Real-time measurement of the intracellular pH of yeast cells during glucose metabolism using ratiometric fluorescent nanosensors

Intracellular pH is a key parameter that influences many biochemical and metabolic pathways that can also be used as an indirect marker to monitor metabolic and intracellular processes. Herein, we utilise ratiometric fluorescent pH-sensitive nanosensors with an extended dynamic pH range to measure the intracellular pH of yeast (Saccharomyces cerevisiae) during glucose metabolism in real-time. Ratiometric fluorescent pH-sensitive nanosensors consisting of a polyacrylamide nanoparticle matrix covalently linked to two pH-sensitive fluorophores, Oregon green (OG) and 5(6)carboxyfluorescein (FAM), and a reference pH-insensitive fluorophore, 5(6)carboxytetramethylrhodamine (TAMRA), were synthesised. Nanosensors were functionalised with acrylamidopropyltrimethyl ammonium hydrochloride (ACTA) to confer a positive charge to the nanoparticle surfaces that facilitated nanosensor delivery to yeast cells, negating the need to use stress inducing techniques. The results showed that under glucose-starved conditions the intracellular pH of yeast population (n ≈ 200) was 4.67 ± 0.15. Upon addition of D-(+)-glucose (10 mM), this pH value decreased to pH 3.86 ± 0.13 over a period of 10 minutes followed by a gradual rise to a maximal pH of 5.21 ± 0.26, 25 minutes after glucose addition. 45 minutes after the addition of glucose, the intracellular pH of yeast cells returned to that of the glucose starved conditions. This study advances our understanding of the interplay between glucose metabolism and pH regulation in yeast cells, and indicates that the intracellular pH homestasis in yeast is highly regulated and demonstrates the utility of nanosensors for real-time intracellular pH measurements

Prediction models for childhood asthma: a systematic review

Background The inability to objectively diagnose childhood asthma before age five often results in both under‐treatment and over‐treatment of asthma in preschool children. Prediction tools for estimating a child's risk of developing asthma by school‐age could assist physicians in early asthma care for preschool children. This review aimed to systematically identify and critically appraise studies which either developed novel or updated existing prediction models for predicting school‐age asthma. Methods Three databases (MEDLINE, Embase and Web of Science Core Collection) were searched up to July 2019 to identify studies utilizing information from children ≤5 years of age to predict asthma in school‐age children (6‐13 years). Validation studies were evaluated as a secondary objective. Results Twenty‐four studies describing the development of 26 predictive models published between 2000 and 2019 were identified. Models were either regression‐based (n = 21) or utilized machine learning approaches (n = 5). Nine studies conducted validations of six regression‐based models. Fifteen (out of 21) models required additional clinical tests. Overall model performance, assessed by area under the receiver operating curve (AUC), ranged between 0.66 and 0.87. Models demonstrated moderate ability to either rule in or rule out asthma development, but not both. Where external validation was performed, models demonstrated modest generalizability (AUC range: 0.62‐0.83). Conclusion Existing prediction models demonstrated moderate predictive performance, often with modest generalizability when independently validated. Limitations of traditional methods have shown to impair predictive accuracy and resolution. Exploration of novel methods such as machine learning approaches may address these limitations for future school‐age asthma predictio

Novel method for assessing basophil activation by measuring altered expression of membrane-bound and intracellular basogranulin stores

BackgroundBasophil activation tests can provide valuable information on allergic sensitivity to a range of different allergens. The most widely employed methods involve flow cytometric detection of increased expression of membrane-bound CD63 or CD203c following addition of allergen to basophils in vitro.The identification of basogranulin, a unique basic protein stored in basophil granules, has opened the way for new basophil activation methods to be explored.MethodsBlood was collected from healthy subjects and patients with a history of allergy to food, drugs, house dust and grass pollen. Basophils were stimulated with specific allergen, anti-IgE antibody, or the peptide f-met-leu-phe (FMLP). Flow cytometry was performed with non-permeabilised and permeabilised cells with antibody specific for basogranulin (BB1) or CD63, and data analysed with CellQuest software.ResultsFlow cytometry with permeablised cells indicated depletion of intracellular stores of basogranulin following basophil activation. Associated with basogranulin release was the presence of increased quantities of this marker on the basophil membrane following cellular activation. Increased membrane expression of basogranulin mirrored that for CD63; and with allergens and other stimuli tested the measurement of cell surface basogranulin represented a more sensitive means for assessing basophil activation in vitro. The flow cytometric assays for basogranulin were optimised for use with samples of whole blood so as to avoid the need for basophil purification.ConclusionsThe rapidity, simplicity and sensitivity of basogranulin-based methods for measuring basophil activation will facilitate their application to clinical samples and allow better assessment for allergic sensitivity

Circulating miRNAs – a potential tool to identify severe asthma risk?

Background: Identifying patients at risk of severe asthma is vitally important given the disproportionate burden of disease imposed by that state. However, biomarkers to support such needs remain elusive. Methods: In this letter, we assessed whether specific panels of circulating miRNAs (microRNAs) can differentiate between mild and severe asthma patients as well as between healthy subjects and severe asthma patients. Results: To our knowledge, the miRNAs identified in our work such as miR-28-3p, miR-16-2-3p, and miR-210-3p have not been previously reported as differentially expressed in the serum of severe asthma patients. Conclusion: Our findings suggest that miRNA expression profiles may have the capability as potential biomarkers that signal the risk of having severe asthma. As such, these findings have significant novelty and merit wider dissemination to facilitate further work in this field.</p

Real-world omalizumab and mepolizumab treated difficult asthma phenotypes and their clinical outcomes

Background: Omalizumab and Mepolizumab are biologic drugs with proven efficacy in clinical trials. However, a better understanding of their real-world effectiveness in severe asthma management is needed. Objectives: To better understand the real-world effectiveness of Omalizumab and Mepolizumab, elucidate the clinical phenotypes of patients treated with these drugs, identify baseline characteristics associated with biologic response and assess the spectrum of responses to these medications. Methods: Using real-world clinical data, we retrospectively phenotyped biologic naïve patients from the Wessex AsThma CoHort of difficult asthma (N = 478) commenced on Omalizumab (N = 105) or Mepolizumab (N = 62) compared to severe asthma patients not receiving biologics (SNB, N = 178). We also assessed multiple clinical endpoints and identified features associated with response. Results: Compared to SNB, Omalizumab patients were younger, diagnosed with asthma earlier, and more likely to have rhinitis. Conversely, compared to SNB, Mepolizumab patients were predominantly older males, diagnosed with asthma later, and more likely to have nasal polyposis but less dysfunctional breathing. Both treatments reduced exacerbations, Acute Healthcare Encounters [AHE] (emergency department or hospital admissions), maintenance oral corticosteroid dose, and improved Asthma Control Questionnaire 6 (ACQ6) scores. Omalizumab response was independently associated with more baseline exacerbations (p =.024) but fewer AHE (p =.050) and absence of anxiety (p =.008). Lower baseline ACQ6 was independently associated with Mepolizumab response (p =.007). A composite group of non-responders demonstrated significantly more psychopathologies and worse baseline subjective disease compared to responder groups. Conclusions and Clinical Relevance: In a difficult asthma cohort, Omalizumab and Mepolizumab were used in distinct clinical phenotypes but were both multidimensionally efficacious. Certain baseline clinical characteristics were associated with poorer biologic responses, such as psychological co-morbidity, which may assist clinicians in biologic selection. These characteristics also emphasize the need for comprehensive approaches to support these patients.</p

Comprehensive characterisation of difficult-to-treat asthma reveals near absence of T2-low status

Background: asthma is conventionally stratified as type 2-inflammation (T2) high or T2-low disease. Identifying T2-status has therapeutic implications for patient management but real-world understanding of this T2 paradigm in difficult-to-treat/ severe asthma remains limited.Objectives: to identify prevalence of T2-high status in difficult-to-treat asthma patients using a multicomponent definition and compare clinical and pathophysiological characteristics between patients classified as T2-high and T2-low.Methods: 388 biologic naïve patients from the Wessex Asthma Cohort of difficult asthma (WATCH) study, United Kingdom, were evaluated. T2-high asthma was defined as fractional exhaled nitric oxide (FeNO)≥20ppb and/or peripheral blood eosinophils (PBE) ≥150 cells/ul and/or need for maintenance oral corticosteroids and/or clinically allergy-driven asthma.Results: this multicomponent assessment identified T2-high asthma in 93% (360/388) of patients. Body Mass Index, inhaled corticosteroid dose, asthma exacerbations and common comorbidities did not differ by T2-status. Significantly worse airflow limitation was found in T2-high compared to T2-low patients (FEV1/FVC 65.9% vs 74.6%). 75% patients defined as T2-low asthma had raised PBE within the preceding 10-years, leaving only 7 patients (1.8%) who never had T2-signals. Incorporation of sputum eosinophilia ≥2% into the multicomponent definition in a subset of 117 patients with induced sputum data similarly found that 96% (112/117) met criteria for T2-high asthma of which 50% (56/112), had sputum eosinophils ≥2%.Conclusions: amost all patients with difficult-to-treat asthma have T2-high disease with &lt;2% of patients never displaying T2-defining criteria. This highlights a need to comprehensively assess T2 status in clinical practice before labelling a patient with difficult-to-treat asthma as T2-low.</p