Casal, M. | bioRxiv Science

bioRxiv2022

NIT: an open-source tool for information theoretic analysis of neural population data

Information theory provides a popular and principled framework for the analysis of neural data. It allows to uncover in an assumption-free way how neurons encode and transmit information, capturing both linear and non-linear coding mechanisms and including the information carried by interactions of any order. To facilitate its application, here we present Neuroscience Information Toolbox (NIT), a new toolbox for the accurate information theoretical analysis of neural data. NIT contains widely used tools such as limited sampling bias corrections and discretization of neural probabilities for the calculation of stimulus coding in low-dimensional representation of neural activity (e.g. Local Field Potentials or the activity of small neural population).Importantly, it adds a range of recent tools for quantifying information encoding by large populations of neurons or brain areas, for the directed transmission of information between neurons or areas, and for the calculation of Partial Information Decompositions to quantify the behavioral relevance of neural information and the synergy and redundancy among neurons and brain areas. Further, because information theoretic algorithms have been previously validated mainly with electrophysiological recordings, here we used realistic simulations and analysis of real data to study how to optimally apply information theory to the analysis of two-photon calcium imaging data, which are particularly challenging due to their lower signal-to-noise and temporal resolution. We also included algorithms (based on parametric and non-parametric copulas) to compute robustly information specifically with analog signals such as calcium traces. We provide indications on how to best process calcium imaging traces and to apply NIT depending on the type of calcium indicator, imaging frame rate and firing rate levels. In sum, NIT provides a toolbox for the comprehensive and effective information theoretic analysis of all kinds of neural data, including calcium imaging.

neuroscience↗

bioRxiv2021

Interactions of cytosolic termini of the Jen1 monocarboxylate transporter are critical for trafficking, transport activity and endocytosis

Plasma membrane (PM) transporters of the major facilitator superfamily (MFS) are essential for cell metabolism and growth, as well as for survival in response to stress or cytotoxic drugs, in both prokaryotes and eukaryotes. In the yeast Saccharomyces cerevisiae, Jen1 is a monocarboxylate/H+ symporter that has been used to dissect the molecular details underlying control of cellular expression, transport mechanism and turnover of MFS transporters. Here, we present evidence supporting previously non-described roles of the cytosolic N- and C- termini in Jen1 biogenesis, PM stability and activity, through functional analyses of rationally designed truncations and chimeric constructs with UapA, a S. cerevisiae endocytosis-insensitive purine transporter from Aspergillus nidulans. Our results reveal a cryptic role of the N-terminal region and thus show that both cytosolic N- and C-termini are critical for Jen1 trafficking to the PM, transport activity and endocytosis. In particular, we provide evidence that the N- and the C-cytosolic termini of Jen1 undergo transport-dependent dynamic intra-molecular interactions, which critically affect the mechanism of transport and turnover of Jen1. Our results support an emerging concept where the cytosolic tails of PM transporters control transporter expression and function, through flexible intra-molecular interactions with each other and the transmembrane core of the protein. This idea may be extended to other MFS members providing a deeper understanding of conserved, but also evolving, mechanisms underlying MFS transporter structure-function relationships.

microbiology↗