Atg9-centered multi-omics integration reveals new autophagy regulators in Saccharomyces cerevisiae

Omic AI reveals new autophagy regulators from the Atg1 interactome in Saccharomyces cerevisiae

In Saccharomyces cerevisiae, Atg1 is a core autophagy-related (Atg) protein kinase (PK) in regulating macroautophagy/autophagy, by physically interacting with numerous other proteins, or by phosphorylating various substrates. It is unclear how many Atg1-interacting partners and substrates are also involved in regulating autophagy. Here, we conducted transcriptomic, proteomic and phosphoproteomic profiling of Atg1-dependent molecular landscapes during nitrogen starvation-triggered autophagy, and detected 244, 245 and 217 genes to be affected by ATG1 in the autophagic process at mRNA, protein, and phosphorylation levels, respectively. Based on the Atg1 interactome, we developed a novel artificial intelligence (AI) framework, inference of autophagy regulators from multi-omic data (iAMD), and predicted 12 Atg1-interacting partners and 17 substrates to be potentially functional in autophagy. Further experiments validated that Rgd1 and Whi5 are required for bulk autophagy, as well as physical interactions and co-localizations with Atg1 during autophagy. In particular, we demonstrated that 2 phosphorylation sites (p-sites), pS78 and pS149 of Whi5, are phosphorylated by Atg1 to regulate the formation of Atg1 puncta during autophagy initiation. A working model was illustrated to emphasize the importance of the Atg1-centered network in yeast autophagy. In addition, iAMD was extended to accurately predict Atg proteins and autophagy regulators from other PK interactomes, indicating a high transferability of the method. Taken together, we not only revealed new autophagy regulators from the Atg1 interactome, but also provided a useful resource for further analysis of yeast autophagy.

Structural robustness and temporal vulnerability of the starvation-responsive metabolic network in healthy and obese mouse liver

Adaptation to starvation is a multimolecular and temporally ordered process. We sought to elucidate how the healthy liver regulates various molecules in a temporally ordered manner during starvation and how obesity disrupts this process. We used multiomic data collected from the plasma and livers of wild-type and leptin-deficient obese (ob/ob) mice at multiple time points during starvation to construct a starvation-responsive metabolic network that included responsive molecules and their regulatory relationships. Analysis of the network structure showed that in wild-type mice, the key molecules for energy homeostasis, ATP and AMP, acted as hub molecules to regulate various metabolic reactions in the network. Although neither ATP nor AMP was responsive to starvation in ob/ob mice, the structural properties of the network were maintained. In wild-type mice, the molecules in the network were temporally ordered through metabolic processes coordinated by hub molecules, including ATP and AMP, and were positively or negatively coregulated. By contrast, both temporal order and coregulation were disrupted in ob/ob mice. These results suggest that the metabolic network that responds to starvation was structurally robust but temporally disrupted by the obesity-associated loss of responsiveness of the hub molecules. In addition, we propose how obesity alters the response to intermittent fasting.

Drosophila as a Robust Model System for Assessing Autophagy: A Review

Autophagy is the process through which a body breaks down and recycles its own cellular components, primarily inside lysosomes. It is a cellular response to starvation and stress, which plays decisive roles in various biological processes such as senescence, apoptosis, carcinoma, and immune response. Autophagy, which was first discovered as a survival mechanism during starvation in yeast, is now known to serve a wide range of functions in more advanced organisms. It plays a vital role in how cells respond to stress, starvation, and infection. While research on yeast has led to the identification of many key components of the autophagy process, more research into autophagy in more complex systems is still warranted. This review article focuses on the use of the fruit fly Drosophila melanogaster as a robust testing model in further research on autophagy. Drosophila provides an ideal environment for exploring autophagy in a living organism during its development. Additionally, Drosophila is a well-suited compact tool for genetic analysis in that it serves as an intermediate between yeast and mammals because evolution conserved the molecular machinery required for autophagy in this species. Experimental tractability of host-pathogen interactions in Drosophila also affords great convenience in modeling human diseases on analogous structures and tissues.

Autophagy Alters the Susceptibility of Candida albicans Biofilms to Antifungal Agents

Candida albicans (C. albicans) reigns as a major cause of clinical candidiasis. C. albicans biofilms are known to increase resistance to antifungal agents, making biofilm-related infections particularly challenging to treat. Drug resistance is of particular concern due to the spread of multidrug-resistant fungal pathogens, while autophagy is crucial for the maintenance of cellular homeostasis. Therefore, this study aimed to investigate the effects of an activator and an inhibitor of autophagy on the susceptibility of C. albicans biofilms to antifungal agents and the related mechanisms. The susceptibility of C. albicans biofilms to different antifungal agents after treatment with or without the autophagy activator or inhibitor was evaluated using XTT assay. Alkaline phosphatase (ALP) activity and reactive oxygen species (ROS) level, as well as the expression of ROS-related and autophagy-related genes, were examined to evaluate the autophagic activity of C. albicans biofilms when treated with antifungal agents. The autophagosomes were observed by transmission electron microscopy (TEM). The susceptibility of C. albicans biofilms to antifungal agents changed when autophagy changed. The ALP activity and ROS level of C. albicans biofilms increased with the treatment of antifungal agents, and autophagosomes could be observed in C. albicans biofilms. Autophagy was involved in the susceptibility of C. albicans biofilms to antifungal agents.

Autophagy in hepatic ischemia-reperfusion injury

Hepatic ischemia-reperfusion injury (HIRI) is a major complication of liver resection or liver transplantation that can seriously affect patient's prognosis. There is currently no definitive and effective treatment strategy for HIRI. Autophagy is an intracellular self-digestion pathway initiated to remove damaged organelles and proteins, which maintains cell survival, differentiation, and homeostasis. Recent studies have shown that autophagy is involved in the regulation of HIRI. Numerous drugs and treatments can change the outcome of HIRI by controlling the pathways of autophagy. This review mainly discusses the occurrence and development of autophagy, the selection of experimental models for HIRI, and the specific regulatory pathways of autophagy in HIRI. Autophagy has considerable potential in the treatment of HIRI.

Response of genes related to iron and porphyrin transport in Porphyromonas gingivalis to blue light

BACKGROUND

Antimicrobial blue light (aBL) kills a variety of bacteria, including Porphyromonas gingivalis. However, little is known about the transcriptomic response of P. gingivalis to aBL therapy. This study was designed to evaluate the selective cytotoxicity of aBL against P. gingivalis over human cells and to further investigate the genetic response of P. gingivalis to aBL at the transcriptome level.

METHODS

Colony forming unit (CFU) testing, confocal laser scanning microscopy (CLSM), and scanning electron microscopy (SEM) were used to investigate the antimicrobial effectiveness of blue light against P. gingivalis. The temperatures of the irradiated targets were measured to prevent overheating. Multiple fluorescent probes were used to quantify reactive oxygen species (ROS) generation after blue-light irradiation. RNA sequencing (RNA-seq) was used to investigate the changes in global gene expression. Following the screening of target genes, real-time quantitative polymerase chain reaction (RT-qPCR) was performed to confirm the regulation of gene expression.

RESULTS

A 405 nm aBL at 100 mW/cm² significantly killed P. gingivalis within 5 min while sparing human gingival fibroblasts (HGFs). No obvious temperature changes were detected in the irradiated surface under our experimental conditions. RNA-seq showed that the transcription of multiple genes was regulated, and RT-qPCR revealed that the expression levels of the genes RgpA and RgpB, which may promote heme uptake, as well as the genes Ftn and FetB, which are related to iron homeostasis, were significantly upregulated. The expression levels of the FeoB-2 and HmuR genes, which are related to hydroxyl radical scavenging, were significantly downregulated.

CONCLUSIONS

aBL strengthens the heme uptake and iron export gene pathways while reducing the ROS scavenging pathways in P. gingivalis, thus improving the accumulation of endogenous photosensitizers and enhancing oxidative damage to P. gingivalis.

iPCD: A Comprehensive Data Resource of Regulatory Proteins in Programmed Cell Death

Programmed cell death (PCD) is an essential biological process involved in many human pathologies. According to the continuous discovery of new PCD forms, a large number of proteins have been found to regulate PCD. Notably, post-translational modifications play critical roles in PCD process and the rapid advances in proteomics have facilitated the discovery of new PCD proteins. However, an integrative resource has yet to be established for maintaining these regulatory proteins. Here, we briefly summarize the mainstream PCD forms, as well as the current progress in the development of public databases to collect, curate and annotate PCD proteins. Further, we developed a comprehensive database, with integrated annotations for programmed cell death (iPCD), which contained 1,091,014 regulatory proteins involved in 30 PCD forms across 562 eukaryotic species. From the scientific literature, we manually collected 6493 experimentally identified PCD proteins, and an orthologous search was then conducted to computationally identify more potential PCD proteins. Additionally, we provided an in-depth annotation of PCD proteins in eight model organisms, by integrating the knowledge from 102 additional resources that covered 16 aspects, including post-translational modification, protein expression/proteomics, genetic variation and mutation, functional annotation, structural annotation, physicochemical property, functional domain, disease-associated information, protein–protein interaction, drug–target relation, orthologous information, biological pathway, transcriptional regulator, mRNA expression, subcellular localization and DNA and RNA element. With a data volume of 125 GB, we anticipate that iPCD can serve as a highly useful resource for further analysis of PCD in eukaryotes.