Biology subjects

Fedorov, D.

Publications and source records attributed to Fedorov, D..

5 recordsLinked to original sources

bioRxiv2025

A phenomenological interpretation of multiple bursting patterns in Lateral Habenula neurons

The Lateral Habenula (LHb) is a small brain structure specialized in encoding aversive signals. Bursting activity in the LHb has been consistently linked to mood regulation, with increased bursting activity proposed to promote depressive behaviors. Bursting is a complex dynamic process that has been extensively studied and modeled in other neuronal contexts. However, at the LHb this type of activity has typically been described only as transient periods of high frequency firing. Here, to provide a deeper understanding of LHb bursting, we analyzed this activity from the perspective of dynamical systems. Ex vivo, LHb neurons display a variety of bursting patterns, characterized at one extreme by a dominating square-wave type and in other by parabolic type, plus transitional forms referred to as triangular bursting. Notably, these bursting patterns, which reflect different LHb output modes, can occur within the same neuron, suggesting that they may correspond to distinct dynamic states of the same LHb neuron. To capture these complex behaviors, we propose an idealized multiple-timescale dynamical model. This model successfully reproduces the three main bursting patterns observed in experimental data. Furthermore, we identify a special point in the parameter space, termed the saddle-node homoclinic bifurcation, which acts as an organizing center demarcating the boundary between the two primary bursting patterns and around which the third pattern appear. Our model suggests that LHb bursting activity is structured around distinct dynamic states with potentially diverse and unexplored impacts on mood regulation. By providing new insights into the dynamic principles underlying LHb bursting, this framework may advance our understanding of its biological significance.

neuroscience↗

bioRxiv2023

CyVerse: Cyberinfrastructure for Open Science

CyVerse, the largest publicly-funded open-source research cyberinfrastructure for life sciences, has played a crucial role in advancing data-driven research since the 2010s. As the technology landscape evolved with the emergence of cloud computing platforms, machine learning and artificial intelligence (AI) applications, CyVerse has enabled access by providing interfaces, Software as a Service (SaaS), and cloud-native Infrastructure as Code (IaC) to leverage new technologies. CyVerse services enable researchers to integrate institutional and private computational resources, custom software, perform analyses, and publish data in accordance with open science principles. Over the past 13 years, CyVerse has registered more than 110,000 verified accounts from 160 countries and was used for over 1,600 peer-reviewed publications. Since 2011, 45,000 students and researchers have been trained to use CyVerse. The platform has been replicated and deployed in two countries outside the US, with additional private deployments on commercial clouds for US government agencies and multinational corporations. In this manuscript, we present a strategic blueprint for creating and managing SaaS cyberinfrastructure and IaC as free and open-source software.

scientific communication and education↗

bioRxiv2023

Repurposing host-guest chemistry to sequester virulence and eradicate biofilms in multidrug resistant Pseudomonas aeruginosa and Acinetobacter baumannii

The limited diversity in targets of available antibiotic therapies has put tremendous pressure on the treatment of bacterial pathogens, where numerous resistance mechanisms that counteract their function are becoming increasingly prevalent. Here, we utilize an unconventional anti-virulence screen of host-guest interacting macrocycles, and identify a water-soluble synthetic macrocycle, Pillar[5]arene, that is non-bactericidal/bacteriostatic and has a mechanism of action that involves binding to both homoserine lactones and lipopolysaccharides, key virulence factors in Gram-negative pathogens. Pillar[5]arene is active against Top Priority carbapenem- and third/fourth-generation cephalosporin-resistant Pseudomonas aeruginosa and Acinetobacter baumannii, suppressing toxins and biofilms and increasing the penetration and efficacy of standard-of-care antibiotics in combined administrations. The binding of homoserine lactones and lipopolysaccharides also sequesters their direct effects as toxins on eukatryotic membranes, neutralizing key tools that promote bacterial colonization and impede immune defenses, both in vitro and in vivo. Pillar[5]arene evades both existing antibiotic resistance mechanisms, as well as the build-up of rapid tolerance/resistance. The versatility of macrocyclic host-guest chemistry provides ample strategies for tailored targeting of virulence in a wide range of Gram-negative infectious diseases.

biochemistry↗

bioRxiv2019

Genome Complexity Browser: estimation and visualization of prokaryote genome variability

MotivationComparative genomics studies may be used to acquire new knowledge about chromosomal architecture - the rules to combine a set of genes in a genome of a living organism. Hundreds of thousands of prokaryote genomes were sequenced and assembled. Still, there is a lack of computational tools able to compare hundreds of genomes simultaneously, i.e. to find hotspots of genome rearrangements and horizontal gene transfer or to analyze which part of an operon is conservative and which is variable.\n\nResultsWe developed Genomic Complexity Browser (GCB), a tool that allows to visualize gene contexts in a graph form and evaluate genome variability of different parts of a prokaryotic chromosome. We introduce a measure called complexity, which is an indirect measure of genome variability. Intraspecies and interspecies comparisons reveal that regions with high complexity tend to be located in a similar context in different strains and species. While many of such hot spots are associated with prophages and pathogenicity islands, some of them lack these determinants and mechanisms that govern their dynamics are to be elucidated.\n\nAvailabilityGCB is freely available as a web server at http://gcb.rcpcm.org and as a stand-alone application at https://github.com/DNKonanov/GCB\n\nContactparaslonic@gmail.com

bioinformatics↗

bioRxiv2019

Analyzing the weak dimerization of a cellulose binding module by sedimentation velocity experiments

Cellulose binding modules (CBMs) are found widely in different proteins that act on cellulose. Because they allow a very easy way of binding recombinant proteins to cellulose, they have become widespread in many biotechnological applications involving cellulose. One commonly used variant is the CBMCipA from Clostridium thermocellum. Here we studied the dimerization of CBMCipA, because we were interested if its solution behavior could have an impact on its use in biotechnical applications. As the principal approach, we used sedimentation velocity analytical ultracentrifugation. To enhance our understanding of the possible interactions, we used molecular dynamics simulations. By analysis of the sedimentation velocity data using a discrete model genetic algorithm we found that the CBMCipA shows a weak dimerization interaction with a dissociation constant KD of about 87 M. As the KD of CBMCipA binding to cellulose is about 0.6 M, we conclude that the dimerization is unlikely to affect cellulose binding. However, at the high concentrations used in some applications of the CMBCipA, its dimerization is likely to have an effect on its solution behavior. The work shows that analytical ultracentrifugation is a very efficient tool to analyze this type of weak interactions. Moreover, we provide here a protocol for data analysis in the program Ultrascan for determining dissociation constants by sedimentation velocity experiments.

biophysics↗