Various cellular stress components change as the rat ages: An insight into the putative overall age-related cellular stress network

The neurobiological effects of senescence on dopaminergic system: A comprehensive review

Over time, the body undergoes a natural, multifactorial, and ongoing process named senescence, which induces changes at the molecular, cellular, and micro-anatomical levels in many body systems. The brain, being a highly complex organ, is particularly affected by this process, potentially impairing its numerous functions. The brain relies on chemical messengers known as neurotransmitters to function properly, with dopamine being one of the most crucial. This catecholamine is responsible for a broad range of critical roles in the central nervous system, including movement, learning, cognition, motivation, emotion, reward, hormonal release, memory consolidation, visual performance, sexual drive, modulation of circadian rhythms, and brain development. In the present review, we thoroughly examine the impact of senescence on the dopaminergic system, with a primary focus on the classic delimitations of the dopaminergic nuclei from A8 to A17. We provide in-depth information about their anatomy and function, particularly addressing how senescence affects each of these nuclei.

Network analysis of the autophagy biochemical network in relation to various autophagy-targeted proteins found among SARS-CoV-2 variants of concern

Autophagy is an important cellular process that triggers a coordinated action involving multiple individual proteins and protein complexes while SARS-CoV-2 (SARS2) was found to both hinder autophagy to evade host defense and utilize autophagy for viral replication. Interestingly, the possible significant stages of the autophagy biochemical network in relation to the corresponding autophagy-targeted SARS2 proteins from the different variants of concern (VOC) were never established. In this study, we performed the following: autophagy biochemical network design and centrality analyses; generated autophagy-targeted SARS2 protein models; and superimposed protein models for structural comparison. We identified 2 significant biochemical pathways (one starts from the ULK complex and the other starts from the PI3P complex) within the autophagy biochemical network. Similarly, we determined that the autophagy-targeted SARS2 proteins (Nsp15, M, ORF7a, ORF3a, and E) are structurally conserved throughout the different SARS2 VOC suggesting that the function of each protein is preserved during SARS2 evolution. Interestingly, among the autophagy-targeted SARS2 proteins, the M protein coincides with the 2 significant biochemical pathways we identified within the autophagy biochemical network. In this regard, we propose that the SARS2 M protein is the main determinant that would influence autophagy outcome in regard to SARS2 infection.

Network analytics approach towards identifying potential antivirulence drug targets within the Staphylococcus aureus staphyloxanthin biosynthetic network

Staphylococcus aureus is associated with several clinically significant infections among humans and infections associated with antibiotic-resistant strains are growing in frequency. Antivirulence strategies shift the target of drugs from bacterial growth to the infection process resulting to milder evolutionary pressure for the development of bacterial resistant strains. Staphyloxanthin (STX) is a yellowish-orange carotenoid pigment synthesized by S. aureus and this carotenoid functions as an important virulence factor for the bacteria. In this study, we elucidated whether network analytics can be used as a viable tool to identify significant components in the STX biosynthetic network which in-turn could serve as possible antivirulence drug targets. For confirmation, we correlated our results to known drugs that were able to inhibit STX biosynthesis. Throughout this study, we established that crtN(1) activity and 4,4'-diaponeurosporene amounts are significant components in the STX biosynthetic network and, moreover, network analytics can aid in identifying antivirulence drug targets within the STX biosynthetic network. Similarly, we found that network analytics is capable of identifying multiple potential targets simultaneously. Taken together, we propose that an effective antivirulence drug against S. aureus STX biosynthesis would involve targeting crtN(1) activity, 4,4'-diaponeurosporene levels, or both components.