AutophagyNet: high-resolution data source for the analysis of autophagy and its regulation.

Macroautophagy/autophagy is a highly-conserved catabolic procss eliminating dysfunctional cellular components and invading pathogens. Autophagy malfunction contributes to disorders such as cancer, neurodegenerative and inflammatory diseases. Understanding autophagy regulation in health and disease has been the focus of the last decades. We previously provided an integrated database for autophagy research, the Autophagy Regulatory Network (ARN). For the last eight years, this resource has been used by thousands of users. Here, we present a new and upgraded resource, AutophagyNet. It builds on the previous database but contains major improvements to address user feedback and novel needs due to the advancement in omics data availability. AutophagyNet contains updated interaction curation and integration of over 280,000 experimentally verified interactions between core autophagy proteins and their protein, transcriptional and post-transcriptional regulators as well as their potential upstream pathway connections. AutophagyNet provides annotations for each core protein about their role: 1) in different types of autophagy (mitophagy, xenophagy, etc.); 2) in distinct stages of autophagy (initiation, expansion, termination, etc.); 3) with subcellular and tissue-specific localization. These annotations can be used to filter the dataset, providing customizable download options tailored to the user's needs. The resource is available in various file formats (e.g. CSV, BioPAX and PSI-MI), and data can be analyzed and visualized directly in Cytoscape. The multi-layered regulation of autophagy can be analyzed by combining AutophagyNet with tissue- or cell type-specific (multi-)omics datasets (e.g. transcriptomic or proteomic data). The resource is publicly accessible at http://autophagynet.org.Abbreviations: ARN: Autophagy Regulatory Network; ATG: autophagy related; BCR: B cell receptor pathway; BECN1: beclin 1; GABARAP: GABA type A receptor-associated protein; IIP: innate immune pathway; LIR: LC3-interacting region; lncRNA: long non-coding RNA; MAP1LC3B: microtubule associated protein 1 light chain 3 beta; miRNA: microRNA; NHR: nuclear hormone receptor; PTM: post-translational modification; RTK: receptor tyrosine kinase; TCR: T cell receptor; TLR: toll like receptor.

Probiotic supplementation during antibiotic treatment is unjustified in maintaining the gut microbiome diversity: a systematic review and meta-analysis.

BACKGROUND: Probiotics are often used to prevent antibiotic-induced low-diversity dysbiosis, however their effect is not yet sufficiently summarized in this regard. We aimed to investigate the effects of concurrent probiotic supplementation on gut microbiome composition during antibiotic therapy. METHODS: We performed a systematic review and meta-analysis of randomized controlled trials reporting the differences in gut microbiome diversity between patients on antibiotic therapy with and without concomitant probiotic supplementation. The systematic search was performed in three databases (MEDLINE (via PubMed), Embase, and Cochrane Central Register of Controlled Trials (CENTRAL)) without filters on 15 October 2021. A random-effects model was used to estimate pooled mean differences (MD) with 95% confidence intervals (CI). This review was registered on PROSPERO (CRD42021282983). RESULTS: Of 11,769 identified articles, 15 were eligible in the systematic review and 5 in the meta-analyses. Quantitative data synthesis for Shannon (MD = 0.23, 95% CI: [(-)0.06-0.51]), Chao1 (MD = 11.59 [(-)18.42-41.60]) and observed OTUs (operational taxonomic unit) (MD = 17.15 [(-)9.43-43.73]) diversity indices revealed no significant difference between probiotic supplemented and control groups. Lacking data prevented meta-analyzing other diversity indices; however, most of the included studies reported no difference in the other reported α- and ß-diversity indices between the groups. Changes in the taxonomic composition varied across the eligible studies but tended to be similar in both groups. However, they showed a potential tendency to restore baseline levels in both groups after 3-8 weeks. This is the first meta-analysis and the most comprehensive review of the topic to date using high quality methods. The limited number of studies and low sample sizes are the main limitations of our study. Moreover, there was high variability across the studies regarding the indication of antibiotic therapy and the type, dose, and duration of antimicrobials and probiotics. CONCLUSIONS: Our results showed that probiotic supplementation during antibiotic therapy was not found to be influential on gut microbiome diversity indices. Defining appropriate microbiome diversity indices, their standard ranges, and their clinical relevance would be crucial.

Microscopic colitis is a risk factor for low bone density: a systematic review and meta-analysis.

Background: Microscopic colitis (MC) is a chronic inflammatory disease of the large bowel characterized by watery diarrhea, substantially decreasing the patient's quality of life. Scarce data suggest that MC is associated with low bone density (LBD). Objectives: We aimed to assess whether MC is a risk factor for LBD and the proportion of patients with MC having LBD. Design: A systematic review and meta-analysis of studies reporting bone density measurements in MC patients. Data Sources and Methods: We systematically searched five databases from inception to October 16, 2021 (Pubmed, Embase, Cochrane, Scopus, and Web of Science). We used the random-effect model to calculate pooled odds ratios (ORs) and pooled event rates with 95% confidence intervals (CIs). To ascertain the quality of evidence of our outcomes, we followed the recommendations of the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) Working Group. Results: The systematic search yielded a total of 3046 articles. Four articles were eligible for quantitative synthesis. All of them used age- and sex-matched controls to evaluate LBD occurrence among patients with MC. The odds of having LBD were twofold increased (OR = 2.13, CI: 1.42-3.20) in the presence of MC, the odds of osteopenia occurrence were 2.4 (OR = 2.45, CI: 1.11-5.41), and of osteoporosis 1.4 (OR = 1.42, CI: 0.65-3.12). The proportion of LBD was 0.68 (CI: 0.56-0.78), osteopenia was 0.51 (CI: 0.43-0.58), and osteoporosis was 0.11 (CI: 0.07-0.16) among the MC population. Our findings' certainty of the evidence was very low following the GRADEPro guideline. Conclusion: Our data demonstrate that MC is associated with a twofold risk for LBD. Based on our findings, we suggest screening patients for bone mineral density upon diagnosis of MC. Further prospective studies with higher patient numbers and longer follow-up periods on this topic are needed. Registration: Our protocol was prospectively registered with PROSPERO (CRD42021283392).

Investigating microscopic colitis as a risk factor for having low bone density in a literature overview and statistical approach Microscopic colitis (MC) is an underdiagnosed chronic inflammatory large bowel disease, characterized by watery diarrhea, which substantially impacts the patient's quality of life. The etiology of MC is still unclear but is suspected to be multifactorial. Moreover, low bone density (LBD) has been associated with the disease. Scarce data investigate the relationship of MC with LBD, although they share common risk factors, like advanced age and female sex. LBD has two forms; the mild is osteopenia and the severe form is osteoporosis. The most severe complications of osteoporosis are osteoporotic fractures, which can culminate in a life-threatening state and amplify the hospital expenses burden. Our primary aim was to assess if MC increases the risk of LBD. Furthermore, we estimated the proportions of bone mineral changes in the MC population. Following a rigorous methodology, our data suggest that MC doubles the odds of LBD. Furthermore, we have shown that two-thirds of the MC population suffers from bone density decrease, half of them have osteopenia, and one in 10 MC patients has osteoporosis. In conclusion, we highly suggest screening patients with MC for bone mineral density at the moment of diagnosis.

No Association between Gastrointestinal Rebleeding and DOAC Therapy Resumption: A Systematic Review and Meta-Analysis.

BACKGROUND: There are recommendations for anticoagulation resumption after gastrointestinal bleeding (GIB), although data addressing this topic by direct oral anticoagulants (DOACs)-treated patients is lacking. We aim to determine the safety and efficacy of restarting DOACs after GIB. METHODS: Studies that reported rebleeding, thromboembolic events, and mortality after restarting or withholding DOACs were selected. The systematic research was conducted in five databases (MEDLINE, EMBASE, CENTRAL, Web of Science, and Scopus). The random effect model was implemented to calculate the pooled odds ratio (OR). The ROBINS-I tool was used for risk of bias assessment, and the certainty of the evidence was evaluated with the GRADE approach. RESULTS: Four retrospective cohort studies (1722 patients) were included in the meta-analysis. We did not find a significant increase in the risk of rebleeding in patients restarting DOACs after index GIB (OR = 1.12; 95% CI: 0.74-1.68). The outcomes of thromboembolic events and mortality data were not suitable for meta-analytic calculations. Single studies did not show statistically significant differences. Data quality assessment showed a serious overall risk of bias and very low quality of evidence (GRADE D). CONCLUSION: DOAC resumption after a GIB episode may not elevate the risk of rebleeding. However, the need for high-quality randomized clinical trials is crucial.

SignaLink3: a multi-layered resource to uncover tissue-specific signaling networks.

Signaling networks represent the molecular mechanisms controlling a cell's response to various internal or external stimuli. Most currently available signaling databases contain only a part of the complex network of intertwining pathways, leaving out key interactions or processes. Hence, we have developed SignaLink3 (http://signalink.org/), a value-added knowledge-base that provides manually curated data on signaling pathways and integrated data from several types of databases (interaction, regulation, localisation, disease, etc.) for humans, and three major animal model organisms. SignaLink3 contains over 400 000 newly added human protein-protein interactions resulting in a total of 700 000 interactions for Homo sapiens, making it one of the largest integrated signaling network resources. Next to H. sapiens, SignaLink3 is the only current signaling network resource to provide regulatory information for the model species Caenorhabditis elegans and Danio rerio, and the largest resource for Drosophila melanogaster. Compared to previous versions, we have integrated gene expression data as well as subcellular localization of the interactors, therefore uniquely allowing tissue-, or compartment-specific pathway interaction analysis to create more accurate models. Data is freely available for download in widely used formats, including CSV, PSI-MI TAB or SQL.

On the role of bacterial metalloproteases in COVID-19 associated cytokine storm.

The cytokine release syndrome or cytokine storm, which is the hyper-induction of inflammatory responses has a central role in the mortality rate of COVID-19 and some other viral infections. Interleukin-6 (IL-6) is a key player in the development of cytokine storms. Shedding of interleukin-6 receptor (IL-6Rα) results in the accumulation of soluble interleukin-6 receptors (sIL-6R). Only relatively few cells express membrane-bound IL-6Rα. However, sIL-6R can act on potentially all cells and organs through the ubiquitously expressed gp130, the coreceptor of IL-6Rα. Through this, so-called trans-signaling, IL-6-sIL-6R is a powerful factor in the development of cytokine storms and multiorgan involvement. Some bacteria (e.g., Serratia marcescens, Staphylococcus aureus, Pseudomonas aeruginosa, Listeria monocytogenes), commonly considered to cause co-infections during viral pneumonia, can directly induce the shedding of membrane receptors, including IL-6Rα, or enhance endogenous shedding mechanisms causing the increase of sIL-6R level. Here we hypothesise that bacteria promoting shedding and increase the sIL-6R level can be an important contributing factor for the development of cytokine storms. Therefore, inhibition of IL-6Rα shedding by drastically reducing the number of relevant bacteria may be a critical element in reducing the chance of a cytokine storm. Validation of this hypothesis can support the consideration of the prophylactic use of antibiotics more widely and at an earlier stage of infection to decrease the mortality rate of COVID-19. Video abstract.

[Treatment of De Quervain's tendinopathy with conservative methods]. / A De Quervain-féle tendinopathia kezelése konzervatív módszerekkel.

Introduction: De Quervain's tendinopathy affects the region of the wrist and the hand. Thumb motion becomes painful. This illness is caused by a degenerative process rather than inflammation. Primary treatment methods are splinting, taking non-steroid anti-inflammatory drugs and different physical therapeutic modalities, administration of a steroid injection into the tendon sheath or surgical release of the tendon sheath may be performed. Aim: The aim of the present study was to investigate whether conservative treatment complemented by eccentric training could provide an adequate alternative to the currently accepted treatment options. Method: The eccentric training lasted for 8 weeks (if necessary for 12 weeks). Following the introduction to exercises, patients (n = 9) repeated the training several times a day, which was controlled during weekly meetings. At the 1st, 8th and 12th meetings, inspection and the following measurements were performed: range of motion, muscle strength, evaluation and number of painful regions including the completion of patient questionnaires. Data were analysed with paired samples t-tests and repeated measures ANOVA. IBM SPSS Statistics 25.0 and Microsoft Office Excel Professional Plus 2016 programs were used. Results were regarded significant at level of p<0.05. Results: Significant improvements were found in the intensity of pain (Numeric Pain Rating Scale p = 0.005, n = 9) and in the functionality of the hand and wrist (Quick Disabilities of the Arm, Shoulder and Hand questionnaire part 1. p<0.001, part 2. p<0.001, Patient-Rated Wrist Evaluation questionnaire p<0.001; n = 9). Conclusion: With careful patient selection, conservative treatment complemented by eccentric training could be an alternative to current treatment options. Orv Hetil. 2020; 161(11): 419-424.

Autophagy Regulatory Network - a systems-level bioinformatics resource for studying the mechanism and regulation of autophagy.

Autophagy is a complex cellular process having multiple roles, depending on tissue, physiological, or pathological conditions. Major post-translational regulators of autophagy are well known, however, they have not yet been collected comprehensively. The precise and context-dependent regulation of autophagy necessitates additional regulators, including transcriptional and post-transcriptional components that are listed in various datasets. Prompted by the lack of systems-level autophagy-related information, we manually collected the literature and integrated external resources to gain a high coverage autophagy database. We developed an online resource, Autophagy Regulatory Network (ARN; http://autophagy-regulation.org), to provide an integrated and systems-level database for autophagy research. ARN contains manually curated, imported, and predicted interactions of autophagy components (1,485 proteins with 4,013 interactions) in humans. We listed 413 transcription factors and 386 miRNAs that could regulate autophagy components or their protein regulators. We also connected the above-mentioned autophagy components and regulators with signaling pathways from the SignaLink 2 resource. The user-friendly website of ARN allows researchers without computational background to search, browse, and download the database. The database can be downloaded in SQL, CSV, BioPAX, SBML, PSI-MI, and in a Cytoscape CYS file formats. ARN has the potential to facilitate the experimental validation of novel autophagy components and regulators. In addition, ARN helps the investigation of transcription factors, miRNAs and signaling pathways implicated in the control of the autophagic pathway. The list of such known and predicted regulators could be important in pharmacological attempts against cancer and neurodegenerative diseases.

Starvation-response may not involve Atg1-dependent autophagy induction in non-unikont parasites.

Autophagy, the lysosome-mediated self-degradation process, is implicated in survival during starvation in yeast, Dictyostelium and animals. In these eukaryotic taxa (collectively called Unikonts), autophagy is induced primarily through the Atg1/ULK1 complex in response to nutrient depletion. Autophagy has also been well-studied in non-unikont parasites, such as Trypanosoma and Plasmodium, and found important in their life-cycle transitions. However, how autophagy is induced in non-unikonts remains largely unrevealed. Using a bioinformatics approach, we examined the presence of Atg1 and of its complex in the genomes of 40 non-unikonts. We found that these genomes do not encode typical Atg1 proteins: BLAST and HMMER queries matched only with the kinase domain of Atg1, while other segments responsible for regulation and protein-binding were missing. Non-unikonts also lacked other components of the Atg1-inducing complex. Orthologs of an alternative autophagy inducer, Atg6 were found only in the half of the species, indicating that the other half may possess other inducing mechanisms. As key autophagy genes have differential expression patterns during life-cycle, we raise the possibility that autophagy in these protists is induced mainly at the post-transcriptional level. Understanding Atg1-independent autophagy induction mechanisms in these parasites may lead to novel pharmacological interventions, not affecting human Atg1-dependent autophagy.

Complex regulation of autophagy in cancer - integrated approaches to discover the networks that hold a double-edged sword.

Autophagy, a highly regulated self-degradation process of eukaryotic cells, is a context-dependent tumor-suppressing mechanism that can also promote tumor cell survival upon stress and treatment resistance. Because of this ambiguity, autophagy is considered as a double-edged sword in oncology, making anti-cancer therapeutic approaches highly challenging. In this review, we present how systems-level knowledge on autophagy regulation can help to develop new strategies and efficiently select novel anti-cancer drug targets. We focus on the protein interactors and transcriptional/post-transcriptional regulators of autophagy as the protein and regulatory networks significantly influence the activity of core autophagy proteins during tumor progression. We list several network resources to identify interactors and regulators of autophagy proteins. As in silico analysis of such networks often necessitates experimental validation, we briefly summarize tractable model organisms to examine the role of autophagy in cancer. We also discuss fluorescence techniques for high-throughput monitoring of autophagy in humans. Finally, the challenges of pharmacological modulation of autophagy are reviewed. We suggest network-based concepts to overcome these difficulties. We point out that a context-dependent modulation of autophagy would be favored in anti-cancer therapy, where autophagy is stimulated in normal cells, while inhibited only in stressed cancer cells. To achieve this goal, we introduce the concept of regulo-network drugs targeting specific transcription factors or miRNA families identified with network analysis. The effect of regulo-network drugs propagates indirectly through transcriptional or post-transcriptional regulation of autophagy proteins, and, as a multi-directional intervention tool, they can both activate and inhibit specific proteins in the same time. The future identification and validation of such regulo-network drug targets may serve as novel intervention points, where autophagy can be effectively modulated in cancer therapy.

NRF2-ome: an integrated web resource to discover protein interaction and regulatory networks of NRF2.

NRF2 is the master transcriptional regulator of oxidative and xenobiotic stress responses. NRF2 has important roles in carcinogenesis, inflammation, and neurodegenerative diseases. We developed an online resource, NRF2-ome, to provide an integrated and systems-level database for NRF2. The database contains manually curated and predicted interactions of NRF2 as well as data from external interaction databases. We integrated NRF2 interactome with NRF2 target genes, NRF2 regulating TFs, and miRNAs. We connected NRF2-ome to signaling pathways to allow mapping upstream NRF2 regulatory components that could directly or indirectly influence NRF2 activity totaling 35,967 protein-protein and signaling interactions. The user-friendly website allows researchers without computational background to search, browse, and download the database. The database can be downloaded in SQL, CSV, BioPAX, SBML, PSI-MI, and in a Cytoscape CYS file formats. We illustrated the applicability of the website by suggesting a posttranscriptional negative feedback of NRF2 by MAFG protein and raised the possibility of a connection between NRF2 and the JAK/STAT pathway through STAT1 and STAT3. NRF2-ome can also be used as an evaluation tool to help researchers and drug developers to understand the hidden regulatory mechanisms in the complex network of NRF2.

The NRF2-related interactome and regulome contain multifunctional proteins and fine-tuned autoregulatory loops.

NRF2 is a well-known, master transcription factor (TF) of oxidative and xenobiotic stress responses. Recent studies uncovered an even wider regulatory role of NRF2 influencing carcinogenesis, inflammation and neurodegeneration. Prompted by these advances here we present a systems-level resource for NRF2 interactome and regulome that includes 289 protein-protein, 7469 TF-DNA and 85 miRNA interactions. As systems-level examples of NRF2-related signaling we identified regulatory loops of NRF2 interacting proteins (e.g., JNK1 and CBP) and a fine-tuned regulatory system, where 35 TFs regulated by NRF2 influence 63 miRNAs that down-regulate NRF2. The presented network and the uncovered regulatory loops may facilitate the development of efficient, NRF2-based therapeutic agents.