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The bacterial Lux system is used as a gene expression reporter. It is fast, sensitive and non-destructive, enabling high frequency measurements. Originally developed for bacterial cells, it has also been adapted for eukaryotic cells, and can be used for whole cell biosensors, or in real time with live animals without the need for euthanasia. However, correct interpretation of bioluminescent data is limited: the bioluminescence is different from gene expression because of nonlinear molecular and enzyme dynamics of the Lux system. We have developed a computational approach that, for the first time, allows users of Lux assays to infer gene transcription levels from the light output. This approach is based upon a new mathematical model for Lux activity, that includes the actions of LuxAB, LuxEC and Fre, with improved mechanisms for all reactions, as well as synthesis and turn-over of Lux proteins. The model is calibrated with new experimental data for the LuxAB and Fre reactions from Photorhabdus luminescens—the source of modern Lux reporters—while literature data has been used for LuxEC. Importantly, the data show clear evidence for previously unreported product inhibition for the LuxAB reaction. Model simulations show that predicted bioluminescent profiles can be very different from changes in gene expression, with transient peaks of light output, very similar to light output seen in some experimental data sets. By incorporating the calibrated model into a Bayesian inference scheme, we can reverse engineer promoter activity from the bioluminescence. We show examples where a decrease in bioluminescence would be better interpreted as a switching off of the promoter, or where an increase in bioluminescence would be better interpreted as a longer period of gene expression. This approach could benefit all users of Lux technology.

Identifying genes and traits that have diverged during domestication provides key information of importance for maintaining and even increasing yield and nutrients in existing crops. A ‘bottom up’ population genetics approach was used to identify signatures of selection across the eggplant genome, to better understand the process of domestication. RNA-seq data was obtained for four wild eggplants (Solanum insanum L.) and 16 domesticated eggplants (S. melongena L.) and mapped to the eggplant genome. SNPs exhibiting signatures of selection in domesticates were identified as those exhibiting high FST between the two populations (evidence of significant divergence) and low π for the domesticated population (indicative of a selective sweep). Some of these regions appear to overlap with previously identified QTL for domestication traits. Genes in regions of linkage disequilibrium surrounding these SNPs were searched against the Arabidopsis thaliana and tomato genomes to find orthologues. Subsequent Gene Ontology (GO) enrichment analysis identified over-representation of GO terms related to photosynthesis and response to the environment. This work reveals genomic changes involved in eggplant domestication and improvement, and how this compares to observed changes in the tomato genome, revealing shared chromosomal regions involved in the domestication of both species.

23The bacterial Lux system is used as a gene expression reporter. It is fast, sen-24 sitive and non-destructive, enabling high frequency measurements. Originally 25 developed for bacterial cells, it has been adapted for eukaryotic cells, and can 26 be used for whole cell biosensors, or in real time with live animals without the 27 need for slaughter. However, correct interpretation of bioluminescent data is 28 limited: the bioluminescence is different from gene expression because of non-29 linear molecular and enzyme dynamics of the Lux system. We have developed 30 a modelling approach that, for the first time, allows users of Lux assays to infer 31 gene transcription levels from the light output. We show examples where a de-32 crease in bioluminescence would be better interpreted as a switching off of the 33 promoter, or where an increase in bioluminescence would be better interpreted 34 as a longer period of gene expression. This approach could benefit all users of 35 Lux technology. 36 Introduction 37The lux operon contains genes for the bacterial bioluminescent reaction [1, 2]: 38 luxA and luxB encode the α and β subunits of the heterodimeric bacterial lu-39 ciferase; luxC encodes a 54kDa fatty acid reductase; luxD encodes a 33kDa acyl 40 transferase; and luxE encodes a 42kDa acylprotein synthetase. These genes, 41 including their order (luxCDABE ), are conserved in all lux systems of biolumi-42 nescent bacteria. An additional gene (luxF ), with homology to luxA and luxB, 43 is located between luxB and luxE in some species. The light emitting reaction, 44 catalysed by the LuxAB complex, involves the oxidation of FMNH 2 and the 45 conversion of a long chain fatty aldehyde (tetradecanal in vivo) to its cognate 46 acid, with the emission of blue-green light. LuxC, D and E together form the 47 fatty acid reductase complex, involved in a series of reactions that recycle the 48 fatty acid back to aldehyde. In E. coli and other species, Fre has been shown 49 to be the enzyme responsible for flavin reduction back to FMNH 2 . 50Gene expression can be measured by cloning a promoter of interest upstream 51 of the lux operon, and interpreting the bioluminescence from bacteria containing 52 such constructs as a measure of transcription [3, 4]. This provides a reporter 53 that can measure gene expression at high frequency and with less background 54 noise than other reporters, such as GFP [5, 4], and has found great value in 55 both bacteria [6] and eukaryotes[7], with important recent applications in whole 56 2 cell biosensors[8], live animal infection models[9, 10] and live tumour infection 57 models[11]. 58 However, this light is an integrated signal of transcription, mRNA half-59 life, translation and protein turn-over, the bioluminescence reaction kinetics 60and substrate availability and cycling. As a consequence, absolute transcription 61 activity cannot be directly inferred from the data generated. This is a limitation 62 in the current use of Lux technologies. For example, some studies using Lux 63 ...