Extracellular vesicles secreted by primary human bronchial epithelial cells reduce Pseudomonas aeruginosa burden and inflammation in cystic fibrosis mouse lung.

Cystic fibrosis (CF) results in a reduction in the volume of airway surface liquid, increased accumulation of viscous mucus, persistent antibiotic-resistant lung infections that cause chronic inflammation, and a decline in lung function. More than 50% of adults with CF are chronically colonized by Pseudomonas aeruginosa (P. aeruginosa), the primary reason for morbidity and mortality in people with CF (pwCF). Although highly effective modulator therapy (HEMT) is an important part of disease management in CF, HEMT does not eliminate P. aeruginosa or lung inflammation. Thus, new treatments are required to reduce lung infection and inflammation in CF. In a previous in vitro study, we demonstrated that primary human bronchial epithelial cells (HBECs) secrete extracellular vesicles (EVs) that block the ability of P. aeruginosa to form biofilms by reducing the abundance of several proteins necessary for biofilm formation as well as enhancing the sensitivity of P. aeruginosa to ß-lactam antibiotics. In this study, using a CF mouse model of P. aeruginosa infection, we demonstrate that intratracheal administration of EVs secreted by HBEC reduced P. aeruginosa lung burden and several proinflammatory cytokines including IFN-γ, TNF-α, and MIP-1ß in bronchoalveolar lavage fluid (BALF), even in the absence of antibiotics. Moreover, EVs decreased neutrophils in BALF. Thus, EVs secreted by HBEC reduce the lung burden of P. aeruginosa, decrease inflammation, and reduce neutrophils in a CF mouse model. These results suggest that HBEC via the secretion of EVs may play an important role in the immune response to P. aeruginosa lung infection.NEW & NOTEWORTHY Our findings show that extracellular vesicles secreted by primary human bronchial epithelial cells significantly reduce Pseudomonas aeruginosa burden, inflammation, and weight loss in a cystic fibrosis mouse model of infection.

Rocket-miR, a translational launchpad for miRNA-based antimicrobial drug development.

IMPORTANCE: Antimicrobial-resistant infections contribute to millions of deaths worldwide every year. In particular, the group of bacteria collectively known as ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter sp.) pathogens are of considerable medical concern due to their virulence and exceptional ability to develop antibiotic resistance. New kinds of antimicrobial therapies are urgently needed to treat patients for whom existing antibiotics are ineffective. The Rocket-miR application predicts targets of human miRNAs in bacterial and fungal pathogens, rapidly identifying candidate miRNA-based antimicrobials. The application's target audience are microbiologists that have the laboratory resources to test the application's predictions. The Rocket-miR application currently supports 24 recognized human pathogens that are relevant to numerous diseases including cystic fibrosis, chronic obstructive pulmonary disease (COPD), urinary tract infections, and pneumonia. Furthermore, the application code was designed to be easily extendible to other human pathogens that commonly cause hospital-acquired infections.

Heterogeneity in Vaccinal Immunity to SARS-CoV-2 Can Be Addressed by a Personalized Booster Strategy.

SARS-CoV-2 vaccinations were initially shown to substantially reduce risk of severe disease and death. However, pharmacokinetic (PK) waning and rapid viral evolution degrade neutralizing antibody (nAb) binding titers, causing loss of vaccinal protection. Additionally, there is inter-individual heterogeneity in the strength and durability of the vaccinal nAb response. Here, we propose a personalized booster strategy as a potential solution to this problem. Our model-based approach incorporates inter-individual heterogeneity in nAb response to primary SARS-CoV-2 vaccination into a pharmacokinetic/pharmacodynamic (PK/PD) model to project population-level heterogeneity in vaccinal protection. We further examine the impact of evolutionary immune evasion on vaccinal protection over time based on variant fold reduction in nAb potency. Our findings suggest viral evolution will decrease the effectiveness of vaccinal protection against severe disease, especially for individuals with a less durable immune response. More frequent boosting may restore vaccinal protection for individuals with a weaker immune response. Our analysis shows that the ECLIA RBD binding assay strongly predicts neutralization of sequence-matched pseudoviruses. This may be a useful tool for rapidly assessing individual immune protection. Our work suggests vaccinal protection against severe disease is not assured and identifies a potential path forward for reducing risk to immunologically vulnerable individuals.

Impact of adjuvants on the biophysical and functional characteristics of HIV vaccine-elicited antibodies in humans.

Adjuvants can alter the magnitude, characteristics, and persistence of the humoral response to protein vaccination. HIV vaccination might benefit from tailored adjuvant choice as raising a durable and protective response to vaccination has been exceptionally challenging. Analysis of trials of partially effective HIV vaccines have identified features of the immune response that correlate with decreased risk, including high titers of V1V2-binding IgG and IgG3 responses with low titers of V1V2-binding IgA responses and enhanced Fc effector functions, notably antibody-dependent cellular cytotoxicity (ADCC) and antibody-dependent cellular phagocytosis (ADCP). However, there has been limited opportunity to compare the effect of different adjuvants on these activities in humans. Here, samples from the AVEG015 study, a phase 1 trial in which participants (n = 112) were immunized with gp120SF-2 and one of six different adjuvants or combinations thereof were assessed for antibody titer, biophysical features, and diverse effector functions. Three adjuvants, MF59 + MTP-PE, SAF/2, and SAF/2 + MDP, increased the peak magnitude and durability of antigen-specific IgG3, IgA, FcγR-binding responses and ADCP activity, as compared to alum. While multiple adjuvants increased the titer of IgG, IgG3, and IgA responses, none consistently altered the balance of IgG to IgA or IgG3 to IgA. Linear regression analysis identified biophysical features including gp120-specific IgG and FcγR-binding responses that could predict functional activity, and network analysis identified coordinated aspects of the humoral response. These analyses reveal the ability of adjuvants to drive the character and function of the humoral response despite limitations of small sample size and immune variability in this human clinical trial.

The Nuclear-to-Cytoplasmic Ratio: Coupling DNA Content to Cell Size, Cell Cycle, and Biosynthetic Capacity.

Though cell size varies between different cells and across species, the nuclear-to-cytoplasmic (N/C) ratio is largely maintained across species and within cell types. A cell maintains a relatively constant N/C ratio by coupling DNA content, nuclear size, and cell size. We explore how cells couple cell division and growth to DNA content. In some cases, cells use DNA as a molecular yardstick to control the availability of cell cycle regulators. In other cases, DNA sets a limit for biosynthetic capacity. Developmentally programmed variations in the N/C ratio for a given cell type suggest that a specific N/C ratio is required to respond to given physiological demands. Recent observations connecting decreased N/C ratios with cellular senescence indicate that maintaining the proper N/C ratio is essential for proper cellular functioning. Together, these findings suggest a causative, not simply correlative, role for the N/C ratio in regulating cell growth and cell cycle progression.

Beyond the new normal: Assessing the feasibility of vaccine-based suppression of SARS-CoV-2.

As the COVID-19 pandemic drags into its second year, there is hope on the horizon, in the form of SARS-CoV-2 vaccines which promise disease suppression and a return to pre-pandemic normalcy. In this study we critically examine the basis for that hope, using an epidemiological modeling framework to establish the link between vaccine characteristics and effectiveness in bringing an end to this unprecedented public health crisis. Our findings suggest that a return to pre-pandemic social and economic conditions without fully suppressing SARS-CoV-2 will lead to extensive viral spread, resulting in a high disease burden even in the presence of vaccines that reduce risk of infection and mortality. Our modeling points to the feasibility of complete SARS-CoV-2 suppression with high population-level compliance and vaccines that are highly effective at reducing SARS-CoV-2 infection. Notably, vaccine-mediated reduction of transmission is critical for viral suppression, and in order for partially-effective vaccines to play a positive role in SARS-CoV-2 suppression, complementary biomedical interventions and public health measures must be deployed simultaneously.

Protein nanocomposites: Special inferences to lysozyme based nanomaterials.

Protein nanocomposites have attracted considerable research interest in recent times owing to the combined advantageous properties of nanotechnology and proteins. Lysozyme holds enormous potential in various biomedical applications as it possesses antibacterial properties, anti-inflammatory, anti-cancer, and analgesic properties. Considering its multifunctional aspects, structural stability and ease of production and modification, special focus has been attributed to this protein. Nanocomposites have either been fabricated completely from lysozyme or have been conjugated to lysozyme considering its versatile biotechnological applications. The current review describes the recent advances of protein nanocomposites using lysozyme as a prime example. Along with the principles, techniques, and applications involved in protein based nanocomposites, this review also provides a comprehensive account of interactions between lysozyme and different nanoparticles. Numerous studies that have integrated the utilization of lysozyme and nanotechnology for a variety of applications have also been discussed at length.

Amelioration of biomass and lipid in marine alga by an endophytic fungus Piriformospora indica.

BACKGROUND: Many studies have been carried out on the growth-modulating efficiency of plants by the colonization of an endophytic fungus Piriformospora indica. However, studies involving the co-culture of alga with endophytic fungal strains for enhanced biodiesel production are rare. In this study, the interaction between P. indica and Parachlorella kessleri-I, a marine algal strain, was assessed at metabolic level. RESULTS: In association with an endophytic fungus, the algal biomass enhanced from 471.6 to 704 mg/L, and the fatty acid methyl ester (FAME) profile of P. kessleri-I increased substantially. In case of FAME profile of co-cultured P. kessleri-I, two essential components of biodiesel, i.e. elaidic acid and oleic acid, increased by 1.4- and 1.8-fold, respectively. To ascertain changes in the metabolic profile of P. kessleri-I by P. indica co-culture, gas chromatography-mass spectrometry (GC-MS)-based untargeted metabolomics study was performed to identify the metabolites involved; and differential nature of the essential metabolites was also confirmed using HPLC and LC-MS. Significant modulation of the bioactive metabolites such as succinate, oxo-propanoate, l-alanine, glutamate, acetate and 1,2 propanediol, hydroxy butane was observed. CONCLUSION: The metabolites like glutamate and succinate that usually belong to the GABA shunt pathway were observed to be upregulated. The pathway links nitrogen metabolism and carbon metabolism, thus influencing the growth and lipid profile of the algae. These differential metabolites thus indicated the important commensal association between the endophytic fungus and autotrophic marine alga, and established that endophytic fungus can be handy for the sustainability of algal biofuel industries.

Elucidating Protein-protein Interactions Through Computational Approaches and Designing Small Molecule Inhibitors Against them for Various Diseases.

BACKGROUND: To carry out wide range of cellular functionalities, proteins often associate with one or more proteins in a phenomenon known as Protein-Protein Interaction (PPI). Experimental and computational approaches were applied on PPIs in order to determine the interacting partners, and also to understand how an abnormality in such interactions can become the principle cause of a disease. OBJECTIVE: This review aims to elucidate the case studies where PPIs involved in various human diseases have been proven or validated with computational techniques, and also to elucidate how small molecule inhibitors of PPIs have been designed computationally to act as effective therapeutic measures against certain diseases. RESULTS: Computational techniques to predict PPIs are emerging rapidly in the modern day. They not only help in predicting new PPIs, but also generate outputs that substantiate the experimentally determined results. Moreover, computation has aided in the designing of novel inhibitor molecules disrupting the PPIs. Some of them are already being tested in the clinical trials. CONCLUSION: This review delineated the classification of computational tools that are essential to investigate PPIs. Furthermore, the review shed light on how indispensable computational tools have become in the field of medicine to analyze the interaction networks and to design novel inhibitors efficiently against dreadful diseases in a shorter time span.