Environment, population, and biology: a short history of modern epidemiology

Since its origin in the 19th century, epidemiology has faced an internal tension between an approach oriented toward biology and the study of mechanisms, and an approach oriented toward populations and their interactions with the environment. Initially, this tension took the form of an opposition between microbiology and statistics. We describe the early roots of the quantitative approach to health and disease and several historical examples of the above tension. The search for the causes of pellagra exemplifies our thesis. In Italy, where pellagra was endemic, contrasting opinions coexisted between the hypothesis of contaminated maize, supported by Cesare Lombroso, and the hypothesis of a prevailing role of poverty and poor nutrition. In the United States, Joseph Goldberger found no evidence for the hypothesis of contaminated maize or for a microbiological agent, but recognized the central role of nutrition. The "cure" Goldberger proposed was land reform, but he continued studying the disease from a mechanistic point of view; shortly after his death, niacin deficiency was identified as the cause of pellagra. The tension between mechanistic and population-based studies is still present within epidemiology and is in fact essential for the success of the discipline.     

Quantitative biology: where modern biology meets physical sciences

Quantitative methods and approaches have been playing an increasingly important role in cell biology in recent years. They involve making accurate measurements to test a predefined hypothesis in order to compare experimental data with predictions generated by theoretical models, an approach that has benefited physicists for decades. Building quantitative models in experimental biology not only has led to discoveries of counterintuitive phenomena but has also opened up novel research directions. To make the biological sciences more quantitative, we believe a two-pronged approach needs to be taken. First, graduate training needs to be revamped to ensure biology students are adequately trained in physical and mathematical sciences and vice versa. Second, students of both the biological and the physical sciences need to be provided adequate opportunities for hands-on engagement with the methods and approaches necessary to be able to work at the intersection of the biological and physical sciences. We present the annual Physiology Course organized at the Marine Biological Laboratory (Woods Hole, MA) as a case study for a hands-on training program that gives young scientists the opportunity not only to acquire the tools of quantitative biology but also to develop the necessary thought processes that will enable them to bridge the gap between these disciplines.What does a mathematician looking at bacterial division under a microscope have in common with a biologist programming a stochastic simulation of microtubule growth? For one, both can be found at the Physiology Course at the Marine Biological Laboratory (MBL) in Woods Hole, MA, which brings together graduate students and young postdocs who have a passion for quantitative biology. Students enter the course with a wide array of scientific backgrounds, including chemistry, molecular biology, mathematics, and theoretical physics. Although at first hesitant to step outside their comfort zones, students leave the course confident and courageous in their abilities to work across traditional academic boundaries. Having experienced this transformation ourselves as participants in the 2014 Physiology Course, we wanted to share some of our insights and how they have influenced our perspectives on the present challenges and exciting future of quantitative cell biology.“When you cannot express [what you are speaking about] in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely, in your thoughts, advanced to the stage of science.” The need for quantification in the life sciences could not have been better worded than it is in this quote from Lord Kelvin. One of the key take-home messages from the course has been the crucial need for advancement of quantitative cell biology, which uses accurate measurements to refine a hypothesis, with the aim of comparing experimental data with predictions generated by theoretical models. We strongly believe that quantitative approaches not only aid in better addressing existing biological questions but also enable the formulation of new ones.The present time is particularly ripe for implementing quantitative approaches in cell biology, due to the wealth of data available and the depth of control we now have over many experimental systems. In the past 20 years, we have sequenced the human genome, broken the diffraction limit in microscopy, and begun to explore the possibilities of the micron-scaled experiments with microfluidics. With these tools in hand, the means to obtain quantitative data are not limited to a select few model systems; this level of experimental detail allows us to craft theoretical models that not only fit the data but have real predictive power. We can then return to our respective experimental systems with new hypotheses and interrogate them anew, reaping the benefits of an approach that has benefited physicists for decades.Building quantitative models in biology has been a powerful approach that has often revealed counterintuitive phenomena and insights while at the same time leading to novel research directions. This is of particular importance today, as experiments are becoming increasingly expensive and are rapidly accumulating vast amounts of data. It is now possible to perform “virtual” preliminary experiments in silico using quantitative models and pre-existing data and only then move to “real” laboratory experiments to test the developed hypotheses. Researchers trained this way can perform more focused experiments instead of adopting the traditional exploratory mode in the lab, saving both time and resources. However, we recognize that a majority of biology graduates have not been rigorously trained in the mathematical and physical sciences. Similarly, many physics graduates often remember their introductory biology classes simply for the rote memorization of protein names and signaling pathways, leading to the wrong assumption that biology is all about remembering three-letter abbreviations such as WNT, MYC, and so on. This can often create a misleading picture of biology.These challenges could be overcome by finding a common language between biologists, physicists, and mathematicians. A simple example of this is the word “model.” The same word can mean very different things to scientists depending upon their training: to a physicist it refers to quantitative visualization of a process via certain well-defined mathematical parameters; a biologist, on the other hand, might use the word to refer to a schematic depiction (also called a cartoon) of a biochemical reaction. We aim to reduce this gap between biological and physical sciences and bring these two communities together.One way to train young scientists in such an approach is to provide opportunities for hands-on engagement with the methods and thought processes necessary to partake in both fields. The MBL Physiology Course is an excellent case study for a training program that gives young scientists the building blocks and community necessary for success in bridging quantitative/physical sciences and biology. The course starts with a weeklong boot camp designed to bring students of different backgrounds up to speed on basic tools in quantitative biology. Students purify proteins, program in MATLAB, and build microscopes. The most important skill that biologists acquire is not simply learning how to write lines of MATLAB code, but rather phrasing biological phenomena in mathematical terms through equations and simulations. Building confocal microscopes and optical tweezers on a bare optical table creates trust in the tools we depend on to acquire quantitative data. Physicists, on the other hand, learn to purify motor proteins like kinesins and dyneins from native sources (squid), in the process coming face-to-face with the natural context of the biological questions that they are addressing.This interdisciplinary approach helps students from diverse backgrounds develop a common language. After the boot camp, students work together on three 2-week-long research projects under the guidance of leading scientists. Projects range from studying the spatial organization of the human oral microbiome and observing the development of the Caenorhabditis elegans embryo all the way to performing computational simulations of cytoskeletal polymers. By working together in a highly informal and stimulating environment, physicists learn to appreciate biological problems and biologists begin to see biological phenomena in a new light as a result of the novel physical tools and methodologies they learn from their peers. As an example, course participants Rikki Garner and Daniel Feliciano successfully collaborated to study how competition between two highly processive microtubule motors that work in opposition controls microtubule length. While Rikki (mentored by Jané Kondev) tackled the question theoretically using a random walk model, Daniel, under the mentorship of Joe Howard, carried out the experimental measurements via an in vitro assay to test Rikki''s predictions. Other examples of quantitative and biological expertise coming together to address biological questions include studying the displacement and transport of proteins at the interface between cells and synthetic supported lipid bilayers (Figure 1), observing and quantifying the cytoplasmic streaming as well as the filter-feeding flow vortices in the giant single-celled organism Stentor coeruleus (Figure 2), and imaging the spatial organization of complex oral microbial communities (Figure 3).Open in a separate windowFIGURE 1:Proteins are organized based on size at the membrane interface. The membrane interface between a cell and a supported lipid bilayer (SLB) was formed by the interaction of synthetic adhesion molecules, one protein (bound to the membrane via a His-tag) and another protein that interacts and binds with the membrane-bound protein (expressed in the S2 cells). Note that the long noninteracting protein (21 nm, magenta colored) but not the shorter noninteracting protein (8 nm, magenta colored), which is bigger than the synthetic interacting dimer (16 nm, red–green colored) is excluded from the cell–SLB interface. Both of these noninteracting proteins are bound to the SLB and do not interact with the cell. Scale bar: 10 μm. (Prepared by L.Z. and Nan Hyung Hong under the guidance of Matt Bakalar, Eva Schmid, and Dan Fletcher.)Open in a separate windowFIGURE 2:Stentor coeruleus is a giant single-celled organism that feeds by creating flow vortices in water and directing prey into its oral opening using this flow. (A) Maximum intensity projection of time-lapse images showing flow fields in the feeding flow generated by S. coeruleus. The flow is generated by the coordinated ciliary beating of the mouth cilia. (B) Flow velocity and flow directions were quantified by the particle image velocimetry method. The circularity of flow has also been indicated—the blue cloud around the oral cilia indicates clockwise flow, and red indicates anticlockwise flow. Scale bar: 100 μm. (Prepared by S.S. under the guidance of Mark Slabodnick, Tatyana Makushok, and Wallace Marshall in collaboration with Jack Costello, Providence College.)Open in a separate windowFIGURE 3:Spatial organization of complex microbial communities in an oral plaque sample taken from a volunteer as seen by combinatorial labeling and spectral imaging–fluorescent in situ hybridization (CLASI-FISH). Microbes seen here are Corynebacterium (pink), Neisseriaceae (blue), Fusobacterium (green), Pasteurellaceae (yellow), Streptococcus (cyan), and Actinomyces (red). (Prepared by Bryan Weinstein, Lishibanya Mohapatra, and Matti Gralka under the guidance of Blair Rossetti, Jessica Mark Welch, and Gary Borisy.)An invaluable aspect of the course is the informal nature of the interaction. There are a wide variety of morning seminar speakers, and in the question-and-answer sessions following the talks, the speakers discuss not only science but also the successes and failures they experienced while moving across the boundaries of biological and physical sciences. The interactive and collaborative nature of the course encourages students to not just learn from one another but to actually teach one another. “Chalk talks” and interactions happen spontaneously and are the strongest indication of the richness of the intellectual exchange among members of the community. Prime examples in the 2014 course are the chalk talks on Python (Bryan Weinstein), Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) cloning (Dan Dickinson), and the basics of microfluidics (Sindy Tang).Although we have benefited immensely from this interdisciplinary course, we understand that it might not be feasible for all graduate students to participate in such courses. Nevertheless, we believe that the scientific community should work together to replicate elsewhere, at least partially, the strengths of this course to allow students to benefit from this approach. Students should be encouraged to host and attend seminars from speakers with diverse backgrounds, which will expose them to research areas different from their own. Biology students should also be exposed to mathematical and statistical instruction early in their research careers, preferably at the undergraduate level, to enable them to build strong foundations. Students should also be encouraged to participate in short-term, low-pressure interdisciplinary collaborations to broaden their understanding and initiate interactions with other fields. Short summer/winter schools—for example, the physical biology of the cell courses at Cold Spring Harbor and the International Centre for Theoretical Physics (Italy)–International Centre for Theoretical Sciences (India) Winter School on Quantitative Systems Biology, 2013, in Bangalore, India—can serve as the perfect stage for this.In conclusion, we expect that quantitative approaches will be indispensable for better addressing biological questions in the future. Our experience is that combining traditional experimental cell biology with quantitative thinking leads to hitherto unknown scientifically rich domains, and we ourselves have found this exploratory journey to be both achievable and rewarding. Although bridging the gap may appear to be difficult at times, it is extremely satisfying when accomplished, and doing it within a highly motivated and supportive community is what makes the connection possible and extremely useful.     

Immunome Research

Immunology research has been transformed in the post-genomics era, with high throughput molecular biology and information technologies taking an increasingly central role. This has led to the development of a new area of science termed "Immunomics", that encompasses genomic, high throughput and bioinformatic approaches to immunology. In recognition of the increasing importance of this field, Immunome Research is a new Open Access, online journal, that will publish cutting edge research across the field of Immunomics. Immunome Research will publish a wide range of article types including specialty immunology databases, immunology database tools, immunome epitope research, epitope analysis tools, high-throughput technologies (gene sequencing, microarrays, proteomics), white papers, mathematical and theoretical models, and prediction tools. Immunome Research is the official journal of the International Immunomics Society (IIMMS).     

One hundred years of pleiotropy: a retrospective

Pleiotropy is defined as the phenomenon in which a single locus affects two or more distinct phenotypic traits. The term was formally introduced into the literature by the German geneticist Ludwig Plate in 1910, 100 years ago. Pleiotropy has had an important influence on the fields of physiological and medical genetics as well as on evolutionary biology. Different approaches to the study of pleiotropy have led to incongruence in the way that it is perceived and discussed among researchers in these fields. Furthermore, our understanding of the term has changed quite a bit since 1910, particularly in light of modern molecular data. This review traces the history of the term "pleiotropy" and reevaluates its current place in the field of genetics.     

Quantitative genetics,version 3.0: where have we gone since 1987 and where are we headed?

The last 20 years since the previous World Congress have seen tremendous advancements in quantitative genetics, in large part due to the advancements in genomics, computation, and statistics. One central theme of this last 20 years has been the exploitation of the vast harvest of molecular markers—examples include QTL and association mapping, marker-assisted selection and introgression, scans for loci under selection, and methods to infer degree of coancestry, population membership, and past demographic history. One consequence of this harvest is that phenotyping, rather than genotyping, is now the bottleneck in molecular quantitative genetics studies. Equally important have been advances in statistics, many developed to effectively use this treasure trove of markers. Computational improvements in statistics, and in particular Markov Chain Monte Carlo (MCMC) methods, have facilitated many of these methods, as have significantly improved computational abilities for mixed models. Indeed, one could argue that mixed models have had at least as great an impact in quantitative genetics as have molecular markers. A final important theme over the past 20 years has been the fusion of population and quantitative genetics, in particular the importance of coalescence theory with its applications for association mapping, scans for loci under selection, and estimation of the demography history of a population. What are the future directions of the field? While obviously important surprises await us, the general trend seems to be moving into higher and higher dimensional traits and, in general, dimensional considerations. We have methods to deal with infinite-dimensional traits indexed by a single variable (such as a trait varying over time), but the future will require us to treat much more complex objects, such as infinite-dimensional traits indexed over several variables and with graphs and dynamical networks. A second important direction is the interfacing of quantitative genetics with physiological and developmental models as a step towards both the gene–phenotype map as well as predicting the effects of environmental changes. The high-dimensional objects we will need to consider almost certainly have most of their variation residing on a lower (likely much lower) dimensional subspace, and how to treat these constraints will be an important area of future research. Conversely, the univariate traits we currently deal with are themselves projections of more complex structures onto a lower dimensional space, and simply treating these as univariate traits can result in serious errors in understanding their selection and biology. As a field, our future is quite bright. We have new tools and techniques, and (most importantly) new talent with an exciting international group of vibrant young investigators who have received their degrees since the last Congress. One cloud for concern, however, has been the replacement at many universities of plant and animal breeders with plant and animal molecular biologists. Molecular tools are now an integral part of breeding, but breeding is not an integral part of molecular biology.     

At the dawn of a new revolution in life sciences

In a recently published article Sydney Brenner argued that the most relevant scientific revolution in biology at his time was the breakthrough of the role of "information" in biology.The fundamental concept that integrates this new biological "information" with matter and energy is the universal Turing machine and von Neumann's self-reproducing machines.In this article we demonstrate that in contrast to Turing/von Neumann machines living cells can really reproduce themselves.Additionally current knowledge on the roles of noncoding RNAs indicates a radical violation of the central dogma of molecular biology and opens the way to a new revolution in life sciences.     

2009 Society for Medical Anthropology Conference: Changing Anthropology,Changing Society

Fifty years after the founding of the field of medical anthropology, the Society for Medical Anthropology of the American Anthropological Association held its first independent meeting on September 24-27, 2009, at Yale University.Fifty years after the founding of the field of medical anthropology, the Society for Medical Anthropology of the American Anthropological Association held its first independent meeting on September 24-27, 2009, at Yale University in New Haven, Connecticut. The conference, Medical Anthropology at the Intersections, drew an international audience of more than 1,000 scholars.In her opening remarks, program Chair Marcia Inhorn noted that medical anthropology has been interdisciplinary since its inception. This assertion was supported at a roundtable discussion, Founding Medical Anthropology and the Society for Medical Anthropology, which featured four of the field’s founders.Asked to identify the factors that led to the development of medical anthropology, the panelists emphasized the role of changes in the practice and landscape of medicine in the late 1950s and early 1960s in the United States. According to Hazel Weidman, who helped spearhead the Society for Medical Anthropology, medical personnel sought social scientists’ guidance in the new clinical environments created by the increasing involvement of U.S. physicians in global development work and by the community-oriented approach to mental health encouraged by the Community Mental Health Act of 1963. The novel inclusion of lifestyle as a determinant of health at this time also played a role, according to Clifford Barnett. Norman Scotch, author of a 1963 review that had helped define medical anthropology as a field, noted that physicians at the time were very interested in the possible applications of the social sciences to medicine [1,2]. Joan Ablon recalled that this emphasis on application led some academic anthropologists to dismiss the medical anthropologist as a “handmaiden to the doctors.” Despite such resistance, interest in medical anthropology as a sub-field was clearly growing among anthropologists. When Weidman helped organize the first gathering of medical anthropologists at an anthropology conference in 1967, attendance was twice what was expected. Panel organizer Alan Harwood noted that the Society for Medical Anthropology transformed its newsletter into a professional journal, Medical Anthropology Quarterly, in 1983. According to Inhorn, the society has 1,300 members today.For the panelists, medical anthropology’s potential for application makes it a compelling scholarly pursuit. As Barnett stated in explaining his decision to work in anthropology: “If you know how a society works, you can change it.”     

Evolvability as the proper focus of evolutionary developmental biology

SUMMARY Research conducted under the label of evolutionary developmental biology has tended to revolve around a few central issues such as modularity, integration, and canalization. Yet, as the field has grown, it has become increasingly difficult to define in terms of its central question and relation to broader evolutionary concerns. We argue that these central issues of evo-devo gain their currency from connections to a central question that defines the field, and we propose that this central question is about the nature of evolvability. However, not all research currently carried out under the label of "evo-devo" speaks to this focal concern. The aim of this article is therefore to argue for a precise formulation of evolutionary developmental biology's core question.     

Global radiation oncology waybill

Background/aim

Radiation oncology covers many different fields of knowledge and skills. Indeed, this medical specialty links physics, biology, research, and formation as well as surgical and clinical procedures and even rehabilitation and aesthetics. The current socio-economic situation and professional competences affect the development and future or this specialty. The aim of this article was to analyze and highlight the underlying pillars and foundations of radiation oncology, indicating the steps implicated in the future developments or competences of each.

Methods

This study has collected data from the literature and includes highlights from discussions carried out during the XVII Congress of the Spanish Society of Radiation Oncology (SEOR) held in Vigo in June, 2013. Most of the aspects and domains of radiation oncology were analyzed, achieving recommendations for the many skills and knowledge related to physics, biology, research, and formation as well as surgical and clinical procedures and even supportive care and management.

Results

Considering the data from the literature and the discussions of the XVII SEOR Meeting, the “waybill” for the forthcoming years has been described in this article including all the aspects related to the needs of radiation oncology.

Conclusions

Professional competences affect the development and future of this specialty. All the types of radio-modulation are competences of radiation oncologists. On the other hand, the pillars of Radiation Oncology are based on experience and research in every area of Radiation Oncology.     

Editors' Note

Winner of the Southwood Prize 2002
Each year, each of the Journals of the British Ecological Society offers a prize for the best paper by a young author. In our case, the award is named in honour of Prof. Sir Richard Southwood. The editors of the Journal of Applied Ecology are delighted to announce that the Southwood Prize for 2002 has been awarded to Dr Stephanie Kramer-Schadt for her co-paper with E. Revilla, T. Wiegand, F. Knauer, P. Kaczensky, U. Breitenmoser, L. Bufka, J. Cerveny, P. Koubek, T. Huber, C. Stanisa & L. Trepl on: 'Assessing the suitability of central European landscapes for the re-introduction of Eurasian lynx' ( Journal of Applied Ecology , 39 , 189–203).
The editors particularly liked the strong conservation biology theme of this work, and also the way it addressed a very real management problem by blending state-of-the-art methods for modelling with a substantial set of real field data.
It is particularly appropriate that the prize this year should be won by a young scientist from the European mainland, from where there is a continued growth of high-quality submissions to the Journal.     

A brief history of the Japan Society for Cell Biology

The Japan Society for Cell Biology (JSCB) was first founded in 1950 as the Japan Society for Cellular Chemistry under the vigorous leadership of Seizo Katsunuma, in collaboration with Shigeyasu Amano and Satimaru Seno. The Society was provisionally named as above simply because cell biology had not yet been coined at that time in Japan, although in prospect and reality the Society was in fact for the purpose of pursuing cell biology. Later in 1964, the Society was properly renamed as the Japan Society for Cell Biology. After this renaming, the JSCB made great efforts to adapt itself to the rapid progress being made in cell biology. For this purpose the Society's constitution was created in 1966 and revised in 1969. According to the revised constitution, the President, Executive Committee and Councils were to be determined by ballot vote. The style of the annual meetings was gradually modified to incorporate general oral and poster presentations in addition to Symposia (1969-1974). The publication of annual periodicals in Japanese called Symposia of the Japan Society for Cellular Chemistry (1951-1967) and later Symposia of the Japan Society for Cell Biology (1968-1974) was replaced by a new international journal called Cell Structure and Function initiated in 1975. This reformation made it possible for the Society to participate in the Science Council of Japan in 1975 and finally in 1993 to acquire its own study section of Cell Biology with grants-in-aid from the Ministry of Education and Science, Japan. The JSCB hosted the 3rd International Congress on Cell Biology (ICCB) in 1984 and the 3rd Asian-Pacific Organization for Cell Biology (APOCB) Congress in 1998, thus contributing to the international advancement of cell biology. Now the membership of JSCB stands at approximately 1,800 and the number of presentations per meeting is 300 to 400 annually. Although a good number of interesting and important findings in cell biology have been reported from Japan, the general academic activity of the JSCB is far less than one might expect. This is simply due the fact that academic activity in the field of cell biology in Japan is divided among several other related societies such as the Japan Society for Molecular Biology and the Japan Society for Developmental Biology, among others.     

An expanding role for cell biologists in drug discovery and pharmacology

The profound challenges facing clinicians, who must prescribe drugs in the face of dramatic variability in response, and the pharmaceutical industry, which must develop new drugs despite ever-rising costs, represent opportunities for cell biologists interested in rethinking the conceptual basis of pharmacology and drug discovery. Much better understanding is required of the quantitative behaviors of networks targeted by drugs in cells, tissues, and organisms. Cell biologists interested in these topics should learn more about the basic structure of drug development campaigns and hone their quantitative and programming skills. A world of conceptual challenges and engaging industry–academic collaborations awaits, all with the promise of delivering real benefit to patients and strained healthcare systems.Four decades of molecular and cellular biology has fundamentally improved our understanding of human disease, but this undeniable revolution has had less impact than hoped on human health, particularly in the area of discovery and use of therapeutic drugs. The missing link between basic science and useful therapeutics is the quantitative, multifactorial understanding of networks that operate within and between cells and of the changes that drugs induce in these networks (Berger and Iyengar, 2009 ). Contributing to this understanding of drugs and network dynamics represents a significant opportunity for cell biologists interested in careers in industry and for academic scientists seeking industrial collaborations. Success in such “translational” research is not simply a matter of applying known concepts to practical problems; interesting new ideas and science are required (Loscalzo and Barabasi, 2011 ). Fifty years ago, pharmacology and pathophysiology provided cell biologists with many fundamental research problems, and there is every reason to believe this will also be true in the future.Insufficient understanding of pathological and therapeutic mechanisms at a cellular level has contributed to the growing difficulty of bringing new drugs to market. Even when drugs win approval, it is rare that we can predict which patients will benefit from them. As a result, patients have too few treatment options, many serious illnesses remain difficult to treat, and the cost of new medicines is too high (often at the limit of what healthcare systems can support). High-throughput “-omic” approaches have been hailed as a means to understand disease and develop new drugs, but an outstanding opportunity exists for fundamental contributions from cell biologists. A central feature of cell biology is its emphasis on applying diverse conceptual and analytical approaches to biological processes that are inherently multifactorial. This is in contrast to “-omic” approaches, in which the focus is usually on one type of data collected in volume (gene sequences being one example).The role of cell biology in unraveling disease mechanisms is well established, but the value of cell biology in drug development is less well appreciated. Cell and molecular biologists currently play a role during the earliest preclinical stages of drug development in the identification and evaluation of potential drug targets (Figure 1). However, it is increasingly apparent that existing procedures for qualifying targets are inadequate, and this manifests itself as frequent and expensive late-stage failures of efficacy (typically during phase II and III clinical studies (Paul et al., 2010 ). To overcome this problem, we require a much better understanding of the functions of target proteins within the context of cellular networks in normal and diseased cells, both in culture and in the organism (“network biology”). Opportunities exist for cell biologists to help define optimal therapeutic strategies (e.g., aiding in the choice between using a recombinant antibody or small molecule) and to ascertain exposure/response relationships in tissues. Cell biologists also have an important role to play in understanding acquired resistance. A lack of durable responses is the bane of many recently approved targeted drugs. Finally, in diseases such as cancer, we have many plausible targets (the Akt kinase, for example), but it is not clear how to inhibit the target without causing excessive toxicity. It is also unclear why only a subset of patients responds to even the most potent and selective inhibitors. In our opinion, many drugs fail because cell biology is ignored during the later stages of drug development, when selecting indications and drug combinations and determining dosing schedules are the key tasks.Open in a separate windowFIGURE 1:Traditional and emerging roles for cell biologists in drug development and pharmacology. Traditionally, cell biologists have worked on the earliest phases of drug discovery, during the identification and validation of targets. However, by expanding their horizons and adding new skills, cell biologists can become well-suited to other roles later in development, roles in which the stakes are higher and sophisticated understanding of the underlying biology less common. Some of these fields are traditional (e.g., pharmacokinetics and pharmacodynamics [PK/PD]; black) and others are newly emerging (e.g., systems pharmacology; red).Cell biology also has an important role to play in discerning the precise mechanisms of action of existing drugs; it is a remarkable fact that we understand very few drug responses in mechanistic detail. This is as true of the latest generations of targeted therapeutics (many of which aim for selective inhibition of disease-specific mutants) as for older drugs that constitute the mainstay of standard-of-care therapy. The challenge lies less in the interaction between a drug and its intended target than in the consequences of target inhibition for cellular phenotype. This is particularly true when we consider genetic variation from one patient to the next and from one cell to the next within a single patient (particularly with diseases such as cancer). Cellular responses to the microtubule inhibitor and anticancer drug Taxol are an excellent example. Despite being an “old-fashioned” cytotoxic drug, Taxol and its various derivatives are a mainstay of contemporary cancer care, and more patients have probably benefited from taxanes than from all the targeted anticancer drugs combined (Ni Chonghaile et al., 2011 ). Understanding responses to taxanes at a cellular level has also been central to understanding the biology of the spindle assembly checkpoint and mitosis in general. Over the past two decades, checkpoint pathways have been identified and studied in many organisms, and we now understand in detail how processes such as mitotic catastrophe cause cell death (Mitchison, 2012 ). Remarkably, however, the factors that determine whether a cell lives or dies when exposed to Taxol differ dramatically between cultured cells and xenografted tumors (never mind real human tumors); progress through mitosis is always required in culture, but apparently not in the mouse (Orth et al., 2011 ). Understanding this difference represents a fascinating problem in cell biology likely to reveal how cell-autonomous processes, such as mitosis, interact with factors from the local environment in controlling cell fate. Such understanding could also have a real and immediate impact on cancer care.Over the past decade, the success of classical antimitotic chemotherapeutics, such as Taxol, has given rise to efforts to develop other antimitotic agents. For example, drugs that target spindle motors promised to combine the therapeutic antimitotic effects of Taxol, while minimizing neuropathy (motors such as Eg5 are not expressed in neurons [ Huszar et al., 2009 ]). Despite a massive effort by multiple companies, these drugs have proven disappointing in the clinic, as have many drugs that target mitotic kinases. It is now clear that inhibiting mitosis in cancer cells simply does not have the effects we have assumed for the past 50 years, and those antimitotic drugs that do work must do something fundamentally more. Working this out is likely to advance our understanding of the complexities of cell division in humans and animals. However, given the time pressures in industry, there is little opportunity to pursue “failed” drugs, and academic cell biologists have largely ignored problems such as the mechanisms of cell killing by antimitotic agents in real tumors. We must adopt a more holistic and physiological perspective in which we admit that detailed mechanistic understanding is required not only in model organisms and HeLa cells, but also in myriad normal and diseased tissues that have low mitotic index, unusual forms of endo-replication, and complex interactions with neighboring cells. New programs sponsored by the National Center for Advancing Translational Sciences promise to provide some support for this type of research (Allison, 2012 ).More generally, while we all recognize that the “one gene–one disease” paradigm is insufficient for understanding human disease and for selecting patients who will respond to therapy, an effective alternative remains to be developed. Even when the multiplicity of factors involved in a particular disease can be discerned, this understanding does not necessarily reveal how to develop a treatment or cure. For therapy, we must elucidate not only the nature of the initial insult (e.g., a cancer-causing mutation) but also the operation of biological networks that attempt to compensate for the insult (to reestablish homeostasis) and variation in network properties from one individual to the next. It is also important that we identify and understand factors that determine the concentrations and biodistribution of drugs in patients with diverse genotypes. This, in turn, requires a multiscale, network-based approach involving systemic and quantitative study of biological processes at the cellular, tissue, and organismal levels and of the effects of drugs on these processes—precisely the areas in which cell biology has much to contribute.Despite these opportunities, several factors stand in the way of a greater role for cell biologists in drug discovery and development. The first is an unfamiliar vocabulary. We are repeatedly amazed by postdocs who have decided they want to pursue a career in biotechnology or the pharmaceutical industry but who have not spent the time to learn the basics of the drug discovery process from preclinical development to phased clinical trials. Anyone interested in an industrial career should stay abreast of the lively and interesting debates about the best ways to structure and evaluate trials (Kelloff and Sigman, 2012 ). An industrial career usually requires writing more but shorter reports than an academic career, and familiarity with the language of drug discovery makes report writing much easier. A career in industry also benefits from knowledge of the diverse scientific, medical, and business factors that determine success in a drug development campaign. At the same time, it is important to note that some key drug discovery concepts, such as “target identification” or “target qualification,” are widely used but elusive. They imply that the key task is identifying (or cloning) a specific target protein and then screening for agonists and antagonists. As mentioned above, the current challenge increasingly involves understanding targets in the context of biological networks, homeostatic processes, and pathophysiological mechanisms (Wang et al., 2012 ). This implies a more nuanced and holistic approach to understanding the ways the targets and drugs interact (Chene, 2012 ).Many cell biologists in industry find themselves involved in the development or evaluation of assays, particularly for high-throughput screening. Evaluating such screens requires basic understanding of statistics and the trade-offs between false-positive and false-negative results (Atkinson and Lalonde, 2007 ). If high-content screening by imaging is involved, then it is necessary to develop and apply machine vision approaches. Unfortunately, many cell biologists are insufficiently trained in basic statistics, and they have poor programming skills. In our experience, this can be a significant impediment to employment in industry that can be overcome by taking courses in probability and statistics and by gaining practical experience with MatLab or languages such as Python and R. Particularly in biotech, learning the rudiments of intellectual property law can also be a real asset, since it makes it easier to spot patentable inventions.Even the largest drug companies have come to doubt their ability to pursue development projects all the way from target identification to drug approval. It is widely believed that more frequent and effective collaborations between industry and academe are part of the solution (Rubin and Gilliland, 2012 ). This obviously represents a significant opportunity for academic cell biologists. However, the days in which companies were willing to shower academic institutions with generous and unrestricted financial support are long gone. It is now necessary to develop research programs that revolve around concrete goals and deliverables. In our experience, this can be an exciting process for academics accustomed to the conservatism of federal grants, since industry is often willing to pursue ideas that are risky and innovative. Moreover, we have rarely found the perceived difference between applied and basic research to be a significant issue. However, very different expectations over the duration of projects are a major challenge. Industry typically works on 12- to 18-month time lines and academe on a schedule that is at least twice as long. In our experience, even the most effective industry–academic projects tend to underdeliver over the first 18 months, and then only prove their worth in subsequent years. Industry must be more sensitive to the fact that starting a new project in an academic setting means recruiting a new student or postdoc and that there is no way for such an individual to be trained and to succeed with only 18 months of support. However, academics must learn to accommodate the real need for industrial partners to reevaluate projects after approximately 18 months. In our opinion, academics could speed up the initial stages of a project and industry should slow down. We have personally witnessed many industrial projects that were discontinued without reaching a firm conclusion, only to result in an exciting opportunity being missed or to leave open questions that impede progress many years later. A frank discussion of these issues is essential at the outset of any collaborative project.Despite obvious challenges, we envision an expanding role for cell biologists in drug discovery that extends beyond their traditional involvement in early-stage target identification. Significant opportunities exist in better qualifying potential targets and in identifying the role of target proteins in cellular function and pathophysiology. Better understanding of targets in the context of cellular and tissue networks should make it possible to design better therapeutics based on optimizing selectivity, affinity, and type of molecule. Cell biologists can also become more involved in clinical development of new and standard-of-care drugs, particularly with respect to identifying indications, developing diagnostics, and stratifying populations. In this case, learning more about the clinical phases of drug development is valuable. In our personal experience, the most effective approaches are those that involve quantitative analysis and combine experimentation and modeling. This often goes under the name “systems biology” but can easily be viewed as a natural evolution of cell biology in the face of ever-larger data sets and more complex cellular mechanisms. Thus, if we had a single piece of advice for cell biologists interested in pharmacology or drug discovery, it is to acquire or hone skills in statistics, bioinformatics, programming, and applied mathematics in general.Open in a separate windowP. K. SorgerOpen in a separate windowP. K. Sorger     

Modeling genetic architecture: a multilinear theory of gene interaction

The map from genotype to phenotype is an exceedingly complex function of central importance in biology. In this work we derive and analyze a mathematically tractable model of the genotype-phenotype map that allows for any order of gene interaction. By assuming that the alterations of the effect of a gene substitution due to changes in the genetic background can be described as a linear transformation, we show that the genotype-phenotype map is a sum of linear and multilinear terms of operationally defined "reference" effects at each locus. The "multilinear" model is used to study the effect of epistasis on quantitative genetic variation, on the response to selection, and on genetic canalization. It is shown how the model can be used to estimate the strength of "functional" epistasis from a variety of genetic experiments.     

From beads on a string to the pearls of regulation: the structure and dynamics of chromatin

The assembly of eukaryotic chromatin, and the bearing of its structural organization on the regulation of gene expression, were the central topics of a recent conference organized jointly by the Biochemical Society and Wellcome Trust. A range of talks and poster presentations covered topical aspects of this research field and illuminated recent advances in our understanding of the structure and function of chromatin. The two-day meeting had stimulating presentations complemented with lively discourse and interactions of participants. In the present paper, we summarize the topics presented at the meeting, in particular highlighting subjects that are reviewed in more detail within this issue of Biochemical Society Transactions. The reports bring to life the truly fascinating molecular and structural biology of chromatin.     

Relationships between the close congeners Anthoxanthum odoratum and A. alpinum (Poaceae, Pooideae) assessed by morphological and molecular methods

Anthoxanthum alpinum Löve & Löve has been described as a diploid perennial distributed in northern Eurasia and the high mountains of central and eastern Europe. Difficulties in finding reliable morphological differences between this taxon and the widespread tetraploid Anthoxanthum odoratum L. have resulted in taxonomists treating them as conspecific, despite the cytological differentiation. The purpose of this study was to use different approaches to assess the relationships between close congeners, such as the pair A. odoratum / A. alpinum . Macromorphological, micromorphological, and molecular data were gathered and analysed for 14 populations representing both taxa from Scandinavia and the Iberian Peninsula. Different cluster analyses were performed to study the relatedness between individuals and populations. Subsequently, a principal components analysis was computed on the basis of macromorphological quantitative traits, and principal coordinates analysis was used to analyse qualitative, micromorphological, and random amplification of polymorphic DNA (RAPD) data. An analysis of molecular variance was applied to the molecular data, and the genetic differentiation between samples was measured using the F _ST estimator. The results showed that the geographical origin was more important than the ploidy level in explaining the relatedness between specimens and populations. Moreover, a strong correlation was found between the micromorphological traits and environmental parameters. The results of the analyses do not support the assignment of a specific taxonomic rank to A. alpinum .  © 2008 The Linnean Society of London, Botanical Journal of the Linnean Society , 2008, 156 , 237–252.     

Proteomics and phosphoproteomics for the mapping of cellular signalling networks

Proteomics is transitioning from inventory mapping to the mapping of functional cellular contexts. This has been enabled by progress in technologies as well as conceptual strategies. Here, we review recent advances in this area with focus on cellular signalling pathways. We discuss genetics-based methods such as yeast two hybrid methods as well as biochemistry-based methods such as two-dimensional gel electrophoresis, quantitative proteomics, interaction proteomics, and phosphoproteomics. A central tenet is that by its ability to capture dynamic changes in protein expression, localisation and modification modern proteomics has become a powerful tool to map signal transduction pathways and deliver the functional information that will promote insights in cell biology and systems biology.     

Engineering and control of biological systems: A new way to tackle complex diseases

The ongoing merge between engineering and biology has contributed to the emerging field of synthetic biology. The defining features of this new discipline are abstraction and standardisation of biological parts, decoupling between parts to prevent undesired cross-talking, and the application of quantitative modelling of synthetic genetic circuits in order to guide their design. Most of the efforts in the field of synthetic biology in the last decade have been devoted to the design and development of functional gene circuits in prokaryotes and unicellular eukaryotes. Researchers have used synthetic biology not only to engineer new functions in the cell, but also to build simpler models of endogenous gene regulatory networks to gain knowledge of the "rules" governing their wiring diagram. However, the need for innovative approaches to study and modify complex signalling and regulatory networks in mammalian cells and multicellular organisms has prompted advances of synthetic biology also in these species, thus contributing to develop innovative ways to tackle human diseases. In this work, we will review the latest progress in synthetic biology and the most significant developments achieved so far, both in unicellular and multicellular organisms, with emphasis on human health.