A perhaps surprising detail connects common consumer products such as laundry detergents, leather gloves, baby food, and silk shirts, and more complex products such as ulcer-treating plasters and mouth freshener products: their production involves enzymes, lots of them.

As global sales exceed $5 billion per annum, it is interesting to see new approaches emerge which add rationale to the art of enzyme adaptation to industrial use.

While alkali tolerant proteases have long been used in the detergent and leather industries, their importance in the production of protein-fortified drinks, tenderisation of meat, or production of blood pressure regulators is less widely known. More recently, environmental concerns and cost pressures have increased demand for enzymatic catalysis, and at ambient temperatures.

This should be easy: most of our planet’s biosphere is actually quite cold, with oceans and polar regions together covering over 85% of the Earth’s surface. Correspondingly, many organisms have evolved their molecular machinery to cope with being exposed to temperatures permanently below 5°C (Rodrigues and Tiiedje, 2008)[1]. But unfortunately, some of the most common targets for enzymatic breakdown in industrial processes, like cellulose for biofuel production, are found less frequently in these cold environments, compared to temperate ones. The question for biotechnology is therefore: How efficiently can we mimic evolution and adapt known enzymes from temperate organisms for industrial use at lower temperatures? This task is much harder to achieve than many might think, especially if the first idea that comes to mind is site-directed mutagenesis.

The Arrhenius equation, which explains the effect of temperature on any chemical reaction, predicts a 2- to 3-fold increase in enzymatic catalysis for every 10ºC increase in environmental temperature. But is the metabolism of a cold adapted fish swimming at 0ºC really 20-times slower than that of a desert scorpion at 40ºC? Evolution has produced compensatory changes to otherwise shared enzymatic pathways which alter the rates at which these enzymes work optimally, closing the metabolic gap between the species.

Unlike the point mutations required to produce an antibody for a new target, however, cold adaptation is a feature of the overall protein structure, not one localized to a specific region like a binding site. Consequently, our traditional approach to protein engineering using site-directed or random mutagenesis, or structure informed semi-rational protein design are less helpful in manipulating global protein attributes.

Good news then, that help for better cold-adaptation strategies seems to be on its way: In August 2016, the draft genome sequence of Arthrobacter agilis [2], a cold-adapted, Gram-positive bacterium from a subglacial lake in the north-western Himalayas, was published (Singh et al, 2016) [3]. Enzymes from other Arthrobacter species are known for their industrial utility (proteases) and the availability of gene sequences from Arthrobacter agilis will also be a great resource not only for a range of naturally cold-adapted hydrolytic and other enzymes, but also for semi-rational protein engineering approaches to cold adaptation generally.

Recently, for example, the crystal structure [4] of a GH1 β-galactosidase from Exiguobacterium antarcticum surprizingly revealed enzyme oligomerization as a strategy for cold adaptation (Zanphorlin et al, 2016) [5], resulting in 10-fold higher activity at low temperatures. The underlying principle for this very significant improvement might well allow improvements to other β-galactosidases to boost activity in un-heated condition and reduce the cost of industrial ethanol and high-value biological products.

Perhaps a combination of proteome-wide analysis of thermal adaptation between organisms using sequence algorithms and a 3D structural comparison of orthologous enzymes will point towards common protein engineering opportunities for cold adaptation – not just for industrial enzymes, but perhaps also to expand our understanding of evolutionary pressures on species in predicted models of global environmental change.

Hans Hoppe