A rise-to-threshold process for a relative-value decision.

Whereas progress has been made in the identification of neural signals related to rapid, cued decisions1-3, less is known about how brains guide and terminate more ethologically relevant decisions in which an animal's own behaviour governs the options experienced over minutes4-6. Drosophila search for many seconds to minutes for egg-laying sites with high relative value7,8 and have neurons, called oviDNs, whose activity fulfills necessity and sufficiency criteria for initiating the egg-deposition motor programme9. Here we show that oviDNs express a calcium signal that (1) dips when an egg is internally prepared (ovulated), (2) drifts up and down over seconds to minutes-in a manner influenced by the relative value of substrates-as a fly determines whether to lay an egg and (3) reaches a consistent peak level just before the abdomen bend for egg deposition. This signal is apparent in the cell bodies of oviDNs in the brain and it probably reflects a behaviourally relevant rise-to-threshold process in the ventral nerve cord, where the synaptic terminals of oviDNs are located and where their output can influence behaviour. We provide perturbational evidence that the egg-deposition motor programme is initiated once this process hits a threshold and that subthreshold variation in this process regulates the time spent considering options and, ultimately, the choice taken. Finally, we identify a small recurrent circuit that feeds into oviDNs and show that activity in each of its constituent cell types is required for laying an egg. These results argue that a rise-to-threshold process regulates a relative-value, self-paced decision and provide initial insight into the underlying circuit mechanism for building this process.

An internal expectation guides Drosophila egg-laying decisions.

To better understand how animals make ethologically relevant decisions, we studied egg-laying substrate choice in Drosophila. We found that flies dynamically increase or decrease their egg-laying rates while exploring substrates so as to target eggs to the best, recently visited option. Visiting the best option typically yielded inhibition of egg laying on other substrates for many minutes. Our data support a model in which flies compare the current substrate's value with an internally constructed expectation on the value of available options to regulate the likelihood of laying an egg. We show that dopamine neuron activity is critical for learning and/or expressing this expectation, similar to its role in certain tasks in vertebrates. Integrating sensory experiences over minutes to generate an estimate of the quality of available options allows flies to use a dynamic reference point for judging the current substrate and might be a general way in which decisions are made.

Standardization of functional reporter and antibiotic resistance cassettes to facilitate the genetic engineering of filamentous fungi.

The unique physiological properties of fungi are useful for a myriad of applications, which could greatly benefit from increased control of native pathways and introduction of recombinant genes. However, fungal genetic engineering is still limited in scope and accessibility, largely due to lack of standardization. To help standardize the genetic engineering of filamentous fungi, we created BioBricks of commonly used antibiotic resistance genes, neomycin phosphotransferase (nptII) and hygromycin phosphotransferase (hph), which confer resistance to G418 (Geneticin) and hygromycin B, respectively. Additionally, we created a BioBrick of the constitutive trpC promoter, from the tryptophan biosynthesis pathway of Aspergillus nidulans, and used it to create a composite part including the GFP gene. The functionality of these parts was demonstrated in the model fungal organism Cochliobolus heterostrophus, and as these tools are in modular BioBrick format, they can be easily used to facilitate genetic engineering of other fungal species.

An arsenic-specific biosensor with genetically engineered Shewanella oneidensis in a bioelectrochemical system.

Genetically engineered microbial biosensors have yet to realize commercial success in environmental applications due, in part, to difficulties associated with transducing and transmitting traditional bioluminescent information. Bioelectrochemical systems (BESs) output a direct electric signal that can be incorporated into devices for remote environmental monitoring. Here, we describe a BES-based biosensor with genetically encoded specificity for a toxic metal. By placing an essential component of the metal reduction (Mtr) pathway of Shewanella oneidensis under the control of an arsenic-sensitive promoter, we have genetically engineered a strain that produces increased current in response to arsenic when inoculated into a BES. Our BES-based biosensor has a detection limit of ~40 µM arsenite with a linear range up to 100 µM arsenite. Because our transcriptional circuit relies on the activation of a single promoter, similar sensing systems may be developed to detect other analytes by the swap of a single genetic part.