Mairesse, O. | Search bioRxiv

bioRxiv2024

Sleep Fragmentation Modulates the Neurophysiological Correlates of Cognitive Fatigue

Cognitive fatigue (CF) is a critical factor affecting performance and well-being. It can be altered in suboptimal sleep quality conditions, e.g., in patients suffering from obstructive sleep apnea who experience both intermittent hypoxia and sleep fragmentation (SF). Understanding the neurophysiological basis of SF in healthy individuals can provide insights to improve cognitive functioning in disrupted sleep conditions. In this electroencephalographical (EEG) study, we investigated in 16 healthy young participants the impact of experimentally induced SF on the neurophysiological correlates of CF measured before, during, and after practice on the TloadDback, a working memory task tailored to each individuals maximal cognitive resources. Participants spent two times three consecutive nights in the laboratory, once in an undisrupted sleep (UdS) condition and once in a SF condition induced by non-awakening auditory stimulations, counterbalanced, and performed the TloadDback task both in a high (HCL) and a low (LCL) cognitive load condition. EEG activity was recorded during wakefulness in the 5-minutes resting state immediately before and after, as well as during the 16-minutes of the TloadDback task practice. In the high cognitive load under sleep fragmentation (HCL/SF) condition, high beta power increased during the TloadDback indicating heightened cognitive effort, and beta and alpha power increased in the post- vs. pre task resting state, suggesting a relaxation rebound. In the low cognitive load/undisturbed sleep (LCL/UdS) condition, low beta activity increased suggesting a relaxed focus, as well as mid beta activity associated with active thinking. These findings highlight the dynamic impact of SF on the neurophysiological correlates of CF and underscore the importance of sleep quality and continuity to maintain optimal cognitive functioning.

neuroscience↗

bioRxiv2024

Pear flower and leaf microbiome dynamics during the naturally occurring spread of Erwinia amylovora

Erwinia amylovora is the causal pathogen of fire blight, a contagious disease that affects apple and pear trees and other members of the family Rosaceae. In this study, we investigated the population dynamics of the pear flower microbiome in an agricultural setting during the naturally occurring infection of E. amylovora. Five potential factors were considered: collection date, the flowers phenological stage, location on the tree, location within the orchard, and pear cultivar. The phenological stage and the collection date were identified as the most important factors associated with pear flower microbiome composition. The location of the tree in the orchard and the flowers location on the tree had a marginal effect on the microbiome composition. The leaf microbiome reflected that of the abundant phenological stage on each date. The flower microbiome shifted towards E. amylovora, dominating the community as time and phenological stages progressed, leading to decreased community diversity. The strain population of E. amylovora remained similar throughout the entire collection period. In contrast, other taxa, including Pseudomonas, Pantoea, Lactobacillus, and Sphingomonas, were represented by dozens of amplicon sequence variants (ASVs), and different succession patterns in their populations were observed. Some of the taxa identified include known antagonists to E. amylovora. Overall, our results suggest that flower physiology and the interaction with the environment are strongly associated with the pear flower microbiome and should be considered separately. Strain succession patterns for the different taxa under E. amylovora spread may help in choosing candidates for antagonist-based treatments for fire blight. ImportanceThe spread of pathogens in plants is an important ecological phenomenon and has a significant economic impact on agriculture. Flowers serve as the entry point for E. amylovora, but members of the flower microbiome can inhibit or slow down the proliferation and penetration of the pathogen. Knowledge about leaf and flower microbiome response to the naturally occurring spread of E. amylovora is still lacking. The current study is the first to describe the flower microbiome dynamics during the naturally occurring infection of E. amylovora. Unlike previous studies, our experiment design enabled us to evaluate the contribution of five important environmental parameters to the community composition. We identified different strain succession patterns across different taxa in the flower consortia throughout the season. These results contribute to our understanding of plant microbial ecology during pathogen spread and can help to improve biological treatments for these diseases.

microbiology↗