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Processing biological materials with 3-dimensional (3D) printers has attracted increasing interest in several research areas. At the same time, off-the-shelf solutions are increasingly available in a wider variety to meet the current market demand. However, most of the available bioprinters are closed source, thus, modifications are quite challenging or require an avoidable consultation process with the manufacturer. Furthermore, the entry prices for basic machines amount to several thousands of euros. Whereas, high-end 3D bio printers with a vast array of features are available for several hundred thousand euros. Due to the immense potential of this tool in the field of biotechnology it is important to extend the availability of this technology for research purposes in terms of adaptability and price. This ongoing work focuses on open-source 3D printer heads with the ability to extrude biological materials. The print heads include several techniques to process low as well as high viscose biomaterials such as agar and gelatin. Additionally, obstacles such as continuous substrate tempering or integration into existing 3D printers are addressed. The work presented is open source and thus freely adaptable to any user’s specific needs. Our goal is to process a diverse range of biomaterials with different print techniques.
The identification of biomarkers is crucial for cancer diagnosis, understanding the underlying biological mechanisms, and developing targeted therapies. In this study, we propose a machine learning approach to predict ovarian cancer patients’ outcomes and platinum resistance status using publicly available gene expression data. Six classical machine-learning algorithms are compared on their predictive performance. Those with the highest score are analyzed by their feature importance using the SHAP algorithm. We were able to select multiple genes that correlated with the outcome and platinum resistance status of the patients and validated those using Kaplan–Meier plots. In comparison to similar approaches, the performance of the models was higher, and different genes using feature importance analysis were identified. The most promising identified genes that could be used as biomarkers are TMEFF2, ACSM3, SLC4A1, and ALDH4A1.
Glycolysis is one of the primordial pathways of metabolism, playing a pivotal role in energy metabolism and biosynthesis. Glycolytic enzymes are known to form transient multi-enzyme assemblies. Here we examine the wider protein-protein interactions of plant glycolytic enzymes and reveal a moonlighting role for specific glycolytic enzymes in mediating the co-localization of mitochondria and chloroplasts. Knockout mutation of phosphoglycerate mutase or enolase resulted in a significantly reduced association of the two organelles. We provide evidence that phosphoglycerate mutase and enolase form a substrate-channelling metabolon which is part of a larger complex of proteins including pyruvate kinase. These results alongside a range of genetic complementation experiments are discussed in the context of our current understanding of chloroplast-mitochondrial interactions within photosynthetic eukaryotes.
The isoquinoline quaternary alkaloid Berberine possesses a variety of pharmacological properties that suggests its promising application for an anticancer delivery system design utilizing its ability to intercalate DNA. In the current work, we have investigated the effects of Berberine on the human T cell leukemia cell line in vitro. Fluorescent microscopy of leukemic cells revealed Berberine nuclear localization. The results showed that Berberine inhibited leukemic cell growth in a time- and dose-dependent manner, that was associated with reactive oxygen species production intensification and caspase 3/7 activity increase with followed apoptosis induction. Berberine was used as a toxic and phototoxic agent for triple system synthesis along with DNA as a carrier and nanosilver as a plasmonic accelerator of Berberine electronic transitions and high energy emission absorbent centers. The proposed method allows to obtain the complex of DNA with Berberine molecules and silver nanoparticles. The optical properties of free components as well as their various combinations, including the final triple system DNA-Nanosilver-Berberine, were investigated. Obtained results support the possibility to use the triple system DNA-Nanosilver-Berberine as an alternative therapeutic agent for cancer treatment.
The isoquinoline quaternary alkaloid Berberine possesses a variety of pharmacological properties that suggests its promising application for an anticancer delivery system design utilizing its ability to intercalate DNA.In the current work we have investigated the effects of Berberine on the human T-cell leukemia cell line in vitro.Fluorescent microscopy of leukemic cells revealed Berberine nuclear localization. The results showed that Berberine inhibited leukemic cell growth in a time-and dose-dependent manner, that was associated with reactive oxygen species production intensification and caspase 3/7 activity increase with followed apoptosis induction.Berberine was used as a toxic and phototoxic agent for triple system synthesis along with DNA as a carrier and nanosilver as a plasmonic accelerator of Berberine electronic transitions and high energy emission absorbent centers.The proposed method allows to obtain the complex of DNA with Berberine molecules and silver nanopoarticles. The optical properties of free components as well as their various combinations, including the final triple system DNA-Nanosilver-Berberine, were investigated. Obtained results support the possibility to use the triple system DNA-Nanosilver-Berberine as an alternative therapeutic agent for cancer treatment.
Most biochemical reactions depend on the pH value of the aqueous environment and some are strongly favoured to occur in an acidic environment. A non-invasive control of pH to tightly regulate such reactions with defined start and end points is a highly desirable feature in certain applications, but has proven difficult to achieve so far. We report a novel optical approach to reversibly control a typical biochemical reaction by changing the pH and using acid phosphatase as a model enzyme. The reversible photoacid G-acid functions as a proton donor, changing the pH rapidly and reversibly by using high power UV LEDs as an illumination source in our experimental setup. The reaction can be tightly controlled by simply switching the light on and off and should be applicable to a wide range of other enzymatic reactions, thus enabling miniaturization and parallelization through non-invasive optical means.
The use of explosives has led to a widespread distribution of 2,4,6-trinitrotoluene (TNT) and its by- and degradation products in the soil on former production and testing sites. The investigation of those large contaminated sites is so far based on a few selected soil samples, due to high costs of conventional HPLC and GC analysis, although huge differences in concentrations can already be found in small areas and different collection depths. We introduce a novel high-throughput screening system for those areas, which combines a smartphone-based collection of GPS data and soil characteristics with a fast MALDI-TOF MS quantification of explosives in soil sample extracts and finally a heatmap visualization of the explosives’ spread in soil and an analysis of correlation between concentrations and soil characteristics. The analysis of a 400 m2 area presented an extensive contamination with TNT and lower concentrations of the degradation and by-products aminodinitrotoluenes (ADNT) and dinitrotoluenes (DNT) next to a former production facility for TNT. The contamination decreased in deeper soil levels and depended on the soil type. Pure humus samples showed significantly lower contaminations compared to sand and humus/sand mixtures, which is likely to be caused by an increased binding potential of the humic material. No correlation was found between the vegetation and the concentration of explosives. Since the results were obtained and visualized within several hours, the MALDI-TOF MS based comprehensive screening and heatmap analysis might be valuable for a fast and high-throughput characterization of contaminated areas.
Leishmania species are protozoan parasites and the causative agents of leishmaniasis, a vector borne disease that imposes a large health burden on individuals living mainly in tropical and subtropical regions. Different Leishmania species are responsible for the distinct clinical patterns, such as cutaneous, mucocutaneous, and visceral leishmaniasis, with the latter being potentially fatal if left untreated. For this reason, it is important to perform correct species identification and differentiation. Fourier transform infrared spectroscopy (FTIR) is an analytical spectroscopic technique increasingly being used as a potential tool for identification of microorganisms for diagnostic purposes. By employing mid-infrared (MIR) spectral data, it is not only possible to assess the chemical structures but also to achieve differentiation supported by multivariate statistic analysis. This work comprises a pilot study on differentiation of Leishmania species of the Old World (L. major, L. tropica, L. infantum, and L. donovani) as well as hybrids of distinct species by using vibrational spectroscopic fingerprints. Films of intact Leishmania parasites and their deoxyribonucleic acid (DNA) were characterized comparatively with respect to their biochemical nature and MIR spectral patterns. The strains’ hyperspectral datasets were multivariately examined by means of variance-based principal components analysis (PCA) and distance-based hierarchical cluster analysis (HCA). With the implementation of MIR spectral datasets we show that a phenotypic differentiation of Leishmania at species and intra-species level is feasible. Thus, FTIR spectroscopy can be further exploited for building up spectral databases of Leishmania parasites in view of high-throughput analysis of clinical specimens.
Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.
The human microbiome has become an area of intense research due to its potential impact on human health. However, the analysis and interpretation of this data have proven to be challenging due to its complexity and high dimensionality. Machine learning (ML) algorithms can process vast amounts of data to uncover informative patterns and relationships within the data, even with limited prior knowledge. Therefore, there has been a rapid growth in the development of software specifically designed for the analysis and interpretation of microbiome data using ML techniques. These software incorporate a wide range of ML algorithms for clustering, classification, regression, or feature selection, to identify microbial patterns and relationships within the data and generate predictive models. This rapid development with a constant need for new developments and integration of new features require efforts into compile, catalog and classify these tools to create infrastructures and services with easy, transparent, and trustable standards. Here we review the state-of-the-art for ML tools applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities. This scoping review focuses on ML based software and framework resources currently available for the analysis of microbiome data in humans. The aim is to support microbiologists and biomedical scientists to go deeper into specialized resources that integrate ML techniques and facilitate future benchmarking to create standards for the analysis of microbiome data. The software resources are organized based on the type of analysis they were developed for and the ML techniques they implement. A description of each software with examples of usage is provided including comments about pitfalls and lacks in the usage of software based on ML methods in relation to microbiome data that need to be considered by developers and users. This review represents an extensive compilation to date, offering valuable insights and guidance for researchers interested in leveraging ML approaches for microbiome analysis.
Ziel dieser Arbeit war die Erhöhung der Temperaturtoleranz des Cyanobakteriums Synechocystis sp. PCC 6803 mittels ungerichteter Mutagenese und adaptiver Evolution. Trotz des erneuten Interesses an Cyanobakterien und Mikroalgen in den letzten Jahren, gibt es nur relativ wenige aktuelle Studien zum Einsatz dieser Methoden an Cyanobakterien. Zur Analyse eines mittels Mutagenese erzeugten Gemischs an Stämmen, ist es von großem Vorteil Hochdurchsatz-Methoden zur Kultivierung und zum Screening einsetzen zu können. Auf Basis eines Pipettierroboters wurde solch eine Plattform für phototrophe Mikroorganismen neu entwickelt und folgend stetig verbessert. Die Kultivierung erfolgt in 2,2ml Deepwell-Mikrotiterplatten innerhalb einer speziell angefertigten Kultivierungskammer. Schüttelbedingungen, Beleuchtung, Temperatur und CO2-Atmosphäre sind hierbei vollständig einstellbar.Die Plattform erlaubt semi-kontinuierliche Kultivierungen mit automatisierten Verdünnungen von hunderten Kulturen gleichzeitig. Automatisierte Messungen des Wachstums, des Absorptionsspektrums, der Chlorophyllkonzentration, MALDI-TOF-MS sowie eines neu entwickelten Vitalitätsassays wurden etabliert. Für die Mutagenese wurden die Letalität- und die nicht-letale Punktmutationsrate von ultravioletter Strahlung und Methylmethansulfonat für Synechocystis charakterisiert. Synechocystis wurde mit den so ermittelten optimalen Dosen mehrfach behandelt und anschließend einer in vivo Selektion unterzogen. Somit wurde dessen Temperaturtoleranz um bis zu 3°C erhöht. Über die Screeningplattform wurden die thermotolerantesten monoklonalen Stämme identifiziert. Nach einer Validierung wurde das vollständige Genom der Stämme sequenziert. Hierdurch wurden erstmals Mutationen in verschiedenen Genen mit der Langzeittemperaturtoleranz von Synechocystis in Verbindung gebracht. Bei einigen dieser Gene ist es sehr unwahrscheinlich, dass sie mittels anderer Verfahren hätten identifiziert werden können.
Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action
(2023)
The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish “gold standard” protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory ‘omics’ features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.
Background
Berberine (Ber) is a herbal alkaloid with pharmacological activity in general and a high anticancer potency in particular. However, due to its low bioavailability, the difficulty in reaching a target and choosing the right dose, there is a need to improve approaches of Ber use in anticancer therapy. In this study, Ber, noncovalently bound to a carbon nanostructure C60 fullerene (C60) at various molar ratios of the components, was explored against Lewis lung carcinoma (LLC).
Methods
C60–Ber noncovalent nanocomplexes were synthesized in 1:2, 1:1 and 2:1 molar ratios. Ber release from the nanocomplexes was studied after prolonged incubation at different pH with the liquid chromatography–mass spectrometry analysis of free Ber content. Biological effects of the free and C60-complaxated Ber were studied in vitro towards LLC cells with phase-contrast and fluorescence microscopy, flow cytometry, MTT reduction, caspase activity and wound closure assays. The treatment with C60–Ber nanocomplex was evaluated in vivo with the LLC-tumored C57Bl mice. The mice body weight, tumor size, tumor weight and tumor weight index were assessed for four groups, treated with saline, 15 mg C60/kg, 7.5 mg Ber/kg or 2:1 C60-Ber nanocomplex (15 mg C60/kg, 7.5 mg Ber/kg).
Results
Ber release from C60–Ber nanocomplexes was promoted with medium acidification. LLC cells treatment with C60–Ber nanocomplexes was followed by enhanced Ber intracellular uptake as compared to free Ber. The cytotoxicity of the studied agents followed the order: free Ber < 1:2 < 1:1 < 2:1 C60–Ber nanocomplex. The potency of cytotoxic effect of 2:1 C60–Ber nanocomplex was confirmed by 21.3-fold decrease of IC50 value (0.8 ± 0.3 µM) compared to IC50 for free Ber (17 ± 2 µM). C60–Ber nanocomplexes induced caspase 3/7 activation and suppressed the migration activity of LLC cells. The therapeutic potency of 2:1 C60–Ber nanocomplex was confirmed in a mouse model of LLC. The tumor growth in the group treated with 2:1 C60–Ber nanocomplex is suppressed by approximately 50% at the end of experiment, while in the tumor-bearing group treated with free Ber no therapeutic effect was detected.
Conclusions
This study indicates that complexation of natural alkaloid Ber with C60 may be a novel therapeutic strategy against lung carcinoma.
Die Kombination von fortschrittlichen Materialien und kontrolliertem Oberflächendesign mit komplexen Proteinen aus der natürlichen Photosynthese ist derzeit eines der Hauptthemen bei der Entwicklung von Biohybridsystemen und Biophotovoltaik. In dieser Studie werden transparente makroporöse Indium-Zinn-Oxid-(μITO-) Elektroden mit dem trimeren Superkomplex Photosystem I (PSI) aus dem Cyanobakterium Thermosynechococcus elongatus sowie dem kleinen Redoxprotein Cytochrom c (Cyt c) kombiniert, um neuartige und effiziente biohybride Photokathoden herzustellen. Mit diesen bis zu 40 μm hohen 3D-Strukturen können beide Proteine in einer annähernden Monolage abgeschieden werden und die elektrische Kommunikation mit der Elektrode kann erzielt werden. Der generierte Photostrom folgt dabei linear der kontrollierbaren Schichtdicke der μITO-Elektrode, wobei
Stromdichten von bis zu 150 μA cm –2 erhalten werden. Eine effiziente elektrische Kopplung der Proteine kann durch die hohe interne Quanteneffizienz von 30 % gezeigt werden.
Pituitary neuroendocrine tumors (PitNET) do not only belong to the most common intracranial neoplasms but seem to be generally more common than has been thought. Minimally invasive liquid biopsies have the potential to improve their early screening efficiency as well as monitor prognosis by facilitating the diagnostic procedures. This review aims to assess the potential of using liquid biopsies of different kinds of biomarker species that have only been obtained from solid pituitary tissues so far. Numerous molecules have been associated with the development of a PitNET, suggesting that it often develops from the cumulative effects of many smaller genetic or epigenetic changes. These minor changes eventually pile up to switch critical molecules into tumor-promoting states, which may be the key regulatory nodes representing the most potent marker substances for a diagnostic test. Drugs targeting these nodes may be superior for the therapeutic outcome and therefore the identification of such pituitary-specific cellular key nodes will help to accelerate their application in medicine. The ongoing genetic degeneration in pituitary adenomas suggests that repeated tumor profiling via liquid biopsies will be necessary for personalized and effective treatment solutions.
Recent progress in nanobiotechnology has attracted interest to a biomedical application of the carbon nanostructure C60 fullerene since it possesses a unique structure and versatile biological activity. C60 fullerene potential application in the frame of cancer photodynamic therapy (PDT) relies on rapid development of new light sources as well as on better understanding of the fullerene interaction with cells.
The aim of this study was to analyze C60 fullerene effects on human leukemic cells (CCRF-CEM) in combination with high power single chip light-emitting diodes (LEDs) light irradiation of different wavelengths: ultraviolet (UV, 365 nm), violet (405 nm), green (515 nm) and red (632 nm). The time-dependent accumulation of fullerene C60 in CCRF-CEM cells up to 250 ng/106 cells at 24 h with predominant localization within mitochondria was demonstrated with immunocytochemical staining and liquid chromatography mass spectrometry. In a cell viability assay we studied photoexcitation of the accumulated C60 nanostructures with ultraviolet or violet LEDs and could prove that significant phototoxic effects did arise. A less pronounced C60 fullerene phototoxic effect was observed after irradiation with green, and no effect was detected with red light. A C60 fullerene photoactivation with violet light induced substantial ROS generation and apoptotic cell death, confirmed by caspase3/7 activation and plasma membrane phosphatidylserine externalization. Our work proved C60 fullerene ability to induce apoptosis of leukemic cells after photoexcitation with high power single chip 405 nm LED as a light source. This underlined the potential for application of C60 nanostructure as a photosensitizer for anticancer therapy.
C60 Fullerene as an Effective Nanoplatform of Alkaloid Berberine Delivery into Leukemic Cells
(2019)
A herbal alkaloid Berberine (Ber), used for centuries in Ayurvedic, Chinese, Middle-Eastern, and native American folk medicines, is nowadays proved to function as a safe anticancer agent. Yet, its poor water solubility, stability, and bioavailability hinder clinical application. In this study, we have explored a nanosized carbon nanoparticle—C60 fullerene (C60)—for optimized Ber delivery into leukemic cells. Water dispersions of noncovalent C60-Ber nanocomplexes in the 1:2, 1:1, and 2:1 molar ratios were prepared. UV–Vis spectroscopy, dynamic light scattering (DLS), and atomic force microscopy (AFM) evidenced a complexation of the Ber cation with the negatively charged C60 molecule. The computer simulation showed that π-stacking dominates in Ber and C60 binding in an aqueous solution. Complexation with C60 was found to promote Ber intracellular uptake. By increasing C60 concentration, the C60-Ber nanocomplexes exhibited higher antiproliferative potential towards CCRF-CEM cells, in accordance with the following order: free Ber < 1:2 < 1:1 < 2:1 (the most toxic). The activation of caspase 3/7 and accumulation in the sub-G1 phase of CCRF-CEM cells treated with C60-Ber nanocomplexes evidenced apoptosis induction. Thus, this study indicates that the fast and easy noncovalent complexation of alkaloid Ber with C60 improved its in vitro efficiency against cancer cells.
New representative of carbacylamidophosphates - diphenyl-N-(trichloroacetyl)-amidophosphate (HL), which contains two phenoxy substituents near the phosphoryl group, was synthesized, identified by elemental analysis and IR and NMR spectroscopy, and tested as a cytotoxic agent itself and in combination with C60 fullerene.
According to molecular simulation results, C60 fullerene and HL could interact with DNA and form a rigid complex stabilized by stacking interactions of HL phenyl groups with C60 fullerene and DNA G nucleotide, as well as by interactions of HL CCl3 group by ion-π bonds with C60 molecule and by electrostatic bonds with DNA G nucleotide.
With the use of MTT test, the cytotoxic activity of HL against human leukemic CCRF-CM cells with IC50 value detected at 10 μM concentration at 72 h of cells treatment was shown. Under combined action of 16 μM C60 fullerene and HL, the value of IC50 was detected at lower 5 μM HL concentration and at earlier 48 h period of incubation, besides the cytotoxic effect of HL was observed at a low 2.5 μM concentration at which HL by itself had no influence on cell viability. Binding of C60 fullerene and HL with minor DNA groove with formation of a stable complex is assumed to be one of the possible reasons of their synergistic inhibition of CCRF-CЕM cells proliferation.
Application of C60 fullerene in combination with 2.5 μM HL was shown to have no harmful effect on structural stability of blood erythrocytes membrane. Thus, combined action of C60 fullerene and HL in a low concentration potentiated HL cytotoxic effect against human leukemic cells and was not followed by hemolytic effect.
Polymer-multiwalled carbon nanotube (MWCNT) nanohybrids, which differ in surface charge have been synthesized to study the bioelectrocatalysis of adsorbed cellobiose dehydrogenase (CDH) from Phanerochaete sordida on gold electrodes. To obtain negatively charged nanohybrids, poly(3-amino-4-methoxybenzoic acid-co-aniline) (P(AMB-A)) was covalently linked to the surface of MWCNTs while modification with p-phenylenediamine (PDA) converted the COOH-groups to positively charged amino groups. Fourier transform infrared spectroscopy (FTIR) measurements verified the p-phenylenediamine (PDA) modification of the polymer-CNT nanohybrids. The positively charged nanohybrid MWCNT-P(AMB-A)-PDA promoted direct electron transfer (DET) of CDH to the electrode and bioelectrocatalysis of lactose was observed. Amperometric measurements gave an electrochemical response with KMapp = 8.89 mM and a current density of 410 nA/cm2 (15 mM lactose). The catalytic response was tested at pH 3.5 and 4.5. Interference by ascorbic acid was not observed. The study proves that DET between the MWCNT-P(AMB-A)-PDA nanohybrids and CDH is efficient and allows the sensorial detection of lactose.