Molecular basis of RNA guanine-7 methyltransferase (RNMT) activation by RAM

Maturation and translation of mRNA in eukaryotes requires the addition of the 7-methylguanosine cap. In vertebrates, the cap methyltransferase, RNA guanine-7 methyltransferase (RNMT), has an activating subunit, RNMT-Activating Miniprotein (RAM). Here we report the first crystal structure of the human RNMT in complex with the activation domain of RAM. A relatively unstructured and negatively charged RAM binds to a positively charged surface groove on RNMT, distal to the active site. This results in stabilisation of a RNMT lobe structure which co-evolved with RAM and is required for RAM binding. Structure-guided mutagenesis and molecular dynamics simulations reveal that RAM stabilises the structure and positioning of the RNMT lobe and the adjacent α-helix hinge, resulting in optimal positioning of helix A which contacts substrates in the active site. Using biophysical and biochemical approaches, we observe that RAM increases the recruitment of the methyl donor, AdoMet (S-adenosyl methionine), to RNMT. Thus we report the mechanism by which RAM allosterically activates RNMT, allowing it to function as a molecular rheostat for mRNA cap methylation.     

Establishment of Elevated Serum Levels of IL-10, IL-8 and TNF-β as Potential Peripheral Blood Biomarkers in Tubercular Lymphadenitis: A Prospective Observational Cohort Study

Background

Tubercular lymphadenitis (TL) is the most common form of extra-pulmonary tuberculosis (TB) consisting about 15–20% of all TB cases. The currently available diagnostic modalities for (TL), are invasive and involve a high index of suspicion, having limited accuracy. We hypothesized that TL would have a distinct cytokine signature that would distinguish it from pulmonary TB (PTB), peripheral tubercular lymphadenopathy (LNTB), healthy controls (HC), other lymphadenopathies (LAP) and cancerous LAP. To assess this twelve cytokines (Tumor Necrosis Factor (TNF)—α, Interferon (IFN) -γ, Interleukin (IL)-2, IL-12, IL-18, IL-1β, IL-10, IL-6, IL-4, IL-1Receptor antagonist (IL-1Ra), IL-8 and TNF-β, which have a role in pathogenesis of tuberculosis, were tested as potential peripheral blood biomarkers to aid the diagnosis of TL when routine investigations prove to be of limited value.

Methods and Findings

A prospective observational cohort study carried out during 2010–2013. This was a multi-center study with three participating hospitals in Delhi, India where through random sampling cohorts were established. The subjects were above 15 years of age, HIV-negative with no predisposing ailments to TB (n = 338). The discovery cohort (n = 218) had LNTB (n = 50), PTB (n = 84) and HC (n = 84). The independent validation cohort (n = 120) composed of patients with cancerous LAP (n = 35), other LAP (n = 20) as well as with independent PTB (n = 30), LNTB (n = 15) and HC (n = 20). Eight out of twelve cytokines achieved statistical relevance upon evaluation by pairwise and ROC analysis. Further, variable selection using random forest backward elimination revealed six serum biosignatures including IL-12, IL-4, IL-6, IL-10, IL-8 and TNF-β as optimal for classifying the LNTB status of an individual. For the sake of clinical applicability we further selected a three analyte panel (IL-8, IL-10 and TNF-β) which was subjected to multinomial modeling in the independent validation cohort which was randomised into training and test cohorts, achieving an overwhelming 95.9% overall classifying accuracy for correctly classifying LNTB cases with a minimal (7%) misclassification error rate in the test cohort.

Conclusions

In our study, a three analyte serum biosignatures and probability equations were established which can guide the physician in their clinical decision making and step wise management of LNTB patients. This set of biomarkers has the potential to be a valuable adjunct to the diagnosis of TL in cases where AFB positivity and granulomatous findings elude the clinician.     

Glycosylation of monoclonal antibody products: Current status and future prospects

Protein based therapeutics have started to dominate the pharmaceutical landscape primarily due to the high efficacy that they have demonstrated against complex diseases. Despite the significant success, issues with regards to safety, efficacy and quality of biotherapeutics have been a point of considerable debate and concern among the various stakeholders. The correlation between the glycoform profile and the safety and efficacy of a drug, in particular, has garnered significant attention of researchers worldwide. An escalated emphasis is presently given to develop an understanding of how the various process parameters as well molecular biology considerations contribute to glycan heterogeneity. This paper aims to review the major developments that have occurred in this area over the last decade. The impact of the various process parameters on glycan expression, methods for obtaining a pre‐determined glycan levels/profiles of a protein therapeutic and developments in the area of real‐time glycan monitoring and control are discussed. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1091–1102, 2016     

CFD of mixing of multi‐phase flow in a bioreactor using population balance model

Mixing in bioreactors is known to be crucial for achieving efficient mass and heat transfer, both of which thereby impact not only growth of cells but also product quality. In a typical bioreactor, the rate of transport of oxygen from air is the limiting factor. While higher impeller speeds can enhance mixing, they can also cause severe cell damage. Hence, it is crucial to understand the hydrodynamics in a bioreactor to achieve optimal performance. This article presents a novel approach involving use of computational fluid dynamics (CFD) to model the hydrodynamics of an aerated stirred bioreactor for production of a monoclonal antibody therapeutic via mammalian cell culture. This is achieved by estimating the volume averaged mass transfer coefficient (k_La) under varying conditions of the process parameters. The process parameters that have been examined include the impeller rotational speed and the flow rate of the incoming gas through the sparger inlet. To undermine the two‐phase flow and turbulence, an Eulerian‐Eulerian multiphase model and k‐ε turbulence model have been used, respectively. These have further been coupled with population balance model to incorporate the various interphase interactions that lead to coalescence and breakage of bubbles. We have successfully demonstrated the utility of CFD as a tool to predict size distribution of bubbles as a function of process parameters and an efficient approach for obtaining optimized mixing conditions in the reactor. The proposed approach is significantly time and resource efficient when compared to the hit and trial, all experimental approach that is presently used. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:613–628, 2016     

Temporal genetic stability in natural populations of the waterflea Daphnia magna in response to strong selection pressure

Studies monitoring changes in genetic diversity and composition through time allow a unique understanding of evolutionary dynamics and persistence of natural populations. However, such studies are often limited to species with short generation times that can be propagated in the laboratory or few exceptional cases in the wild. Species that produce dormant stages provide powerful models for the reconstruction of evolutionary dynamics in the natural environment. A remaining open question is to what extent dormant egg banks are an unbiased representation of populations and hence of the species’ evolutionary potential, especially in the presence of strong environmental selection. We address this key question using the water flea Daphnia magna, which produces dormant stages that accumulate in biological archives over time. We assess temporal genetic stability in three biological archives, previously used in resurrection ecology studies showing adaptive evolutionary responses to rapid environmental change. We show that neutral genetic diversity does not decline with the age of the population and it is maintained in the presence of strong selection. In addition, by comparing temporal genetic stability in hatched and unhatched populations from the same biological archive, we show that dormant egg banks can be consulted to obtain a reliable measure of genetic diversity over time, at least in the multidecadal time frame studied here. The stability of neutral genetic diversity through time is likely mediated by the buffering effect of the resting egg bank.     

Attenuation of mitochondrial injury by L-arginine preconditioning of the liver

The present study was aimed to evaluate the efficacy of L-arginine on mitochondrial function in ischemic and reperfusion (I/R) induced hepatic injury. Adult Wistar rat were subjected to 1 h of partial liver ischemia followed by 3 hour reperfusion. Eighteen wistar rats were divided into three groups viz. sham-operated control group (I) (n = 6), ischemia and reperfusion (I/R) group (II) (n = 6), L-arginine treated group (100 mg/kg body weight/daily by oral route for 7 days before induced ischemia reperfusion maneuver) (III) (n = 6). Mitochondrial injury was assessed in terms of decreased (P < 0.05) activities of mitochondrial antioxidant enzymes (GSH, SOD, CAT), respiratory marker enzymes (NADH dehydrogenase, cytochrome c oxidases) and hepatocytes nitric oxide production. Pre-treatment with L-arginine (10 mg/kg/p.o. for 7 days) significantly counteracted the alternations of hepatic enzymes and mitochondrial respiratory and antioxidant enzymes. In addition, electron microscopy and histopathology study showed the restoration of cellular normalcy and accredits the cytoprotective role of L-arginine against I/R induced hepatocellular injury. On the basis of these findings it may be concluded that L-arginine protects mitochondrial function in hepatic ischemic and reperfused liver.     

Interdigitated array microelectrode based impedance biosensor coupled with magnetic nanoparticle-antibody conjugates for detection of Escherichia coli O157:H7 in food samples

An impedance biosensor based on interdigitated array microelectrode (IDAM) coupled with magnetic nanoparticle-antibody conjugates (MNAC) was developed and evaluated for rapid and specific detection of E. coli O157:H7 in ground beef samples. MNAC were prepared by immobilizing biotin-labeled polyclonal goat anti-E. coli antibodies onto streptavidin-coated magnetic nanoparticles, which were used to separate and concentrate E. coli O157:H7 from ground beef samples. Magnitude of impedance and phase angle were measured in a frequency range of 10 Hz to 1 MHz in the presence of 0.1M mannitol solution. The lowest detection limits of this biosensor for detection of E. coli O157:H7 in pure culture and ground beef samples were 7.4 x 10(4) and 8.0 x 10(5)CFU ml(-1), respectively. The regression equation for the normalized impedance change (NIC) versus E. coli O157:H7 concentration (N) in ground beef samples was NIC=15.55 N-71.04 with R(2)=0.95. Sensitivity of the impedance biosensor was improved by 35% by concentrating bacterial cells attached to MNAC in the active layer of IDAM above the surface of electrodes with the help of a magnetic field. Based on equivalent circuit analysis, it was observed that bulk resistance and double layer capacitance were responsible for the impedance change caused by the presence of E. coli O157:H7 on the surface of IDAM. Surface immobilization techniques, redox probes, or sample incubation were not used in this impedance biosensor. The total detection time from sampling to measurement was 35 min.     

Application of multivariate analysis toward biotech processes: case study of a cell-culture unit operation

This paper examines the feasibility of using multivariate data analysis (MVDA) for supporting some of the key activities that are required for successful manufacturing of biopharmaceutical products. These activities include scale-up, process comparability, process characterization, and fault diagnosis. Multivariate data analysis and modeling were performed using representative data from small-scale (2 L) and large-scale (2000 L) batches of a cell-culture process. Several input parameters (pCO2, pO2, glucose, pH, lactate, ammonium ions) and output parameters (purity, viable cell density, viability, osmolality) were evaluated in this analysis. Score plots, loadings plots, and VIP plots were utilized for assessing scale-up and comparability of the cell-culture process. Batch control charts were found to be useful for fault diagnosis during routine manufacturing. Finally, observations made from reviewing VIP plots were found to be in agreement with conclusions from process characterization studies demonstrating the effectiveness of MVDA as a tool for extracting process knowledge.     

Mechanistic modeling based process analytical technology implementation for pooling in hydrophobic interaction chromatography

A major challenge in chromatography purification of therapeutic proteins is batch-to-batch variability with respect to impurity levels and product concentration in the feed. Mechanistic model can enable process analytical technology (PAT) implementation by predicting impact of such variations and thereby improving the robustness of the resulting process and controls. This article presents one such application of mechanistic model of hydrophobic interaction chromatography (HIC) as a PAT tool for making robust pooling decisions to enable clearance of aggregates for a monoclonal antibody (mAb) therapeutic. Model predictions were performed before the actual chromatography experiments to facilitate feedforward control. The approach has been successfully demonstrated for four different feeds with varying aggregate levels (3.84%–5.54%) and feed concentration (0.6 mg/mL–1 mg/mL). The resulting pool consistently yielded a product with 1.32 ± 0.03% aggregate vs. a target of 1.5%. A comparison of the traditional approach involving column fractionation with the proposed approach indicates that the proposed approach results in achievement of satisfactory product purity (98.68 ± 0.03% for mechanistic model based PAT controlled pooling vs. 98.64 ± 0.16% for offline column fractionation based pooling). © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2758, 2019.