The advantages of living organisms are their variability and efficiency in terms of energy as well as the space required for their work. Both in terms of substances to be measured, as well as the measuring device, no electronic sensor currently used can even approach the performance of bacteria for detecting chemical molecules. No electronic device can be compared with the multi-stage variable design, thanks to different reading frames and the effectively used space for information storage such as genes in chromosomes. A physical measuring device is constructed invariably for a specific purpose and can hardly be designed modularly without greater effort and loss of efficiency to allow for later, unforeseen changes of function. In bacteria, the construction plan itself is directly implemented and the measuring devices are constantly produced, used, degraded and recycled. Theoretically, each substrate can be detected at minimal concentrations (of course depending on the ambient volume and cell density) and the resulting signal amplified.

The demand for such a device is high, since there is a wide range of possible applications. For example, for detecting explosives, currently, dogs must be trained expensively for each "new" olfactory compound of an explosive, while bacteria only need another cloning. Quantitative determinations of air quality in confined spaces or open cities can be achieved by recursive control of bioreactors. Even the detection of cancer cells, which today is only possible under harmful conditions, could be accomplished with a microorganism-based sensor (artificial nose).

Theoretically, the processivity can also be calculated as a counterpart to the substrate concentration on the basis of the cell density and determined for different states, thereby enabling the determination of concentrations in addition to the mere binary yes / no detection of the substance. Such conditions may include, but are not limited to, the temperature dependence we have already shown, different pH levels, the presence and absence of light in certain wavelengths, the presence and absence of various substrate molecules, and much more.

If the interface between bacteria and technical devices is extended not just with one gene, but many, we open the door to almost unlimited possibilities. The two interfaces we studied, temperature and pH of the environment, can be almost arbitrarily combined with others (for example, with photoreception of different wavelengths, voltage differences, or even the presence, absence or change in growth factors such as oxygen or other specific molecules). Taken together, the temperature in our experiments offers two possible outcomes: with a heat-inducible promoter, a signal can be produced and detected at elevated temperatures, or not.

Considering heat as 1 and ambient temperature as 0, we get the classical information units of the binary system. The change in pH in turn provides three detection options. In our case, at a pH ≤ 6, a specific promoter induces the production of a GFP mutant, while at neutral pH (around 7.5) no signal is generated and at pH ≥ 8, another fluorescent molecule is expressed. Accordingly, we have three signals: 0, 1 and -1. If we now combine the two differently caused signals, i.e., hot or ambient temperature and pH ≤ 6, pH around 7.5 or pH ≥ 8 we get the state space (1|1, 1|0, 1|-1, 0|1, 0|0, 0|-1), providing us with six different signal combinations. If we added a photoreceptor (detecting the presence or absence of a single wavelength), the number of states doubles to twelve (2 states for temperature times 3 states for pH times 2 states for light), suggesting that our robot could already be fed with twelve different movement patterns.

Whether these twelve different fluorescence signals are detected separately (single bacterial samples are exposed to a single stimulus) or in a shared environment (bioreactor) by means of either multiple detectors (each measuring a single frequency) or a combined detection of superposed wavelengths has to be decided on a case to case basis, since the complexity of simultaneous detection of multiple fluorescence signals increases exponentially.

The idea of ​​processor-oriented computation stands in stark contrast to a strongly parallelized alternative: in just one milliliter of bacterial culture, with adequate bacterial density,  more than 3 billion bacteria can be found. If we can get every single bacterial cell to make one calculation per second, we have a computational power similar to modern computers in a milliliter. There would also be no problem with scalability: Within a few hours, one liter of bacterial culture can be produced from one milliliter, which increases the computing power several fold.