FRIENDSHIP DAY................................True Friends

There are many people that we meet in our lives
but only a very few will make a lasting impression
on our minds and hearts It is these people that we will
think of often and who will always remain
important to us as true friends

What came first the chicken or the egg?

British researchers may have uncovered a partial answer to the age-old question, "what came first the chicken or the egg?"

According to a team, comprising researchers from the University of Warwick and the University of Sheffield, the answer is "chicken" or at least a particular chicken protein.

There is, however, a further twist - this particular chicken protein turns out to come both first and last. That neat trick it performs provides new insights into control of crystal growth which is key to egg shell production.

Scientists have long believed that a chicken eggshell protein called ovocledidin-17 (OC-17) must play some role in egg shell formation. The protein is found only in the mineral region of the egg (the hard part of the shell) and lab bench results showed that it appeared to influence the transformation of (CaCo3) into calcite crystals. The mechanism of this control remained unclear. How this process could be used to form an actual eggshell remained unclear.

University of Warwick researchers Mark Rodger and David Quigley, in collaboration with colleagues at the University of Sheffield, have now been able to apply a powerful computing tool called metadynamics and the UK national supercomputer in Edinburgh to crack this egg problem.

Dr David Quigley from the Department of Physics and Centre for Scientific Computing, University of Warwick, said: "Metadynamics extends conventional molecular dynamics (MD) simulations and is particularly good at sampling transitions between disordered and ordered states of matter."

Using these tools, the team was able to create simulations that showed exactly how the protein bound to amorphous calcium carbonate surface using two clusters of "arginine residues", located on two loops of the protein and creating a literal chemical "clamp" to nano sized particles of calcium carbonate.

While clamped in this way, the OC-17 encourages the nanoparticles of calcium carbonate to transform into "calcite crystallites" that form the tiny of nucleus of crystals that can continue to grow on their own. But they also noticed that sometimes this chemical clamp didn't work. The OC-17 just seemed to detatch from the nanoparticle or "be desorbed".

Professor Mark Rodger from Department of Chemistry and Centre for Scientific Computing, University of Warwick, said: "With the larger nanoparticles we examined we found that the binding sites for this chemical clamp were the same as the smaller nanoparticles but the binding was much weaker. In the simulations we performed, the protein never desorbed from the smaller nanoparticle, but always fell off or desorbed from the larger one. However in each case, desorption occurred at or after nucleation of calcite."

The researchers had therefore uncovered an incredibly elegant process allowing highly efficient recycling of the OC-17 protein. Effectively it acts as a catalyst, clamping on to calcium carbonate particles to kickstart crystal formation and then dropping off when the crystal nucleus is sufficiently large to grow under its own steam. This frees up the OC-17 to promote more yet more crystallisation, facilitating the speedy, literally overnight creation of an egg shell.

The researchers believe that this new insight into the elegant and highly efficient methods of promoting and controlling crystallisation in nature will be of great benefit to anyone exploring how to promote and control artificial forms of crystallisation. '

The study appears in the international edition of the journal Angewandte Chemie.

Support vector machine

Support vector machines (SVMs) are a set of related supervised learning methods used for classification and regression. In simple words, given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that predicts whether a new example falls into one category or the other. Intuitively, an SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. New examples are then mapped into that same space and predicted to belong to a category based on which side of the gap they fall on.

More formally, a support vector machine constructs a hyperplane or set of hyperplanes in a high or infinite dimensional space, which can be used for classification, regression or other tasks. Intuitively, a good separation is achieved by the hyperplane that has the largest distance to the nearest training datapoints of any class (so-called functional margin), since in general the larger the margin the lower the generalization error of the classifier.

Classifying data is a common task in machine learning. Suppose some given data points each belong to one of two classes, and the goal is to decide which class a new data point will be in. In the case of support vector machines, a data point is viewed as a p-dimensional vector (a list of p numbers), and we want to know whether we can separate such points with a p − 1-dimensional hyperplane. This is called a linear classifier. There are many hyperplanes that might classify the data. One reasonable choice as the best hyperplane is the one that represents the largest separation, or margin, between the two classes. So we choose the hyperplane so that the distance from it to the nearest data point on each side is maximized. If such a hyperplane exists, it is known as the maximum-margin hyperplane and the linear classifier it defines is known as a maximum margin classifier.

Caenorhabditis elegans

Caenorhabditis elegans (pronounced /ˌsiːnɵræbˈdaɪtɨs ˈɛlɨɡænz/) is a free-living, transparent nematode (roundworm), about 1 mm in length,which lives in temperate soil environments. Research into the molecular and developmental biology of C. elegans was begun in 1974 by Sydney Brenner and it has since been used extensively as a model organism.
C. elegans is unsegmented, vermiform, and bilaterally symmetrical, with a cuticle integument, four main epidermal cords and a fluid-filled pseudocoelomate cavity. Members of the species have many of the same organ systems as other animals. In the wild, they feed on bacteria that develop on decaying vegetable matter. C. elegans has two sexes: hermaphrodites and males.Individuals are almost all hermaphrodite, with males comprising just 0.05% of the total population on average. The basic anatomy of C. elegans includes a mouth, pharynx, intestine, gonad, and collagenous cuticle. Males have a single-lobed gonad, vas deferens, and a tail specialized for mating. Hermaphrodites have two ovaries, oviducts, spermatheca, and a single uterus.

C. elegans eggs are laid by the hermaphrodite. After hatching, they pass through four juvenile stages (L1–L4). When crowded or in the absence of food, C. elegans can enter an alternative third larval stage called the dauer state. Dauer larvae are stress-resistant and do not age. Hermaphrodites produce all their sperm in the L4 stage (150 sperm per gonadal arm) and then switch over to producing oocytes. The sperm are stored in the same area of the gonad as the oocytes until the first oocyte pushes the sperm into the spermatheca (a kind of chamber where the oocytes become fertilized by the sperm).The male can inseminate the hermaphrodite, which will use male sperm preferentially (both types of sperm are stored in the spermatheca). When self-inseminated the wild-type worm will lay approximately 300 eggs. When inseminated by a male, the number of progeny can exceed 1,000. At 20 °C, the laboratory strain of C. elegans has an average life span of approximately 2–3 weeks and a generation time of approximately 4 days.

C. elegans has five pairs of autosomes and one pair of sex chromosomes. Sex in C. elegans is based on an X0 sex-determination system. Hermaphrodite C. elegans have a matched pair of sex chromosomes (XX); the rare males have only one sex chromosome (X0). The sperm of C. elgans is ameboid, lacking flagella and acrosomes.
Longitudinal section through the hermaphrodite C. elegans

Genome

C. elegans was the first multicellular organism to have its genome completely sequenced. The sequence was published in 1998,although a number of small gaps were present; the last gap was finished by October 2002. The C. elegans genome sequence is approximately 100 million base pairs long and contains approximately 20,100 protein-coding genes.The number of known RNA genes in the genome has increased greatly due to the 2006 discovery of a new class of 21U-RNA gene,and the genome is now believed to contain more than 16,000 RNA genes, up from as little as 1,300 in 2005.Scientific curators continue to appraise the set of known genes, such that new gene predictions continue to be added and incorrect ones modified or removed.

In 2003, the genome sequence of the related nematode C. briggsae was also determined, allowing researchers to study the comparative genomics of these two organisms.Work is now ongoing to determine the genome sequences of more nematodes from the same genus such as C. remanei,C. japonica and C. brenneri.These newer genome sequences are being determined using the whole genome shotgun technique which means they are likely to be less complete and less accurate than that of C. elegans, which was sequenced using the "hierarchical" or clone-by-clone approach.

The official version of the C. elegans genome sequence continues to change as and when new evidence reveals errors in the original sequencing (DNA sequencing is not an error-free process). Most changes are minor, adding or removing only a few base pairs (bp) of DNA. For example, the WS169 release of WormBase (December 2006) lists a net gain of 6 base pairs to the genome sequence.Occasionally more extensive changes are made, as in the WS159 release of May 2006, which added over 300 bp to the sequence

System Biology

Dramatic advances in proteonomics, genomics, and measurement technologies such as DNA arrays have lead to a significantly increased knowledge about biological organisms. Classical and molecular biology have contributed to identify numerous individual genes and proteins, as well as other cellular components, and their specific functions. However, by now it has become clear that understanding biological organisms is not possible by simply collecting information about all involved components. Rather, a holistic understanding of biological organisms requires considering all involved components as well as the interactions among them, since the interactions are ultimately responsible for an organism’s form and functions.

Systems biology aims to obtain a holistic understanding of biological systems such as a single cell, organ or even a whole living organism, by combining approaches from system sciences, life sciences, and information sciences.


An exciting and constantly active field of research, systems biology integrates experimental data and mathematical modeling, knowledge and system analysis, to gain intuition into the mechanisms and dynamics of biological systems. It is expected that the insights obtained using methods from systems biology will lead to significant advances in various fields such as medicine and biochemical engineering. Systems biology, often also called “the sciences of the 21st century”, is an interdisciplinary challenge for biologists, computer scientists, system theoreticians, and physicians.
The main objective of this course is to give an introduction to systems biology, covering aspects from biology, systems theory, and some of the databases/tools available. The course is designed for people interested in the fusion of systems, life, and information sciences. One of the goals is to give a clear insight into the modeling and analysis methods typically used to study biological systems, including metabolism, signal transduction, genetic networks, and cell to cell signaling. Where necessary, a review of the biological basics is given. Topics to be covered include:

* modeling and analysis of biochemical reaction networks
* databases and information science tools
* modeling and analysis of genetic regulatory networks
* experimental techniques typically used in systems biology
* Constrained-based modeling
* Stochastic modeling approaches
* Qualitative and quantitative models
* Sensitivity analysis

Systems biology

Systems biology is a term used to describe a number of trends in bioscience research, and a movement which draws on those trends. Proponents describe systems biology as a biology-based inter-disciplinary study field that focuses on complex interactions in biological systems, claiming that it uses a new perspective (holism instead of reduction). Particularly from year 2000 onwards, the term is used widely in the biosciences, and in a variety of contexts. An often stated ambition of systems biology is the modeling and discovery of emergent properties, properties of a system whose theoretical description is only possible using techniques which fall under the remit of systems biology.

discovery of TRIM 5 alpha

Human immunodeficiency virus type 1 (HIV-1) causes AIDS in humans, and to a lesser extent, in chimpanzees (1, 2). However, not long after the discovery of HIV-1, scientists realized that certain primate species were resistant to HIV-1 infection. In particular, monkeys from Africa and Asia, referred to as Old World monkeys, could not be infected with HIV-1 and did not develop AIDS (3). This discovery brought both excitement and frustration. The block to HIV-1 replication in Old World monkey cells hindered efforts to develop an animal model for testing drugs and vaccines. On the other hand, Old World monkeys had evolved for millions of years in Africa--the epicenter of the current HIV-1 epidemic. Perhaps exposure to past HIV-1-like epidemics led to the emergence of an antiviral defense that protected them against HIV-1.



Determining the cause of HIV-1 resistance in Old World monkey cells stymied HIV researchers for nearly two decades. An early view was that the block resulted from expression of an incompatible receptor on the surface of Old World monkey cells. However, identification of the HIV-1 co-receptor in the mid-1990s disproved this hypothesis. Subsequent studies demonstrated that HIV-1 could enter Old World monkey cells, but a block that targeted the viral capsid prevented the establishment of a permanent infection (4).

Using a genetic screen, we identified TRIM5alpha as the primary block to HIV-1 replication in Old World monkey cells (5). The expression of rhesus monkey TRIM5alpha in human cells potently inhibited HIV-1 infection and prevented the accumulation of reverse transcripts. Importantly, reducing the expression of TRIM5alpha in rhesus monkey cells with small interfering RNA relieved the block to HIV-1.

We initially hypothesized that TRIM5alpha functioned as a cofactor necessary for capsid uncoating. However, subsequent findings argued against this hypothesis. First, knocking down human TRIM5alpha showed no effects on HIV-1 replication in human cells. Second, rodent cells, which do not express TRIM5alpha, supported HIV-1 infection if engineered to express an appropriate receptor. Finally, human TRIM5alpha does not associate with the HIV-1 capsid in biochemical assays. Thus, TRIM5alpha appeared to have evolved primarily as an inhibitory factor aimed at thwarting viral replication, rather than a host factor co-opted by HIV-1 to promote infection.

Further evidence that TRIM5alpha functions primarily as a modulator of innate immunity against retroviruses emerged from comparing the sequences of TRIM5 alpha orthologs from different primate species. We found dramatic length variation, and an unusually high ratio of nonsynonymous to synonymous changes in the C-terminal domain of TRIM5alpha orthologs (6) suggesting that TRIM5alpha has been subjected to strong positive selective pressure during primate evolution. Furthermore, episodic changes in the TRIM5alpha C-terminal domain coincide with periods of retroviral epidemics (6). Indeed, a recent report suggests that selective changes occurred in the TRIM5alpha lineage during acquisition of resistance to an ancient retrovirus. These changes may have had the unfortunate consequence of attenuating TRIM5alpha potency against HIV-1 (7).

Does TRIM5alpha have the ability to block infection by other retroviruses? We found that TRIM5alpha from various Old World monkey species conferred potent resistance to HIV-1, but not SIV (5). New World monkey TRIM5alpha proteins, in contrast, blocked SIV but not HIV-1 infection. Human TRIM5alpha inhibited N-MLV and EIAV replication (8, 9). Thus, the variation among TRIM5 orthologs accounts for the observed patterns of post-entry blocks to retroviral replication among primate species.

To determine why Old World monkey TRIM5alpha but not human TRIM5alpha, potently blocks HIV-1, we systematically altered the human sequence to more closely resemble the monkey sequence. Remarkably, we found that a single amino acid determines the antiviral potency of human TRIM5alpha (10). If a positively charged arginine residue in the C-terminal domain of human TRIM5alpha is either deleted or replaced with an uncharged amino acid, human cells gain the ability to inhibit HIV-1 infection (11). Perhaps some humans have already acquired this change and are naturally resistant to HIV-1 infection.

How does TRIM5 inhibit infection? Following viral entry into the host cell, the capsid core, which encases the viral RNA, must disassemble to allowreverse transcription of the viral RNA into DNA (see the figure). Host factors that mediate capsid uncoating are presumed to exist, but have not been identified.

Because early studies demonstrated that sequences within the capsid determined susceptibility to the block, we asked if TRIM5 associated with the capsid. The association of TRIM5 with the capsid was dependent on the C-terminal domain and the association was necessary for restriction (12). TRIM5 proteins from various Old World monkey species bound the HIV-1 capsid; however, TRIM5 variants that did not restrict HIV, such as New World monkey TRIM5, did not associate with the capsid cores. Human TRIM5 exhibited a very weak association with the HIV-1capsid cores, explaining the lower potency of human TRIM5 in blocking HIV-1 infection (12).

Why does association of TRIM5 with the viral capsid inhibit infection? Previous studies of HIV-1 capsid mutants suggest that capsid disassembly may be a temporally regulated process with either too rapid or too slow disassembly compromising viral infectivity (13). By following the fate of viral cores in the cytosol just after viral entry, we found that TRIM5 caused capsid cores to undergo rapid, and premature, disassembly (12, 14). Accelerated uncoating of the capsid correlated with the ability of TRIM5 variants from different species to restrict HIV-1, SIV, and N-MLV infections. Future studies are needed to determine how TRIM5 promotes rapid disassembly of capsid and why accelerated disassembly is detrimental to infection. Perhaps accelerated disassembly of the retroviral capsid prematurely exposes the viral RNA or viral enzymes to degradation.

The discovery of TRIM5 not only answered a long-standing question in the HIV field, it also revealed a new pathway that protects cells from retroviral infection. The human genome encodes more than 50 members of the TRIM family. Recently, TRIM25 was shown to be essential for RIG-I-mediated antiviral activity (15) and TRIM family members such as TRIM1, TRIM19 (PML), and TRIM22, may block other viruses (16).

At a time when policy-makers and the public express frustration over our inability to produce an HIV vaccine, it is hoped that the discovery of TRIM5 will precipitate new ideas for how to protect human hosts from retroviral infection. Perhaps in the case of retroviruses, innate intracellular immunity mediated by factors like TRIM5 and APOBEC play a particularly crucial role. Efforts aimed at enhancing these innate immune defenses may ultimately prove to be more effective at protecting humans from HIV than vaccine strategies aimed primarily at stimulating humoral or cellular