Algorithms for evaluation of minimal cut sets.

OBJECTIVE: We propose a way to enhance the evaluation of minimal cut sets (MCSs) in biological systems modeled by Petri nets, by providing criteria and methodology for determining their optimality in disabling specific processes without affecting critical system components. METHODS: This study concerns Petri nets to model biological systems and utilizes two primary approaches for MCS evaluation. First is the analyzing impact on t-invariants to identify structural dependencies. Second is assessing the impact on potentially starved transitions caused by the inactivity of specific MCSs. This approach deal with net dynamics. These methodologies aim to offer practical tools for assessing the quality and effectiveness of MCSs. RESULTS: The proposed methodologies were applied to two case studies. In the first case, a cholesterol metabolism network was analyzed to investigate how local inflammation and oxidative stress, in conjunction with cholesterol imbalances, influence the progression of atherosclerosis. The MCSs were ranked, with the top sets presented, focusing on those that disabled the fewest number of t-invariants. In the second case, a carbohydrate metabolism disorder model was examined to understand its impact on atherosclerosis progression. The analysis aimed to identify MCSs that could inhibit the atherosclerosis process by targeting specific transitions. Both studies utilized the Holmes software for calculations, demonstrating the effectiveness of the proposed evaluation methodologies in ranking MCSs for practical biological applications. CONCLUSION: The algorithms proposed in this paper offer an analytical approach for evaluating the quality of MCSs in biological systems. By providing criteria for MCS optimality, these approaches have potential to enhance the utility of MCS analysis in systems biology, aiding in the understanding and manipulation of complex biological networks. Algorithm are implemented within Holmes software, an open-source project available at https://github.com/bszawulak/HolmesPN.

Support Materials of Organic and Inorganic Origin as Platforms for Horseradish Peroxidase Immobilization: Comparison Study for High Stability and Activity Recovery.

In the presented study, a variety of hybrid and single nanomaterials of various origins were tested as novel platforms for horseradish peroxidase immobilization. A thorough characterization was performed to establish the suitability of the support materials for immobilization, as well as the activity and stability retention of the biocatalysts, which were analyzed and discussed. The physicochemical characterization of the obtained systems proved successful enzyme deposition on all the presented materials. The immobilization of horseradish peroxidase on all the tested supports occurred with an efficiency above 70%. However, for multi-walled carbon nanotubes and hybrids made of chitosan, magnetic nanoparticles, and selenium ions, it reached up to 90%. For these materials, the immobilization yield exceeded 80%, resulting in high amounts of immobilized enzymes. The produced system showed the same optimal pH and temperature conditions as free enzymes; however, over a wider range of conditions, the immobilized enzymes showed activity of over 50%. Finally, a reusability study and storage stability tests showed that horseradish peroxidase immobilized on a hybrid made of chitosan, magnetic nanoparticles, and selenium ions retained around 80% of its initial activity after 10 repeated catalytic cycles and after 20 days of storage. Of all the tested materials, the most favorable for immobilization was the above-mentioned chitosan-based hybrid material. The selenium additive present in the discussed material gives it supplementary properties that increase the immobilization yield of the enzyme and improve enzyme stability. The obtained results confirm the applicability of these nanomaterials as useful platforms for enzyme immobilization in the contemplation of the structural stability of an enzyme and the high catalytic activity of fabricated biocatalysts.

Characterizing domain-specific open educational resources by linking ISCB Communities of Special Interest to Wikipedia.

MOTIVATION: Wikipedia is one of the most important channels for the public communication of science and is frequently accessed as an educational resource in computational biology. Joint efforts between the International Society for Computational Biology (ISCB) and the Computational Biology taskforce of WikiProject Molecular Biology (a group of expert Wikipedia editors) have considerably improved computational biology representation on Wikipedia in recent years. However, there is still an urgent need for further improvement in quality, especially when compared to related scientific fields such as genetics and medicine. Facilitating involvement of members from ISCB Communities of Special Interest (COSIs) would improve a vital open education resource in computational biology, additionally allowing COSIs to provide a quality educational resource highly specific to their subfield. RESULTS: We generate a list of around 1500 English Wikipedia articles relating to computational biology and describe the development of a binary COSI-Article matrix, linking COSIs to relevant articles and thereby defining domain-specific open educational resources. Our analysis of the COSI-Article matrix data provides a quantitative assessment of computational biology representation on Wikipedia against other fields and at a COSI-specific level. Furthermore, we conducted similarity analysis and subsequent clustering of COSI-Article data to provide insight into potential relationships between COSIs. Finally, based on our analysis, we suggest courses of action to improve the quality of computational biology representation on Wikipedia.

Computational Pipeline for Reference-Free Comparative Analysis of RNA 3D Structures Applied to SARS-CoV-2 UTR Models.

RNA is a unique biomolecule that is involved in a variety of fundamental biological functions, all of which depend solely on its structure and dynamics. Since the experimental determination of crystal RNA structures is laborious, computational 3D structure prediction methods are experiencing an ongoing and thriving development. Such methods can lead to many models; thus, it is necessary to build comparisons and extract common structural motifs for further medical or biological studies. Here, we introduce a computational pipeline dedicated to reference-free high-throughput comparative analysis of 3D RNA structures. We show its application in the RNA-Puzzles challenge, in which five participating groups attempted to predict the three-dimensional structures of 5'- and 3'-untranslated regions (UTRs) of the SARS-CoV-2 genome. We report the results of this puzzle and discuss the structural motifs obtained from the analysis. All simulated models and tools incorporated into the pipeline are open to scientific and academic use.

RNA World Modeling: A Comparison of Two Complementary Approaches.

The origin of life remains one of the major scientific questions in modern biology. Among many hypotheses aiming to explain how life on Earth started, RNA world is probably the most extensively studied. It assumes that, in the very beginning, RNA molecules served as both enzymes and as genetic information carriers. However, even if this is true, there are many questions that still need to be answered-for example, whether the population of such molecules could achieve stability and retain genetic information for many generations, which is necessary in order for evolution to start. In this paper, we try to answer this question based on the parasite-replicase model (RP model), which divides RNA molecules into enzymes (RNA replicases) capable of catalyzing replication and parasites that do not possess replicase activity but can be replicated by RNA replicases. We describe the aforementioned system using partial differential equations and, based on the analysis of the simulation, surmise general rules governing its evolution. We also compare this approach with one where the RP system is modeled and implemented using a multi-agent modeling technique. We show that approaching the description and analysis of the RP system from different perspectives (microscopic represented by MAS and macroscopic depicted by PDE) provides consistent results. Therefore, applying MAS does not lead to erroneous results and allows us to study more complex situations where many cases are concerned, which would not be possible through the PDE model.

Removal of Persistent Sulfamethoxazole and Carbamazepine from Water by Horseradish Peroxidase Encapsulated into Poly(Vinyl Chloride) Electrospun Fibers.

Enzymatic conversion of pharmaceutically active ingredients (API), using immobilized enzymes should be considered as a promising industrial tool due to improved reusability and stability of the biocatalysts at harsh process conditions. Therefore, in this study horseradish peroxidase was immobilized into sodium alginate capsules and then trapped into poly(vinyl chloride) electrospun fibers to provide additional enzyme stabilization and protection against the negative effect of harsh process conditions. Due to encapsulation immobilization, 100% of immobilization yield was achieved leading to loading of 25 µg of enzyme in 1 mg of the support. Immobilized in such a way, enzyme showed over 80% activity retention. Further, only slight changes in kinetic parameters of free (Km = 1.54 mM) and immobilized horseradish peroxidase (Km = 1.83 mM) were noticed, indicating retention of high catalytic properties and high substrate affinity by encapsulated biocatalyst. Encapsulated horseradish peroxidase was tested in biodegradation of two frequently occurring in wastewater API, sulfamethoxazole (antibiotic) and carbamazepine (anticonvulsant). Over 80% of both pharmaceutics was removed by immobilized enzyme after 24 h of the process from the solution at a concentration of 1 mg/L, under optimal conditions, which were found to be pH 7, temperature 25 °C and 2 mM of H2O2. However, even from 10 mg/L solutions, it was possible to remove over 40% of both pharmaceuticals. Finally, the reusability and storage stability study of immobilized horseradish peroxidase showed retention of over 60% of initial activity after 20 days of storage at 4 °C and after 10 repeated catalytic cycles, indicating great practical application potential. By contrast, the free enzyme showed less than 20% of its initial activity after 20 days of storage and exhibited no recycling potential.

RNAvista: a webserver to assess RNA secondary structures with non-canonical base pairs.

Motivation: In the study of 3D RNA structure, information about non-canonical interactions between nucleobases is increasingly important. Specialized databases support investigation of this issue based on experimental data, and several programs can annotate non-canonical base pairs in the RNA 3D structure. However, predicting the extended RNA secondary structure which describes both canonical and non-canonical interactions remains difficult. Results: Here, we present RNAvista that allows predicting an extended RNA secondary structure from sequence or from the list enumerating canonical base pairs only. RNAvista is implemented as a publicly available webserver with user-friendly interface. It runs on all major web browsers. Availability and implementation: http://rnavista.cs.put.poznan.pl.

A Stochastic Petri Net-Based Model of the Involvement of Interleukin 18 in Atherosclerosis.

Interleukin 18 (IL-18) is a proinflammatory and proatherogenic cytokine with pleiotropic properties, which is involved in T and NK cell maturation and the synthesis of other inflammatory cytokines and cell adhesion molecules. It plays a significant role in orchestrating the cytokine cascade, accelerates atherosclerosis and influences plaque vulnerability. To investigate the influence of IL-18 cytokine on atherosclerosis development, a stochastic Petri net model was built and then analyzed. First, MCT-sets and t-clusters were generated, then knockout and simulation-based analysis was conducted. The application of systems approach that was used in this research enabled an in-depth analysis of the studied phenomenon. Our results gave us better insight into the studied phenomenon and allow revealing that activation of macrophages by the classical pathway and IL-18-MyD88 signaling axis is crucial for the modeled process.

A Role of Inflammation and Immunity in Essential Hypertension-Modeled and Analyzed Using Petri Nets.

Recent studies have shown that the innate and adaptive immune system, together with low-grade inflammation, may play an important role in essential hypertension. In this work, to verify the importance of selected factors for the development of essential hypertension, we created a Petri net-based model and analyzed it. The analysis was based mainly on t-invariants, knockouts of selected fragments of the net and its simulations. The blockade of the renin-angiotensin (RAA) system revealed that the most significant effect on the emergence of essential hypertension has RAA activation. This blockade affects: (1) the formation of angiotensin II, (2) inflammatory process (by influencing C-reactive protein (CRP)), (3) the initiation of blood coagulation, (4) bradykinin generation via the kallikrein-kinin system, (5) activation of lymphocytes in hypertension, (6) the participation of TNF alpha in the activation of the acute phase response, and (7) activation of NADPH oxidase-a key enzyme of oxidative stress. On the other hand, we found that the blockade of the activation of the RAA system may not eliminate hypertension that can occur due to disturbances associated with the osmotically independent binding of Na in the interstitium. Moreover, we revealed that inflammation alone is not enough to trigger primary hypertension, but it can coexist with it. We believe that our research may contribute to a better understanding of the pathology of hypertension. It can help identify potential subprocesses, which blocking will allow better control of essential hypertension.

Holmes: a graphical tool for development, simulation and analysis of Petri net based models of complex biological systems.

SUMMARY: Model development and its analysis is a fundamental step in systems biology. The theory of Petri nets offers a tool for such a task. Since the rapid development of computer science, a variety of tools for Petri nets emerged, offering various analytical algorithms. From this follows a problem of using different programs to analyse a single model. Many file formats and different representations of results make the analysis much harder. Especially for larger nets the ability to visualize the results in a proper form provides a huge help in the understanding of their significance. We present a new tool for Petri nets development and analysis called Holmes. Our program contains algorithms for model analysis based on different types of Petri nets, e.g. invariant generator, Maximum Common Transitions (MCT) sets and cluster modules, simulation algorithms or knockout analysis tools. A very important feature is the ability to visualize the results of almost all analytical modules. The integration of such modules into one graphical environment allows a researcher to fully devote his or her time to the model building and analysis. AVAILABILITY AND IMPLEMENTATION: Available at http://www.cs.put.poznan.pl/mradom/Holmes/holmes.html. CONTACT: piotr@cs.put.poznan.pl.

New in silico approach to assessing RNA secondary structures with non-canonical base pairs.

BACKGROUND: The function of RNA is strongly dependent on its structure, so an appropriate recognition of this structure, on every level of organization, is of great importance. One particular concern is the assessment of base-base interactions, described as the secondary structure, the knowledge of which greatly facilitates an interpretation of RNA function and allows for structure analysis on the tertiary level. The RNA secondary structure can be predicted from a sequence using in silico methods often adjusted with experimental data, or assessed from 3D structure atom coordinates. Computational approaches typically consider only canonical, Watson-Crick and wobble base pairs. Handling of non-canonical interactions, important for a full description of RNA structure, is still very difficult. RESULTS: We introduce our novel approach to assessing an extended RNA secondary structure, which characterizes both canonical and non-canonical base pairs, along with their type classification. It is based on predicting the RNA 3D structure from a user-provided sequence or a secondary structure that only describes canonical base pairs, and then deriving the extended secondary structure from atom coordinates. In our example implementation, this was achieved by integrating the functionality of two fully automated, high fidelity methods in a computational pipeline: RNAComposer for the 3D RNA structure prediction and RNApdbee for base-pair annotation. CONCLUSIONS: The presented methodology ties together existing applications for RNA 3D structure prediction and base-pair annotation. The example performance, applying RNAComposer and RNApdbee, reveals better accuracy in non-canonical base pair assessment than the compared methods that directly predict RNA secondary structure.

Identification of a suitable qPCR reference gene in metastatic clear cell renal cell carcinoma.

There is no data on reference gene (RG) selection in metastatic clear-cell renal cell carcinoma (mccRCC) for quantitative PCR (qPCR) data normalization. We aimed at selecting the most stable RG for further determination of new prognostic markers. Thirty-five nonmetastatic and 35 mccRCC patients undergoing radical nephrectomy were included. Paired primary tumor (T, n = 70) and normal (C, n = 70) kidney fragments were collected; from 12 out of 35 mccRCC cases, we also collected metastasized regional lymph nodes and adrenal gland tissues (M, n = 12). After RNA extraction, reverse transcription and qPCR were performed. Samples were divided into four analyzed groups. Fifteen candidate RGs were tested by RefFinder tool and manual statistics. To present the importance of RG selection, TP53 gene expression levels in samples were normalized with the use of RG data. RPL13 gene was the most stable RG in analysis of 35 primary tumor nonmetastatic versus 35 mccRCC samples and matched metastasized T/C/M samples (n = 12, each group). GUSB was the most suitable RG in total 152 samples and in paired T and C (n = 140) kidney samples. Expression of GUSB, RPL13, and the RPL13 + RPLP0 pair were independent of clinical/sample variables. Normalization of TP53 expression levels showed variability of GAPDH and ACTB assays. GUSB or RPL13 assays should be used in mccRCC for qPCR data normalization whereas GAPDH and ACTB assays should be avoided. Prior RG studies should precede each qPCR gene expression study since RG selection is associated with the origin and proportion of specimens.

Sorting signal targeting mRNA into hepatic extracellular vesicles.

Intercellular communication mediated by extracellular vesicles has proved to play an important role in normal and pathological scenarios. However not too much information about the sorting mechanisms involved in loading the vesicles is available. Recently, our group has characterized the mRNA content of vesicles released by hepatic cellular systems, showing that a set of transcripts was particularly enriched in the vesicles in comparison with their intracellular abundance. In the current work, based on in silico bioinformatics tools, we have mapped a novel sequence of 12 nucleotides C[TA]G[GC][AGT]G[CT]C[AT]GG[GA], which is significantly enriched in the set of mRNAs that accumulate in extracellular vesicles. By including a 3'-UTR containing this sequence in a luciferase mRNA reporter, we have shown that in a hepatic cellular system this reporter mRNA was incorporated into extracellular vesicles. This study identifies a sorting signal in mRNAs that is involved in their enrichment in EVs, within a hepatic non-tumoral cellular model.

[Role of the Hippo pathway in cell proliferation and organ size control. Disorders of the pathway in cancer diseases]. / Rola szlaku Hippo w kontroli proliferacji komórkowej i wielkosci narzadów oraz jego zaburzenia w chorobach nowotworowych

The Hippo pathway (also known as SWH--Salvador/Warts/Hippo), discovered for the first time in Drosophila melanogaster, is responsible for cell proliferation and organ size control in mammalian systems. The components of the pathway are two kinases and their adaptor proteins which inhibit the transcription co-activator YAP by phosphorylation. When the pathway is inactive (as an effect of upstream component gene expression disorders), activated YAP is translocated to the nucleus where it cooperates with TEAD transcription factor and promotes expression of genes that regulate cell proliferation and apoptosis. YAP acts generally as an oncogene, although there are some reports describing its role as a tumor suppressor. Since all of the core components are well known, the latest reports provide mostly information about upstream components of the Hippo pathway or its interaction with other biochemical pathways. Because of the Hippo pathway's role in the cell cycle, it has become a very attractive object for studies of the genetic background of cancer. The under- or overexpression of genes involved in the Hippo pathway has been described in many different types of cancers. Moreover, it has been shown that there is a strong connection between cancer cell phenotype and highly activated YAP presence in the nucleus. This paper reviews the most important data about Hippo pathway regulation in Drosophila and mammals, including its numerous disorders and their implications for cell function.

Key Therapeutic Targets to Treat Hyperglycemia-Induced Atherosclerosis Analyzed Using a Petri Net-Based Model.

Chronic superphysiological glucose concentration is a hallmark of diabetes mellitus (DM) and a cause of damage to many types of cells. Atherosclerosis coexists with glucose metabolism disturbances, constituting a significant problem and exacerbating its complications. Atherosclerosis in DM is accelerated, so it is vital to slow its progression. However, from the complex network of interdependencies, molecules, and processes involved, choosing which ones should be inhibited without blocking the pathways crucial for the organism's functioning is challenging. To conduct this type of analysis, in silicotesting comes in handy. In our study, to identify sites in the network that need to be blocked to have an inhibitory effect on atherosclerosis in hyperglycemia, which is toxic for the human organism, we created a model using Petri net theory and performed analyses. We have found that blocking isoforms of protein kinase C (PKC)-PKCß and PKCγ-in diabetic patients can contribute to the inhibition of atherosclerosis progression. In addition, we have discovered that aldose reductase inhibition can slow down atherosclerosis progression, and this has been shown to reduce PKC (ß and γ) expression in DM. It has also been observed that diminishing oxidative stress through the inhibitory effect on the AGE-RAGE axis may be a promising therapeutic approach in treating hyperglycemia-induced atherosclerosis. Moreover, the blockade of NADPH oxidase, the key enzyme responsible for the formation of reactive oxygen species (ROS) in blood vessels, only moderately slowed down atherosclerosis development. However, unlike aldose reductase blockade, or direct PKC (ß and γ), the increased production of mitochondrial ROS associated with mitochondrial dysfunction effectively stopped after NADPH oxidase blockade. The results obtained may constitute the basis for further in-depth research.

3D printed polylactide scaffolding for laccase immobilization to improve enzyme stability and estrogen removal from wastewater.

This study reports a biocatalytic system of immobilized laccase and 3D printed open-structure biopolymer scaffoldings. The scaffoldings were computer-designed and 3D printed using polylactide (PLA) filament. The immobilization of laccase onto the 3D printed PLA scaffolds were optimized with regard to pH, enzyme concentration, and immobilization time. Laccase immobilization resulted in a small reduction in reactivity (in terms of Michaelis constant and maximum reaction rate) but led to significant improvement in chemical and thermal stability. After 20 days of storage, the immobilized and free laccase showed 80% and 35% retention of the initial enzymatic activity, respectively. The immobilized laccase on 3D printed PLA scaffolds achieved 10% improvement in the removal of estrogens from real wastewater as compared to free laccase and showed the significant reusability potential. Results here are promising but also highlight the need for further study to improve enzymatic activity and reusability.

Nanostructured supports for multienzyme co-immobilization for biotechnological applications: Achievements, challenges and prospects.

The synergistic combination of current biotechnological and nanotechnological research has turned to multienzyme co-immobilization as a promising concept to design biocatalysis engineering. It has also intensified the development and deployment of multipurpose biocatalysts, for instance, multienzyme co-immobilized constructs, via biocatalysis/protein engineering to scale-up and fulfil the ever-increasing industrial demands. Considering the characteristic features of both the loaded multienzymes and nanostructure carriers, i.e., selectivity, specificity, stability, resistivity, induce activity, reaction efficacy, multi-usability, high catalytic turnover, optimal yield, ease in recovery, and cost-effectiveness, multienzyme-based green biocatalysts have become a powerful norm in biocatalysis/protein engineering sectors. In this context, the current state-of-the-art in enzyme engineering with a synergistic combination of nanotechnology, at large, and nanomaterials, in particular, are significantly contributing and providing robust tools to engineer and/or tailor enzymes to fulfil the growing catalytic and contemporary industrial needs. Considering the above critics and unique structural, physicochemical, and functional attributes, herein, we spotlight important aspects spanning across prospective nano-carriers for multienzyme co-immobilization. Further, this work comprehensively discuss the current advances in deploying multienzyme-based cascade reactions in numerous sectors, including environmental remediation and protection, drug delivery systems (DDS), biofuel cells development and energy production, bio-electroanalytical devices (biosensors), therapeutical, nutraceutical, cosmeceutical, and pharmaceutical oriented applications. In conclusion, the continuous developments in nano-assembling the multienzyme loaded co-immobilized nanostructure carriers would be a unique way that could act as a core of modern biotechnological research.

In silico and in vitro analysis of the impact of single substitutions within EXO-motifs on Hsa-MiR-1246 intercellular transfer in breast cancer cell.

MiR-1246 has recently gained much attention and many studies have shown its oncogenic role in colorectal, breast, lung, and ovarian cancers. However, miR-1246 processing, stability, and mechanisms directing miR-1246 into neighbor cells remain still unclear. In this study, we aimed to determine the role of single-nucleotide substitutions within short exosome sorting motifs - so-called EXO-motifs: GGAG and GCAG present in miR-1246 sequence on its intracellular stability and extracellular transfer. We applied in silico methods such as 2D and 3D structure analysis and modeling of protein interactions. We also performed in vitro validation through the transfection of fluorescently labeled miRNA to MDA-MB-231 cells, which we analyzed by flow cytometry and fluorescent microscopy. Our results suggest that nucleotides alterations that disturbed miR-1246 EXO-motifs were able to modulate miRNA-1246 stability and its transfer level to the neighboring cells, suggesting that the molecular mechanism of RNA stability and intercellular transfer can be closely related.

2D-PAGE as an effective method of RNA degradome analysis.

The continuously growing interest in small regulatory RNA exploration is one of the important factors that have inspired the recent development of new high throughput techniques such as DNA microarrays or next generation sequencing. Each of these methods offers some significant advantages but at the same time each of them is expensive, laborious and challenging especially in terms of data analysis. Therefore, there is still a need to develop new analytical methods enabling the fast, simple and cost-effective examination of the complex RNA mixtures. Recently, increasing attention has been focused on the RNA degradome as a potential source of riboregulators. Accordingly, we attempted to employ a two-dimensional gel electrophoresis as a quick and uncomplicated method of profiling RNA degradome in plant or human cells. This technique has been successfully used in proteome analysis. However, its application in nucleic acids studies has been very limited. Here we demonstrate that two dimensional electrophoresis is a technique which allows one to quickly and cost-effectively identify and compare the profiles of 10-90 nucleotide long RNA accumulation in various cells and organs.

Control of Cholesterol Metabolism Using a Systems Approach.

Cholesterol is an essential component of mammalian cells and is involved in many fundamental physiological processes; hence, its homeostasis in the body is tightly controlled, and any disturbance has serious consequences. Disruption of the cellular metabolism of cholesterol, accompanied by inflammation and oxidative stress, promotes the formation of atherosclerotic plaques and, consequently, is one of the leading causes of death in the Western world. Therefore, new drugs to regulate disturbed cholesterol metabolism are used and developed, which help to control cholesterol homeostasis but still do not entirely cure atherosclerosis. In this study, a Petri net-based model of human cholesterol metabolism affected by a local inflammation and oxidative stress, has been created and analyzed. The use of knockout of selected pathways allowed us to observe and study the effect of various combinations of commonly used drugs on atherosclerosis. The analysis results led to the conclusion that combination therapy, targeting multiple pathways, may be a fundamental concept in the development of more effective strategies for the treatment and prevention of atherosclerosis.