populations over the long term. With time of the essence, these aerial surveys will speed that work, and help sustain orangutans' refuge in the treetops, above their human relatives. Tracking Orangutans from the Sky DOI: 10.1371/journal.pbio.0030022 The nematode Caenorhabditis elegans is a little less lonely than the rest of us-it is a self-fertile hermaphrodite, which as a larva makes and stores sperm before switching to egg production for the remainder of its lifespan. (C. elegans also maintains some males at a low frequency, about 1 in 500, and the hermaphrodite's eggs can be fertilized by sperm either from males or themselves.) A sister species, C. briggsae, is also hermaphroditic, but phylogenetic evidence suggests the last common ancestor of the two species had a female/male mode of reproduction. This raises the question of how the sex determination mechanisms, which must have evolved independently, differ between the two species. In this issue, Sudhir Nayak, Johnathan Goree, and Tim Schedl show that a crucial difference lies in the activities of two genes.
In C. elegans, the early period of sperm production is controlled by multiple proteins, two of which are the focus of this study, the RNA-binding protein GLD-1 (encoded by the gene gld-1) and the Fbox-containing protein FOG-2 (encoded by the gene fog-2). Together, they repress translation of a gene, tra-2, by binding to its messenger RNA. This allows another gene, fem-3, to transiently masculinize the larval germline to produce sperm.
Comparing the genomes of C. elegans and C. briggsae, Schedl and colleagues found they share 30 out of 31 sex The Evolution of Self-Fertile Hermaphroditism: The Fog Is Clearing DOI: 10.1371/journal.pbio.0030030 determination genes, but not fog-2. More surprisingly, they found that the role of gld-1 in sex determination is opposite in the two species. When C. elegans is deprived of gld-1, would-be hermaphrodites produce only oocytes. But when C. briggsae is deprived of gld-1, would-be hermaphrodites produce only sperm. Thus, the authors conclude, the control of hermaphrodite spermatogenesis is fundamentally different in the two species.
By further examining the C. elegans genome, the authors showed that fog-2 arose from a gene duplication event after the C. elegans-C. briggsae split, which occurred approximately 100 million years ago. Since then, its fi nal exon, which codes for the C-terminal end of the protein, has undergone rapid evolution. The authors also show that this is the "business end" of the protein for its interaction with GLD-1, suggesting that the divergence of C. elegans and C. briggsae sex determination pathways resulted, in part, from FOG-2's new interaction with GLD-1.
Exactly what the role of fog-2 is in C. elegans is still unclear. The authors speculate that it may recruit additional factors onto the gld-1/tra-2 mRNA complex, increasing effi ciency of translation repression. Much remains to be discovered about C. briggsae sex determination as well. The authors suggest that additional genetic differences promoting self-fertility are likely to have accumulated since the two species diverged, which may act to strengthen the male-female germline switching signal. Investigation of this possibility may shed more light on how hermaphroditism operates in these two species, and how a developmental pathway controlling sex determination can evolve. In 1995, the fi rst complete bacterial genome sequence was published. Now, nearly 200 bacterial genomes have been completed, and a new one hits the scientifi c press most weeks. This burgeoning industry is not just scientifi c "stamp collecting," however. Having all these genome sequences may provide useful clues about why some bacteria cause human disease, how to control their spread, and how to treat the infections caused by them. By comparing genome sequences, scientists can learn much more about what makes a bacteria tick than they can learn from a single sequence.
Derrick Fouts and his colleagues have taken this comparative approach with Campylobacter. Infection with a Campylobacter species is one of the most common causes of human bacterial gastroenteritis. In the US, 15 out of every 100,000 people are diagnosed with campylobacteriosis every year, and with many cases going unreported, up to 0.5% of the general population may unknowingly harbor Campylobacter in their gut annually. Diarrhea, cramps, abdominal pain, and fever develop within 2-5 days of picking up a pathogenic Campylobacter species, and in most people, the illness lasts for 7-10 days. But the infection can sometimes be fatal, and some individuals develop Guillain-Barré syndrome, in which the nerves that join the spinal cord and brain to the rest of the body are damaged, sometimes permanently.
Campylobacteriosis is usually caused by C. jejuni, a spiralshaped bacterium normally found in cattle, swine, and birds, where it causes no problems. But the illness can also be caused by C. coli (also found in cattle, swine, and birds), C. upsaliensis (found in cats and dogs), and C. lari (present in seabirds in particular). Disease-causing bacteria generally get into people via contaminated food, often undercooked or poorly handled poultry, although contact with contaminated water, livestock, or household pets can also cause disease.
In 2000, C. jejuni was the fi rst food-borne pathogen to be completely sequenced, but we still know little about how Campylobacter species cause disease. In their search for clues, Derrick Fouts and coworkers have completely sequenced the genome of C. jejuni strain RM1221 (isolated from a chicken carcass) and compared it with the previously sequenced C. jejuni strain NCTC 11168 and with the unfi nished sequences of C. coli strain RM2228 (a multi-drug-resistant chicken isolate), C. lari strain RM2100 (a clinical isolate), and C. upsaliensis strain RM3195 (taken from a patient with Guillain-Barré syndrome).
The researchers describe numerous differences and Wild-type C. elegans hermaphrodite stained to highlight the nuclei of all cells similarities between these different Campylobacter strains and species. For example, there are major structural differences between the genomes caused by the insertion of new stretches of DNA. Some of these pieces of DNA may carry genes that improve bacterial virulence or fi tness, so their presence could help to explain the different biological behaviors of these strains. There are also major variations in the genes responsible for synthesis of molecules that are important for the interaction of Campylobacter with the environment. Such differences could underlie the host specifi city of the different species. Differences between the Campylobacter species in genes that are likely to be involved in aspects of bacterial virulence, such as adherence, motility, and toxin formation, are all detailed by Fouts et al., who also describe a new putative Campylobacter virulence locus. Further work is needed to relate these genomic differences to functional differences, but this detailed comparative genomic analysis provides the core blueprint for this important family of human pathogens. And in doing so, it lays the foundation for the development of new ways to monitor and control Campylobacter in the food chain and in human infection. It's hard to believe it was just ten years ago that scientists reported the fi rst complete genome sequence of an organism, the bacterial pathogen Haemophilus infl uenzae. The list has grown considerably since then: add over 160 bacterial species (and counting), most major model organisms, and an ever-growing list of mammalsincluding, of course, humans. With 99% of our genome now fully sequenced, the Human Genome Project's next major goal is to identify all the functional elements contained in our 2.85 billion nucleotides. Such an effort is hardly trivial: producing the sequence of a mammalian-size genome can run from $10 to $50 million, the estimated price tag of the Cow Genome Project.
In an ideal world, any organism would be fair game for sequencing, but in the real world, sequencing resources are scarce. Comparing genome sequences turns out to be a great way to identify regions that have important functions, but comparative genomics studies would be far more effi cient if scientists could fi gure out in advance which genomes would reveal the most information about a particular question. Taking up that challenge, computational biologist Sean Eddy reports a statistical model that predicts how many genomes, and at what evolutionary distance, are needed for effective comparative genomic analyses. In addition to confi rming some working principles of comparative genomics, the model also reveals a surprisingly simple guideline for future studies.
Comparative genomics works by aligning sequences of different organisms to identify patterns that operate over both large and small distances. Aligning mouse chromosomes with human chromosomes, for example, shows that 99% of our protein-coding genes align with homologous sequences in mice. Underlying such analyses is the principle that DNA sequences that are highly conserved are likely to be functionally important. A common assumption is that adding more comparative genomes to the alignment helps distinguish functionally signifi cant from irrelevant conserved sequences.
How do you go about creating an abstract model that captures what Eddy calls the "essential fl avor of comparative genomic analysis"? His model puts aside the specifi c characteristics of individual organisms, genomic features, and analysis programs in favor of identifying higherlevel patterns and scaling relationships, specifi cally between the number of genomes, evolutionary distance, and feature size (features include genetic elements like exons and transcription factors).
The model shows that the number of genomes required to identify conserved regions-that is, regions evolving under selection-scales inversely with the size of the feature being sought. Thus, to look for conserved sequences half as long, you need twice as many genomes, assuming a constant evolutionary distance and statistical power. For example, to identify a conserved human feature the size of a coding exon (about 50 nucleotides), it is suffi cient to compare just the human and mouse genomes. But to identify conserved single nucleotides, you would need 55 comparative genomes at "mouse-like" evolutionary distances (roughly 75 million years).
Things get a little trickier when varying evolutionary distance. We can see a substitution only at a given point in time: we can't tell how many times a site has changed, for example, or whether it changed at some point and then changed back. But at short evolutionary distances-where it's safer to assume no sites have changed more than once-the evolutionary distance is roughly the same as the fraction of sites identifi ed as changed, and evolutionary distance and the number of genomes needed scale inversely. Therefore, the closer the evolutionary distance, the more genomes needed: one would need seven times as many comparative genomes using human/baboon distances, for example, compared to human/mouse distances. So when it comes to using primate sequences to study the human genome, our most distant relatives (such as lemurs) offer far more comparative analysis power than our next of kin (chimps and bonobos).
While this model confi rms the intuitive assumption that identifying smaller features requires more genomes, it reveals an inverse scaling relationship far more direct, and precise, than previously imagined. With the next phase of the Human Genome Project under way, Eddy's model offers valuable guidelines for identifying which genomes and how many might best meet this ambitious goal. There are many different sexdetermining systems in plants and animals with separate sexes (dioecious species). In some species, environmental factors activate sex-determining genes that trigger expression of genes leading to male or female development. Other species have evolved specialized sex chromosomes. In the well-known X-Y system of mammals, individuals inheriting a Y chromosome become males, and XX individuals become females.
Sex chromosomes have arisen independently in many taxonomic groups. It is an interesting question whether the same mechanisms were involved each time. Similarities in sex chromosome evolution have been reported between birds and mammals (although in birds, females are the heterozygous sex). In a new study, Michael Nicolas and colleagues uncover striking parallels in the details of sex chromosome evolution between mammals and a far more distant group: plants.
Sex chromosomes are an oddity in fl owering plants. They are limited to dioecious species, a subset of plants that carry male and female organs (stamens and carpels, respectively) on separate individuals (most fl owering plants are hermaphrodites). The genus Silene, which includes the White Campion, includes both dioecious and hermaphrodite species. The authors focus on three dioecious species, Silene dioica, S. latifolia, and S. diclinis, which share an X-Y sexdetermination system where Y specifi es maleness.
The theory of sex chromosome evolution holds that sex chromosomes were once homologs (a pair of equivalent autosomes-the non-sex chromosomes) that evolved different morphology and gene content because they lost their ability to recombine. Suppression of recombination is thought to start around the sex-determining region, but may eventually affect much of the sex chromosomes. Recombination is a key genetic process in which two chromosomes pair and exchange their sequences. In the absence of recombination, the two chromosomes of a pair evolve separately.
In the case of mammals, whose sex chromosomes evolved about 320 million years ago, loss of recombination led to widely diverged X and Y chromosomes that pair only over a very small region, the pseudoautosomal region (PAR; because in this region the X and Y still behave like autosomes). The X and Y chromosomes of dioecious Silene species are morphologically distinct, like those of mammals, and they also have a PAR and a nonrecombining region. Nicolas and colleagues' results shed some light on how recombination suppression evolved on the Silene sex chromosomes.
The authors studied four genes outside the PAR on the Silene X chromosomes that are also present on their Y chromosomes. They mapped the genes relative to the PAR and compared the nucleotide sequences of the X and Y version of each gene in each species. As expected of sequences that no longer recombine, the X and Y versions of each gene have diverged. Strikingly, the extent of nucleotide divergence increases with the gene's distance from the PAR.
Evolutionary biologists use sequence divergence as a clock: the longer two originally identical sequences have been isolated from one another, the more independent mutations they accumulate. The picture that emerges from the Silene data is one of a progressive suppression of recombination, gradually diminishing the PAR. A similar scenario has been proposed in mammals and birds. However, the authors estimate that the Silene sex chromosomes started diverging only 10 million years ago. The Silene chromosomes might therefore offer a better chance to observe recombination suppression in its early stages, and perhaps to get at its mechanisms.
The authors also report evidence for some degeneration of the Silene Y chromosome genes. Y degeneration is well documented in mammals, in which most X-linked genes have no Y-linked counterparts. Understanding X-Y divergence in Silene species may thus shed light on the evolution of sex chromosomes in vertebrates as well. Genomes of important crops such as sorghum, soybean, maize, and wheat hover between 735 Mb and 16,900 Mb, and determining their complete sequences is daunting and costly.
Wide size variations do not necessarily refl ect differences in gene content, but rather refl ect the presence of repetitive sequence elements that do not generally code for genes. Repetitive elements account for at least 75% of the maize and sorghum genomes. In a new study, Joseph Bedell and his colleagues describe a way to fi lter away repetitive elements when sequencing the genome of sorghum (Sorghum bicolor), a staple crop in much of the developing world because of its resilience in arid climates.
The authors use an approach known as methylation fi ltration that has been employed before for pilot plant genome analyses.
Here they present compelling evidence of the method's reliability when applied to large-scale genome sequencing. The approach is built on the observation that in plants, methylation-a chemical tagging of DNA with methyl groupsoccurs at repetitive sequences to a much greater degree than at gene sequences. This provides an opportunity to concentrate sequencing efforts on the coding portion of the genome.
To eliminate repetitive sequences, the authors introduced small pieces of sorghum chromosomes into bacteria strains designed to specifi cally destroy DNA sequences that carry methyl groups. Using two independent assessments, they estimated that methylation fi ltration reduced the amount of sorghum DNA they would need to sequence by two thirds, from 735 Mb to approximately 250 Mb.
But were any genes lost in the fi ltration step? The authors compared their results to partial sequence information Separating Wheat from Chaff in Plant Genomes DOI: 10.1371/journal.pbio.0030039 In February 2003, the fi rst (and so far only) epidemic of severe acute respiratory syndrome (SARS) started in Guangdong Province, China. A respiratory illness that begins with a high temperature and can develop into life-threatening pneumonia, SARS is spread by close person-to-person contact. Before the end of the month, a Guangdong doctor had inadvertently taken the infection to Hong Kong. A woman staying in the same Hong Kong hotel as the doctor then carried the disease to Toronto. In March, the World Health Organization issued a global alert and warned against unnecessary travel to affected areas. Because of these and other containment efforts, 8,098 people became ill with SARS, rather than the predicted millions; 774 people died. The last case of the epidemic was reported in Taiwan in June 2003, and since then there have been only two cases in Singapore and nine in China.
By May 2003, a coronavirus had been identifi ed as the cause of SARS, and the full genome sequence of this new human pathogen, which may have jumped from civet cats to people, had been published. From the viral genome, researchers have deduced the sequences and structures of the viral proteins, hoping to use this information to develop treatments and vaccines for SARS. But could the structure of the RNA genome itself also be a target for antiviral drugs?
The genome of the SARS virus is a single strand of RNA that folds into regular repeating patterns to form secondary structures such as helices. These then fold and bend in three dimensions to form complex tertiary structures. William Scott and colleagues have used X-ray crystallography to measure the exact positions of individual ribonucleotides and the interactions between them in a small segment of the SARS virus genome called the s2m element. This element sits at one end of the viral genome, and, as the researchers show, its sequence is highly conserved in related coronaviruses. Furthermore, unlike the rest of the SARS genome, which changes rapidly, the s2m element is absolutely conserved in SARS variants obtained from patients during the SARS epidemic. This strong sequence conservation indicates that the tertiary structure of s2m could be important for viral function, and when the researchers solved the three-dimensional crystal structure of the element, they found that it had a unique tertiary structure. In particular, there was a right-angle kink in its helical axis and a tunnel with a net negative charge.
The biological role of a new protein can often be deduced by comparing its shape with that of proteins with known functions. Scott and colleagues used this approach to hypothesize that the function of the s2m element involves interaction with a conserved host factor during the SARS life cycle. Finding a similar 90° kink in a region of ribosomal RNA that binds factors necessary for the initiation of protein synthesis, the researchers speculate that the SARS virus may use the s2m element to hijack its host cell's protein synthesis machinery. This and other putative roles need to be tested experimentally, but given that the s2m element is absent in the human genome, its unusual structural features could be an attractive target for the design of antiviral therapeutic agents. Structure of a conserved RNA element within the SARS virus genome generated previously from bacterial artifi cial chromosomes (BACs). BACs offer the most comprehensive representation of the genome because they contain large pieces of unmodifi ed sorghum chromosomal DNA. Of the 148 genes identifi ed on 14 sorghum BACs, 133 appeared in the fi ltered set. This means that the methylation fi ltration method captured at least 90% of the genes in the sorghum genome and 96% (131/137) if a repeat cluster of 11 known methylated genes is removed from the analysis.
Methylation fi ltration also compared favorably to shotgun sequencing, a method that reads the whole genome in small fragments that are progressively assembled into larger pieces by computer analysis. The authors reported that after sequencing 285 Mb of fi ltered sorghum DNAapproximately 1.15 times the length of the sorghum coding regions-they obtained on average 65% of the length of 96% of the genes. Theoretical calculations and simulation based on the genome of Arabidopsis-a plant model organism-predicted that shotgun approach would yield similar results (67% of the length of 96% of the genes) after sequencing the equivalent of 1.15 times its total length (rather than 1.15 times the length of just the coding regions). Thus, methylation fi ltration can provide as much information on coding sequences as the shotgun approach, with less investment in sequencing.
Methylation fi ltration does not yield a complete genome map, but it offers quicker, more affordable access to genes than most commonly used sequencing approaches. Sorghum is closely related to maize and sugar cane, and more distantly to rice. The availability of its genome sequence offers the chance for more in-depth experiments into the evolution of the grass family, and promises important insights into the genetic control of drought resistance. Amidst the hoopla over the exact number of genes we have in our genome-more than a fruitfl y, fewer than a rice plant-a more fundamental genetic truth has often been obscured. The expression of 20,000-30,000 genes is under the control of an uncounted host of non-coding sequences, which bind transcription factors and thereby regulate when and where genes are expressed. Unlike coding sequences, whose signatures are easy to spot, the characteristic features of noncoding regulatory elements are largely unknown, making their discovery by simple sequence analysis diffi cult. In this issue, Greg Elgar and colleagues attack this problem by comparing the noncoding sequences of the human and the pufferfi sh.
Since the last common ancestor of these two species existed 450 million years ago, the authors reasoned that noncoding sequences conserved between them are likely to be fundamental to vertebrate development. Through sequence alignment with increasingly strict criteria, they identifi ed 1,373 highly conserved non-coding elements (CNEs), with an average length of about 200 base pairs. The average sequence match is 84%: not perfect, but much higher than for coding regions shared by humans and pufferfi sh. A quick check showed that virtually all the sequences also occurred in rodents, chickens, and zebrafi sh, but not in the nematode, fruitfl y, or even the sea squirt, a primitive non-vertebrate chordate.
CNEs are not spread uniformly throughout the genome. Instead, they are bunched together in fewer than 200 clusters, most of them in close proximity to genes implicated in transcriptional regulation or development. This Highly conserved vertebrate non-coding elements direct tissue-specifi c reporter gene expression A small rodent rustles through a fi eld in the still night, making just enough noise to betray its location to a circling barn owl. A female frog sits on the bank of a pond amid a cacophony of courting bullfrogs, immune to the mating calls of all but her own species. Thanks to a sophisticated sensory processing system, animals can cut through a vast array of ambient auditory stimuli to extract meaningful information that allows them to tell where a sound came from, for example, or whether they should respond to a particular mating call.
An acoustic stimulus arrives at the ear as sound energy in the form of air pressure fl uctuations. The sound signal triggers oscillations in mechanical resonators such as the eardrum and hair sensilla. These oscillations convert sound energy into mechanical energy, opening ion channels in auditory receptor cells and producing electrical currents that change the neuron's membrane potential. This, in turn, produces the action potential that carries the sound signal to the brain. This multistep signal transduction process takes less than a millisecond, but exactly how it occurs at this time scale remains obscure. Direct measurements of the individual steps can't be made without destroying the mechanical structure; consequently, most measurements are taken downstream of the mechanical oscillations at locations like the auditory nerve. Likewise, the temporal resolution of most stimulus-response trials is far too imprecise to analyze processing at the sub-millisecond level.
Given these experimental limitations, Tim Gollisch and Andreas Herz turned to computational methods and showed that it's possible to reveal the individual steps of complex signal processing by analyzing the output activity alone. Using grasshopper auditory receptors as models, the authors identifi ed the individual signal-processing steps from eardrum vibrations to electrical potential within a sub-millisecond time frame and propose a model for auditory signaling.
The crucial step in their study is the search for those sets of inputs (stimuli) that would yield a given fi xed output (response). To get the parameters to describe the fi nal output, the authors generated a sound stimulus (two short clicks) and recorded axon responses of receptor neurons in a grasshopper auditory nerve. From these recordings, they defi ned the fi xed output as the probability of a receptor neuron fi ring a single action potential. They then asked how the various parameters, which were associated with different time scales, could produce the same predefi ned fi ring probability.
By varying the stimulus parameters and comparing the obtained values within their mathematical framework-and making certain assumptions, for example, that the steps signal through a "feedforward" process-they could then tease out the individual processing steps that contribute to the desired output within the required time frame. With this approach, Gollisch and Herz disentangled individual steps of two consecutive integration processes-which they conclude are the mechanical resonance of the eardrum and the electrical integration of the receptor neuron-down to the microsecond level. Surprisingly, this fi ne temporal resolution is achieved even though the neuron's action potentials jitter by about one millisecond.
Thus, using just the fi nal output, this approach can extract the temporal details of the individual processes that contribute to the chain of auditory transduction events. While this method is best-suited for deconstructing unidirectional pathways, the authors suggest it could also help separate "feedforward" from feedback signaling components, especially when feedback is triggered by the fi nal steps. But since many sensory systems share the same basic signal-processing steps, this method is likely applicable to a broad range of problems. clustering of CNEs suggests they may not only attract transcription factors, but may also infl uence the local topology of the DNA, thereby controlling access to their associated gene. Several clusters also appear in regions without any known genes-the identifi cation of these clusters might lead to the discovery of new developmentally signifi cant genes.
While "in silico" discoveries such as this can be the jumping-off point for whole new areas of investigation, their validity must be tested "in aqua," in the wet biology of real organisms. For this Elgar and colleagues chose the zebrafi sh, because its transparent embryo is ideal for observing developmental events. They injected individual CNEs into embryos, along with a green fl uorescent protein (GFP) reporter. By day two of development, 23 out of 25 CNEs injected had upregulated GFP expression, indicating interaction of these sequences with endogenous transcription factors. Different CNEs caused different regional patterns of expression, in keeping with their presumed roles in distinct developmental processes.
The discovery of these developmentally important sequences opens several avenues of new research. For example, analyzing the sequence and location of these CNEs may help point the way to other non-coding elements that remain undiscovered. It is also likely that mutations in these critical sequences cause human diseases. Studying how such mutations drive development astray may lead to better understanding not only of these diseases, which are likely to be rare, but also of normal human development.
Whiskers don't fossilize, so it's hard to say when they fi rst evolved. But it's quite likely they emerged along with mammals, over 200 million years ago. To elude the eye (and feet) of ungainly dinosaurs, it's thought these shrew-like prototypes foraged at night and sought refuge underground, where the sensory advantages of whiskers would come in handy. Nocturnal animals use whiskers much like the blind use walking sticks: to navigate their surroundings, explore close objects, and avoid running into things.
Whiskers, or vibrissae, connect to nerves, blood vessels, and muscles. These special connections allow rats, for example, to actively "whisk" the surface of objects and discern fi ne differences in texture, just as we move our fi ngertips along a surface to pick up details. In the wild, whisking helps rats navigate unfamiliar terrain to fi nd food. But how does the brain know what the animal is touching?
Rat whiskers scan surfaces in a rhythmic motion that excites sensory receptor cells embedded in their whisker pad. Receptors in each whisker shaft are innervated by several hundred "fi rst-order neurons" that relay sensory signals to second-order neurons in the brain stem, then on to third-order neurons in the thalamus, and fi nally on to the cortex, where sensory stimuli are integrated in cell clusters called barrels.
Ehsan Arabzadeh, Erik Zorzin, and Mathew Diamond work with rats to investigate how sensory receptors extract fundamental features from complex and diverse stimuli to encode texture. Not much is known about how receptor and cortical neurons respond to active whisking along irregular surfaces, though responses to simple stimuli (like sinusoidal vibrations) suggest that neurons might represent texture by encoding kinetic features of whisker vibrations, in particular, velocity. In a new study, Diamond and colleagues investigate the connection between textures, whisker vibrations, and neural codes: do distinct textures produce distinct vibrations? If so, how are these vibrations encoded and reported?
The authors fi rst collected kinetic data of whiskers moving across different textured surfaces. Stimulating cranial nerve VII of anesthetized rats (the motor nerve) generated whisking movements akin to those seen in conscious rats; the kinetics of these movements and the vibrations of the whisker shafts were measured under different conditions, including no contact with objects ("free whisk"), contact with smooth objects, and contact with various grades of sandpaper. These vibrations were then "played back" to other rats, while measuring the neuronal activity at two critical stages in the sensory pathway: the fi rst-order neurons that innervate the whiskers and the barrel cortex neurons that integrate the incoming signal.
Altogether, the authors collected a neural dataset consisting of fi rstorder recordings, barrel cortical cluster recordings, and simultaneous paired recordings from both sites, all in response to playback of the library of texture-related vibrations. This approach afforded the opportunity to directly compare encoding of information at both levels in the sensory pathway. These recordings show, the authors argue, that temporally distinct fi ring patterns in the trigeminal ganglion (the cell bodies of the fi rst-order neurons) and cortex captured the kinetic features of the texture-induced vibrations. Each texture's "kinetic signature" is encoded by a characteristic, temporally precise fi ring pattern associated with whisker movement. Compared to free whisking, coarse sandpaper produced irregular bursts of high and low velocity, and both fi rst-order and cortical neurons fi red far more impulses for coarse sandpaper than for free whisks. The authors then used stimuli consisting of random velocities to uncover the "tuning curves" of neurons, and simulations showed that these neuronal tuning curves could perfectly predict the real neural responses to textures. Noting the close match between the simulated and natural responses, Diamond and colleagues conclude that the texture-induced fi ring patterns observed in the fi rst-order and cortical neurons suggest that neurons selectively encode elemental kinetic featuresnamely, high velocity-to tell rats what they're whisking. This selectivity allows even a single whisker to transmit signifi cant bits of texture-specifi c information to the brain. Interesting as rat whisking may be, these fi ndings have relevance beyond the world of whiskered beings, shedding light on the underlying neural processes that translate touch into recognition.

Timing of neuronal activity captures sensory information
If you're a cat fancier, you're well aware that hair follicles are expendable. The product of a spontaneous mutation that caught a cat breeder's eye, le chat nu, would quickly succumb in the wild-its winter coat consists of little more than a ridge of fur down the midback and tail-and needs special care to thrive as a pet. Hairless animals in the lab, on the other hand, can be very instructive. Understanding how hair develops sheds light on the fundamental processes that generate a wide range of tissues and organs, including the lungs, cornea, and mammary glands.
How complex, three-dimensional structures emerge from single sheets of cells is a fundamental question in developmental biology. The dispensability of hair follicles makes them the perfect model system for studying this question-specifi cally, how structures and organs develop from buds. In a new study, Elaine Fuchs and colleagues use a three-pronged approach-involving gene expression analysis, transgenic mice, and cell cultures-to study how epithelial buds, the precursors of hair follicles, form. Their experiments point to two key actors in a signaling pathway that molds a targeted cluster of cells into a hair bud.
During the budding process, overlapping signaling pathways from two adjacent embryonic cell layers-the epithelium and the mesenchyme-direct morphogenesis. The mesenchymal cells initiate the cell-to-cell "crosstalk" that controls bud formation by fi rst directing a small cluster of epithelial cells to form a placode, the pouch that forms hair plugs. The placode in turn directs underlying mesenchymal cells to form the base of the hair follicle, called the dermal papilla, and both structures contribute to the mature hair follicle. During development, cells are constantly bombarded with external signals. The trick is fi guring out which signals trigger the transcriptional and behavioral properties in cells that spur bud formation.
In previous experiments, Fuchs and colleagues showed that reducing expression of E-cadherin-a membrane protein that forms the adhesive junctions between epidermal cells-is essential for allowing the cell remodeling required for bud formation. Here, the authors analyze the timing of external signals against the response of targeted cells to determine how targeted cells translate signals into changes in cell adhesion and remodeling, proliferation, and differentiation-the agents of most types of organogenesis.
Since Snail, a protein that impedes the transcription of a subset of genes, functions in many developmental processes requiring epithelial remodeling, the authors reasoned it might do the same in hair bud formation. Working with developing mouse embryos, they saw a spike in Snail expression on embryonic day 17.5, coinciding with hair bud formation, enhanced cell proliferation, and the down-regulation of E-cadherin. Artifi cially sustaining Snail expression in the skin of transgenic mice caused abnormal levels of cell proliferation in the epidermis and reduced cell adhesion.
Working with skin keratinocytes, precursors of hair fi bers, Fuchs and colleagues explored several signaling proteins known to be involved in bud formation as possible activators of Snail expression. When the authors treated keratinocytes with small amounts of one stimulator, TGF-β2, they saw "rapid and transient induction of Snail." Snail proteins were absent from 17.5-dayold knockout mice lacking TGF-β2 but not from their nonmutant littermates. Conversely, transgenic mice with elevated TGF-β2 signaling activity displayed ectopic expression of Snail. Knockout mice lacking TGF-β2 also showed higher levels of E-cadherin-normally down-regulated by Snail-than their nonmutant littermates.
Altogether, these fi ndings suggest that TGF-β2 signaling transiently induces Snail, which in turn down-regulates E-cadherin and activates a proliferation pathway in the developing bud. Reduced E-cadherin, the authors conclude, appears to contribute to Snail-mediated enhanced proliferation by allowing proteins normally sequestered at the membrane to operate in a proliferation pathway after the number of cellular junctions diminishes. By identifying which molecules are active in specifi c cell types at specifi c developmental stages, this study lays the foundation for dissecting the mechanisms that connect two key processes-intercellular remodeling and proliferation-in epithelial development. And since the consequences of TGF-β2 activity seen here in the hair bud more closely resemble certain types of skin cancer progression than skin development, a mechanistic understanding of hair follicle development promises to shed light on how skin cancer develops as well.

Transgenic epidermis expressing Snail (red) results in expanded keratin 1 expression (green)
Multiple sclerosis (MS) can be an unpredictable disease. It develops when the body's immune system attacks healthy nerve cells and disrupts normal nerve signaling. Patients experience a wide range of symptoms-including tingling, paralysis, pain, fatigue, and blurred vision-that can appear independently or in combination, sporadically or persistently. Although symptoms appear in no particular order, fl are-ups are common in the majority of patients.
MS fl are-ups are commonly treated with beta-interferon. Adverse effects are not uncommon, and, more importantly, a sizable proportion of patients show a reduced response, or no response at all. Given the variability of the disease and treatment response, being able to predict how a particular patient is likely to respond to interferon would help doctors decide how close to monitor the patient or even whether to consider alternative treatments. In a new study, Sergio Baranzini et al. describe a computational model that can predict a patient's therapeutic response to interferon based on their gene expression profi les.
Immune cells typically secrete interferons to fend off viruses and other pathogens. Interferons stem viral infection by inhibiting cell division in neighboring cells-thus preventing the virus from reproducing-and triggering pathways that kill the infected cells. It's thought that interferon therapy may relieve symptoms associated with MS by correcting imbalances in the immune system that lead to disease. Interferon therapy produces changes in the gene expression profi le of targeted cells-that is, it inhibits or activates certain genes-which in turn alters the cells' activity.
Blood samples were taken from 52 patients with relapsingremitting MS (marked by acute fl are-ups followed by partial or full recovery), and their RNA was isolated from a class of immune cells called peripheral blood mononuclear cells. After patients started interferon therapy, blood was taken at specifi c time points over the course of two years. Baranzini et al. measured the expression level of 70 genes-including a number involved in interferon interactions and immune regulation-at each time point.
The authors used statistical analyses to search for gene expression profi les that were associated with patients' therapeutic outcomes. They looked for patterns in analyses of single genes, gene pairs, and gene triplets, and found their model's predictive accuracy increased with gene number. They also looked for genes that showed different expression patterns over the two years based on patient response, time passed, and patient response over time. These analyses identifi ed genes that increased activity independently of clinical response (interferon can activate genes that have no effect on disease), as well as genes that were associated with a good or poor response. Some of these genes were also the best predictors of patient response before therapy was started.
This approach can predict the probability of a good or poor clinical response with up to 86% accuracy. Baranzini et al. offer hypotheses to explain how the observed gene activity might produce the differential responses to therapy-for example, a poor response may stem from downstream signaling events rather than from problems with drug metabolism. But the authors caution that the mechanisms connecting these genetic signatures to specifi c outcomes-and the mechanisms that produce a positive interferon response-have yet to be established. For now, these patterns should be thought of as markers. Still, these results suggest that doctors could one day tailor MS patients' treatments to their molecular profi le, and perhaps take some of the uncertainty out of this capricious disease. Over 250 million years ago (mya), all the continents of Earth formed a single land mass called Pangaea. Some 50 million years later, this supercontinent began to split in two, forming Laurasia-now North America, Asia, and Europe-and Gondwana-present-day Antarctica, Australia, South America, Africa, and India. After another 50 million years, Gondwana, too, broke up. At the end of the Cretaceous period, New Zealand split off (about 80 mya), then South America and Australia separated from Antarctica (about 35 mya). Fairy-tale quality aside, the story of continental drift fi ts comfortably with the geological and fossil record and feeds our understanding of current distributions of plant biodiversity.
Although we know how and when Pangaea broke apart, the distribution of fossils of the same species on many different continents, separated by vast ocean waters, challenges us to explain how they got there. Plant life on New Zealand, for example, shares striking similarities to that on other Southern Hemisphere land masses, but scientists have yet to agree on how this came to pass. In particular, one genus, Nothofagus-the southern beech tree, a plant whose 80-millionyear-old fossil history goes back to the days of Gondwana-has polarized views on the nature of Southern Hemisphere biogeography.
One theory suggests that geographic barriers (New Zealand and Australia are

Expression levels of three genes in beta-interferon responders (red)
and non-responders (blue) separated by the Tasman Sea) would have prevented species expansion after the break-up of the continents, so similar contemporary species must have already existed in both places before New Zealand broke away from Gondwana. In this scenario, called vicariance, ancestors of existing lineages drifted with the repositioned land masses. Another hypothesis, born of existing distributions and fossil data, suggests that long-range oceanic dispersal is more likely. But since Nothofagus seeds are not considered ocean-worthy vessels, many believe vicariance is the only possible explanation.
Peter Lockhart and colleagues argue that a clear picture of the divergence dates of various southern beech species could help clarify the relative contributions of vicariance versus dispersal. But they would need signifi cant lengths of DNA sequences to reliably characterize the evolutionary history of each species.
Consequently, Lockhart and colleagues analyzed a 7.2-kilobase fragment of the chloroplast genome (which typically ranges from 110,000 bp to 160,000 bp) for 11 species of three Nothofagus subgenera-Lophozonia, Fuscospora, and Nothofagus-from South America, Australia, and New Zealand. Reconstructing the trees' evolutionary relationships (phylogeny) based on analyses of their chloroplast sequences, the authors discovered a nuanced evolutionary history that supports vicariance for some species and dispersal for others.
Assuming that beech was present throughout Gondwana (which fossil data support), the sequence of the Gondwana breakup should be refl ected in the beech's phylogeny. New Zealand beeches should be more distantly related to both Australian and South American species, because of the greater period of separation-65 million years compared to 30 million years. Yet Australian and New Zealand beeches are more closely related to each other than to South American species, which refl ects more recent relationships. Given that fossils of all beech subgenera extend back to the New Zealand Cretaceous period, the dating of splits and the nature of the relationships indicate extinction of beech lineages within current subgenera in New Zealand, and possibly in Australia and South America.
Lockhart and colleagues' analyses suggest that the relationships of the Australian and New Zealand Lophozonia and Fuscospora species are too recent to have roots in Gondwana, indicating a role for transoceanic dispersal. The evolutionary relationship between the Australasian and South American Fuscospora lineages, however, is consistent with vicariance. These divergence results, the authors conclude, indicate that current distributions of Nothofagus cannot be explained solely by continental drift (followed by extinction of some species) and that contemporary New Zealand Nothofagus species are not direct descendants of the beeches thought to have reached the island after the split from Antarctica.
Taken together, the results highlight the need for caution in evaluating fossil evidence. The fossil record doesn't necessarily capture when a species fi rst appeared, and a continuous fossil presence can mask extinctions and reinvasions. The authors conclude that their molecular data make the case for investigating possible mechanisms of long-range dispersalespecially the dispersal properties of Nothofagus seeds-and stresses the need to consider more complex hypotheses to explain something as dynamic and complex as the evolutionary history of biodiversity.


extfieldsofstudy: Biology Medicine

text:
Phylogenetic analysis and sequence comparisons of structural and non-structural SARS coronavirus proteins in Taiwan.

Taiwan experienced a large number of severe acute respiratory syndrome (SARS) viral infections between March and July 2003; by September of that year, 346 SARS cases were confirmed by RT-PCR or serological tests. In order to better understand evolutionary relationships among SARS coronaviruses (SCoVs) from different international regions, we performed phylogenetic comparisons of full-length genomic and protein sequences from 45 human SCoVs (including 12 from Taiwan) and two civet SCoVs. All the Taiwanese SARS-CoV strains which associated with nosocomial infection formed a monophyletic clade within the late phase of the SARS epidemic. This Taiwanese clade could be further divided into two epidemic waves. Taiwan SCoVs in the first wave clustered with three isolates from the Amoy Gardens housing complex in Hong Kong indicating their possible origin. Of the 45 human SCoVs, one isolate from Guangdong province, China, exhibited an extra 29-nucleotide fragment between Orf 10 and Orf 11—similar to the civet SCoV genome. Nucleotide and protein sequence comparisons suggested that all SCoVs of late epidemic came from human-to-human transmission, while certain SCoVs of early epidemic might have originated in animals.

Introduction
On 7 August 2003, the World Health Organization (WHO, 2003) reported that the 2003 SARS pandemic infection had spread to more than 30 countries, affecting 8422 people and killing 916. Later that year a novel coronavirus (SARS-CoV) was isolated from SARS patients Ksiazek et al., 2003;Peiris et al., 2003b;Poutanen et al., 2003); an animal inoculation experiment identified a causal relationship between SARS and SARS-CoV infection . Zhong et al. (2003) identified the geographic origin of the epidemic as Guangdong province, China, and the originating month as November 2002. The first SARS case in Taiwan was diagnosed on 14 March 2003. Its history was traced to a trip by the index case to Guangdong in mid-February, when the SARS epidemic in that province reached its peak (CDC, 2003;ROC CDC, 2003). The index case transmitted the virus to his wife and son; the first SARS coronavirus in Taiwan-SCoV TW1-was isolated from the son (Hsueh et al., 2003).
On 26 March a male resident of the Amoy Gardens housing complex in Hong Kong (hereafter referred to as Mr. X) flew to Taiwan. On 27 March he took a train from Taipei to Taichung City to visit his younger brother. That night he experienced a high fever; most likely he also read a local news report of a major SARS outbreak in Amoy Gardens that same day (Peiris et al., 2003a). He returned to Hong Kong on 28 March. After he was admitted to a hospital, Mr. www.elsevier.com/locate/meegid Infection, Genetics and Evolution 5 (2005) 261-269 X made a phone call to warn his younger brother, but it was too late. The younger brother who developed symptoms on 31 March became the first SARS-related fatality (TC1) in Taiwan. A second index case (SCoV-TWC) was isolated from this patient (the younger brother) by the ROC CDC .
The third index case was Ms. A, a female adult who traveled on the same Taiwanese train as Mr. X on 27 March. Two days later she visited a hospital in Taipei complaining of general fatigue. In addition to the local hospital, she visited two private clinics before being referred to Taipei Municipal Hoping hospital on 9 April. She spent less than 6 h in that hospital's emergency room, but she probably transmitted the virus to two patients, an assistant nurse who escorted her to the X-ray room, and a laundry worker who handled her isolation gown. These individuals transmitted the SARS virus to other medical personnel and patients, resulting in the entire hospital being shut down for more than 2 months starting on 24 April. According to the ROC CDC, the Hoping hospital nosocomial infection resulted in 66 probable and 22 suspected SARS cases (Wu et al., 2003). Even though the Taiwanese government imposed a quarantine on 28 April on all air travelers arriving from China, Hong Kong, Singapore, Macau, or Toronto, the virus still spread to different parts of the main island of Taiwan and the adjacent Penghu Islands. By 1 September, 346 SARS cases in Taiwan had been confirmed by RT-PCR or serological tests (WHO, 2003).
The size of the SCoV genome is approximately 29.7 kb (Marra et al., 2003;Rota et al., 2003). The 5 0 portion of the genome (21 kb, about two-thirds) contains the code for the replicase gene, including two large open reading frames (Orfs), referred to as Orfs 1a and 1b. The other onethird of the genome contains Orfs for four structural proteins (spike [S], envelope [E], membrane [M], and nucleocapsid [N]) and nine putative non-structural proteins (Orfs 3,4,7,8,9,10,11,13 and 14). Recently, Guan et al. (2003) isolated SCoV-like viruses from Himalayan palm civets and raccoon dogs in southern China. According to a comparative analysis of human and animal SCoV genomes, the three animal SCoVs (SZ1, SZ13 and SZ16) all retain a 29-nucleotide sequence inserted between Orfs 10 and 11.
For this study, we used phylogenetic analysis to investigate relationship among 12 Taiwanese SARS-CoVs and between those SCoVs from other countries. One specific goal was to determine whether the SARS-CoV isolate from Mr. X's younger brother (TWC) clustered with the isolate from Ms. A (TWC2), and whether either one of those isolates clustered with isolates from other Amoy Gardens residents (Chim et al., 2003). We also compared the amino acid sequences of the S, E, M, and N structural proteins and three of the nine putative non-structural proteins (Orfs 3, 10, and 11) for 47 SARS-CoVs including 12 Taiwanese strains.

Phylogenetic tree analysis
A BLAST search was performed to locate SARS CoV sequences in the GenBank database. A total of 47 full-length nucleotide sequences from SARS CoV isolates (including two civet isolates) were aligned and edited using the BioEdit program (Hall, 1999). Phylogenetic analyses were conducted with the Phylip 3.6b (Felsenstein, 1989) and MEGA2 programs (Kumar et al., 2001) using the neighbor-joining (NJ) and Fitch and Wagner parsimony (Pars) methods. Evolutionary distances were estimated with the Kimura twoparameter model (Kimura, 1980). NJ and Pars tree robustness were statistically evaluated by bootstrap analysis (100 samples).

Nucleotide sequence accession numbers
The accession numbers for the SCoVs used in this study are Urbani:

Results
To better understand evolutionary relationships between SCoVs isolated in Taiwan and those isolated in other parts of the world, we constructed phylogenetic trees with two different methods using full-length genomic sequences from 45 human (12 Taiwanese) and two civet SCoVs. Tree topologies were consistent for the NJ (Fig. 1a) and Pars (Fig.  1b) methods. Two human SCoV epidemics were identified. The late epidemic SCoVs formed a well-supported monophyletic clade with bootstrap values of 98 and 88 for the NJ and Pars trees, respectively. The early epidemic sequences did not cluster into a monophyletic clade, even though they did clearly differed from those of late epidemic. Fig. 1. Human and civet SCoV phylogenetic trees, produced with the neighbor-joining (NJ) method using full-length (29.7 kb) sequences. Branch bootstrap values from 100 reps: (a) using the SZ3 civet SCoV as a root; (b) a tree produced using the parsimony (Pars) method. All early epidemic SCoVs had Chinese origins: Beijing (BJ01, BJ02, BJ03 and BJ04), Guangzhou (GD01 and GZ50), and Hong Kong (CUHK-W1).
All the Taiwanese SCoVs sequences which associated with nosocomial infection clustered into a monophyletic clade (bootstrap values 75 and 78 for NJ and Pars trees, respectively) within the late epidemic and could be further classified into two epidemic waves. Second wave was a monophyletic clade supported by bootstrap values of 74 and 75 for NJ and Pars tree, respectively, while first wave was not a fully resolved cluster. TWC (from Mr. X's younger brother) did not cluster with three isolates from Amoy Gardens (CUHK-AG03, CUHK-AG02, CUHK-AG01), but did cluster with an isolate (WHU) from Wuhan, China (bootstrap value 90 for NJ tree) (Fig. 1a).
Pairwise comparison methods were used to analyze nucleotide sequence variation within the full-length genomes of 20 human SCoVs (7 from early epidemic and 13 from late epidemic) (Fig. 2). Two civet SCoV sequences (SZ3 and SZ16) were used as references for comparison.  Our results revealed that the highest variation rate was in the 3 0 one-third of the viral genome, especially the nucleotide sequences near the junction between the replicase 1B and spike genes; Orf 3 also had a relatively high sequence variation rate. Amino acid sequences for the S, M, E, and N structural proteins of 45 human SCoVs were compared with those of the SZ-16 civet SCoV (Fig. 3). The S protein was divided into S1 and S2 domains according to the molecular model proposed by Spiga et al. (2003). The S1 domain (N-terminal 17-680 amino acid residues, responsible for receptorbinding) had 18 (2.7%) amino acid differences; the S2 domain (681-1255 amino acid residues) had 11 (1.9%)-a total of 29 (2.3%) differences in the S proteins of 43 SCoVs. The S genes of WHU and ZMY1 contained several nucleotide insertions that interrupted the open reading frames. The amino acid distances of S proteins were 1.3% (16.4/1239) for early epidemic SCoVs and 1.4% (17.2/1239) for late epidemic SCoVs in comparison with civet SCoVs. Intra-group sequence variation for early epidemic was 0.3% (n = 7) and for late epidemic 0.09% (n = 38) ( Table 1). The numbers of amino acid differences were 4 for the E protein (5.3%), 7 for M (3.2%), 4 for N (0.9%), and 11 for Orf 3 (4.0%) (Fig. 3). Amino acid distances among the 45 human SCoVs were 0.18% (0.13/76) for the E protein, 0.75% (1.67/ 221) for M, 0.04% (0.16/422) for N, and 1.53% (4.20/274) for Orf 3 (Table 1 and Fig. 4).
Among the 45 human SCoVs that we analyzed, an isolate (GD01) from Guangdong province China, contained an extra 29-nucleotide fragment. Both WHU and TWC had dinucleotide deletions at the 30th and 31st nucleotides of Orf 10, resulting in a frame shift and premature stop of the putative protein (Fig. 5). In addition, we observed a 5nucleotide deletion at the 32nd nucleotide of Orf 10 in Sin2748; this also resulted in a frame shift and premature translation stop.

Discussion
Both the NJ and Pars trees separated the human SCoVs into two epidemics, even though early epidemic SCoVs failed to cluster into a well-supported monophyletic clade ( Fig. 1a and b). The early epidemic sequences were more closely related than the late epidemic sequences to civet SCoVs; all seven early epidemic SCoVs were from either Fig. 2. Plot analyses were used to compare diversity distributions among genes from 20 human SCoVs. The average genetic distance from the reference genome of civet SCoVs of 20 human SCoVs are plotted over the entire genome of SCoV. Genomic sequences from the SZ3 and SZ16 civet SCoVs were used as references. The X-axis is the nucleotide location of the SARS-CoV genome. The Y-axis is the rate of nucleotide differences between 20 human SCoVs and civet SCoVs. Sequence variation distance plots were generated with a 1000 bp window, 100 bp steps by Simplot program.
Guangdong province or Beijing. Among all the analyzed human SCoVs, GD01 was the only one having an extra 29nucleotide fragment which was also found in the civet SCoVs . Furthermore, the average intragroup amino acid distance for the S gene in early epidemic was higher than for late epidemic (Table 1). We also identified a signature amino acid sequence pattern (amino acid residues 77 and 244; Fig. 6) shared by early epidemic isolates and civet SCoVs. These evidences suggested that late epidemic SCoVs were transmitted from human-tohuman, while certain early epidemic SCoVs (e.g., GD01) might have been transmitted from animals to humans before spreading among various human populations.
Among the Taiwanese SCoVs, our phylogenetic analysis does not support the hypothesis of an epidemiological link between the first and third index cases (Mr. X and Ms. A). According to our NJ tree, TWC (a SCoV isolate from Mr. X's younger brother) clustered with the WHU SCoV from Wuhan, China (bootstrap = 92), while TWC-3 (Ms. A's isolate) clustered with CUHK-AG02 and CUHK-AG03, both of which originated in Hong Kong's Amoy Gardens housing complex. A sequence analysis demonstrated that TWC and WHU had di-nucleotide deletions in Orf 10, resulting in a shift in the open reading frame (Fig. 5). Therefore, even though Mr. X and Ms. A took the same train from Taipei to Taichung, the evidence indicates that Mr. X was not the source of Ms. A's infection; that source has yet to be identified.
As shown in the diversity plot, the S gene and Orf 3 at the junction between the replicase 1B and S genes had a higher number of sequence variations compared to other genomic regions (Fig. 2). This influenced our decision to perform additional sequence comparisons of the S, E, M and N structural genes and Orfs 3 and 10.   The S proteins of coronaviruses have been described as large, type I membrane glycoproteins that are responsible for both the binding of receptors to host cells and membrane fusion Xiao et al., 2003). The type I glycoproteins of coronaviruses, whose trimers resemble typical viral spikes, is transformed into virions through noncovalent interactions with M proteins. Coronavirus S proteins contain two domains (or two subunits, depending on whether or not S is cleaved) (Spiga et al., 2003). The S1 domain contains virus-neutralizing epitopes and the receptor-binding domain (Leparc-Goffart et al., 1998;Sanchez et al., 1999). Xiao et al. (2003) recently localized the SCoV receptor-binding domain (RBD) to amino acid residues 303-537 of the S1 protein. As shown in Fig. 6, we observed seven amino acid differences in the RBD of the S protein, including amino acid residues 311, 344, 360, 442, 479, 487 and 501. If we assume that the RBD is (a) conserved among different SCoVs, including civet SCoVs (Bonavia et al., 2002), and (b) more than 30-50 amino acids in length (Lasky et al., 1987), then it is possible that the RBD can be mapped onto amino acid residues 360-442.


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ICln159 folds into a pleckstrin homology domain-like structure. Interaction with kinases and the splicing factor LSm4.

ICln is a multifunctional protein involved in regulatory mechanisms as different as membrane ion transport and RNA splicing. The protein is water-soluble, and during regulatory volume decrease after cell swelling, it is able to migrate from the cytosol to the cell membrane. Purified, water-soluble ICln is able to insert into lipid bilayers to form ion channels. Here, we show that ICln159, a truncated ICln mutant, which is also able to form ion channels in lipid bilayers, belongs to the pleckstrin homology (PH) domain superfold family of proteins. The ICln PH domain shows unusual properties as it lacks the electrostatic surface polarization seen in classical PH domains. However, similar to many classical PH domain-containing proteins, ICln interacts with protein kinase C, and in addition, interacts with cAMP-dependent protein kinase and cGMP-dependent protein kinase type II but not cGMP-dependent protein kinase type Ibeta. A major phosphorylation site for all three kinases is Ser-45 within the ICln PH domain. Furthermore, ICln159 interacts with LSm4, a protein involved in splicing and mRNA degradation, suggesting that the ICln159 PH domain may serve as a protein-protein interaction platform.

ICln is a small (Ϸ25 kDa), multifunctional protein involved in regulatory mechanisms as different as cell volume regulation and RNA splicing (1,2). Proteins involved in more than one regulatory mechanisms were recently defined as "connector hubs" (3) and play a pivotal role in cell function. Knock-out of such proteins is usually lethal. Accordingly, functional knockout of the ICln protein in mouse or nematode is lethal in the very early stages of development. No vital embryos can be obtained in either animal system (2,4), which suggests a key role of ICln in cell homeostasis.
During a hypotonic challenge, ICln migrates from the cytosol toward the cell membrane, suggesting a role for ICln in cell volume regulation (15). This regulatory mechanism is further substantiated by the finding that heterologous expression of ICln in Xenopus laevis oocytes is followed by the appearance of ion currents (1) resembling those elicited by swelling of mammalian cells (2,16). Furthermore, ICln-specific antibodies (5) or antisense oligodeoxynucleotides (17,18) leading to a specific knock-down of the ICln protein impair regulatory volume decrease (RVD) 1 in native cells. Conversely, overexpression of ICln in mammalian cells increases RVD currents during a hypotonic challenge (2,19,20). In bacteria, overexpression of ICln leads to an improved tolerance to hypotonicity, an effect that can be reversed by the extracellular application of nucleotides (21,22). The extracellular effect of nucleotides was also shown for heterologous expression of ICln in oocytes, and the putative binding site for nucleotides was identified (1,23). The above mentioned findings point toward a channel function of ICln (1). The successful reconstitution of purified ICln in artificial lipid bilayers demonstrated that ICln can indeed form ion conducting channels, the selectivity of which depends on the lipid composition of the membrane (23)(24)(25)(26).
Another well documented function of ICln is its role in splicing. In the cytosol, ICln forms two separate complexes with splicing factors. One complex (6S) contains ICln and the Sm heteromers D1⅐D2, D3⅐B/BЈ and E⅐F⅐G. The other complex is composed of ICln, the arginine methyltransferase PRMT5, MEP-50, and Sm proteins and is termed the methylosome. The current hypothesis on the role of ICln in the splicing process is that ICln sequesters newly synthesized Sm proteins and directs these proteins to the methylosome, a protein complex that methylates Sm and possibly LSm proteins, prior to the assembly of the cytoplasmic UsnRNA core particle by the survival of motor neurons complex (6 -8).
For both functions of ICln, e.g. ion transport as well as splicing, the structure of ICln is of utmost importance to better understand, on a molecular level, the regulatory mechanisms involved. The aim of the present study was to get insight into the protein-protein interaction of ICln based on the structure of its water-soluble form, which seems to connect multiple and different regulatory modules, a concept common for connector hubs in complex protein networks (3). Here, we show the NMR solution structure of ICln 159 , which demonstrates that ICln belongs to the pleckstrin homology (PH) domain superfold family of proteins.
PH domains are highly conserved in regulatory proteins involved in intracellular signaling. The best characterized physiological role of PH domains is to recruit and tether their host proteins to the cell membrane (27). PH domains are also known as substrates for different kinases (27). Indeed, it was shown that ICln can be phosphorylated by a CKI/CKII-like kinase (28). Sequence analysis predicts that ICln could also be phosphorylated by purified protein kinase C (PKC), cAMP-dependent protein kinase (PKA), and cGMP-dependent protein kinase type I␤ or II (PKGI or PKGII). Here, we show that ICln 159 interacts with PKC, PKA and, in addition, with PKGII, but not PKGI. The finding that ICln 159 interacts with LSm proteins, as well as kinases, suggests that the ICln PH domain may serve as connector hub.

MATERIALS AND METHODS
Cloning-Starting from human (Homo sapiens) and dog (Canis canis) cDNA, the open reading frames of full-length LSm4 and ICln, as well as of the different ICln truncations, were amplified by PCR using standard protocols. The PCR products were cloned in-frame into the mammalian expression vectors pECFP-C1, pEYFP-C1, pECFP-N1, pEYFP-N1 (Clontech) to produce fusion proteins suitable for fluorescence resonance energy transfer (FRET). For protein purification, ICln and ICln truncations as well as LSm4 were cloned into the bacterial expression vector pET3-His (23). The primer pairs and restriction sites used for amplification and cloning are given in the Supplemental Material.
Protein Purification-Purification and labeling of ICln and its truncations in E. coli BL21(DE3) for NMR, interaction, and bilayer experiments are described in detail in Refs. 23, 25, and 29. For the purification of hsLSm4, bacterial lysates were cleared by centrifugation and loaded onto a cation exchange column (bed volume, 8 ml, MacroPrep High S, Bio-Rad). After washing with 1 M NaCl in 25 mM K 2 HPO 4 , 1 mM dithiothreitol, 5% glycerol, pH 7.2, bound proteins were eluted by increasing NaCl to 2 M. Fractions containing LSm4 were pooled, concentrated, and applied to a Sephacryl S100 gel filtration column (bed volume 125 ml, Bio-Rad) equilibrated with 25 mM K 2 HPO 4 , 150 mM NaCl, 1 mM dithiothreitol, 5% glycerol, pH 7.2. Fractions containing LSm4 were pooled, concentrated, and stored at Ϫ70°C. Protein-protein interaction assays were performed in gel filtration chromatography equilibration buffer at 4°C.
After the membrane was formed and its stability was assessed, ICln 159 (500 ng/ml) was added to the cis and trans chambers. The experiments were made at 28°C, in a symmetrical solution composed of 100 mM KCl, 5 mM HEPES, pH 8.00. To determine the ion selectivity of reconstituted ICln 159 , we chose a gradient for the ions employed that had a higher salt concentration in the trans chamber (150 mM KCl, 5 mM HEPES, pH 8.00) and a lower concentration in the cis chamber (10 mM KCl, 5 mM HEPES pH 8.00). The chloride gradient (⌬PDCl) was measured after each experiment and used to calculate the pK/pCl value according to the Goldman-Hodgkin-Katz equation. Reversal potentials were determined graphically by interpolation and were normalized to a gradient of 15 (23,25). NMR Analysis-NMR data were acquired at 298 K on Varian Inova 800 and 500 mHz spectrometers equipped with pulse field gradient triple resonance probes (H/N/C). The NMR sample conditions were 1 mM protein, 25 mM K 2 HPO 4 , 150 mM NaCl in 90% H 2 O, 10% 2 H 2 O, pH 7.0. NMR data were processed and analyzed with NMRPipe (30) and NMRView (31). Backbone and side-chain signal assignments as well as relaxation experiments were obtained using standard triple resonance experiments (32). Three bond nitrogen-carbon ( 3 JC␥N) and carbonylcarbon ( 3 JC␥C) couplings were measured by quantitative J methods (33,34). Three-dimensional structures were generated by simulated annealing with the XPLOR-NIH package (35). NOE distance restraints were derived from three-dimensional 15 N/ 13 C-nuclear Overhauser effect spectroscopy-heteronuclear single quantum coherence (150 ms) crosspeaks, which were classified into strong, medium, weak (1.8 -2.2 Å͉1.8 -3.4Å͉1.8 -6Å). Hydrogen bonds within the ␣-helix and between adjacent ␤-strands were inferred from NOE patterns. Backbone torsion angle restraints were obtained from backbone secondary chemical shifts using the TALOS software package (36) and X1 restraints from experimental 3 JC␥N/ 3 JC␥C couplings. The geometric quality of the calculated structures was analyzed using PROCHECK-NMR (37).
In Vitro Phosphorylation-Full-length and mutant ICln (1 g/assay) were phosphorylated in vitro using purified catalytic subunit of PKA, purified PKC (both purchased from Promega), and recombinant Histagged human PKGI or PKGII in a buffer containing 20 mM Tris/HCl (pH ϭ 7.4) and 10 mM MgCl 2 , supplemented with 0.5 mM CaCl 2 , 0.6 g of diolein, and 6 g of phosphatidylserine (PKC), 2 mM ␤-mercaptoethanol (PKA and PKGI or PKGII), or 0.01% Triton X-100 and 20 M cGMP (PKGI or PKGII). Phosphorylation was started by the addition of 5 l of ATP (final concentration 120 M) containing 1 Ci of [␥-32 P]ATP (Amersham Biosciences) and terminated after 30 min (30°C) by the addition of SDS sample mix. Proteins were separated by SDS-PAGE.
Mass Spectrometry-Samples were digested overnight at 37°C with two different enzymes. Digestion with Staphylococcus aureus V8 Protease (Roche Applied Science) was performed in a 25 mM sodium phos- phate buffer (pH 7.8), and digestion with trypsin (Roche Applied Science, sequencing grade) was performed in a 10 mM NH 4 HCO 3 buffer (pH 8.9). Protein digests were analyzed using capillary high pressure liquid chromatography connected on-line to a LCQ ion trap instrument (ThermoFinnigan, San Jose, CA) equipped with a nanospray interface as published previously (38). The nanospray voltage was set at 1.6 kV, and the heated capillary was held at 170°C. Tandem mass spectrometry spectra were searched against the Madin-Darby canine kidney ICln sequence using TurboSEQUEST (BioWorks; ThermoFinnigan) with subsequent manual validation. Phosphorylation (ϩ80 Da) was searched on serine, threonine, and tyrosine residues as variable modification.
FRET-FRET and acceptor photobleaching techniques as well as the normalized FRET (NFRET) calculations employed in this study are described in detail in Ritter et al. (20).
Salts, Chemicals, and Drugs-All salts and chemicals were of pro analysis grade. Lipids were purchased from Avanti Polar Lipids.
Statistical analysis-All values are given as mean Ϯ S.E.. Data were tested for differences in the means by Student's t test after verifying normal distribution and equal variance within the data sets. A statistically significant difference was assumed at p Ͻ 0.05.

RESULTS
The NMR Structure of ICln-As shown in Fig. 1, the fulllength ICln protein from Madin-Darby canine kidney cells con-sists of 235 amino acids (aa) (1). Since this protein is prone to degradation (within days at room temperature), we decided to modify ICln by C-terminal truncation to circumvent problems with proteolysis during NMR data acquisition. Deleting the C-terminal 76 aa leads to an ICln protein comprised of the N-terminal 159 aa, which contains the putative transmembrane ␤-strands (1). This truncated form of ICln (ICln 159 ) proved to be very stable (for more than 1 week at room temperature), is monomeric in solution, and forms functional ion channels in lipid bilayers with a pK/pCl of 21.87 Ϯ 4.2 (n ϭ 12). The selectivity of these channels can, similarly to full-length ICln, be shifted toward chloride after the addition of 2 mM Ca 2ϩ (pK/pCl ϭ 7.86 Ϯ 1.6; n ϭ 7; Supplemental Materials, Supplement 1).
The NMR structure of ICln 159 exhibits a PH domain topology. It consists, as shown in Fig. 2a, of a pair of nearly orthogonal antiparallel ␤-sheets with strands ␤ 2 , ␤ 3 , and ␤ 4 forming one side of the ␤-barrel and strands ␤ 1 , ␤ 5 , ␤ 6 , and ␤ 7 forming the other side of the ␤-barrel (Supplemental Materials, Table  I). Near the C terminus, the ␤-barrel is capped by an ␣-helix that is formed by residues 117-133. The loops between ␤ 5 and ␤ 6 as well as ␤ 6 and ␤ 7 are highly mobile as evidenced by little or no deviation of their shifts from random coil values and the high 15 N T 2 values of the amides (Fig. 2b).
Phosphorylation of ICln by PKA, PKC, and PKGII-In platelets, pleckstrin, the archetypical PH domain protein, is the main substrate for PKC. As shown in Fig. 1, the sequence of ICln contains several putative phosphorylation sites for PKC, PKA, and PKGI or PKGII. Phosphorylation by a CKI/CKII-like kinase was shown by Sanchez-Olea et al. (28) and discussed as a potential regulatory mechanism (40).
Here, we show that ICln can be phosphorylated by PKA, PKC, and PKGII but not by PKGI (Fig. 4a). To pin down possible phosphorylation sites, we selectively mutated Ser-45 (exchanging serine by alanine; S45A) in ICln; the results are summarized in Fig. 4b. In ICln S45A , phosphorylation by PKA is abolished, and phosphorylation by either PKC or PKGII is markedly reduced, demonstrating that Ser-45 is the sole target for PKA and the prime target for PKC as well as PKGII. The serine 45 is located in the ␤ 3 -strand of the ICln PH domain (Fig. 1). To identify further phosphorylation sites of PKGII within the ICln PH domain, we subjected PKGII-phosphorylated ICln 159 to mass spectrometry. We searched for peptides that differ by 80 mass units (mass of a single phosphate group), and by doing so, we identified Ser-2 and Ser-93 as additional PKGII phosphorylation sites of ICln 159 . Interestingly, Ser-93 is located within the mobile loop between strands ␤ 6 and ␤ 7 of the ICln PH domain. No threonine or tyrosine phosphorylation was detected.
PKGII Decreases RVD Channel (RVDC) Activity-RVD is one of the functional modules in which ICln is involved. Since kinases (PKA and PKC) are able to modulate RVDC (41), we tested whether PKGII is also able to modulate endogenous RVDC. RVDC activity was measured in NIH3T3 fibroblasts after reducing the extracellular osmolality by 50 mosM. This maneuver leads to an increase of RVDC currents from 0.03 Ϯ 0.01 nA (n ϭ 9) to 1.04 Ϯ 0.19 nA (n ϭ 9) at a holding potential of ϩ40 mV (Supplemental Materials, Supplement 3). To measure the effect of PKGII on RVDC, we overexpressed PKGII in fibroblasts and tested the PKGII effect, after activation with cGMP, on the endogenous RVDC. The baseline transcription of PKGII in fibroblasts is very low, and fibroblasts are not the prime target for PKGII action (42). PKGII is primarily expressed in cells of the intestinal mucosa and the brain as well as epithelial cells in the kidney (42). For the overexpression of PKGII, we used an internal ribosome entry site construct, which allows the simultaneous expression of PKGII and GFP (as a transfection marker) as two separate proteins. The expression of GFP alone did not significantly alter RVDC currents (from 0.11 Ϯ 0.04 nA (n ϭ 9; isotonic) to 0.91 Ϯ 0.19 nA (n ϭ 9; hypotonic); Supplemental Materials, Supplement 3). The expression of PKGII, however, abolishes inward currents of endogenous RVDC and markedly attenuates currents in the outward direction (reduction from 0.91 Ϯ 0.19 nA (n ϭ 9) to 0.33 Ϯ 0.06 nA (n ϭ 9)), without altering the currents under isotonic conditions (Fig. 5a).
As described earlier, ICln is a substrate for PKGII; however, the reduced activity of RVDC followed by the expression and activation of PKGII could also be the result of the phosphorylation of a protein not related to ICln. To test for this hypothesis, we tried to determine the phosphorylation of ICln in PKGIIexpressing cells. We were not able to detect phosphorylated ICln under these conditions (data not shown), most likely because the membrane fraction of ICln is, as reported, very small (5), and therefore, the expected fraction of PKGII phosphorylated ICln probably below the sensitivity of our assay. Therefore, we used another approach to test whether ICln is able to interact with PKGII under in vivo conditions. As shown in Fig.  5b, ICln and PKGII indeed interact at the level of the cell ICln Binds to LSm4, a Component of the Splicing and RNA Degradation Machinery-Using the yeast two-hybrid system, we were able to identify ICln partner proteins involved in another functional module, namely RNA splicing, i.e. Sm proteins (B/BЈ, D1, D2, D3) as well as LSm proteins (LSm2 (SmX) and LSm4) ((10), and data not shown). Here, we show that ICln as well as ICln 159 are able to bind to LSm4 in vitro (Fig. 6, a-e).
The LSm4 protein has a molecular mass of 16.5 kDa and a calculated pI of 10.12 and is thus positively charged at physiological pH. In native PAGE, purified LSm4 does therefore not migrate into the gel. Consequently, LSm4 can only migrate into the gel, if it forms a complex with purified ICln 159 (Fig. 6b, lane  1) or full-length ICln (Fig. 6b, lane 3), both of which are negatively charged (pI 4.17 and pI 4.05, respectively) and thus able to enter the gel and migrate toward the anode (Fig. 6b, lanes  2 and 4). The results obtained with native PAGE were verified by gel filtration chromatography (Fig. 6, a, c, and e) and Western blotting (not shown) using LSm4-specific antibodies.
The interaction between ICln and LSm4 observed in vitro was also tested under in vivo conditions. For these experiments, fusion proteins of LSm4 and ICln with ECFP as well as EYFP were constructed for FRET measurements. For these experiments, the donor ECFP protein was fused to the N terminus of ICln (ECFP-ICln), and the acceptor EYFP protein was fused to the N terminus of LSm4 (EYFP-LSm4). In HEK293T cells co-transfected with ECFP-ICln and EYFP-LSm4, acceptor (EYFP-LSm4) photo-bleaching leads to an increase in donor (ECFP-ICln) fluorescence, demonstrating FRET and thus interaction between ICln and LSm4 in living cells (Fig. 6f). FRET can be detected in the cytosol and in the immediate vicinity of the cell membrane (Fig. 6f, inset). Exchanging donor and acceptor on the respective proteins did not alter the result in quantity and quality (Fig. 6f). However, fusing the fluorescing proteins (donor and acceptor) to the C termini of ICln, or both LSm4 and ICln, annihilated the FRET signal (Fig. 6f).
To identify the binding site for LSm4 on ICln, we performed gel filtration chromatography and native PAGE using LSm4 and two different ICln mutants. As shown in Fig. 6, c and d, using the ICln ⌬loop mutant did not prevent complex formation; however, deleting further C-terminal 25 aa from ICln 159 , leading to ICln 134 , did prevent LSm4 complex formation, suggesting that these 25 aa comprise the binding site for LSm4 (Fig. 6d). DISCUSSION ICln is a multifunctional protein involved in several different regulatory modules within the living cell. Ion transport is one of these modules since ICln is able to form ion channels by directly inserting from its water-soluble form into the lipid membrane. Such a mode for channel insertion is well known for water-soluble bacterial toxin channels (43). Further functional modules are the regulation of RNA splicing by the interaction of ICln with splicing factors (6 -8, 10, 40) and the regulation of the cytoskeleton by ICln (5,(11)(12)(13). The ability of ICln to interact with more than one regulatory module suggests that the water-soluble form of ICln acts as a connector hub (3) for different regulatory mechanisms. The aim of the present study was to identify the structure of the water-soluble form, i.e. the connector hub form of ICln. Based on the structure of ICln, we aimed to identify binding sites for partner proteins such as LSm4 or phosphorylation sites of different kinases. This experimental framework provides an important guidepost for further studies aimed to elucidate the regulation of protein networks in which ICln is involved.
In this study, we determined the structure of a deletion mutant of ICln, i.e. ICln 159 , which is water-soluble, able to form ion channels in lipid bilayers, binds to LSm4, and serves as a substrate for PKA, PKC, and PKGII. The reason for using ICln 159 was the instable nature of full-length ICln when used for the NMR analysis.
ICln 159 folds into a PH domain-like structure. PH domains are a large family of structurally homologous protein domains of moderate to low sequence homology and are found in many proteins involved in signal transduction (44 -46). The canonical structure of PH domains is a core seven-stranded ␤-sandwich capped by a C-terminal ␣-helix and three major interstrand loops that could serve as putative binding sites for proteinprotein interactions (46). As described here, the ␤ 6 -␤ 7 loop of ICln is particularly mobile and long when compared with other PH domains. Usually, this loop is built by 4 -5 aa. However, PH domains tolerate large insertions without effect on the core structure, e.g. one of the two PH motifs of phospholipase C␥ is split at the ␤ 3 -␤ 4 loop by three Src homology domains leading to an insertion of 258 aa (47). Accordingly, deletion of 15 aa within the ␤ 6 -␤ 7 loop did not alter the structure of ICln 159 , demonstrating that the length of the ␤ 6 -␤ 7 loop is not affecting the core structure.
Scrutinizing the aa sequence of ICln 159 for possible sites of phosphorylation and analyzing putative target serines and threonines for accessibility on the structural model reveals three sites of interest, i.e. Thr-34, Ser-45, and Ser-115. As shown by single point mutagenesis, Ser-45 is the main target for PKA and PKC, as well as PKGII. It is noteworthy that in contrast to other substrates of PKGII in vivo, i.e. cystic fibrosis transmembrane conductance regulator (CFTR) (48,49), ICln is able to discriminate between PKGI and PKGII in vitro (Fig.  4a). Three PKGII phosphorylation sites, Ser-2, Ser-45, and Ser-93, were identified by single point mutagenesis or mass spectrometry. As shown in Fig. 4b, Ser-45 is the main phosphorylation site for PKGII as well as PKC. Interestingly, Ser-93 is located exactly within the mobile loop connecting strands ␤ 6 and ␤ 7 , and preliminary experiments indicate that this loop is important for current formation in lipid bilayers. 2 Therefore, it is intriguing to speculate that phosphorylation of Ser-93 could modulate the ICln-induced current. This scenario is speculative; however, FRET experiments reported in this study suggest a interaction between ICln and PKGII at the cell membrane, in vivo. Additional experiments need to be done to clarify this issue.
ICln 159 binds to LSm4, which is most likely methylated by PRMT5 that also methylates Sm proteins (9,50,51). PRMT5 possibly binds to AD3 at the C terminus of ICln (51). The experiments summarized in this study show that the binding of ICln to LSm4 involves the second acidic domain (AD2; Fig. 1) situated immediately after the capping ␣-helix of the ICln PH domain, but not AD1, located in the ␤ 6 -␤ 7 loop of the ICln PH domain. It is interesting to note that within this acidic domain, there is a serine at position 142, which is phosphorylated by cytosolic extracts (40). This phosphorylation may potentially regulate Sm/LSm binding to ICln. However, this hypothesis needs to be tested.
In conclusion, the water-soluble form of ICln is a PH domainlike structure with an overall negative surface potential. The protein is a potential target for PKA, PKC, and PKGII phos- phorylation and binds strongly to LSm4, a positively charged protein that is part of the spliceosome and of the RNA degradation machinery. As summarized in Fig. 7, water-soluble ICln acts as a protein-protein interaction platform involved in different regulatory modules, which is a key feature of connector hubs in complex protein networks (3). By solving the structure of ICln 159 , by determining the binding site of ICln for LSm4, and by demonstrating that ICln can be phosphorylated by PKC, PKA, and PKGII on Ser-45 as well as Ser-2 and Ser-93 (PKGII), we provide a valuable guidepost for the systematic exploration of the involvement of ICln in such diverse regulatory mechanisms as cell volume regulation, RNA splicing, RNA degradation, and cytoskeletal reorganization.