BosR and PlzA reciprocally regulate RpoS function to sustain Borrelia burgdorferi in ticks and mammals.

The RNA polymerase alternative σ factor RpoS in Borrelia burgdorferi (Bb), the Lyme disease pathogen, is responsible for programmatic-positive and -negative gene regulation essential for the spirochete's dual-host enzootic cycle. RpoS is expressed during tick-to-mammal transmission and throughout mammalian infection. Although the mammalian-phase RpoS regulon is well described, its counterpart during the transmission blood meal is unknown. Here, we used Bb-specific transcript enrichment by tick-borne disease capture sequencing (TBDCapSeq) to compare the transcriptomes of WT and ΔrpoS Bb in engorged nymphs and following mammalian host-adaptation within dialysis membrane chambers. TBDCapSeq revealed dramatic changes in the contours of the RpoS regulon within ticks and mammals and further confirmed that RpoS-mediated repression is specific to the mammalian-phase of Bb's enzootic cycle. We also provide evidence that RpoS-dependent gene regulation, including repression of tick-phase genes, is required for persistence in mice. Comparative transcriptomics of engineered Bb strains revealed that the Borrelia oxidative stress response regulator (BosR), a noncanonical Fur family member, and the cyclic diguanosine monophosphate (c-di-GMP) effector PlzA reciprocally regulate the function of RNA polymerase complexed with RpoS. BosR is required for RpoS-mediated transcription activation and repression in addition to its well-defined role promoting transcription of rpoS by the RNA polymerase alternative σ factor RpoN. During transmission, ligand-bound PlzA antagonizes RpoS-mediated repression, presumably acting through BosR.

Engineering a "detect and destroy" skin probiotic to combat methicillin-resistant Staphylococcus aureus.

The prevalence and virulence of pathogens such as methicillin-resistant Staphylococcus (S.) aureus (MRSA), which can cause recurrent skin infections, are of significant clinical concern. Prolonged antibiotic exposure to treat or decolonize S. aureus contributes to development of antibiotic resistance, as well as depletion of the microbiome, and its numerous beneficial functions. We hypothesized an engineered skin probiotic with the ability to selectively deliver antimicrobials only in the presence of the target organism could provide local bioremediation of pathogen colonization. We constructed a biosensing S. epidermidis capable of detecting the presence of S. aureus quorum sensing autoinducer peptide and producing lysostaphin in response. Here, we demonstrate in vitro activity of this biosensor and present and discuss challenges to deployment of this and other engineered topical skin probiotics.

A Markovian Entropy Measure for the Analysis of Calcium Activity Time Series.

Methods to analyze the dynamics of calcium activity often rely on visually distinguishable features in time series data such as spikes, waves, or oscillations. However, systems such as the developing nervous system display a complex, irregular type of calcium activity which makes the use of such methods less appropriate. Instead, for such systems there exists a class of methods (including information theoretic, power spectral, and fractal analysis approaches) which use more fundamental properties of the time series to analyze the observed calcium dynamics. We present a new analysis method in this class, the Markovian Entropy measure, which is an easily implementable calcium time series analysis method which represents the observed calcium activity as a realization of a Markov Process and describes its dynamics in terms of the level of predictability underlying the transitions between the states of the process. We applied our and other commonly used calcium analysis methods on a dataset from Xenopus laevis neural progenitors which displays irregular calcium activity and a dataset from murine synaptic neurons which displays activity time series that are well-described by visually-distinguishable features. We find that the Markovian Entropy measure is able to distinguish between biologically distinct populations in both datasets, and that it can separate biologically distinct populations to a greater extent than other methods in the dataset exhibiting irregular calcium activity. These results support the benefit of using the Markovian Entropy measure to analyze calcium dynamics, particularly for studies using time series data which do not exhibit easily distinguishable features.