Acidification Model Research Articles

Cytosolic acidification and oxidation are the toxic mechanisms of SO2 in Arabidopsis guard cells.

SO2/H2SO3 can damage plants. However, its toxic mechanism has still been controversial. Two models have been proposed, cytosolic acidification model and cellular oxidation model. Here, we assessed the toxic mechanism of H2SO3 in three cell types of Arabidopsis thaliana, mesophyll cells, guard cells and petal cells. The sensitivity of guard cells of CHLORIDE CHANNEL a (CLCa)-knockout mutants to H2SO3 was significantly lower than those of wildtype plants. Expression of other CLC genes in mesophyll cells and petal cells were different from guard cells. Treatment with antioxidant, disodium 4,5-dihydroxy-1,3-benzenedisulfonate (tiron), increased the median lethal concentration (LC50) of H2SO3 in guard cells indicating the involvement of cellular oxidation, while the effect was negligible in mesophyll cells and petal cells. These results indicate that there are two toxic mechanisms of SO2 to Arabidopsis cells: cytosolic acidification and cellular oxidation, and the toxic mechanism may vary among cell types.

A biogeochemical model of acidification: MAGIC is alive and well

A biogeochemical model of acidification: <scp>MAGIC</scp> is alive and well

Major drivers of soil acidification over 30 years differ in paddy and upland soils in China

Elevated nitrogen (N) fertilization has largely increased crop production in China, but also increased acidification risks, thereby threatening crop yields. However, natural soil acidification due to bicarbonate (HCO3) leaching and base cation (BC) removal by crop harvest also affect soil acidity whereas the input of HCO3 and BC via fertilizers and manure counteract soil acidification. Insights in rates and drivers of soil acidification in different land use types is too limited to support crop- and site-specific mitigation strategies. In this study, we assessed the historical changes in cropland acidification rates and their drivers for the period 1985–2019 at 151 sites in a typical Chinese county with the combined nutrient and soil acidification model VSD+. VSD+ could well reproduce long-term changes in pH and in the BC concentrations of calcium, magnesium and potassium between 1985 and 2019 in non-calcareous soils. In paddy soils, the acidity production rate decreased from 1985 onwards, mainly driven by a pH-induced reduction in HCO3 leaching and N transformations. In upland soils, however, acidity production was mainly driven by N transformations and hardly changed over time. Crop BC removal by harvesting played a minor role in both paddy and upland soils, but its relative importance increased in paddy soils. The acidity input was partly neutralized by HCO3 input from fertilizers and manure, which decreased over time due to a change from ammonia bicarbonate to urea. Soil buffering by both BC and aluminium release decreased in paddy soils due to a reduction in net acidity production, while it stayed relatively constant in upland soils. We conclude that acidification management in paddy soils requires a focus on avoiding high HCO3 leaching whereas the management in upland soils should focus on balancing N with recycling organic manure and crop residues.

Single-strain behavior predicts responses to environmental pH and osmolality in the gut microbiota.

Changes to gut environmental factors such as pH and osmolality due to disease or drugs correlate with major shifts in microbiome composition; however, we currently cannot predict which species can tolerate such changes or how the community will be affected. Here, we assessed the growth of 92 representative human gut bacterial strains spanning 28 families across multiple pH values and osmolalities in vitro. The ability to grow in extreme pH or osmolality conditions correlated with the availability of known stress response genes in many cases, but not all, indicating that novel pathways may participate in protecting against acid or osmotic stresses. Machine learning analysis uncovered genes or subsystems that are predictive of differential tolerance in either acid or osmotic stress. For osmotic stress, we corroborated the increased abundance of these genes in vivo during osmotic perturbation. The growth of specific taxa in limiting conditions in isolation in vitro correlated with survival in complex communities in vitro and in an in vivo mouse model of diet-induced intestinal acidification. Our data show that in vitro stress tolerance results are generalizable and that physical parameters may supersede interspecies interactions in determining the relative abundance of community members. This study provides insight into the ability of the microbiota to respond to common perturbations that may be encountered in the gut and provides a list of genes that correlate with increased ability to survive in these conditions.IMPORTANCETo achieve greater predictability in microbiota studies, it is crucial to consider physical environmental factors such as pH and particle concentration, as they play a pivotal role in influencing bacterial function and survival. For example, pH is significantly altered in various diseases, including cancers, inflammatory bowel disease, as well in the case of over-the-counter drug use. Additionally, conditions like malabsorption can affect particle concentration. In our study, we investigate how changes in environmental pH and osmolality can serve as predictive indicators of bacterial growth and abundance. Our research provides a comprehensive resource for anticipating shifts in microbial composition and gene abundance during complex perturbations. Moreover, our findings underscore the significance of the physical environment as a major driver of bacterial composition. Finally, this work emphasizes the necessity of incorporating physical measurements into animal and clinical studies to better understand the factors influencing shifts in microbiota abundance.

Generalized neural closure models with interpretability

Improving the predictive capability and computational cost of dynamical models is often at the heart of augmenting computational physics with machine learning (ML). However, most learning results are limited in interpretability and generalization over different computational grid resolutions, initial and boundary conditions, domain geometries, and physical or problem-specific parameters. In the present study, we simultaneously address all these challenges by developing the novel and versatile methodology of unified neural partial delay differential equations. We augment existing/low-fidelity dynamical models directly in their partial differential equation (PDE) forms with both Markovian and non-Markovian neural network (NN) closure parameterizations. The melding of the existing models with NNs in the continuous spatiotemporal space followed by numerical discretization automatically allows for the desired generalizability. The Markovian term is designed to enable extraction of its analytical form and thus provides interpretability. The non-Markovian terms allow accounting for inherently missing time delays needed to represent the real world. Our flexible modeling framework provides full autonomy for the design of the unknown closure terms such as using any linear-, shallow-, or deep-NN architectures, selecting the span of the input function libraries, and using either or both Markovian and non-Markovian closure terms, all in accord with prior knowledge. We obtain adjoint PDEs in the continuous form, thus enabling direct implementation across differentiable and non-differentiable computational physics codes, different ML frameworks, and treatment of nonuniformly-spaced spatiotemporal training data. We demonstrate the new generalized neural closure models (gnCMs) framework using four sets of experiments based on advecting nonlinear waves, shocks, and ocean acidification models. Our learned gnCMs discover missing physics, find leading numerical error terms, discriminate among candidate functional forms in an interpretable fashion, achieve generalization, and compensate for the lack of complexity in simpler models. Finally, we analyze the computational advantages of our new framework.

Spatially Explicit Soil Acidification under Optimized Fertilizer Use in Sub-Saharan Africa

Acidic soils (pH &lt; 5.5) cover roughly 30% of Sub-Saharan Africa. Low nitrogen fertilizer application (15 kg N ha−1 yr−1) has no effect on soil acidification in Sub-Saharan Africa (SSA). However, the effect of optimized fertilizer use on soil acidification (H+) in SSA crops remains unknown. This study intended to predict the spatial variation of H+ caused by optimized fertilizer use using data from 5782 field trials in SSA cropland. We used ensemble machine learning to predict spatial variation (H+) after measuring the inputs and outputs of major elements and their effect on H+ production. The results revealed that H+ ranged spatially from 0 to 16 keq H+ ha−1 yr−1. The most protons (H+) were produced by cassava, banana, and Irish potatoes systems with 12.0, 9.8, and 8.9 keq H+ ha−1 yr−1, respectively. The results of the 10-fold cross validation for the soil acidification model were a coefficient of determination (R2) of 0.6, a root mean square error (RMSE) of 2.1, and a mean absolute error (MAE) of 1.4. Net basic cation loss drives soil acidification under optimized fertilizer application and climate covariates had a higher relative importance than other covariates. Digital soil mapping can produce soil acidification maps for sustainable land use and management plans.

Pitting behavior of the AA6061 alloy and Al5N in a diluted chloride solution

AbstractThe effect of aeration on the pitting potential (Ep) of the AA6061 alloy and high‐purity aluminum (Al5N) is studied in diluted chloride solutions. The Ep values are determined by a potentiodynamic scan in aerated and de‐aerated solutions of 10−3 M NaCl and 10−3 M NaCl + 0.05 M KH2PO4/K2HPO4 buffer. Applying the hypothesis testing procedure, it is concluded that the presence of oxygen in a 10−3 M NaCl solution decreases the Ep for AA6061 by 100 mV and does not affect the Ep for Al5N. This decrease is related to the alloy dissolution around the iron‐rich particles and is analyzed in terms of the model of localized acidification.

Membrane-Activated Fluorescent Probe for High-Fidelity Imaging of Mitochondrial Membrane Potential.

Mitochondrial membrane potential (ΔΨm) is a key indicator of cell health or injury due to its vital roles in adenosine 5'-triphosphate synthesis. Thus, monitoring ΔΨm is of great significance for the assessment of cell status, diagnosis of diseases, and medicament screening. Cationic fluorescent probes suffer from severe photobleaching or false positive signals due to the luminescence of the probe on non-mitochondria. Herein, we report a lipophilic cationic fluorescent probe [1-methyl-2-(4-(1,2,2-triphenylvinyl)styryl)-β-naphthothiazol-1-ium trifluoromethanesulfonate (TPE-NT)] with the features of aggregation-induced emission and intramolecular charge transfer for imaging ΔΨm in live cells. TPE-NT is enriched on the surface of the mitochondrial inner membrane due to the negative ΔΨm, and its fluorescence is activated in the high-viscosity microenvironment. The false positive signals of emission from TPE-NT on non-mitochondria are therefore effectively eliminated. Moreover, TPE-NT exhibits a Stokes shift of >200 nm, near-infrared (∼675 nm) emission, excellent photostability, and low cytotoxicity, which facilitate real-time imaging in live cells. Cell imaging confirmed that the probe can rapidly and reliably report mitochondrial depolarization (decrement of ΔΨm) during cell damage caused by CCCP and H2O2 as well as mitochondrial polarization (increment of ΔΨm) by oligomycin. Furthermore, the probe successfully detected the reduction of ΔΨm in these cell models of hypoxia, heat damage, acidification, aging, inflammation, mitophagy, and apoptosis caused by hypoxia, heatstroke, lactate/pyruvate, doxorubicin, lipopolysaccharide, rapamycin, monensin, and nystatin, respectively.

Development of the UKESM-TOPAZ Earth System Model (Version 1.0) and Preliminary Evaluation of its Biogeochemical Simulations

Earth system models (ESMs) comprise various Earth system components and simulate the interactions between these components. ESMs can be used to understand climate feedbacks between physical, chemical, and biological processes and predict future climate. We developed a new ESM, UKESM-TOPAZ, by coupling the UK ESM (UKESM1) and the Tracers of Phytoplankton with Allometric Zooplankton (TOPAZ) biogeochemical module. We then compared the preliminary simulated biogeochemical variables, which were conducted over a period of 70 years, using observational and existing UKESM1 model data. Similar to UKESM1, the newly developed UKESM-TOPAZ closely simulated the relationship between the El Niño-Southern Oscillation and chlorophyll concentration anomalies during the boreal winter. However, there were differences in the chlorophyll distributions in the eastern equatorial Pacific between the two models, which were due to dissolved iron, as this value was higher in UKESM-TOPAZ than in UKESM1. In a mean field analysis, the distributions of the major marine biogeochemical variables in UKESM-TOPAZ (i.e., nitrate, silicate, dissolved oxygen, dissolved inorganic carbon, and alkalinity) were not significantly different from those of UKESM1, likely because the models share the same initial conditions. Our results indicate that TOPAZ has a simulation performance that does not lag behind UKESM1’s basic biogeochemical model (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration, and Acidification; MEDUSA). The UKESM-TOPAZ model can simulate the variability of the observed Niño 3.4 and 4 indices more closely than UKESM1. Thus, the UKESM-TOPAZ model can be used to deepen our understanding of the Earth system and to estimate ESM uncertainty.

Active Blood Acidification Greatly Enhances Oxygen Supply to the Teleost Retina

Most ray-finned fishes possess a unique system for retinal oxygen delivery, where intracellular acidification of red blood cells (RBCs) in the retinal capillaries induces oxygen offloading from pH-sensitive hemoglobin. A countercurrent vascular network, the choroid rete mirabile, posterior to the retina augments this “oxygen-secretory” mechanism and confers retinal PO2 values that can exceed 1300 mmHg in some species. We hypothesized that the choroid rete mirabile exerts an active role in intracellular RBC acidification to facilitate retinal oxygen secretion. We show the presence and enzymatic activities of extracellular carbonic anhydrase (CA) and vacuolar-type H+-ATPase (VHA) in the lumen of the choroid rete mirabile. These data are consistent with a pathway, where VHA secretes H+ into the choroid rete mirabile lumen, which combines with HCO3– to form CO2 (catalyzed by extracellular CA) that rapidly diffuses into the RBC facilitating hemoglobin oxygen offloading. Next, we validated the model in vivo by injecting an extracellular CA inhibitor (C18) into the dorsal aorta of anesthetized rainbow trout with a PO2 electrode implanted into the retina. Here, the inhibition of extracellular CA resulted in a rapid reduction in retinal PO2 from 517 to 226 mmHg within minutes. These data strongly support the proposed model for RBC acidification in the choroid rete mirabile. Further, in vivo data show that this mechanism primarily augments oxygen diffusion to the inner retinal segments involved in signal-processing and that the evolution of this pathway was tightly associated with the morphological expansion of this part of the retina. Together, these data suggest that the evolutionary origin of retinal oxygen secretion in the early history of the ray-finned fishes was associated with a greatly enhanced capacity for visual processing, potentially permitting improved visual prey detection and the colonization of novel environments.

Quantification of Protein Reabsorption Energetics in the Kidney Proximal Tubule

Proteinuria can result from increased glomerular protein filtration, but insufficient or reduced protein reabsorption in the proximal tubule (PT) may also play a role. Protein is reabsorbed via receptor-mediated endocytosis, a process that is pH-dependent and requires energy in the form of ATP. Specifically, ATP is hydrolyzed by V-type ATPase, and the resulting energy is used to acidify the endocytic vesicle by pumping H+ ions into the endosome. This reduces the internal endosome pH and causes protein-receptor complex dissociation, which allows the protein to be further processed by the cell. Alterations in intracellular pH or ATP availability may impact the PT epithelial cells’ ability to form endosomes and reabsorb protein. To quantify the relationship between cellular pH, protein reabsorption, and ATP utilization, we developed a mathematical model that quantifies the energy demands of protein reabsorption in the kidney proximal tubule. The model assumes normal kidney function and focuses on albumin reabsorption for simplification. To determine the energy required to acidify a single endosome (ATP/endosome), we expanded upon a published mathematical model of general lysosome acidification that quantifies the H+ ions required to acidify a vesicle and the final pH reached, accounting for ClC-7 antiporters and proton leak, as a function of intracellular pH (Ishida et al. J Gen Phys 2013). The Nernst equation was used to determine the cumulative energy (ΔG) required to pump H+ ions into one endosome until a final stable internal pH is reached. To determine the rate of endosome formation required to reabsorb a normal filtered albumin load, we first calculated the albumin reabsorption rate per unit length of the proximal tubule as a function of albumin filtration rate, nephron number, and tubular dimensions. Next, using previous experimentally measured values for membrane internalization velocity and early endocytic radius, the rate of endosome formation required to reabsorb the filtered albumin load was calculated (total endosomes formed /sec). Total rate of ATP required to reabsorb a filtered load of albumin was then determined as the product of ATP/endosomes and total endosomes formed / second. At normal intracellular pH and normal filtered albumin load, it is estimated that 83,600 endosomes, with a radius of 0.34 µm, and 25,000 molecules of ATP are needed to reabsorb 740 µg of albumin per second for one proximal tubule. This is a very small fraction of total ATP utilized by the cell. To our knowledge, this model is the first to quantify the energetics of PT endosome formation and protein reabsorption. It provides a tool to quantitatively evaluate the impact of variations in factors such as intracellular pH, filtered protein load, and energy availability on the PT's ability to acidify endosomes and reabsorb protein. This may aid in future elucidation of pathological mechanisms of proteinuria.

Loss of Furin in β-Cells Induces an mTORC1-ATF4 Anabolic Pathway That Leads to β-Cell Dysfunction.

FURIN is a proprotein convertase (PC) responsible for proteolytic activation of a wide array of precursor proteins within the secretory pathway. It maps to the PRC1 locus, a type 2 diabetes susceptibility locus, but its specific role in pancreatic β-cells is largely unknown. The aim of this study was to determine the role of FURIN in glucose homeostasis. We show that FURIN is highly expressed in human islets, whereas PCs that potentially could provide redundancy are expressed at considerably lower levels. β-cell-specific Furin knockout (βFurKO) mice are glucose intolerant as a result of smaller islets with lower insulin content and abnormal dense-core secretory granule morphology. mRNA expression analysis and differential proteomics on βFurKO islets revealed activation of activating transcription factor 4 (ATF4), which was mediated by mammalian target of rapamycin C1 (mTORC1). βFurKO cells show impaired cleavage or shedding of vacuolar-type ATPase (V-ATPase) subunits Ac45 and prorenin receptor, respectively, and impaired lysosomal acidification. Blocking V-ATPase pharmacologically in β-cells increased mTORC1 activity, suggesting involvement of the V-ATPase proton pump in the phenotype. Taken together, these results suggest a model of mTORC1-ATF4 hyperactivation and impaired lysosomal acidification in β-cells lacking Furin, causing β-cell dysfunction.

Use of the Critical Acidification Model to Estimate the Influence of W in the Localized Corrosion Resistance of 25Cr Super Duplex Stainless Steels

Two super duplex stainless steels (SDSS) with different W content, namely UNS S32750 (W-free) and UNS S39274 (2.1 wt.% W), were tested in simulated crevice corrosion environments to determine the influence of W on their corrosion resistance. Anodic potentiodynamic polarization experiments were performed in two different crevice-like-solutions: 1 M HCl (as reference for a pH = 0 environment), and 7 M LiCl, adjusted to the same pH value. Galvele’s critical acidification model was used to estimate the theoretical critical potential (Ecrit) and comparatively evaluate the corrosion resistance of the two SDSS. The anodic potentiodynamic polarization results showed a statistically significant difference between the two materials in only one test condition, i.e., 7 M Cl− at 60 °C. Additionally, the quantification of chemical dissolution of the metal cations after the tests suggested a surface enrichment in W only in the 7 M chloride solution. Scanning electron microscope (SEM) analysis indicated a uniform dissolution experienced by UNS S32750 in this environment, whereas UNS S39274 suffered selective corrosion of the ferrite-phase. These observations were reflected in a slight increase in the Ecrit values of UNS S32974 estimated with Galvele’s model.

Spatiotemporal variability, source apportionment, and acid-neutralizing capacity of atmospheric wet base-cation deposition in China

Atmospheric wet deposition of base cations (BCs) plays a significant role in providing plant nutrients and buffering acidification. However, the temporal dynamic of wet BC deposition in China during the past two decades remain unclear. Here, we used long-term monitoring and literature data since 2000 to assess the temporal dynamics (seasonal and inter-annual variation), spatial patterns, main influencing factors, source apportionment, and capacity to neutralize the acidity of wet BC depositions at site, regional, and national scales. The results showed that total wet deposition of BCs was, on average, 2.12 keq ha−1 yr−1, where Ca2+ accounted for 65.57% of the total deposition, followed by Na+ (13.21%), Mg2+ (13.68%), and K+ (7.55%). Qinghai-Tibet had significantly lower BC deposition fluxes than northern, southern, and central China, as well as Inner Mongolia. Exchangeable BCs in soil, PM10 in the atmosphere, energy consumption, and cement production are significantly related to wet BC deposition, which account for 79.17% of the variation in the spatial deposition of BC. Influenced by the strategies to control acid rain and particulate matter in China, interannual variations showed a stabilization trend after a continuous decline from 2000 to 2017, which can be explained by inter-annual changes in PM10, energy consumption and cement production. Statistical methods confirmed that 45.95% of wet BC deposition was derived from crustal contributions, 27.78% from sea salt sources, and 26.27% from anthropogenic sources. Furthermore, we found that wet deposition of BCs neutralized 84.85% of the acidity due to NO3− and SO42− depositions. Under the emissions reduction strategy, there has been a decrease in the deposition of BC. However, SO42− and NO3− depositions decreased faster than BC deposition, which buffered a higher proportion of acidic depositions. Our findings contribute to an improved understanding of wet BC deposition in China, an evaluation of their capacity to neutralize acidity, and important parameters for acidification models.

Application of acidification parameter optimization method

The acidification technology is an important measure to increase the production and increase the injection of oil and water wells. However, due to the complicated working conditions of the acidification measures and the difficulty in determining the construction parameters, it is necessary to establish the acidification model of the injection wells and optimize the parameters. The paper uses the grey correlation analysis method to find the correlation between each construction parameter and the daily injection volume of the injection well, establishes the BP neural network program, trains it according to the existing data and predicts the artificial controllable parameters in turn to find the best construction parameter combination. Taking a single well as an example to predict the parameters and guide the on-site construction. The results show that combining the mathematical method with the acidification construction technology of the injection well and establishing the model prediction parameters can significantly improve the injection efficiency of the injection well.

Protons in small spaces: Discrete simulations of vesicle acidification.

The lumenal pH of an organelle is one of its defining characteristics and central to its biological function. Experiments have elucidated many of the key pH regulatory elements and how they vary from compartment-to-compartment, and continuum mathematical models have played an important role in understanding how these elements (proton pumps, counter-ion fluxes, membrane potential, buffering capacity, etc.) work together to achieve specific pH setpoints. While continuum models have proven successful in describing ion regulation at the cellular length scale, it is unknown if they are valid at the subcellular level where volumes are small, ion numbers may fluctuate wildly, and biochemical heterogeneity is large. Here, we create a discrete, stochastic (DS) model of vesicular acidification to answer this question. We used this simplified model to analyze pH measurements of isolated vesicles containing single proton pumps and compared these results to solutions from a continuum, ordinary differential equations (ODE)-based model. Both models predict similar parameter estimates for the mean proton pumping rate, membrane permeability, etc., but, as expected, the ODE model fails to report on the fluctuations in the system. The stochastic model predicts that pH fluctuations decrease during acidification, but noise analysis of single-vesicle data confirms our finding that the experimental noise is dominated by the fluorescent dye, and it reveals no insight into the true noise in the proton fluctuations. Finally, we again use the reduced DS model explore the acidification of large, lysosome-like vesicles to determine how stochastic elements, such as variations in proton-pump copy number and cycling between on and off states, impact the pH setpoint and fluctuations around this setpoint.

Impaired lysosomal acidification triggers iron deficiency and inflammation in vivo.

Lysosomal acidification is a key feature of healthy cells. Inability to maintain lysosomal acidic pH is associated with aging and neurodegenerative diseases. However, the mechanisms elicited by impaired lysosomal acidification remain poorly understood. We show here that inhibition of lysosomal acidification triggers cellular iron deficiency, which results in impaired mitochondrial function and non-apoptotic cell death. These effects are recovered by supplying iron via a lysosome-independent pathway. Notably, iron deficiency is sufficient to trigger inflammatory signaling in cultured primary neurons. Using a mouse model of impaired lysosomal acidification, we observed a robust iron deficiency response in the brain, verified by in vivo magnetic resonance imaging. Furthermore, the brains of these mice present a pervasive inflammatory signature associated with instability of mitochondrial DNA (mtDNA), both corrected by supplementation of the mice diet with iron. Our results highlight a novel mechanism linking impaired lysosomal acidification, mitochondrial malfunction and inflammation in vivo.

Model of influenza virus acidification.

Internal acidification of the influenza virus, mediated by the M2 proton channel, is a key step in its life cycle. The interior M1 protein shell dissolves at pH~5.5 to 6.0, allowing the release of vRNA to the cytoplasm upon fusion of the viral envelope with the endosomal membrane. Previous models have described the mechanisms and rate constants of M2-mediated transport but did not describe the kinetics of pH changes inside the virus or consider exterior pH changes due to endosome maturation. Therefore, we developed a mathematical model of M2-mediated virion acidification. We find that ~32,000 protons are required to acidify a typically-sized virion. Predicted acidification kinetics were consistent with published in vitro experiments following internal acidification. Finally, we applied the model to the in vivo situation. For all rates of endosomal maturation considered, internal acidification lagged ~1 min behind endosomal acidification to pH 6. For slow endosomal maturation requiring several minutes or more, internal and endosomal pH decay together in pseudo-equilibrium to the late endosomal pH~5.0. For fast endosomal maturation (≲2 min), a lag of tens of seconds continued toward the late endosomal pH. Recent experiments suggest in vivo maturation is in this “fast” regime where lag is considerable. We predict that internal pH reaches the threshold for M1 shell solvation just before the external pH triggers membrane fusion mediated by the influenza protein hemagglutinin, critical because outward proton diffusion through a single small fusion pore is faster than the collective M2-mediated transport inward.

The effect of Lactobacillus delbrueckii subsp bulgaricus proteinase on properties of milk gel acidified with glucono‐δ‐lactone

SummaryLactobacillus delbrueckii subsp. bulgaricus CH9‐3 proteinase is an enzyme that plays an important role in yogurt fermentation, by which its use is linked to gel properties of yogurt. In this work, a modified glucono‐δ‐lactone (GDL) acidification model was used to simulate the fermentation of yogurt and study the effect of CH9‐3 proteinase on GDL‐acidified milk gel. The results showed that the proteinase significantly improved the quality of milk gel by increasing its firmness, consistency, and viscosity index, while decreasing its syneresis. Furthermore, the proteinase could accelerate the formation of milk gel as indicated by the decrease in surface charge of milk gel. The findings demonstrate that CH9‐3 proteinase has a positive effect on the properties of milk gel, and thus may have promising applications in the yogurt making industry.

Identifying Dormant Growth State of Mycobacteria by Orthogonal Analytical Approaches on a Single Cell and Ensemble Basis.

Tuberculosis is currently the single most deadly infectious disease in the world and a public health priority as defined by WHO. Although the disease is in general curable, treatment success is hampered by the necessity of a long and side effect prone treatment. Low treatment efficiency may be partly due to the special growth states that mycobacteria enter to avoid being killed by antibiotics and to persist longer within the host. Such growth states have been recently defined as dormant or persistent. We produced dormant model-organism cultures using an acidification model and characterized those by a multilayered approach using mass spectrometry (MALDI-TOF), microscopy (SEM, Raman), and microbiological techniques (CFU, OD600, ATP-levels). With a fast and 96-well-adapted extraction protocol, mycobacteria could be inactivated and extracted for MALDI-TOF analysis. For the first time, we demonstrate growth-state-dependent changes in the mass signatures of the culture, allowing for a reliable differentiation of dormant state and exponential growth. We also demonstrate resuscitation from dormant state back to exponential growth. Viable mycobacteria were immobilized, and single organisms were analyzed individually by Raman microscopy. For single-cell Raman microscopy, Mycobacterium smegmatis cultures were fixed using a new fast and gentle single-step immobilization technique on a hydrophobic glass slide. We were able to distinguish single viable bacteria in the dormant state from their rapidly growing, genetically identical counterparts, identifying the growth state of the culture based on single-organism spectra. This allows for the separation of heterogeneous cultures depending on their growth state using the destruction-free optical method of Raman microscopy.