Drugst.One -- A plug-and-play solution for online systems medicine and network-based drug repurposing

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.Comment: 45 pages, 6 figures, 7 table

Small RNA dynamics in cholinergic systems

Natural science is only just beginning to understand the complex processes surrounding transcription. Epitranscriptional regulation is in large parts conveyed by transcription factors (TFs) and two recently discovered small RNA (smRNA) species: microRNAs (miRNAs) and transfer RNA fragments (tRFs). As opposed to the fairly well-characterised function of TFs in shaping the phenotype of the cell, the effects and mechanism of action of smRNA species is less well understood. In particular, the multi-levelled combinatorial interaction (many-to-many) of smRNAs presents new challenges to molecular biology. This dissertation contributes to the study of smRNA dynamics in mammalian cells in several ways, which are presented in three main chapters. I) The exhaustive analysis of the many-to-many network of smRNA regulation is reliant on bioinformatic support. Here, I describe the development of an integrative database capable of fast and efficient computation of complex multi-levelled transcriptional interactions, named miRNeo. This infrastructure is then applied to two use cases. II) To elucidate smRNA dynamics of cholinergic systems and their relevance to psychiatric disease, an integrative transcriptomics analysis is performed on patient brain sample data, single-cell sequencing data, and two closely related in vitro human cholinergic cellular models reflecting male and female phenotypes. III) The dynamics between small and large RNA transcripts in the blood of stroke victims are analysed via a combination of sequencing, analysis of sorted blood cell populations, and bioinformatic methods based on the miRNeo infrastructure. Particularly, importance and practicality of smRNA:TF:gene feedforward loops are assessed. In both analytic scenarios, I identify the most pertinent regulators of disease-relevant processes and biological pathways implicated in either pathogenesis or responses to the disease. While the examples described in chapters three and four of this dissertation are disease-specific applications of miRNeo, the database and methods described have been developed to be applicable to the whole genome and all known smRNAs

Why most pre-published research findings are false.

Caused by the recent surge in preprint volume, particularly in the light of the immense rapidity of Covid-19 research, the question arises, “How reliable are the findings that are reported via preprint?” This question poses serious challenges in estimation and validation of the extent of false or even fraudulent science on preprint servers, and has far-reaching implications for editorial policies. As preprint volume continuously grows, but the interval between preprint and publication does not, the limit of peer-review is fast approaching. The scientific merit or validity of preprints is not assessed by preprint service providers, and hence it is feasible to assume that, comparatively, preprints will be less reproducible than peer-reviewed articles. Publication metadata predict a saturation of the peer-review process in the coming decade, and necessitate an open discussion about editorial policies and publication infrastructure in the biomedical field

A Platform for the Biomedical Application of Large Language Models

The wealth of knowledge we have amassed in the context of biomedical science has grown exponentially in the last decades. Consequently, understanding and contextualising scientific results has become increasingly difficult for any single individual. In contrast, current Large Language Models (LLMs) can remember an enormous amount of information, but have notable shortcomings, such as a lack of generalised awareness, logical deficits, and a propensity to hallucinate. To improve biomedical analyses, we propose to combine human ingenuity and machine memory by means of an open and modular conversational platform, ChatGSE (https://chatgse.streamlit.app). We safeguard against common LLM shortcomings using general and biomedicine-specific measures and allow automated integration of popular bioinformatics methods. Ultimately, we aim to improve the AI-readiness of biomedicine and make LLMs more useful and trustworthy in research applications.Comment: 12 pages, 1 figur

Integrative transcriptomics reveals sexually dimorphic microRNA control of the cholinergic/neurokine interface in schizophrenia and bipolar disorder

RNA-sequencing analyses are often limited to identifying lowest p-value transcripts, which does not address polygenic phenomena. To overcome this limitation, we developed an integrative approach that combines large scale transcriptomic meta-analysis of patient brain tissues with single-cell sequencing data of CNS neurons, short RNA-sequencing of human male- and female-originated cell lines, and connectomics of transcription factor- and microRNA-interactions with perturbed transcripts. We used this pipeline to analyze cortical transcripts of schizophrenia and bipolar disorder patients. While these pathologies show massive transcriptional parallels, their clinically well-known sexual dimorphisms remain unexplained. Our method explicates the differences between afflicted men and women, and identifies disease-affected pathways of cholinergic transmission and gp130-family neurokine controllers of immune function, interlinked by microRNAs. This approach may open new perspectives for seeking biomarkers and therapeutic targets, also in other transmitter systems and diseases

Integrative transcriptomics reveals sexually dimorphic microRNA control of the cholinergic/neurokine interface in schizophrenia and bipolar disorder

RNA sequencing analyses are often limited to identifying lowest p value transcripts, which does not address polygenic phenomena. To overcome this limitation, we developed an integrative approach that combines large-scale transcriptomic meta-analysis of patient brain tissues with single-cell sequencing data of CNS neurons, short RNA sequencing of human male- and female-originating cell lines, and connectomics of transcription factor and microRNA interactions with perturbed transcripts. We used this pipeline to analyze cortical transcripts of schizophrenia and bipolar disorder patients. Although these pathologies show massive transcriptional parallels, their clinically well-known sexual dimorphisms remain unexplained. Our method reveals the differences between afflicted men and women and identifies disease-affected pathways of cholinergic transmission and gp130-family neurokine controllers of immune function interlinked by microRNAs. This approach may open additional perspectives for seeking biomarkers and therapeutic targets in other transmitter systems and diseases

Integrating knowledge and omics to decipher mechanisms via large‐scale models of signaling networks

Abstract Signal transduction governs cellular behavior, and its dysregulation often leads to human disease. To understand this process, we can use network models based on prior knowledge, where nodes represent biomolecules, usually proteins, and edges indicate interactions between them. Several computational methods combine untargeted omics data with prior knowledge to estimate the state of signaling networks in specific biological scenarios. Here, we review, compare, and classify recent network approaches according to their characteristics in terms of input omics data, prior knowledge and underlying methodologies. We highlight existing challenges in the field, such as the general lack of ground truth and the limitations of prior knowledge. We also point out new omics developments that may have a profound impact, such as single‐cell proteomics or large‐scale profiling of protein conformational changes. We provide both an introduction for interested users seeking strategies to study cell signaling on a large scale and an update for seasoned modelers

Distinct CholinomiR Blood Cell Signature as a Potential Modulator of the Cholinergic System in Women with Fibromyalgia Syndrome

Fibromyalgia syndrome (FMS) is a heterogeneous chronic pain syndrome characterized by musculoskeletal pain and other key co-morbidities including fatigue and a depressed mood. FMS involves altered functioning of the central and peripheral nervous system (CNS, PNS) and immune system, but the specific molecular pathophysiology remains unclear. Anti-cholinergic treatment is effective in FMS patient subgroups, and cholinergic signaling is a strong modulator of CNS and PNS immune processes. Therefore, we used whole blood small RNA-sequencing of female FMS patients and healthy controls to profile microRNA regulators of cholinergic transcripts (CholinomiRs). We compared microRNA profiles with those from Parkinson’s disease (PD) patients with pain as disease controls. We validated the sequencing results with quantitative real-time PCR (qRT-PCR) and identified cholinergic targets. Further, we measured serum cholinesterase activity in FMS patients and healthy controls. Small RNA-sequencing revealed FMS-specific changes in 19 CholinomiRs compared to healthy controls and PD patients. qRT-PCR validated miR-182-5p upregulation, distinguishing FMS patients from healthy controls. mRNA targets of CholinomiRs bone morphogenic protein receptor 2 and interleukin 6 signal transducer were downregulated. Serum acetylcholinesterase levels and cholinesterase activity in FMS patients were unchanged. Our findings identified an FMS-specific CholinomiR signature in whole blood, modulating immune-related gene expression

Central cholinergic function and metabolic changes in streptozotocin‐induced rat brain injury

As glucose hypometabolism in the brain is an early sign of Alzheimer´s dementia (AD), the diabetogenic drug streptozotocin (STZ) has been used to induce Alzheimer‐like pathology in rat brain by intracereboventricular injection (icv‐STZ). However, many details of the pathological mechanism of STZ in this AD model remain unclear. Here, we report metabolic and cholinergic effects of icv‐STZ using microdialysis in freely moving animals. We found that icv‐STZ at a dose of 3 mg/kg (2 × 1.5 mg/kg) causes overt toxicity reflected in body weight loss. Three weeks after STZ administration, histological examination revealed a high number of glial fibrillary acidic protein reactive cells in the hippocampus, accompanied by Fluoro‐Jade C‐positive cells in the CA1 region. Glucose and lactate levels in microdialysates were unchanged, but mitochondrial respiration measured ex vivo was reduced by 9%–15%. High‐affinity choline uptake, choline acetyltransferase, and acetylcholine esterase (AChE) activities in the hippocampus were reduced by 16%, 28%, and 30%, respectively. Importantly, extracellular acetylcholine (ACh) levels in the hippocampus were unchanged and responded to behavioral and pharmacological challenges. In comparison, extracellular ACh levels and cholinergic parameters in the striatum were unchanged or slightly increased. We conclude that the icv‐STZ model poorly reflects central cholinergic dysfunction, an important characteristic of dementia. The icv‐STZ model may be more aptly described as an animal model of hippocampal gliosis

Distinct CholinomiR blood cell signature as a potential modulator of the cholinergic system in women with fibromyalgia syndrome

Fibromyalgia syndrome (FMS) is a heterogeneous chronic pain syndrome characterized by musculoskeletal pain and other key co-morbidities including fatigue and a depressed mood. FMS involves altered functioning of the central and peripheral nervous system (CNS, PNS) and immune system, but the specific molecular pathophysiology remains unclear. Anti-cholinergic treatment is effective in FMS patient subgroups, and cholinergic signaling is a strong modulator of CNS and PNS immune processes. Therefore, we used whole blood small RNA-sequencing of female FMS patients and healthy controls to profile microRNA regulators of cholinergic transcripts (CholinomiRs). We compared microRNA profiles with those from Parkinson's disease (PD) patients with pain as disease controls. We validated the sequencing results with quantitative real-time PCR (qRT-PCR) and identified cholinergic targets. Further, we measured serum cholinesterase activity in FMS patients and healthy controls. Small RNA-sequencing revealed FMS-specific changes in 19 CholinomiRs compared to healthy controls and PD patients. qRT-PCR validated miR-182-5p upregulation, distinguishing FMS patients from healthy controls. mRNA targets of CholinomiRs bone morphogenic protein receptor 2 and interleukin 6 signal transducer were downregulated. Serum acetylcholinesterase levels and cholinesterase activity in FMS patients were unchanged. Our findings identified an FMS-specific CholinomiR signature in whole blood, modulating immune-related gene expression