SEARCH · bioRxiv Science

Results for “biochemistry”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27Linked to original sources

bioRxiv2022

Molecular insights into the MCM8/9 helicase complex in DNA unwinding and translocation

MCM8 and MCM9 form a functional helicase complex (MCM8/9) that plays an essential role in DNA homologous recombination repair for DNA double-strand break. However, the structural characterization of MCM8/9 for DNA binding/unwinding remains unclear. Here, we report structures of the MCM8/9 complex using cryo-electron microscopy single particle analysis. The structures reveal that MCM8/9 is arranged into a heterohexamer through a three-fold symmetry axis, creating a central channel that accommodates DNA. Multiple characteristic hairpins from the N-terminal oligosaccharide/oligonucleotide (OB) domains of MCM8/9 protrude into the central channel and serve to unwind the duplex DNA. When activated by HROB, the structure of MCM8/9s N-tier ring converts its symmetry from C3 to C1 with a conformational change that expands the MCM8/9s trimer interface. Moreover, our structural dynamic analyses revealed that the flexible C-tier ring exhibited rotary motions relative to the N-tier ring, which is required for the unwinding ability of MCM8/9. In summary, our structural and biochemistry study provide a basis for understanding the DNA unwinding mechanism of MCM8/9 helicase in homologous recombination.

biophysics↗

bioRxiv2022

Neuronal membrane proteasomes homeostatically regulate neural circuit activity in vivo and are required for learning-induced behavioral plasticity

Protein degradation is critical for brain function through processes that remain poorly understood. Here we investigated the in vivo function of a recently reported neuronal membrane-associated proteasome (NMP) in the brain of Xenopus laevis tadpoles. We demonstrated that NMPs are present in the tadpole brain with biochemistry and electron microscopy, and showed that they actively degrade neuronal activity-induced nascent proteins. Using in vivo calcium imaging in the optic tectum, we showed that acute inhibition of NMP function rapidly increased spontaneous neuronal activity, resulting in hyper-synchronization among tectal neurons. At the circuit level, inhibiting NMPs abolished learning-dependent improvement in a visuomotor behavior paradigm in live animals. Our data provide the first in vivo characterization of NMP functions in the vertebrate nervous system and suggest that NMP-mediated degradation of activity-induced nascent proteins may serve as a homeostatic modulatory mechanism in neurons that is critical for regulating neuronal activity and experience-dependent circuit plasticity.

neuroscience↗

bioRxiv2022

Cytocapsulae and cytocapsular tubes are golden targets for precise, effective and efficient cancer diagnosis and therapy in 307 kinds of liquid and solid cancers

Cancer is a leading cause of human lethality worldwide. A cancer cell is not only the cytoplasm and nucleus enclosed in the cell membrane. A malignant tumor is not only a mass of cancer cells. Cancer in a patient is not only isolated tumors distributed in tissues and organs. The comprehensive understanding of the complete structural compartments and their biological functions of cancer cells, malignant tumors and tumor systems in patients in vivo is an indispensable prerequisite for effective drug development and efficient clinical cancer pharmacotherapies. However, there remains an open question for a long time: what are the complete structural compartments of cancer cells, malignant tumors and tumor systems in the patient body? Here, we comprehensively and systematically investigated the complete structural compartments of cancer cells, malignant tumors and cytocapsular tube (CCT) network-tumor system (CNTS) of 307 types/subtypes of cancers in 33 kinds of tissues and organs by biochemistry and molecular biology assays with 9,811 clinical cancer tissue specimens from 9,637 cancer patients and >110,000 immunohistochemistry (IHC) fluorescence staining images. We discovered the complete structural compartments of cancer cells, malignant tumors and CNTSs in 307 kinds of cancers, elucidated mechanisms of cytocapsular growth and CCT elongation, and identified the comprehensive procedures of cancer evolution in patients. This study paves avenues for curing all kinds of cancers.

cancer biology↗

bioRxiv2022

NMNAT2 is the major NAD+ provider for vesicular glycolysis generating on-board energy for fast axonal transport cargos

BackgroundBioenergetic maladaptations and axonopathy are often found in the early stages of neurodegeneration. Nicotinamide adenine dinucleotide (NAD), an essential cofactor for energy metabolism, is mainly synthesized by Nicotinamide mononucleotide adenylyl transferase 2 (NMNAT2) in CNS neurons. NMNAT2 mRNA levels are reduced in the brains of Alzheimers, Parkinsons and Huntingtons disease. Here we addressed whether NMNAT2 is required for axonal health of cortical glutamatergic neurons, whose far-projecting axons are vulnerable to neurodegenerative conditions. We also tested if NMNAT2 maintains axonal health by ensuring proper axonal ATP levels for axonal transport, a critical function of axons. MethodsWe generated mouse and cultured neuron models to determine the impact of NMNAT2 loss from cortical glutamatergic neurons on axonal transport, energetic metabolism, and morphological integrity. In addition, we determined if exogenous NAD supplementation or inhibiting NAD hydrolase sterile alpha and TIR motif-containing protein 1 (SARM1) prevented axonal deficits caused by NMNAT2 loss. Our study used a combination of genetic, molecular biology, immunohistochemistry, biochemistry, fluorescent time-lapse imaging, live imaging with optical sensors, and anti-sense oligos application. ResultsWe provide in vivo evidence that NMNAT2 in cortical glutamatergic neurons is required for axonal survival. Using in vivo and in vitro studies we demonstrate that NMNAT2 protects axons by ensuring the proper NAD-redox potential in distal axons of cortical neurons to support glycolysis on vesicular cargos, thus ensuring "onboard" ATP production fueling axonal transport. Exogenous NAD+ supplementation to NMNAT2 KO cortical neurons restores glycolysis and resumes fast axonal transport. Finally, we demonstrate both in vitro and in vivo that reducing the activity of SARM1, an NAD degradation enzyme, can reduce axonal transport deficits and suppress axon degeneration in NMNAT2 KO neurons. ConclusionNMNAT2 ensures axonal health by maintaining NAD redox potential in distal axons to ensure efficient vesicular glycolysis required for fast axonal transport.

neuroscience↗

bioRxiv2022

NICEgame: A workflow for annotating the knowledge gaps in metabolic reconstructions, using known and hypothetical reactions

Advances in medicine and biotechnology rely on the further understanding of biological processes. Despite the increasingly available types and amounts of omics data, significant biochemical knowledge gaps remain uncharacterized. Several approaches have been developed during the past years to identify missing metabolic annotations in genome-scale. However, these approaches suggest missing metabolic reactions within a limited set of already characterized metabolic capabilities. In this study, we introduce NICEgame (Network Integrated Computational Explorer for Gap Annotation of Metabolism), a workflow to characterize missing metabolic capabilities in genome-scale metabolic models using the ATLAS of Biochemistry. NICEgame suggests alternative sets of known and hypothetical reactions to resolve gaps in metabolic networks, assesses their thermodynamic feasibility, and suggests candidate genes and proteins to catalyze the introduced reactions. We use gene essentiality data use to identify metabolic gaps in the latest genome-scale model of Escherichia coli, iML1515. We apply our gap-filling approach and further enhance its genome annotation, by suggesting reactions and putative genes to resolve 46 % of the false negative gene essentiality predictions.

systems biology↗

bioRxiv2022

Spatiotemporal growth pattern during plant nutation implies fast dynamics for cell wall mechanics and chemistry: a multiscale study in Averrhoa carambola

Nutation is the most striking and ubiquitous example of the rhythmic nature of plant development. Although there is a consensus that this wide oscillatory motion is driven by growth, its internal mechanisms have not been fully elucidated yet. In this work, we study the specific case of nutation in compound leaves in the archetypal Averrhoa carambola plant. We quantify the macroscopic growth kinematics with time lapse imaging, image analysis and kinematics modeling. We further characterize the mechanical and chemical properties of the cell wall with atomic force microscopy and immunolabelling. Our data first reveal that the differential growth driving nutation is localized and peaks where the average growth drops. We then show this specific spatiotemporal growth profile is compatible with local contraction events. At the cell wall level, differential growth is further colocalized with an asymmetry of the cell wall elastic modulus, and with an asymmetric distribution of homogalacturonans (HG). Our results not only back up the hypothesis of HG being involved in plant growth, but also build up on it by suggesting a dynamic nature for this process. Significance StatementNutation is an oscillatory motion displayed by many organs of growing plants. Most works on nutation focus on its relation to external stimuli attempting to explain its origins. By contrast, its internal physiological mechanisms remain to be fully explored. Here we propose an experimental and multiscale characterization of undisturbed nutation. We determine the macroscopic growth profile and show it is compatible with cell expansion but also local contractions in the tissues. At the microscopic level, we reveal that both the rigidity and composition of the cell wall are asymmetrically distributed where nutation occurs. The combination of results on both scales brings contributions to the understanding of interplay between global movement, local growth, cell wall mechanics and cell wall biochemistry.

biophysics↗

bioRxiv2022

Machine Learning Informed Predictions of Nanoparticle Mobility and Fate in the Mucus Barrier

Diffusion and transport of nanomaterials through mucus, is of critical importance to many basic and applied areas of research such as drug delivery and infectious disease. However, it is often challenging to interpret the dynamics of nanoparticles within the mucus gel due to its inherently heterogeneous microstructure and biochemistry. In this study, we measured the diffusion of densely PEGylated nanoparticles (NP) in human airway mucus ex vivo using multiple particle tracking and utilized machine learning to classify NP movement as either traditional Brownian motion (BM) or one of two different models of anomalous diffusion, fractional Brownian motion (FBM) and continuous time random walk (CTRW). Specifically, we employed a physics-based neural network model to predict the modes of diffusion experienced by individual NP in human airway mucus. We observed rapidly diffusing NP primarily exhibit BM whereas CTRW and FBM exhibited lower diffusion rates. Given the use of muco-inert nanoparticles, the observed transition from diffusive (BM) to sub-diffusive (CTRW/FBM) motion is likely a result of patient-to-patient variation in mucus network pore size. Using mathematic models that account for the mode of NP diffusion, we predicted the percentage of nanoparticles that would cross the mucus barrier over time in human airway mucus with varied total solids concentration. We also applied this approach to explore the transport modes and predicted fate of influenza A virus within human mucus. These results provide new tools to evaluate the extent of synthetic and viral nanoparticle penetration through mucus in the lung and other tissues.

bioengineering↗

bioRxiv2022

Protease Activity Analysis: A Toolkit for Analyzing Enzyme Activity Data

Analyzing the activity of proteases and their substrates is critical to defining the biological functions of these enzymes and to designing new diagnostics and therapeutics that target protease dysregulation in disease. While a wide range of databases and algorithms have been created to better predict protease cleavage sites, there is a dearth of computational tools to automate analysis of in vitro and in vivo protease assays. This necessitates individual researchers to develop their own analytical pipelines, resulting in a lack of standardization across the field. To facilitate protease research, here we present Protease Activity Analysis (PAA), a toolkit for the preprocessing, visualization, machine learning analysis, and querying of protease activity datasets. PAA leverages a Python-based object-oriented implementation that provides a modular framework for streamlined analysis across three major components. First, PAA provides a facile framework to query datasets of synthetic peptide substrates and their cleavage susceptibilities across a diverse set of proteases. To complement the database functionality, PAA also includes tools for the automated analysis and visualization of user-input enzyme-substrate activity measurements generated through in vitro screens against synthetic peptide substrates. Finally, PAA can supports a set of modular machine learning functions to analyze in vivo protease activity signatures that are generated by activity-based sensors. Overall, PAA offers the protease community a breadth of computational tools to streamline research, taking a step towards standardizing data analysis across the field and in chemical biology and biochemistry at large.

bioinformatics↗

bioRxiv2022

Direct measurement of the aerotactic response in a bacterial suspension

Aerotaxis is the ability of motile cells to navigate towards oxygen. A key question is the dependence of the aerotactic velocity with the local oxygen concentration c. Here we combine simultaneous bacteria tracking and local oxygen concentration measurements using Ruthenium encapsulated in micelles to characterise the aerotactic response of Burkholderia contaminans, a motile bacterium ubiquitous in the environment and present in living organisms. In our experiments, an oxygen gradient is produced by the bacterial respiration in a sealed glass capillary permeable to oxygen at one end, producing a bacterial band travelling towards the oxygen source. We compute the aerotactic response{chi} (c) both at the population scale, from the drift velocity in the bacterial band, and at the bacterial scale, from the angular modulation of the run times. Both methods are consistent with a power-law{chi} {propto} c-2, in good agreement with existing models based on the biochemistry of bacterial membrane receptors.

biophysics↗

bioRxiv2022

Structure and function of diadenylate cyclase DacM from Mycoplasma ovipneumoniae

Cyclic diadenosine monophosphate (c-di-AMP) is a second-messenger nucleotide that is produced by many bacteria. C-di-AMP can not only regulate bacterial growth, cell-wall homeostasis, ion transport and gene transcription, but can also be recognized by multiple sensor / receptor proteins in infected host cells to trigger an innate immune response. Mycoplasma ovipneumoniae causes non-progressive pneumonia in both sheep and goats. Here, we analyzed c-di-AMP signaling in M. ovipneumoniae, which is a genome-reduced obligately pathogenic bacterium. Our results demonstrate that these bacteria can produce c-di-AMP, and we could identify the diadenylate cyclase, which was named DacM. The enzyme was found to utilize both ATP and ADP to synthesize c-di-AMP, resembling CdaM from a novel family of diadenylate cyclases first found in Mycoplasma pneumoniae. Furthermore, we present the crystal structures of DacM in the apo state and substrate-bound state at 3 [A] and 1.9 [A] resolution, respectively. Mutation of residues Asp112, Gly113, Tyr128, Phe129, and Arg143 surrounding the active sites to Ala were lethal to DacM enzymatic activity. These structures provide valuable insights into the biochemistry of c-di-AMP, and offer a basis for the structure-based design of new drugs for animal husbandry.

pathology↗

bioRxiv2022

Replacing bar graphs of continuous data with more informative graphics: Are we making progress?

Recent work has raised awareness about the need to replace bar graphs of continuous data with informative graphs showing the data distribution. The impact of these efforts is not known. This observational meta-research study examined how often scientists in different fields use various graph types, and assessed whether visualization practices have changed between 2010 and 2020. We developed and validated an automated screening tool, designed to identify bar graphs of counts or proportions, bar graphs of continuous data, bar graphs with dot plots, dot plots, box plots, violin plots, histograms, pie charts, and flow charts. Papers from 23 fields (approximately 1,000 papers/field/year) were randomly selected from PubMed Central and screened (n=227,998). F1 scores for different graphs ranged between 0.83 and 0.95 in the internal validation set. While the tool also performed well in external validation sets, F1 scores were lower for uncommon graphs. Bar graphs are more often used incorrectly to display continuous data than they are used correctly to display counts or proportions. The proportion of papers that use bar graphs of continuous data varies markedly across fields (range in 2020: 4%-58%), with high rates in biochemistry and cell biology, complementary and alternative medicine, physiology, genetics, oncology and carcinogenesis, pharmacology, microbiology and immunology. Visualization practices have improved in some fields in recent years. Fewer than 25% of papers use flow charts, which provide information about attrition and the risk of bias. This study highlights the need for continued interventions to improve visualization and identifies fields that would benefit most.

scientific communication and education↗

bioRxiv2022

The RNA-binding protein EIF4A3 promotes axon development by direct control of the cytoskeleton

The exon junction complex (EJC), nucleated by EIF4A3, is indispensable for mRNA fate and function throughout eukaryotes. Unexpectedly, we discover that EIF4A3 directly controls microtubules independent of RNA, and this is critical for neural wiring. While neuronal survival in the developing mouse cerebral cortex depends upon an intact EJC, axonal tract formation requires only Eif4a3. Using human cortical organoids, we demonstrate that EIF4A3 disease mutations also impair neuronal maturation, highlighting conserved functions relevant for neurodevelopmental pathology. Employing biochemistry and molecular modeling we discover that EIF4A3 directly binds to microtubules, mutually exclusive of the RNA-binding complex. In growing neurons, EIF4A3 is essential for microtubule dynamics, and sufficient to promote microtubule polymerization and stability in vitro. Together, our data show that tubulin-bound EIF4A3 orchestrates microtubule dynamics, underlying key events of neuronal development. This reveals a new mechanism by which neurons re-utilize core gene expression machinery to rapidly and directly control the cytoskeleton. HighlightsO_LIThe Exon Junction Complex controls neuronal survival but only EIF4A3 directs axonal growth C_LIO_LIEIF4A3 controls axonal tract formation in vivo. C_LIO_LIHuman EIF4A3 deficient iPSC-derived cortical organoids recapitulate neuronal defects. C_LIO_LIEIF4A3 directly binds to microtubules to control their growth and stability in neurons. C_LI

neuroscience↗

bioRxiv2022

Serum profiles of metabolomic and GDF-15 differentiate idiopathic pulmonary fibrosis from other interstital lung diseases: a preliminary study

Objective1.Explore the differential metabolites and metabolic pathways between different interstitial lung disease (ILD) and healthy controls, so as to find out new biomarkers and metabolic pathways of ILD and provide new biological targets for IPF diagnosis and treatment.2.Detect the levels of serum related fibrosis and metabolic indexes of ILD, explore the relationship between these indexes and the types and general parameters of ILD diseases, and focus on GDF-15 on the basis of metabonomics, explore new metabolic pathways related to ILD, and further expound the pathogenesis of idiopathic pulmonary fibrosis. Method1.According to the inclusion criteria and exclusion criteria, the ILD patients admitted to our hospital from January 1, 2021 to January 1, 2022 were signed with informed consent, and all of them had clear multidisciplinary diagnosis. At the same time, the physical examination in the health management center of our hospital was selected as the healthy control group. General clinical data of ILD patients and healthy controls were collected, including gender, age, onset, clinical manifestations, clinical biochemistry, lung function and other related data. Collect patients peripheral venous blood, keep serum samples, and analyze the serum of ILD patients and healthy controls by liquid chromatography-mass spectrometry (LC-MS) to obtain differential metabolites, metabolic maps and related data. According to the diagnosis, the patients were divided into Idiopathic pulmonary fibrosis (IPF), connective tissue disease-associated interstitial lung disease (CTD-ILD), other interstitial lung disease (ILD) patients and healthy control group. R statistical software was used to observe whether there are differential metabolites in IPF group and healthy control group, CTD-ILD group and healthy control group, other ILD groups and healthy control group, IPF group and CTD-ILD group, IPF group and other ILD groups, CTD-ILD group and other ILD groups by using positive and negative ion flow charts and score charts of orthogonal partial least squares-discriminant analysis. And the potential biomarkers were found through the S-plot diagram of OPLS-DA and the variable weight value VIP>1. ROC curve analysis of differential metabolites was carried out by SPSS21.0 software to analyze the value of differential diagnosis and find out new biomarkers with differential diagnosis significance. Based on KEGG database, the metabolic pathway enrichment analysis of differential metabolites was carried out to find out the main metabolic pathways. 2.Serum levels of type I collagen, KL-6, IL-1{beta}, TNF-, IGF-1 and GDF-15 were detected by Enzyme linked immunosorbent assay (ELISA) in all patients and healthy controls. Using SPSS21.0 statistical software and R statistical software, using T-test, variance analysis or nonparametric test method, according to different diagnoses (IPF/CTD-ILD/ other ILD/ healthy control group, ILD/ healthy control group, IPF/ other), the data were analyzed and compared in subgroups. Pearson correlation analysis was used to analyze the correlation between serum biomarkers and other factors such as lung function, metabolomics and so on. ROC curve was used to analyze the diagnostic efficiency of each index, and the best critical value, sensitivity and specificity were found out. Results1.Analysis of general clinical data and clinical indicators: 26 cases of IPF, 21cases of CTD-ILD, 23 cases of others ILD and 20 cases of healthy control group were included, respectively. There were significant differences in age, sex and smoking history among the four groups (P < 0.05), and the differences were statistically significant. There were statistically significant differences among IPF group, CTD-ILD group and other ILD groups in cough and expectoration symptoms, eosinophil count percentage, creatine kinase, creatine kinase isoenzyme, C-reactive protein and carbon monoxide diffusion capacity (DLco) (P < 0.05). 2. Metabonomics analysis: LC-MC total ion flow chart of serum samples and orthogonal partial least squares discriminant analysis (OPLS-DA) of serum samples showed the difference of ion peak intensity, and there were different metabolites among each group. The OPLS-DA model has good quality evaluation and reliable data analysis. There are 193, 115, 101, 188, 148 and 169 differential metabolites in IPF group and healthy control group, IPF group and CTD-ILD group, CTD-ILD group and other ILD groups, others ILD groups and healthy control group respectively. There is a correlation between the differential metabolites of each ILD subgroup and the healthy control group. The most relevant metabolic pathways in IPF mainly include choline metabolic pathway, metabolic pathway and linoleic acid metabolic pathway in cancer. The metabolic pathways most related to CTD-ILD and other ILD include choline metabolic pathway and retrograde neural signal metabolic pathway in cancer. Metabolic pathway and linoleic acid metabolic pathway may distinguish IPF from other ILD. Metabolites involved in metabolic pathway are L-Glutamate, PE(18:3(6Z,9Z,12Z)/P-18:0) and PC (18: 2 (9z, 12z)/20: 2 (11z, 14z)), respectively. There are three differential metabolites of linoleic acid pathway, namely 12,13-EpOME, 13S-HODE and PC(18:2(9Z,12Z)/20:2(11Z,14Z)). There are 35 kinds of differential metabolites in IPF group and healthy control group, and the top three places of AUC are 3- sulfodeoxycholic acid, 20,22-dihydrodigitalis glycoside, ({+/-}14) (15)-EET-SI, with AUC values of 0.985, sensitivity of 100% and specificity of 92.3%. L- acetylcarnitine, 5-hydroxydodecanoate and L-Glutamate are involved in significant enrichment pathways, among which the ROC curve area of L-Glutamate is the largest, with AUC value of 0.921, cutoff value of 40145.490, sensitivity of 80%, specificity of 96%, and participation in metabolic pathways. 3. Serum metabolism-related detection indexes: The six serum detection indexes of IPF group and CTD-ILD group are higher than those of healthy control group, and the difference is statistically significant (P < 0.05), but the difference between IPF group and CTD-ILD group is not statistically significant (P>0.05). The expression of GDF-15 in IPF group and non-IPF ILD group was higher than that in healthy control group, with significant difference, but there was no significant difference between IPF group and non-IPF ILD group. Type I collagen and IL-1{beta} were negatively correlated with DLco. KL-6 is negatively correlated with the measured values of VC and DLco; IGF-1 was negatively correlated with FVC, VC and DLco (all P<0.05). GDF-15 was positively correlated with type I collagen, KL-6, IL-1{beta}, TNF- and IGF-1, and the difference was statistically significant (P < 0.05). ROC curve shows that the area under ROC curve (AUC) of six serum indexes in IPF group is greater than 0.9; In CTD-ILD group, the AUC of IGF-1 was greater than 0.9, the cutoff value was 35.081ng/ml, the sensitivity was 90%, the specificity was 76%, and the area under ROC curve was greater than 0.8, and the difference was statistically significant. In other ILD groups, the ROC curve area of these six indicators ranged from 0.6 to 0.8, among which IGF-1, GDF-15 and TNF- had diagnostic value. In IPF, L-Glutamate was positively correlated with type I collagen, KL-6, IGF-1, IL-1{beta}, TNF- and GDF-15, and the difference was statistically significant (P < 0.05), with the highest correlation with IGF-1. ConclusionIn this study, the serum samples of IPF patients, CTD-ILD patients, other interstitial lung diseases and healthy controls were analyzed by LM-MS and ELISA, and the following conclusions were drawn. 1.There are differences in serum metabolites in different groups. IPF has three main metabolic pathways, namely choline metabolic pathway, metabolic pathway and linoleic acid metabolic pathway in cancer, among which metabolic pathway and linoleic acid metabolic pathway are different from other groups. There are 35 differential metabolites in IPF and healthy control group with the area under ROC curve larger than 0.80, among which the metabolites with the highest diagnostic value are 3- sulfodeoxycholic acid, 20,22-dihydrodigitalis glycoside and ({+/-}) 14 (15)-EET-SI. The AUC value of L- glutamic acid is the highest among the metabolites that participate in the enrichment pathway significantly. 2. The expressions of type I collagen, KL-6, IL-1{beta}, TNF-, IGF-1 and GDF-15 are different in different ILDs, which have potential diagnostic and differential diagnostic value, and are correlated with lung function indexes. In IPF, GDF-15 is positively correlated with L-Glutamate, which may be involved in metabolic pathway to further promote pulmonary fibrosis.

molecular biology↗

bioRxiv2022

Nitroimidazopyrazinones with oral activity against tuberculosis and Chagas disease in mouse models of infection

Tuberculosis remains one of the leading causes of death from a single infectious agent, surpassing both AIDS and malaria. In recent years, two bicyclic nitroimidazole drugs, delamanid and pretomanid have been approved to treat this airborne infection. This has spurred a renewed interest in developing new and improved nitroimidazole analogs. We have previously identified a new bicyclic heteroaromatic subclass, the nitroimidazopyrazinones, with substituted analogs showing promising activity against Mycobacterium tuberculosis under both aerobic and hypoxic environments. A second generation of nitroimidazopyrazinones with extended biaryl side chain also possessed good antiparasitic activity against Trypanosoma brucei brucei and Trypanosoma cruzi, suggesting the utility of this new scaffold for development into potential candidates against both tuberculosis and the kinetoplastid parasites which cause neglected tropical diseases. In this study, we further evaluated the properties of nitroimidazopyrazinone derivatives by assessing their selectivity against different mycobacterial species, measuring their reduction potential, and determining the kinetic parameters as substrates of the deazaflavin-dependent nitroreductase (Ddn), which is the activating enzyme of delamanid and pretomanid in M. tuberculosis. We also conducted an in vivo evaluation of a lead compound, MCC8967 that demonstrated a favorable pharmacokinetic profile, with good oral bioavailability and efficacy in an acute M. tuberculosis infection model. Two other promising compounds MCC9481 and MCC9482, with good in vitro activity (IC50 = 0.016 and 0.10 {micro}M, respectively) against T. cruzi, the causative agent for Chagas diseases, were similarly tested for in vivo activity. These compounds also exhibited good oral bioavailability, and transiently reduced the acute-stage parasite burden by >98-99% at doses of 50 mg/kg once or twice daily, similar to benznidazole at 100 mg/kg once daily. Overall, we have demonstrated that active nitroimidazopyrazinones have potential to be developed as clinical candidates against both tuberculosis and Chagas disease. Author SummaryTuberculosis and parasitic infections continue to impose a significant threat to public health and economic growth worldwide. Most of the efforts to control these diseases still rely on drug treatments with limited effectiveness and significant side effects. There is now an urgent need to develop new treatments to combat these infections. Here, we report the in vitro and in vivo profile of a new bicyclic nitroimidazole subclass, namely nitroimidazopyrazinones, against mycobacteria and Trypanosoma cruzi. We found that derivatives with monocyclic side chains are selective against Mycobacterium tuberculosis, the causative agent of tuberculosis, but not active against other nontuberculosis mycobacteria. In an acute mouse model, they were able to reduce the bacterial load in lungs via oral administration. From a biochemistry perspective, we demonstrated that deazaflavin-dependent nitroreductase (Ddn) could act effectively on nitroimidazopyrazinones, indicating the potential of Ddn as an activating enzyme for these new compounds in M. tuberculosis. We also showed that derivatives with extended biaryl side chain were effective in suppressing infection in an acute T. cruzi infected murine model, with satisfactory oral bioavailability. These findings improve the understanding of the biological profile of nitroimidazopyrazinones for further development as potential antitubercular and antiparasitic agents.

pharmacology and toxicology↗

bioRxiv2022

Introducing CELLBLOKS: a novel organ-on-a-chip platform allowing a plug-and-play approach towards building organotypic models

Human organs are structurally and functionally complex systems. Their function is driven by interactions between many specialised cell types, which is difficult to unravel on a standard petri-dish format. Conventional "petri-dish" approaches to culturing cells are static and self-limiting. However, current organ-on-a-chip technologies are difficult to use, have a limited throughput and lack compatibility with standard workflow conditions. We developed CELLBLOKS(R) as a novel "plug & play" organ-on-a-chip platform that enables straightforward creation of multiple-cell type organ specific microenvironments and demonstrate its advantages by building a liver model representative of live tissue function. CELLBLOKS(R) allows one to systematically test and identify various cell combinations that replicate optimal hepatic relevance. The combined interactions of fibroblasts, endothelial cells and hepatocytes were analysed using hepatic biochemistry (CYP3A4 and urea), cellular proliferation and transporter activities (albumin). The results demonstrate that optimal liver functional can be achieved in cross talk co-culture combinations compared to conventional mono-culture. The optimised CELLBLOKS(R) liver model was tested to analyse drug-induced liver toxicity using tamoxifen. The data suggests that our CELLBLOKS(R) liver model is highly sensitive to toxic insult compared to mono-culture liver model. In summary, CELLBLOKS(R) provides a novel cell culture technology for creating human relevant organotypic models that are easy and straightforward to establish in laboratory settings.

cell biology↗

bioRxiv2022

Development of transformation for genome editing of an emerging model organism

With the advances in genomic sequencing, many organisms with novel biological properties are ripe for use as emerging model organisms. However, to make full use of them, transformation methods need to be developed to permit genome editing. Here, we present development of transformation for the fungus fly Sciara (Bradysia) coprophila; this may serve as a paradigm for development of transformation for other emerging systems, especially insects. Sciara has a variety of unique biological features including locus-specific developmentally-regulated DNA amplification; chromosome imprinting; a monopolar spindle in male meiosis I; non-disjunction of the X chromosome in male meiosis II; X chromosome elimination in early embryogenesis; germ line limited (L) chromosomes; high resistance to radiation. Mining the unique biology of Sciara requires a transformation system to test mutations of DNA sequences that may play roles for these features. We describe a Sciara transformation system using a modified piggyBac transformation vector and detailed protocols we have developed to accommodate Sciara-specific requirements. This advance will provide a platform for us and others in the growing Sciara community to take advantage of this unique biological system. In addition, the versatile piggyBac vectors described here and transformation methods will be useful for other emerging model systems. Author BiographiesSusan A. Gerbi (Ph.D. with Joseph Gall at Yale University 1970) is the George Eggleston, Professor of Biochemistry at Brown University. Her research includes chromosomes, DNA replication and ribosomal RNA. She was President and is a Fellow of ASCB, a Fellow of AAAS and received the RI Governors Award for Scientific Achievement. Other honors include RNA Society/CSHL Press Distinguished Research Mentor award; GSA George Beadle award; ASCB Senior Leadership/ Mentoring Award. She is a national leader in graduate education, including member of the National Academy of Sciences Panel on Bridges to Independence that led to the NIH K99 program, Chair of the AAMC Graduate Research Education Training Group; Chair of the FASEB Consensus Conference on Graduate Education. Yutaka Yamamoto (M.D. Kansai Medical University 1990; Ph.D. with Walter Gehring at Biozentrum - Basel 1995; postdoc with David Glover at Dundee University and University of Cambridge) is a research associate at Brown University. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=65 SRC="FIGDIR/small/488772v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@17fce9aorg.highwire.dtl.DTLVardef@1d4e96forg.highwire.dtl.DTLVardef@129a689org.highwire.dtl.DTLVardef@1748fd8_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2022

Metalation calculators for E. coli strain JM109 (DE3): Aerobic, anaerobic and hydrogen peroxide exposed cells cultured in LB media

Three web-based calculators, and three analogous spreadsheets, have been generated that predict in vivo metal occupancies of proteins based on known metal affinities. The calculations exploit estimates of the availabilities of the labile buffered pools of different metals inside a cell. Here, metal availabilities have been estimated for a strain of E. coli that is commonly used in molecular biology and biochemistry research, for example in the production of recombinant proteins. Metal availabilities have been examined for cells grown in LB medium aerobically, anaerobically and in response to H2O2 by monitoring the abundance of a selected set of metal-responsive transcripts by qPCR. The selected genes are regulated by DNA-binding metal sensors that have been thermodynamically characterised in related bacterial cells enabling gene expression to be read-out as a function of intracellular metal availabilities expressed as free energies for forming metal complexes. The calculators compare these values with the free energies for forming complexes with the protein of interest, derived from metal affinities, to estimate how effectively the protein can compete with exchangeable binding sites in the intracellular milieu. The calculators then inter-compete the different metals, limiting total occupancy of the site to a maximum stoichiometry of 1, to output percentage occupancies with each metal. In addition to making these new and conditional calculators available, an original purpose of this article was to provide a tutorial which discusses constraints of this approach and presents ways in which such calculators might be exploited in basic and applied research, and in next-generation manufacturing.

cell biology↗

bioRxiv2022

Rapid modeling of experimental molecular kinetics with simple electronic circuits instead of with complex differential equations

Kinetic modeling has relied on using a tedious number of mathematical equations to describe molecular kinetics in interacting reactions. The long list of differential equations with associated abstract variables and parameters inevitably hinders readers easy understanding of the models. However, the mathematical equations describing the kinetics of biochemical reactions can be exactly mapped to the dynamics of voltages and currents in simple electronic circuits wherein voltages represent molecular concentrations and currents represent molecular fluxes. For example, we theoretically derive and experimentally verify accurate circuit models for Michaelis-Menten kinetics. Then, we show that such circuit models can be scaled via simple wiring among circuit motifs to represent more and arbitrarily complex reactions. Hence, we can directly map reaction networks to equivalent circuit schematics in a rapid, quantitatively accurate, and intuitive fashion without needing mathematical equations. We verify experimentally that these circuit models are quantitatively accurate. Examples include i) different mechanisms of competitive, noncompetitive, uncompetitive, and mixed enzyme inhibition, important for understanding pharmacokinetics; ii) product-feedback inhibition, common in biochemistry; iii) reversible reactions, important in many metabolic pathways; and iv) translation and transcription dynamics in a cell-free system, which brings insight into the functioning of all gene-protein networks. We envision that circuit modeling and simulation could become a powerful scientific communication language and tool for quantitative studies of kinetics in biology.

bioengineering↗