When I think of prospecting, I immediately think of the California Gold Rush and the ’49ers. The equivalent of “gold” in bio-prospecting might be a vividly coloured pigment, a sweet flavour, a natural pain killer or some form of material with unusual properties, such as latex.
Today, many prospectors, from individuals to large organisations continue to comb the planet for plants and animals that contain such “treasures”. With the advent of genomics and the more recent democratisation of genome sequencing, which has recently extended its reach to determine the genome sequences of unculturable organisms, the world of bio-prospecting has changed tack. Here I want to explore the future directions and potential benefits of post-genomic Bio-prospecting
The phenomenon of symbiosis has long provided a fertile area for Biology teachers. A familiar example of symbiosis, in which two or more species co-exist for mutual benefit, includes bees taking nectar from flowering plants; in return, the bee transfers the sticky pollen it inadvertantly collects, to fertilise another flower. Many grazing animals process grass through a partnership with a complex population of microbes in their gut, in much the same way, we rely on a population of microbes to aid our own digestive processes. These gut microbes form a “microbiome“. That is a population of microbes that form an ecosystem, often to extend the extraction of nutrients, in a manner not unlike a game of pass the parcel.
At a molecular level, microbiomes represent an example of a community of enzymes. Independent living microbes like E.coli will replicate on a suitable food source every 20-30 minutes. In this time, each cell uses a sequence of enzymatic reactions to convert glucose into the building blocks of nucleic acids that comprise the genome. In turn the genome encodes a wide portfolio of protein and RNA molecules (structural genes) that in turn catalyse intracellular metabolism and generate the lipids and carbohydrates that underpin cell structure and integrity. And importantly, this is accompanied by the generation of ATP, the biofuel that powers many of these physiological processes.
Enzymes are clearly central to life and often operate in networks that combine to form a series of interlinking metabolic cycles and pathways. It has become clear over recent years is that such networks often reach out to neighbouring organisms, pooling their catalytic powers to harness energy from natural materials and even from man made waste products.
Historically, Bio-prospecting has involved the collection of organisms, typically plants and fungi, from “the field”. In one scenario, a medicinal chemistry discovery team may use such samples to carry out a systematic evaluation of some form of extracts isolated from the sample. The screen may be highly focused, such as a screen for a Clostridium difficile antibiotic, or more general; perhaps in search of an inhibitor of cell division in cancer research. Such screens are often restricted to small molecules, since ideal candidates are compounds that can be synthesised rapidly and economically.
The search for novel proteins, including enzymes, requires a slightly different strategy, since total chemical synthesis of a polypeptide is both uneconomical and remains technically challenging, especially at scale. One well known example of a therapeutic protein is insulin. Discovered in the 1920s, the widespread availability of insulin significantly transformed the life expectancy and quality of life of diabetics. In healthy individuals, insulin is produced in the pancreas, in order to regulate blood sugar levels: for the management of type I diabetics, insulin is now routinely administered by injection. The early stage insulin preparations were derived from canine pancreatic extracts, but the search for more suitable forms led the pharmaceutical sector to investigate farm animals, with cattle and pigs proving the most effective sources of the hormone. By 1978, genetic engineering made it possible for Eli Lilly to market the first formulations of insulin (humulin) derived by expression of the human gene encoding insulin in E.coli.
The first use of enzymes in Biotechnology is controversial, since the early production of bread, cheese and alcoholic refreshments, preceded the use of the term. However, in the example of cheese production, proteases such as chymosin (often called rennet or rennin) are added as part of the production process. In a wonderful example of serendipitous bioprospecting, the enzyme is released by the lining of the fourth stomach of the calf! The story goes that in the days when animal hides were used for storing and carrying liquids, what started a journey as milk, ended up as cheese! Much of the motivation of early enzymologists was understanding and improving enzyme catalysis in food and drink production. The early pioneers of enzyme biochemistry worked primarily with yeasts and the low value products from the meat industry. In fact the word enzyme essentially means “in yeast.” More specifically, Kuhne at the University of Heidelberg coined the term enzyme, being derived from the Greek word ενζυμον meaning “in leaven”. The landmark discoveries of insulin and penicillin in the 1920s, laid the foundation for widening the search for enzymes. It is worth remembering that it wasn’t until the 1950s that biological proteins would be chemically defined through the work of Sanger (on insulin) and Stein and Moore (on ribonuclease) and equally that nucleic acids underpin the chemical basis of genetics. It was during this period that the search for novel enzymes began in earnest as biochemists and microbiologists expanded their horizons.
One of the first bacterial enzymes produced commercially was the alkaline protease subtilisin by Novo (now Novozymes), and is derived from the thermostable gram positive species Bacillus licheniformis. The resilience of many secreted enzymes from similar Bacillus species at close to boiling temperatures, led to numerous applications in the detergent sector, which remains today. It wasn’t until the development of molecular cloning (recombinant DNA) technologies that the emphasis shifted from extracting and purifying enzymes from a diverse range of microbes, to expressing the gene encoding the enzyme in either E.coli or yeasts. Fermentation of recombinant enzymes not only led to greater control over production, but circumvented the need for specialist growth media to support the production of biomass. However, not all genes can be expressed in the work-horse strains of fermentation and where the uniqueness and the value of the enzyme is of paramount importance, specialist host organisms are drafted in.
Today, enzymes are once again in the spotlight, owing to the advances in genomics technologies enabling the genes encoding enzymes from unculturable organisms to be identified by bioinformatic analysis and subsequently expressed in a work-horse host organism. In addition, with the advent of directed evolution, it is increasingly possible to improve the performance of an initial starting point enzyme (we refer to these as “ground-state” enzymes) through a series of iterative stages of “random” mutation and biological or biochemical screening. Nature throws up enzymes that are mostly chemically imperfect (you can read more about this issue at the excellent Sandwalk Blog site written by Em Prof by Larry Moran). Enzymes in Nature generally catalyse a reaction at a rate and with a level of specificity that meets the need of the organism under a particular set of nutrient and developmental pressures. There is therefore room for “improvement”. This is achieved by applying what at Entropix we refer to as “unnatural selection”. By imposing selection criteria on a library of variants derived from the ground state gene, we are able to enhance the value of bioprospecting.
The early prospectors were identifiable as hardy pioneers, suitably dressed for wading in cold streams or hacking through tropical forests. The bioprospectors of the future will increasingly be sat in front of a computer screen, toggling between search engines, online gene synthesis and posting instructions to robotic, high-throughput instruments. Nevertheless, our ability to generate novel enzymes will rely on a greater knowledge of natural biodiversity for some time to come, as will our ability to predict enzyme function with the precision needed for many applications. The greater our understanding of the communities of microbes that make up microbiomes and add value to their hosts, the greater the likelihood of developing enzyme communities, which may be necessary to address some of the more challenging areas of Biotechnology including recycling and the synthesis of complex molecules.