Development of a qPCR Protocol to Detect the Cotton Bacterial Blight Pathogen, Xanthomonas citri pv. malvacearum, from Cotton Leaves and Seeds.

Bacterial blight, historically a seed-borne disease of cotton (Gossypium hirsutum) is caused by Xanthomonas citri pv. malvacearum, resulted in significant economic losses prior to development of resistant varieties and implementation of acid-delinting of planting seed. Periodic outbreaks have been associated with seed since the early twentieth century; of note, the disease has experienced a resurgence since 2011. Effective management of bacterial blight is dependent on accurate diagnosis and detection of the pathogen. Currently, detection of X. citri pv. malvacearum is performed by time-consuming microbiological methods. In this study, a novel and sensitive TaqMan-based qPCR protocol was developed to test for X. citri pv. malvacearum in cotton plant tissue. The primers developed are specific to five races of X. citri pv. malvacearum, but not to other Xanthomonas species or cotton-associated nonpathogenic bacteria. The efficiency of this assay was evaluated on artificially inoculated cotton leaves and seed, on naturally infected cotton leaves, and on bolls and seed originating from bacterial blight symptomatic bolls. The protocol's efficiency from artificially inoculated plant tissue was 102 copies g-1 and 37 copies from 1 g seed for leaves and seed, respectively. In addition, X. citri pv. malvacearum was detected from 94% of the seed samples originating from blight symptomatic bolls. The qPCR protocol provides a rapid and accurate method for diagnosis and detection of bacterial blight and offers a tool for monitoring X. citri pv. malvacearum and potentially reducing its spread in seed.

Developmental depression-to-facilitation shift controls excitation-inhibition balance.

Changes in the short-term dynamics of excitatory synapses over development have been observed throughout cortex, but their purpose and consequences remain unclear. Here, we propose that developmental changes in synaptic dynamics buffer the effect of slow inhibitory long-term plasticity, allowing for continuously stable neural activity. Using computational modeling we demonstrate that early in development excitatory short-term depression quickly stabilises neural activity, even in the face of strong, unbalanced excitation. We introduce a model of the commonly observed developmental shift from depression to facilitation and show that neural activity remains stable throughout development, while inhibitory synaptic plasticity slowly balances excitation, consistent with experimental observations. Our model predicts changes in the input responses from phasic to phasic-and-tonic and more precise spike timings. We also observe a gradual emergence of short-lasting memory traces governed by short-term plasticity development. We conclude that the developmental depression-to-facilitation shift may control excitation-inhibition balance throughout development with important functional consequences.

Model-Based Inference of Synaptic Transmission.

Synaptic computation is believed to underlie many forms of animal behavior. A correct identification of synaptic transmission properties is thus crucial for a better understanding of how the brain processes information, stores memories and learns. Recently, a number of new statistical methods for inferring synaptic transmission parameters have been introduced. Here we review and contrast these developments, with a focus on methods aimed at inferring both synaptic release statistics and synaptic dynamics. Furthermore, based on recent proposals we discuss how such methods can be applied to data across different levels of investigation: from intracellular paired experiments to in vivo network-wide recordings. Overall, these developments open the window to reliably estimating synaptic parameters in behaving animals.