Google Health, the new service offered by Google is now online (via bbgm, Life as a Healthcare CIO, GTO). This service helps users to store, organize and share their health profile and medical records, to use a variety of health-related online services and to search for medical information. Understandably, Google places great emphasis on data security and confidentiality. In this regard, I thought it might be worth highlighting several recent and thought-provoking discussions around the issues of data privacy and participative medical investigations.

In a provocative editorial (Bains, 2007, see also Nature Medicine News article), William Bains advocates that collectives of individuals, so-called 'Biomedical Mutual Organization', could organize themselves on a voluntary and self-funded basis to conduct clinical trials that would rely on extensive self-experimentation, data sharing and pooling of analytical resources. This proposal challenges the classical view that those who conduct a clinical trial should avoid conflicts of interest with respect to the outcome of the trial. On the other hand, Bains argues, this system would allow more innovative and radical trials to be performed, given that the subjects of the trial would have increased trust in the research process (being their own trial managers) and, hopefully, a more accurate perception of the risk/benefit balance involved.

Another radical proposal is the concept of 'open-consent' as currently applied within George Church's Personal Genome Project (Church, 2005). Jeantine Lunshof, George Church and colleagues highlight in a recent review (Lunshof et al, 2008) the limitations of the current definitions of genetic privacy and confidentiality in view of the rapid advances in the fields of human genetics and personal genomics. In particular, the creation of large database interlinking individual genome-wide genotypes to extensive phenotypic profiles will make de-identification of such datasets increasingly difficult if not impossible (Lowrance and Collins, 2007). Under these conditions, it appears that the promise of absolute anonymity and confidentiality of private data is becoming unrealistic. Church and colleagues affirm that an 'open-consent' policy would avoid making such false promises and would therefore represent a more realistic way to formulate an adequately informed consent when accepting to participate to a human genomic research study.

At last month's ESF Conference on Systems Biology, Hiroaki Kitano discussed the potential of multi-component, combinatorial therapies (see also Kitano, 2007). He introduced the tentative idea of an 'Open Pharma' strategy, which would attempt to exploit beneficial synergistic effects that may result from combined administration of cheap generic drugs. He envisions that this type of approach could ultimately lead the way to novel and hopefully more affordable therapeutic strategies, which would provide a potential alternative to the current single-target proprietary drug paradigm.

Observing the launch of Google Health within the context of this series of rather revolutionary proposals, it is tempting to imagine for a moment what would result from large-scale self-experimentation with multi-component generic drug cocktails combined with web-enabled data sharing under some form of open-consent... Will 'Participative Open Pharma' be our future?

Research highlight by Kazuharu Arakawa and Masaru Tomita, Institute for Advanced Biosciences, Keio University, Japan

Gene duplications and mutations are central driving forces in the evolution of genomes. Genomes must be robust to such changes in order to be evolvable, and many studies have probed genome robustness using systematic gene knockouts or overexpression experiments. In a recent paper, Isalan et al. (2008) took a new approach to test the robustness of Escherichia coli gene circuitry by reconstructing gene duplication events by shuffling the promoter-ORF pairs for about 300 transcription factors and introducing 598 recombined pairs one-by-one into E. coli to rewire its transcriptional network. Surprisingly, ~95% of such additions are robustly tolerated, and some networks even exhibit greater fitness under various selection pressures. Moreover, the study shows that, in contrast to naive expectations, the introduction of positive or negative feedback loops has little effect on the protein expression levels of regulated ORFs.

Since radical rewiring of the gene circuitry appears to have only a limited impact on expression levels, this work suggests that gene regulatory networks are highly dynamic and underscores the potential importance of post-transcriptional mechanisms for the robustness of transcriptional regulation. Moreover, this work illustrates the fundamental robustness and evolvability of gene regulatory networks, which is reassuring news for synthetic biology.

Isalan M, Lemerle C, Michalodimitrakis K, Horn C, Beltrao P, Raineri E, Garriga-Canut M, Serrano L (2008) Evolvability and hierarchy in rewired bacterial gene networks. Nature 452:840

Two rather contrasting videos on synthetic biology this month. In the first videocast, released by TED, Craig Venter exposes his grand vision of synthetic genomics. He insists on the notion of 'combinatorial genomics', that will combine the power of large scale DNA synthesis ('robots that can make a million chromosomes a day') with a database of 20 million genes, 'the design components of the future'. This approach, a pragmatic mixture of rational function-oriented design and empirical large-scale selection, is envisioned to prepare a modern 'Cambrian explosion' of new synthetic species. It is good to see Craig Venter laughing when announcing casually the 'modest goal of replacing the entire petro-chemical industry'. In any case, Craig Venter appears to be more concerned that the technology may not develop sufficiently rapidly to match the urgency and scale of the major ecological and medical challenges faced by our planet than by potential threats represented by harmful biohacking and bioterror.

The second video, admittedly less entertaining, is a recording of the recent deliberations of the National Science Advisory Board for Biosecurity (NSABB). In his presentation entitled 'Assessing Biosecurity Concerns Related to Synthetic Biology', David Relman presents some preliminary findings and recommendations of the Working Group on Synthetic Genomics (jump to 1hr:34min:37sec). It is interesting to see that no consensus definition of synthetic biology exists among the various practitioners of the field, who all use different blends of the typical bottom-up engineering approach assembling circuits from standard components and top-down strategy, based on the modifications of existing genomes. Beyond the lack of definition, the current ability to predict biological functions from sequence (eg virulence) remains very limited complicating the possibility of realistic risk assessment. Finally, the development of synthetic biology can be seen as an extension of the success of 'kit-based' molecular biology, which facilitates access of these technologies to groups outside the traditional Life Sciences communities and institutions, making the mission of oversight, outreach and eduction more challenging. David Relman also clearly emphasizes the importance of not discouraging the enthusiasm directed towards potentially beneficial research and applications by overzealous oversight and regulations.

The intersection between the two talks above was perhaps made when the question of virulence was raised (jump to 1hr:59min:35sec). The fraction of pathogenic agents is very small compared to the number of existing species, a point also made by Craig Venter, and the rate of appearance of new pathogens is low. The idea was then raised as whether it would be possible to roughly estimate the risk of creating synthetic pathogens by calculating the likelihood that the amount of natural recombination responsible for the emergence of new pathogens 'in the wild' could be matched by an equivalent amount of experimental recombination in the laboratory. In other words, is there any way to estimate the probability that new forms of virulence could emerge from the announced synthetic 'Cambrian explosion'?

Research highlight by Doron Lancet, Crown Human Genome Center, Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel

Living cells are typically asymmetric, having tens of thousands different biopolymers (proteins and polynucleotides), but merely <1000 types of small molecules, such as amino acids and lipids. An exception is certain plant cells that harbor members of ~40,000 strong group of low molecular weight terpenoids, often displaying a complex compositional balance essential for plant growth and survival (Aharoni et al, 2005). Understanding the intricacies of biosynthesis and interconversion of such unusual cellular components appears to require the full power of Systems Biology. In a recent paper, Rios-Estepa et al (2008) harness a systems approach, including iterative cycles of mathematical modeling and experimental testing, to help elucidate the metabolic dynamics of the terpenoid universe.

Specifically they ask how plants vary their monoterpene profiles in response to environmental stress – changing levels of illumination. A highlight of their results is that the variation of terpene metabolic fluxes is mediated by specific events in which members of the terpenoid repertoire exert a regulatory effect on terpene biosynthesis enzymes. Rewardingly, this is predicted by a computer simulation and subsequently verified by experiment. The broader conclusion, applicable to all living organisms, is that as the power of computing grows, it will become possible to make increasingly specific and accurate predictions, that will allow both a better global understanding and the successful engineering of cellular networks.

Aharoni A, Jongsma MA, Bouwmeester HJ (2005) Volatile science? Metabolic engineering of terpenoids in plants. Trends Plant Sci. 10:594-602.

Rios-Estepa R, Turner GW, Lee JM, Croteau RB, Lange BM (2008) A systems biology approach identifies the biochemical mechanisms regulating monoterpenoid essential oil composition in peppermint. Proc Natl Acad Sci U S A. 105:2818-2823

Research highlight by Jeongah Yoon and Thomas S. Deisboeck, Massachusetts General Hospital, Charlestown, MA

Targeting receptor tyrosine kinases (RTKs) is currently thought to be a promising anti-cancer strategy (Baselga, 2006). However, clinical trials with RTK inhibitors demonstrated that some solid tumors are sensitive to these drugs while others are not. For instance, only a subset of non small cell lung cancer (NSCLC) tumors with EGFR-activating mutations seems to respond to EGFR inhibitors (Lynch et al, 2004).

The recent study by Guo et al (2008) aims to shed more light on the causes for such selective drug sensitivity by investigating the downstream signaling pathways of several NSCLC cell lines and a gastric cancer cell line. Using a quantitative global proteomic analysis (PhosphoScan-SILAC) they analyzed the EGFR and c-Met networks, treated with the EGFR inhibitor gefitinib and the c-Met inhibitor Su11274, respectively.

The results show a dramatic decrease in EGFR phosphorylation from 5- to 200-fold after gefitinib treatment as well as a reduction of some adaptor proteins (e.g., Her3, Gab1, and Shc1), adhesion and cytoskeletal proteins. Furthermore, a c-Met-driven gastric cancer cell line demonstrated sensitivity to the c-Met inhibitor, Su11274. The authors observed that the inhibited EGFR and c-Met signaling networks share a number of molecular components which underscores that amplified c-Met can drive the activity of (mutated) EGFR and vice versa. In both cases, the targeted kinase is positioned on top of the hierarchical signaling network and thus controls downstream signaling.

In conclusion, this interesting study suggests that there is a common sub-cellular signaling module that processes drug sensitivity and that the effect of an anti-RTK therapeutic compound is maximized when the targeted kinase uniquely controls the downstream signaling networks.

Baselga J (2006) Targeting tyrosine kinases in cancer: the second wave. Science 312:1175-8

Guo A, Villén J, Kornhauser J, Lee KA, Stokes MP, Rikova K, Possemato A, Nardone J, Innocenti G, Wetzel R, Wang Y, MacNeill J, Mitchell J, Gygi SP, Rush J, Polakiewicz RD, Comb MJ (2008) Signaling networks assembled by oncogenic EGFR and c-Met. Proc Natl Acad Sci U S A. 105:692-7

Lynch TJ, Bell DW, Sordella R, Gurubhagavatula S, Okimoto RA, Brannigan BW, Harris PL, Haserlat SM, Supko JG, Haluska FG, Louis DN, Christiani DC, Settleman J, Haber DA (2004) Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med. 350:2129-39

In a very recent lecture (see full video from NIH VideoCasting) given for the NIH Systems Biology Special Interest Group, Trey Ideker presents a great overview of the various strategies his group has been developing in the recent years in order to integrate multiple types of large scale datasets. While one of the most pervasive 'meme' about high-throughput measurement is that they are "notoriously unreliable" (see Hakes et al, 2008, for a recent example), Trey beautifully illustrates how predictive computational models and novel biological insights can be generated by sophisticated data integration strategies. Three types of applications are presented in his talk:

1. mapping of transcriptional response pathways
2. functional mapping of protein complexes
3. disease diagnosis and stratification

In the last section, Trey presents the study recently published in Molecular Systems Biology (Chuang et al, 2007, video: 00hr:39min:15sec) where the information provided by microarray expression profiling is superposed to a protein-protein physical interaction network to identify 'subnetwork' biomarkers that classify metastatic vs non-metastatic breast tumors.

How to make biology easy to engineer and what are the consequences of success? Drew Endy exposes his views on these key issues in the field of synthetic biology in a video released in the last issue of EDGE.

As a teaser, here are a few quotes from this interview, summarizing in a nutshell his opinion on the current priorities of the field and its future development:

Engineers hate complexity. I hate emergent properties. I like simplicity. I don't want the plane I take tomorrow to have some emergent property while it's flying.

How do you manage the information going into a DNA synthesizer so that you can construct some useful object that'll help you do genetics? [...] I think George Church and Craig Venter have a lot to contribute to it, which will be terrific. It will be part of synthetic biology, but it will be synthetic biology impacting science, which is the worst case scenario for synthetic biology.

Five years from now, we may have just begun to make some good progress on reliable functional composition of standard biological parts. Nobody knows how expensive solving that problem will be, but because biology works there's plenty of existence proofs. [...] If I had to guess, I'd say we'll have a collection of tens of thousands of genetic objects that support reliable functional composition between ten and 15 years from now.

Drew Endy also mentions the need to develop an "ownership sharing and innovation framework" that will be appropriate to this pure engineering approach to synthetic biology. A related question might be to find the appropriate publishing instruments that would provide suitable incentives and (micro)attribution mechanisms for those who will embark in contributing, probably often incrementally, to the projected "tens of thousands of genetic objects". One idea could be here to adopt a two-layered system inspired from the one proposed for "Human Variome Microattribution Reviews". In such a system, a "Part Browser" would provide the list and number of all articles/database entries referring to a specific part while partner journals would commission high-level Part/Device Review articles to highlight a "family" of parts or device that might be of particular relevance to the community. Would this make sense (eventually)? How did the electronic engineering field deal with this problem in its early days?

Research highlight by Frank C.P. Holstege, Department of Physiological Chemistry, University Medical Center Utrecht, the Netherlands.

For eukaryotes, it is widely thought that transcription is primarily regulated through recruitment of the essential machinery to transcription start-sites. Previous hints challenging this paradigm have been confirmed by recent analyses showing that transcription regulation of a large number of genes actually occurs after recruitment. Mechanistically, such studies have gone furthest in Drosophila melanogaster (Muse et al, 2007; Zeitlinger et al, 2007). Here, conservative estimates indicate that more than 10% of genes are regulated through promoter-proximal pausing. On such genes, RNA polymerase II is recruited and initiates transcription, but then pauses around 50 bp downstream of the transcription start-site where it awaits further signals to resume elongation and complete transcription proper. These observations tie in with other observations made in yeast (Radonjic et al, 2005), embryonic stem cells (Bernstein et al, 2006; Lee et al, 2006) and differentiated mammalian cells (Guenther et al, 2007). There are numerous implications to these findings. For example, the widely assumed link between the presence of gene-specific transcription activators and full-length transcription appears to be much looser than expected. These results also underscore the importance of testing established models on a genome-wide scale. Indeed, other such surveys (Birney et al, 2007), indicate that to understand transcription, we may need to take into account even more surprises – such as the presence of ten times more start-sites than protein-coding genes and overlapping transcription units, etc… – than the post-recruitment mechanisms demonstrated in Drosophila.

Bernstein BE, Mikkelsen TS, Xie X, Kamal M, Huebert DJ, Cuff J, Fry B, Meissner A, Wernig M, Plath K, et al. (2006) A bivalent chromatin structure marks key developmental genes in embryonic stem cells. Cell 125: 315-326

Birney E, Stamatoyannopoulos JA, Dutta A, Guigo R, Gingeras TR, Margulies EH, Weng Z, Snyder M, Dermitzakis ET, Thurman RE, et al. (2007) Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 447: 799-816

Guenther MG, Levine SS, Boyer LA, Jaenisch R, and Young RA (2007) A chromatin landmark and transcription initiation at most promoters in human cells. Cell 130: 77-88

Lee TI, Jenner RG, Boyer LA, Guenther MG, Levine SS, Kumar RM, Chevalier B, Johnstone SE, Cole MF, Isono K, et al. (2006) Control of developmental regulators by Polycomb in human embryonic stem cells. Cell 125: 301-313

Muse GW, Gilchrist DA, Nechaev S, Shah R, Parker JS, Grissom SF, Zeitlinger J, and Adelman K (2007) RNA polymerase is poised for activation across the genome. Nat Genet 39: 1507-1511

Radonjic M, Andrau JC, Lijnzaad P, Kemmeren P, Kockelkorn TT, van Leenen D, van Berkum NL, and Holstege FC (2005) Genome-wide analyses reveal RNA polymerase II located upstream of genes poised for rapid response upon S. cerevisiae stationary phase exit. Mol Cell 18: 171-183

Zeitlinger J, Stark A, Kellis M, Hong JW, Nechaev S, Adelman K, Levine M, and Young RA (2007) RNA polymerase stalling at developmental control genes in the Drosophila melanogaster embryo. Nat Genet 39: 1512-1516

A few weeks ago, Jason Kelly explained in his post how Itaya and colleagues (2007) assembled the complete 135 kb rice chloroplast circular genome starting from a collection of 5-6 kb fragments and using sequential in vivo homologous recombination in Bacillus subtilis. Now, Hamilton Smith, Craig Venter and colleagues have achieved the assembly of a complete 583 kb Mycoplasma genitalium genome ("JCVI-1.0", Gibson et al, 2008). The starting fragments were of similar length, 4-5 kb fragments with 80-360 kb overlaps, albeit synthesized chemically rather than by PCR. In contrast to Itaya et al, Ham Smith's team used in vitro recombination (using T4 pol digestion/annealing/Taq pol repair and ligation) in a 3 step hierarchical assembly process and completed the fourth step, the assembly of 4 quarter genomes, using in vivo homologous recombination in yeast (TAR cloning, Larionov et al, 1996). The use of yeast for the last step might be a little worrying, given the high recombination activity in yeast and the propensity for large constructs to rearrange (I used to work with YACs to construct mouse transgenes and I can still feel the pain... but I don't know about the stability of circular TAR clones). In any case, it worked! One final clone was sequenced (7X coverage) and, remarkably, was shown to match exactly the sequence designed!

This impressive technical feat may eventually have tremendous consequences when combined with the transformation procedure ("genome transplantation", ) Venter and colleagues reported last year (Lartigue et al, 2007). As Dawkins noted at the Digital Life Design meeting in Munich a few days ago (see video below for some excerpts of his discussion with Craig Venter and the transcript in Edge), "genetics has become a branch of information technology".

JCVI-1.0 has obviously not been assembled "from scratch". In fact, beside some "watermark" sequences inserted to distinguish the synthetic genome from the native one, the fact that its sequence is a remarkably accurate copy of M. genitalium genome is probably one of the major achievements of the study. The technology for the synthesis of very long DNA of arbitrary sequence (in principle...) is thus progressing at an impressive pace. But writing a genome is not (yet) equivalent to designing it. Exciting (and hard) work remains to be done to bridge this gap and to improve our understanding of how biological functions can be created by assembling genes into a synthetic genome and developing the tools that will make this process rational and efficient, a challenge the synthetic biology community is eager to tackle (see The BioBricks Foundation)...

(via Scintilla)

The article on "Probiotics modulation of mammalian metabolism" published this week in Molecular Systems Biology by Jeremy Nicholson and colleagues (Martin at al, 2008) has attracted some attention (read the nice summary in Science News) in some (very) popular media (here, here, here and here).

In this follow-up study of the paper published last year (Martin et al, 2007), the team lead by Jeremy Nicholson, in collaboration with Nestlé, demonstrates clear physiological effects of oral probiotics administration on mice harbouring a humanized microbiome. The effects are intricate: both the host flora and metabolism are altered. By analyzing metabolite pools in several compartments (liver, blood, urine, feces, gut), and following in parallel the host microbiota, patterns of correlations between microbial species and metabolites start to be visible and reveal the probiotics-induced modulation of the microbial-mammalian interactions. But the actual paper is really just next door (synopsis), so have a look...

How will these results translate to humans? What will be the best way to influence our microbiome? Drugs or yoghurt? These are fascinating questions and the understanding of how our physiology depends on the microbial flora could have profound consequences, particularly in these times when we seem to be in a "rush to gene-based solutions to all our problems" (Wilson, 2007). Will personal genomics have to ultimately develop into personal metagenomics to include our "extended" microbial genome?

Even if I usually prefer to resist the temptation of a self-promoting section in this blog, I find the attention of the media for this topic interesting (despite the usual variable accuracy of newspaper reports) because it points to an area where systems biology provides insights into topics of immediate interest to the general public.

The NIH has recently started its Human Microbiome Project. In this context, this study also underscores the importance of developing model systems and tools to manipulate the microbiome and to analyze the incredibly dense and intricate interactions that connect host and microbial species. A field where top-down systems biology seems indeed a very pragmatic and promising approach.

A controversy seems to be brewing over some recent theories and quantitative analyses addressing the fundamental question of how the Bicoid morphogen gradient is established and decoded in early Drosophila embryos. The transcription factor Bicoid controls the anterior-posterior patterning of the developing embryo. It is translated from maternal mRNA localized at the anterior pole of the egg and its graded distribution activates, in a concentration-dependent manner, the expression of gap genes, thus determining their spatial domain of expression. Synthesis from a localized source combined with diffusion and uniform degradation of the Bicoid morphogen provides one of the simplest models to explain the approximately exponential shape of its gradient. While, historically, patterning has been thought to rely on the gradient at its steady state – that is when synthesis, transport and degradation processes balance each other – the question arose as to whether steady-state can be reached rapidly enough in the quickly developing embryo (Lander, 2007).

In February last year, Naama Barkai and colleagues published a study (Bergmann et al, 2007) in which they propose that the gradient would in fact be interpreted before it has reached its steady-state, when the gradient is still "moving". Experimental evidence for a dynamic evolution of Bcd profile between cleavage cycle 11 and 12 is provided using a reporter gene driven by bicoid-binding sites. These authors further show that a pre-steady-state model implies a reduced sensitivity of the gradient readout to variations in the production of morphogen at its source. One biologically relevant example of this robustness is the observation that the domain of expression of hunchback, a Bicoid target gene, shifts much less in embryos from mothers with altered bicoid gene dosage than would be predicted by a steady-state model.

A few months later, Thomas Gregor and colleagues published two papers (Gregor et al, 2007a, 2007b) reporting a detailed analysis of the profile and dynamics of the Bicoid gradient. Quantitative in vivo imaging of a transgenic bicoid-eGFP reporter revealed several paradoxes. While a stable gradient of nuclear Bicoid is quickly established (within 90min, approx. cleavage cycle 9), the (local) diffusion coefficient of Bicoid, as deduced from photobleaching experiments, appears to be far too small (D=0.3 μm²/s, much less than expected from previous estimations made by injecting labeled dextran molecules) to be compatible with such a rapid establishment of the (long-range) gradient by diffusion alone. These experiments further show that nuclear Bicoid is under a highly dynamic nuclocytoplasmic equilibrium, pointing to a fundamental role for the nucleus in gradient establishment and stability. Finally, the precision with which the Bicoid gradient is transformed into Hunchback expression (see illustration, after Gregor et al 2007b) is estimated to be around 10%. This remarkable level of precision would not only be close to the physical limits of the system, but also strikingly matches the accuracy required to detect changes of Bicoid expression between adjacent cells (10%, equivalent to a difference of only 70 Bicoid molecules per nucleus) and the level of reproducibility of the absolute morphogen concentration from embryo to embryo (10% as well).

In a Correspondence published last week, Bergmann and colleagues (2008) dispute these interpretations and claim that a "reanalysis of their [Gregor et al's] data demonstrates that their findings are consistent with the well-accepted paradigm of diffusion-based patterning and provides further support for the notion that the Bicoid profile is decoded prior to reaching its steady state". Thus, according to these authors, constant nuclear Bicoid levels are not indicative of steady-state of the gradient itself given that cytoplasmic levels may still be changing. The small diffusion coefficient of Bicoid would then be an additional argument in favor of the necessity of a pre-steady-state decoding mechanism. If this is the case, the differences in Bicoid levels between adjascent cells would be much bigger at cleavage cycle 9 (50% instead of 10% at cycle 14), thus resolving the paradox of the high precision of the hunchback response.

In their response (Bialek et al, 2008), Gregor and colleagues reply that if cells would make a decision by reading Bicoid concentration at cycle 9, the boundary between expression domains would be 5 cells wide at stage 14 (=\sqrt{2^14/2^9}), while in reality it is only a single cell wide. While they agree that the overall gradient might not be at steady-state at these early stages, they argue that the stability of nuclear Bicoid levels is functionally highly relevant given that Bicoid is a transcription factor. Finally, they also point out that the deduced local diffusion constant is so small that it is in fact incompatible with observing any Bicoid in the middle of the embryo in the first place, thus suggesting the existence of additional mechanisms to explain establishment of the gradient at the scale of the entire embryo. These and some additional arguments lead Bialek et al to conclude that "the small values of the diffusion constant for Bcd we reported are superficially consistent with their model, but the model provides no basis for understanding any of our observations."

Mmmmh... not an easy one. Those who have additional insights into these subtle but fascinating questions, please let us know!

I highly recommend to visit the NIH VideoCasting page, which hosts many interesting video/podcasts. Even if I realize that this is a bit old according to the blogosphere time scale, I would like to point to this one: "The Future: Consumer Health Information Technology", featuring talks given at a NCI-sponsored meeting on Dec 10, 2007 by Adam Bosworth (formerly "Google Health architect", now starting his own company Keas), Bern Shen (Intel) and Bill Crounse (Microsoft).

In his introduction to the meeting, Bradford Hesse (NCI) colorfully summarizes one of the main concepts exposed by the speakers (the video is very long, so I give some pointers: 0h16min43sec) by comparing the future of healthcare to...an "IKEA flat pack": patients will progressively be empowered to assemble their own care from home, like they would build a piece of (cheap) furniture.

Adam Bosworth (0h25min53sec) presents his very pragmatic vision of how IT could concretely help healthcare (0h39min07sec): a) help the consumer to own and control his personal health data, and this already for very simple basic information; b) provide tools for doctors so that they can deliver personalized care as easily as producing a spreadsheet; c) develop tools for researchers to facilitate the design and implementation of new protocols and clinical trials.

Bill Crounse (Microsoft's other Bill...1h14min30sec) sees 5 major current trends that will increasingly challenge the healthcare system and call for IT solutions (1h26min22sec): a) increasing personal responsibility ("the end of health insurance"); b) progressive "retailization" of healthcare services (eg appearance of "retail minute clinics"); c) commoditization of healthcare providers; d) globalization of access to information (through the web of course); e) globalization of healthcare services. I recommend his little funny anecdote on the high-tech GPS wireless-connected plumber (1h25min30sec) who appears to better equipped than any practicing physician...

The speakers also all insist on the need for massive data integration promoted by the interoperability of formats and coding information, themes that probably sound familiar to many systems biologists.

Toward the end of his talk (1h35min00sec), Bill Crounse shows a short "science-fiction" movie on Microsoft's vision of the future of healthcare: a world full of credit-card sized tablet PCs, touch screens and many other very exciting gadgets (I love gadgets!). But I can't help missing a bit the warmth of human-to-human interactions within this jungle of virtual consultations, retail clinics, remote controlled metabolic parameters, etc... and I didn't quite see in that movie that the doctor would spend more time with his patient or the daughter with her sick Grandma. But this may of course only reflect some old-fashioned side of my temperament...

by Jason Kelly, MIT

Costs for de novo synthesis of DNA fragments (<10kb) are decreasing rapidly, and challenges now lie in the assembly of these fragments into ever-larger sequences. One of the main challenges is the fragility of long DNA sequences during the in vitro steps associated with traditional methods for assembling DNA. In a recent publication, Itaya et al (2007) describe a method for assembling 4-6kb DNA fragments in vivo via incorporation in the B. subtilis genome. They demonstrated this homologous recombination-based method by assembling the 134.5 kb rice chloroplast genome from 31 smaller fragments.

The process involves:

1. Cloning alternating, overlapping 4-6kb DNA fragments into one of two custom vectors with different selective markers.
2. Mixing these vectors sequentially with competent B. subtilis and taking advantage of native homologous recombination to add each fragment to a growing chain within the B. subtilis genome.
3. Each new fragment replaces the selective marker added by the previous fragment, allowing the chaining process to continue by switching the antibiotic selection at each step.
4. Removal of the fully assembled DNA construct from the genome and re-circularization via previously described methods (Tsuge and Itaya, 2001).

Due to it’s reliance on homologous recombination, this method faces challenges in assembling sequences with repeated regions. The rice chloroplast genome contains two such repeated regions (21kb each). The authors demonstrate a work-around for this problem by first using their method to assemble three blocks (72.9, 36.7, and 34.4 kb) of the rice chloroplast genome without internal repeating regions, then assembling these blocks as the final construction steps.

This work-around also demonstrates one method for parallelization of their sequential process. Parallelization provides the speedup necessary for construction of larger DNA segments or genomes. Each addition of a 6kb fragment takes a couple days, so building a synthetic E. coli genome (4.6Mb) through purely serial addition of small fragments would take over four years. A parallelized assembly process combined with Itaya’s previous work (Itaya et al, 2005) incorporating a 3.5Mb natural genome into B. subtilis brings synthetic E. coli-sized genomes closer to reality – will be exciting to watch where this goes.

Note from Thomas: welcome to Jason's new blog, Free Genes

By James CW Locke, California Institute of Technology

A new Science paper from the lab of Alex Webb (Dodd et al, Science, 2007) represents an important step forward in plant circadian research (read also commentary by Imaizumi et al, Science, 2007). The circadian (24 h) clock controls processes throughout the day and night in most organisms, and in plants is involved in multiple pathways including photosynthesis, leaf movement and floral opening. The circadian clock has evolved to consist of multiple interlocking transcriptional feedback loops (at least in eukaryotes), which generate the 24 h rhythm even under constant environmental conditions.

Using a series of elegant experiments Dodd et al uncover a new level of complexity to the plant clock. They first show that cytosolic signaling molecule cyclic adenosine diphosphate ribose (cADPR) is regulated by the clock and is responsible for the previously reported circadian rhythm in intracellular calcium. They go on to show that disruption of cADPR signaling by addition of nicotinamide causes a strong period lengthening of the clock. Thus they have discovered an additional feedback loop (see drawing), and revealed a new class of circadian clock components: cytosolic signaling molecules.

It is also of note that Dodd et al use an existing mathematical model of the Arabidopsis clock (Locke et al, Mol Syst Biol, 2005) to frame the expected effects of their predicted feedback loop. A large amount of systems modeling work has recently been carried out on the clock (summarized in Ueda, Mol Syst Biol, 2006). It is exciting to see how the Arabidopsis clock community has responded to this work. In some cases the models have been used to simulate experiments and to test putative mechanisms (Dodd et al, Science, 2007, Martin-Tryon et al, Plant Physiol, 2007). I believe for systems biology approaches to succeed it is crucial that models must be made easily accessible to experimentalists, which is the case in this field (eg Circadian Modelling). I look forward to seeing the next iteration of the plant circadian clock model, perhaps from the Webb lab including the cADPR feedback loop.

The wave of personal genomics is progressing rapidly. A string of four papers appeared recently (Porreca et al, 2007, Albert et al, 2007, Okou et al 2007, Hodges et al, 2007) reporting on microarrray-based technologies that enable the enrichment of selected genomic fragments in a single massively multiplexed reaction, thus greatly facilitating subsequent resequencing of pre-defined portions of the human genome (eg all coding exons). These technologies are expected to reduce dramatically the cost of targeted resequencing of individual genomes.

On the commercial front, deCODE and 23andMe have launched their personal genome service offering genome-wide SNPs profiling for a little less than $1,000 (NYT articles: Nicholas Wade, Amy Harmon, or Wired, ScienceRoll, Sandra, DNA and You).

The chips used by 23andMe are the "Illumina HumanHap550+ BeadChip, which reads more than 550,000 SNPs (single nucleotide polymorphisms) plus a 23andMe custom-designed set that analyzes more than 30,000 additional SNPs." The profile provided by deCODEme includes "over one million variants across the genome."

So what do you think?