TOPIC:WHOLE CELL SIMULATION BACKGROUND 1. WHAT IS WHOLE CELL SIMULATION? A cell is a fundamental unit of all livingorganism, it is composed by organelles which perform some activities likecellular respiration (mitochondrial), digestion (lysosomes), and it isenveloped with a cell membrane. Simulation is the process of performingexperiments on a model. Using simulation techniques instead of actuallyperforming the experiments can save time and money; in addition, there areexperiments that are impossible to carry out in reality, that may be possibleto simulate. The validity of the model is crucial; if the model is invalid, thesimulation results will also be invalid. As the science is advancing, cell need to bevisualized and modelled at a molecular level in other to strengthen researcheson living organism. This modelling will help many field of medicine indesigning drugs, treating diseases, vaccines designing.
Whole cell simulationas a way of modelling organism cell provides information on cell in a virtualway by giving out detailed images of cells organelles, DNA, RNA, and proteinsetc… It involves developing efficient algorithms, data structures,visualization and communication tools to orchestrate the integration of largequantities of biological data with the goal of computer modelling. 2. WHY WHOLE CELL SIMULATION? The purposeof whole-cell modeling is to predict how genotype determines phenotype. It accountsfor the specific function of every gene product and predict the dynamics ofevery molecule over the entire life cycle.
It has also the potential to enableengineers to rationally design cells to perform useful functions such assynthesizing drugs, sensing disease, and decontaminating waste. In addition,they have the potential to enable physicians to provide personalized medicalcare and acceleratebiomedical science. However, discovering new biology from whole-cell models andother high-through put technologies requires novel tools for exploring andanalyzing complex high-dimensional data. 3.
APPLICATIONOF WHOLE CELL SIMULATIONThere are several possible uses ofwhole-cell simulations based on computer: Firstly, its important use is toverify that the underlying model behaves as its real-world counterpart indifferent environments. Secondly, when provided the model is good enough,simulation can also be used to predict the outcome of experiments. This way, itmay be possible to simulate some experiments that simply cannot be carried outon real cells.
At the last not the least, whole cell simulation provides aframework where a biologist can construct cell models and perform simulationson them in an intuitive way.Whole-cell models identify the limits of ourcurrent knowledge for a given biological system. With all the data that isgenerated for a particular cell or organism, there remains a dramatic gapbetween what is known and what remains to be discovered. To completely “solve”a cell would ideally involve rigorous and coordinated statistical design ofexperiments to comprehensively identify the main and interaction effects in agiven network. Anything short of this will inevitably lead to bothunder-explored areas of the network, which are essentially gaps in our knowledge,as well as controversy when published experimental results exhibit seeminglyinconsistent results in the absence of sufficient network context.-Predict complex, multi-networkphenotypes-Suggest future experiments thatmay lead to new knowledge-Provide a framework for the safeand effective design of genetically-modified organisms • Medical applications of models of human cells: Human models could revolutionize medicine.
Forexample, in the future, we envision that computational oncologists will useaccurate, personalized wholecell models of tumors, parameterized by eachtumor’s genetic variations, to find the optimal combination and dosage of drugsto treat each patient’s cancer. Similar approaches could be used to personalizetherapy for any patient with any disease who is being evaluated for any drug. • Industrial applications of genetically optimizedbacteria: Many economicallytransformative genetic engineering applications of bacteria are currently underinvestigation Khalil 2010, including drug production Ajikumar 2010,renewable fuel synthesis, generating energy from sunlight, and hazardous wastedisposal Lee 2012. However, these efforts are hindered by challenges inpredicting and testing the benefits of possible genetic modifications.
Thisprocess could be improved by (1) using whole-cell models to rationally designgenomes by optimizing in silico phenotypes and (2) using genome editing methodssuch as CRISPR or genome synthesismethods to implement designer genomes. 4. SOFTWAREREQUIRED TO PERFORM SIMULATION AND HOW THE WORK With the advancement incomputerization, softwares have already been developed to stimulatemulti-algorithm models:· WholeCellKB is used toorganize experimental training data.· WholeCellSimDB helps to storesimulation results, and· WholeCellViz is needed tovisualize simulations results. All theabove softwares were designed to facilitate exploration, analysis, andcommunication of whole-cell model data.
And this helps researchers use whole-cellmodel simulations to drive advances in biology and bioengineering. How they work· Using wholeCellvizIt is aweb-based software program for visually exploring and analyzing whole-cellsimulations.It enables users to interactively analyze many aspects of cellphysiology including: -Cell mass,volume, and shape, -Metabolite, RNA,and protein copy numbers, -Metabolicreaction fluxes, -Molecular machinestatuses – DNA polymerase, RNA polymerase. -Chromosome copynumber, superhelicity, integrity, and DNA binding status.
WholeCellVizprovides 14 animated visualizations, including metabolic and chromosome maps.These visualizations help researchers analyze model predictions by displayingpredictions in their biological context. Furthermore, WholeCellViz enables researchers to compare predictions within andacross simulations by allowing users to simultaneously display multiplevisualizations. 5. THEFIRST COMPUTER MODEL OF ORGANISMIt has been said “You discover things a lot faster with acomputer model than you do without it”.
Assistant professor of bioengineering MarkusCovert, PhD at Stanford university created the first softwaresimulation of an entire organism of M. genitalium. This smallest freeorganism commonly known as Mgen, is a sexually transmitted, small and pathogenic bacterium that liveson the ciliated epithelial cellsof the urinary and genital tracts in humans. The Mycoplasma genitalium simulation havebeen introduced in order to predict the dynamics of every molecule over their entire lifecycle. In other words, about 75percent of what biologists know about Mycoplasma genitalium is now being simulated on Covert’scomputer.
That’s already enough to give him two things: confidence aboutintegrating the rest of the coding regions; and a simulation that already workswell enough for his group to ask biologically interesting questions about theorganism, such as why it grows so much more slowly than even its closerelatives. CONCLUSION