Toward the end of the twentieth century, new methods began to change the face of biochemistry. The launching of the Human Genome Project and the development of faster and cheaper sequencing technologies provided biochemists with entire genome sequences, not only of humans, but of numerous other organisms. Huge databases were set up to deal with the volume of sequence information generated by the various genome projects. Computer programs cataloged and analyzed these sequences, making sense of the enormous quantities of data.
Protein coding regions of genomes could be identified and translated “in silico" to deduce the amino acid sequence of the encoded polypeptides. Comparisons could be made between the gene sequences of different organisms. In parallel with the growth of sequence information, more and more protein structures were determined, by using X-ray crystallography and NMR spectroscopy. These structures, too, were deposited in databases to be accessible to all scientists.
The accumulation of vast amounts of sequence and structure information went hand in hand with new and ambitious goals for biochemistry. Modern biotechnology techniques have provided tools for studying biochemistry in entirely new ways. The old ways of dividing and conquering to study individual reactions are now being supplemented by approaches that permit researchers to study cellular biochemistry in its entirety.
These fields of research, which collectively are often referred to as the ‘-omics’ include genomics (study of all the DNA of a cell), proteomics (study of all the proteins of a cell), transcriptomics (study of all the transciption products of a cell), and metabolomics (study of all the metabolic reactions of a cell), among others. As an example, let us consider proteomics. The field of proteomics is concerned with all of the proteins of a cell. Since proteins are the ‘workhorses’ of cells, knowing which ones are being made at any given time provides us with an overview of everything that is happening in the cells under specific conditions.
How is such an analysis performed? First, one extracts all of the proteins from a given cell type (liver, for example). Next, the proteins are separated in a two-step gel method, where the first step resolves proteins based on their charge and the second separates them by mass. The product of this analysis is a single gel (called a 2-D gel) on which all of the proteins have been separated. In the left-right orientation, they differ in their original charge and in the up/down orientation, they differ in their size.
By using such a technique, as many as 6000 cellular proteins can be separated and visualized as spots on a single gel. Robotic techniques allow excision of individual spots and analysis on mass spectrometers to identify every protein present in the original extract.
Why is this useful? There are several ways in which this information can be illuminating. For example, by comparing the proteins in a normal liver cell with those in a cancerous liver cell, one can quickly determine if there are any proteins that are expressed or missing only in the cancer cells. These differences between normal and cancerous cells may provide clues to the mechanisms by which the cancer arose or suggest ways to treat the cancer. Or, the same sort of analysis could be done on cells to find out about the effects of a hormone or drug treatment. Comparison of the proteins found in untreated and treated cells would give a global view of the protein changes resulting from the treatment.
Similar analyses can be performed on the mRNA of cells, employing devices called microarrays. In this case, all the RNAs that are being made at the time that the cell extract is made can be identified by the signals generated when the RNAs hybridize with oligonucleotides complementary to their sequence, that are immobilized in ordered arrays on the surface of a plate. The position and strength of these signals indicates which RNAs are made and in what amounts.
The techniques of proteomics and transcriptomics, together with other “global view" approaches of molecules like lipids, carbohydrates, etc., are allowing biochemists to have, for the first time, a “big picture" view of the activities of cells. While these techniques have already provided valuable new insights, they are still incomplete, as a description of what goes on in cells. This is because they provide us with a snapshot that captures what is happening in cells at the moment that they were disrupted to make the extract. But cells are not static entities. At every moment, they are adapting their activities in response to changing combinations of internal and external conditions. Changes in response to any one signal are modified and in.uenced by the every other condition, within and outside the cell, and understand these complex systems as an integrated whole is the new holy grail of biochemistry.
The aim, then, is to develop models that depict these dynamic interactions within cells, and to understand how such interactions give rise to the properties and behavior that we observe. This is the goal of the emerging field of systems biology that constructs mathematical models and simulations, based on the large data sets generated by transcriptomic, proteomic and other broad-range techniques. Systems biology is truly an interdisciplinary venture, drawing as it does on mathematics and computer science as much as traditional “bench biochemistry". While the original laboratory techniques of biochemistry are by no means obsolete, they will no longer be the sole tools used to understand what goes on inside of cells.
These newer approaches are already leading to applications that are of tremendous value. Understanding the system level differences between normal and diseased cells can lead to major changes in the way diseases are detected, treated or altogether prevented.
One recent triumph of systems biology has been in an intriguing discovery about how antibiotic drugs work. System level studies of many classes of antibiotics revealed that, regardless of how we think they work to kill bacteria, all of the drugs appear to have a common effect – that of increasing the level of oxidative damage, leading to cell death. This observation suggested that the potency of antibiotics could be enhanced by blocking bacterial responses that protect against oxidation damage. This idea was tested by screening large numbers of compounds for the ability to inhibit a pathway that bacteria use to repair their oxidation-damaged DNA. This screen yielded several compounds, the best of which was able to increase the effectiveness of the drug gentamicin by about a thousand-fold. Such compounds will be of increasing value in a world where antibiotic resistance is on the rise.
Another application of systems biology is in the development of more effective vaccines. Till recently, most vaccines have been developed with little understanding of how exactly they stimulate the immune response. As systems biology approaches give us a better understanding of the changes that vaccines bring about to mediate immunity, it will be possible to identify the patterns that characterize stronger immune responses or adverse reactions to vaccines and even to predict how well particular vaccines may work in specific populations or individuals. Similarly, system level studies can help identify which drugs might be most effective, with the fewest side-effects, for a given patient, leading to a new era of personalized medicine.
Related to systems biology, and heavily dependent on it, is synthetic biology, which aims to use the knowledge gained from the former to engineer novel biological systems and pathways. Because the technology now exists to synthesize extremely long pieces of DNA, entire genomes can be made synthetically and used to program cells that they are inserted into. It also allows for the possibility of custom-designing an organism to create particular chemical compounds through artificially assembled pathways.
These methods have already been used to produce the drug artemisinin, which is used to treat malaria. The pathway for making a precursor of artemisinin was created by combining a metabolic pathway from yeast with part of another derived from the plant Artemisia annua, the natural source of artemisinin. Similar efforts are underway for anticancer drugs, novel drugs, favoring compounds, etc. One major goal is to create organisms programmed to make biofuels that could potentially replace petroleum.
The successes of systems and synthetic biology, even in their infancy, promise great advances both in our understanding of living systems and in the applications that arise out of that knowledge. The next fifty years in biological research may well eclipse even the amazing accomplishments of the last. The practice of medicine will be transformed. Regenerative medicine will improve, as a better knowledge of stem cells allows us to use them more effectively to replace cardiac muscle lost in a heart attack, neurons damaged in Parkinson’s or Alzheimer’s, or even to regrow limbs lost in accidents or war. Treatments for our illnesses can be tailored to be optimal for each individual. Biofuels may bail us out when oil supplies run out and engineered organisms may help clean up a polluted planet. And research on longevity may give us the best gift of all- lives extended long enough to witness these advances and to participate in the creation of a new and better world.