Applicability of near-infrared spectroscopy for process monitoring in bioethanol production

The applicability of near-infrared (NIR) spectroscopy to bioethanol production is investigated. The NIR technique can provide assistance for rapid process monitoring, because organic compounds absorb radiation in the wavelength range 1100–2300 nm. For quantification of a sample's chemical composition, a calibration model is required that relates the measured spectral NIR absorbances to concentrations. For calibration, the concentrations in g/l are determined by the analytical reference method high performance liquid chromatography (HPLC). The calibration models are built and validated for moisture, protein, and starch in the feedstock material, and for glucose, ethanol, glycerol, lactic acid, acetic acid, maltose, fructose, and arabinose in the processed broths. These broths are prepared in laboratory experiments: The ground cereal samples are fermented to alcoholic broths (‘mash’), which are divided into an ethanol fraction and the residual fraction ‘stillage’ by distillation. The NIR technology together with chemometrics proved itself beneficial for fast monitoring of the current state of the bioethanol process, primarily for higher concentrated substances (>1 g/l).     

Real‐time monitoring of high‐gravity corn mash fermentation using in situ raman spectroscopy

In situ Raman spectroscopy was employed for real‐time monitoring of simultaneous saccharification and fermentation (SSF) of corn mash by an industrial strain of Saccharomyces cerevisiae. An accurate univariate calibration model for ethanol was developed based on the very strong 883 cm^?1 C–C stretching band. Multivariate partial least squares (PLS) calibration models for total starch, dextrins, maltotriose, maltose, glucose, and ethanol were developed using data from eight batch fermentations and validated using predictions for a separate batch. The starch, ethanol, and dextrins models showed significant prediction improvement when the calibration data were divided into separate high‐ and low‐concentration sets. Collinearity between the ethanol and starch models was avoided by excluding regions containing strong ethanol peaks from the starch model and, conversely, excluding regions containing strong saccharide peaks from the ethanol model. The two‐set calibration models for starch (R² = 0.998, percent error = 2.5%) and ethanol (R² = 0.999, percent error = 2.1%) provide more accurate predictions than any previously published spectroscopic models. Glucose, maltose, and maltotriose are modeled to accuracy comparable to previous work on less complex fermentation processes. Our results demonstrate that Raman spectroscopy is capable of real time in situ monitoring of a complex industrial biomass fermentation. To our knowledge, this is the first PLS‐based chemometric modeling of corn mash fermentation under typical industrial conditions, and the first Raman‐based monitoring of a fermentation process with glucose, oligosaccharides and polysaccharides present. Biotechnol. Bioeng. 2013; 110: 1654–1662. © 2013 Wiley Periodicals, Inc.     

Hemodialysis monitoring using mid‐ and near‐infrared spectroscopy with partial least squares regression

Blood constituents such as urea, glucose, lactate, phosphate and creatinine are of high relevance in monitoring the process of detoxification in ambulant dialysis treatment. In the present work, 2 different vibrational spectroscopic techniques are used to determine those molecules quantitatively in artificial dialysate solutions. The goal of the study is to compare the performance of near‐infrared (NIR) and mid‐infrared (MIR) spectroscopy in hyphenation with partial least squares regression (PLSR) directly by using the same sample set. The results show that MIR spectroscopy is better suited to analyze the analytes of interest. Multilevel multifactor design is used to cover the relevant concentration variations during dialysis. MIR spectroscopy coupled to a multi reflection attenuated total reflection (ATR) cell enables reliable prediction of all target analytes. In contrast, the NIR spectroscopic method does not give access to all 5 components but only to urea and glucose. For both methods, coefficients of determination greater or equal to 0.86 can be achieved in the test‐set validation process for urea and glucose. Lactate, phosphate and creatinine perform well in the MIR with R² ≥ 0.95 using test‐set validation.      

On-line monitoring of human prostate cancer cells in a perfusion rotating wall vessel by near-infrared spectroscopy

PC-3 human prostate cancer cells have been cultivated in a rotating wall vessel in which glucose, lactate, and glutamine profiles were monitored noninvasively and in real time by near-infrared (NIR) spectroscopy. The calibration models were based on off-line spectra from tissue culture experiments described previously (Rhiel et al., Biotechnol Bioeng 77:73-82). Monitoring performance was improved by Fourier filtering of the spectra and initial off-set adjustment. The resulting standard errors of predictions were 0.95, 0.74, and 0.39 mM for glucose, lactate, and glutamine, respectively. The concentration of ammonia could not be accurately measured from the same spectra. In addition, metabolite uptake and production rates were determined for PC-3 prostate cancer cells during exponential growth in batch-mode cultivation. Cells grew with a doubling time of 21 h and consumed glucose and glutamine at rates of 6.8 and 1.8 x 10(-17) mol/cell.s, respectively. This resulted in lactate and ammonia production rates of 11.9 and 1.3 x 10(-17) mol/cell.s, respectively. Compared with other monitoring technologies, this technology has many advantages for spaceflights and stand-alone units; for instance, calibration can be performed at one time and then applied in a reagentless, low-maintenance way at a later time. The resulting concentration information can be incorporated into closed-loop control schemes, thereby leading to better in vitro models of in vivo behavior.     

In‐situ monitoring of Saccharomyces cerevisiae ITV01 bioethanol process using near‐infrared spectroscopy NIRS and chemometrics

The application feasibility of in‐situ or in‐line monitoring of S. cerevisiae ITV01 alcoholic fermentation process, employing Near‐Infrared Spectroscopy (NIRS) and Chemometrics, was investigated. During the process in a bioreactor, in the complex analytical matrix, biomass, glucose, ethanol and glycerol determinations were performed by a transflection fiber optic probe immersed in the culture broth and connected to a Near‐Infrared (NIR) process analyzer. The NIR spectra recorded between 800 and 2,200 nm were pretreated using Savitzky‐Golay smoothing and second derivative in order to perform a partial least squares regression (PLSR) and generate the calibration models. These calibration models were tested by external validation and then used to predict concentrations in batch alcoholic fermentations. The standard errors of calibration (SEC) for biomass, ethanol, glucose and glycerol were 0.212, 0.287, 0.532, and 0.296 g/L and standard errors of prediction (SEP) were 0.323, 0.369, 0.794, and 0.507 g/L, respectively. Calibration and validation criteria were defined and evaluated in order to generate robust and reliable models for an alcoholic fermentation process matrix. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:510–517, 2016     

On-line glucose monitoring by near infrared spectroscopy during the scale up steps of mammalian cell cultivation process development

NIR spectroscopy is a non-destructive tool for in-situ, on-line bioprocess monitoring. One of its most frequent applications is the determination of metabolites during cultivation, especially glucose. Previous studies have usually investigated the applicability of Near Infrared (NIR) spectroscopy at one bioreactor scale but the effect of scale up was not explored. In this study, the complete scale up from shake flask (1 L) through 20 L, 100 L and 1000 L up to 5000 L bioreactor volume level was monitored with on-line NIR spectroscopy. The differences between runs and scales were examined using principal component analysis. The bioreactor runs were relatively similar regardless of scales but the shake flasks differed strongly from bioreactor runs. The glucose concentration throughout five 5000 L scale bioreactor runs were predicted by partial least squares regression models that were based on pre-processed spectra of bioreactor runs and combinations of them. The model that produced the lowest error of prediction (4.18 mM on a 29 mM concentration range) for all five runs in the prediction set was based on the combination of 20 L and 100 L data. This result demonstrated the capabilities and the limitations of an NIR system for glucose monitoring in mammalian cell cultivations.

     

Amperometric glucose biosensors based on layer-by-layer assembly of chitosan and glucose oxidase on the Prussian blue-modified gold electrode

A glucose biosensor based on layer-by-layer (LBL) self-assembling of chitosan and glucose oxidase (GOD) on a Prussian blue film was developed. First, Prussian blue was deposited on a cleaned gold electrode then chitosan and GOD were assembled alternately to construct a multilayer film. The resulting amperometric glucose biosensor exhibited a fast response time (within 10 s) and a linear calibration range from 6 μM to 1.6 mM with a detection limit of 3.1 μM glucose (s/n = 3). With the low operating potential, the biosensor showed little interference to the possible interferents, including ascorbic acid, acetaminophen and uric acid, indicating an excellent selectivity.     

Glucose gradient differences in subcutaneous tissue of healthy volunteers assessed with ultraslow microdialysis and a nanolitre glucose sensor

The abdominal subcutaneous interstitium is easily accessible for monitoring glucose for Diabetes Mellitus research and management. The available glucose sensing devices demand frequent blood sampling by finger pricking for calibration. Moreover, there is controversy about the exact relationship between the levels of glucose in the subcutis and blood. In the present study ultra-slow microdialysis was applied for subcutaneous fluid sampling, allowing continuous measurement of glucose in an equilibrated fluid using a nanolitre size sensor. The present method avoids in vivo calibration. During an oral glucose tolerance test glucose levels were measured simultaneously in blood, in adipose tissue and loose connective tissue layers of the abdominal subcutis in seven healthy subjects. Fasting glucose levels (mM) were 2.52 +/- 0.77 in adipose tissue and 4.67 +/- 0.17 in blood, this difference increasing to 6.40 +/- 1.57 and 11.59 +/- 1.52 at maximal glucose concentration. Moreover, the kinetics of glucose in blood and adipose tissue were different. In contrast, connective tissue glucose levels differed insignificantly (4.71 +/- 0.21 fasting and 11.70 +/- 1.96 at maximum) from those in blood and correlated well (r2 = 0.962). Ultra-slow microdialysis combined with a nanolitre glucose sensor could be of benefit to patients in intensive diabetes therapy. Frequent blood sampling for in vivo calibration can be avoided by monitoring glucose in the abdominal subcutaneous loose connective tissue, rather than in the adipose tissue.     

Near-infrared fluorescence glucose sensing based on glucose/galactose-binding protein coupled to 651-Blue Oxazine

Near-infrared (NIR) fluorescent dyes that are environmentally sensitive or solvatochromic are useful tools for protein labelling in in vivo biosensor applications such as glucose monitoring in diabetes since their spectral properties are mostly independent of tissue autofluorescence and light scattering, and they offer potential for non-invasive analyte sensing. We showed that the fluorophore 651-Blue Oxazine is polarity-sensitive, with a marked reduction in NIR fluorescence on increasing solvent polarity. Mutants of glucose/galactose-binding protein (GBP) used as the glucose receptor were site-specifically and covalently labelled with Blue Oxazine using click chemistry. Mutants H152C/A213R and H152C/A213R/L238S showed fluorescence increases of 15% and 21% on addition of saturating glucose concentrations and binding constants of 6 and 25 mM respectively. Fluorescence responses to glucose were preserved when GBP-Blue Oxazine was immobilised to agarose beads, and the beads were excited by NIR light through a mouse skin preparation studied in vitro. We conclude GBP-Blue Oxazine shows proof-of-concept as a non-invasive continuous glucose sensing system.     

Bioprocess in-line monitoring using Raman spectroscopy and Indirect Hard Modeling (IHM): A simple calibration yields a robust model

To increase the process productivity and product quality of bioprocesses, the in-line monitoring of critical process parameters is highly important. For monitoring substrate, metabolite, and product concentrations, Raman spectroscopy is a commonly used Process Analytical Technology (PAT) tool that can be applied in-situ and non-invasively. However, evaluating bioprocess Raman spectra with a robust state-of-the-art statistical model requires effortful model calibration. In the present study, we in-line monitored a glucose to ethanol fermentation by Saccharomyces cerevisiae (S. cerevisiae) using Raman spectroscopy in combination with the physics-based Indirect Hard Modeling (IHM) and showed successfully that IHM is an alternative to statistical models with significantly lower calibration effort. The IHM prediction model was developed and calibrated with only 16 Raman spectra in total, which did not include any process spectra. Nevertheless, IHM's root mean square errors of prediction (RMSEPs) for glucose (3.68 g/L) and ethanol (1.69 g/L) were comparable to the prediction quality of similar studies that used statistical models calibrated with several calibration batches. Despite our simple calibration, we succeeded in developing a robust model for evaluating bioprocess Raman spectra.     

In vivo glucose monitoring: the clinical reality and the promise

Glucose monitoring is an essential component of modern diabetes management. Three in vivo glucose sensors are now available for clinical use: a subcutaneously implanted amperometric enzyme electrode, a reverse iontophoresis system and a microdialysis-based device. Improvements in glucose-sensing technology continue to be sought, e.g. wired enzyme technology, viscometric affinity sensing and totally implanted glucose sensors. Non-invasive glucose sensing is the ultimate goal of glucose monitoring, but the most investigated approach, near-infrared (NIR) spectroscopy, is presently too imprecise for clinical application. Fluorescence-based glucose sensing offers several advantages and we are investigating strategies which include NIR-based fluorescence resonance energy transfer using concanavalin A/dextran; changes in the intrinsic fluorescence of hexokinase encapsulated in sol-gel; and non-invasive glucose monitoring of cells by measuring glucose-related changes in NADP(H).     

Monitoring a bioprocess for ethanol production using FT-MIR and FT-Raman spectroscopy

The application of Fourier transform mid-infrared (FT-MIR) spectroscopy and Fourier transform Raman (FT-Raman) spectroscopy for process and quality control of fermentative production of ethanol was investigated. FT-MIR and FT-Raman spectroscopy along with multivariate techniques were used to determine simultaneously glucose, ethanol, and optical cell density of Saccharomyces cerevisiae during ethanol fermentation. Spectroscopic measurement of glucose and ethanol were compared and validated with the high-performance liquid chromatography (HPLC) method. Spectral wave number regions were selected for partial least-squares (PLS) regression and principal component regression (PCR) and calibration models for glucose, ethanol, and optical cell density were developed for culture samples. Correlation coefficient (R ²) value for the prediction for glucose and ethanol was more than 0.9 using various calibration methods. The standard error of prediction for the PLS first-derivative calibration models for glucose, ethanol, and optical cell density were 1.938 g/l, 1.150 g/l, and 0.507, respectively. Prediction errors were high with FT-Raman because the Raman scattering of the cultures was weak. Results indicated that FT-MIR spectroscopy could be used for rapid detection of glucose, ethanol, and optical cell density in S. cerevisiae culture during ethanol fermentation. Journal of Industrial Microbiology & Biotechnology (2001) 26, 185–190. Received 16 November 2000/ Accepted in revised form 12 January 2001     

Clinical application of near infrared fiber optic spectroscopy for noninvasive bone assessment

Approaches for noninvasive bone quality assessment are of great clinical need, particularly in individuals that require close monitoring of disease progression. X‐ray measurements are standard approaches to assess bone quality; however, they have several disadvantages. Here, a nonionizing approach for noninvasive assessment of the second metacarpal bone based on near infrared (NIR) spectroscopy was investigated. Transcutaneous bone signal detection was experimentally confirmed with cadaveric hand data, and Monte Carlo modeling further indicated that 50% of the measured signals arise from bone. Spectral data were collected via a NIR fiber optic from the bone of individuals with osteogenesis imperfecta, a disease marked by frequent bone fractures and fragility. Multiple significant correlations were found between spectral parameters related to water, protein and fat, and standard bone quality parameters obtained by X‐ray measurements. The results from this preliminary study highlight the potential application of NIR spectroscopy for the noninvasive assessment of bone quality.     

An interference-free biosensor based on glucose oxidase electrochemically immobilized in a non-conducting poly(pyrrole) film for continuous subcutaneous monitoring of glucose through microdialysis sampling

A glucose biosensor, based on glucose oxidase immobilized in a non-conducting (overoxidised) polypyrrole film, is described which proved practically immune from faradaic interference arising from endogeneous (ascorbate, urate, cysteine) and exogeneous (acetaminophen) electroactive interferents. The bias introduced in the measurement of 5 mM glucose by the given interferents at their maximum physiological levels never exceeded 2% which is, by far, the lowest value ever reported. The biosensor has been used for continuous subcutaneous monitoring of glucose in a rabbit implanted with a microdialysis probe. The potential and limits of this approach are discussed.     

Nondestructive near-infrared spectroscopic measurement of multiple analytes in undiluted samples of serum-based cell culture media.

An adaptive calibration procedure is used to build selective multivariate calibration models for the measurement of glucose, lactate, glutamine, and ammonia in undiluted serum-based cell culture media. This adaptive procedure removes metabolism-induced covariance between these analytes in a series of calibration samples collected during the cultivation of PC-3 human prostate cancer cells. Partial least-squares calibration models are generated from single-beam near-infrared (NIR) spectra collected over the 4800- to 4200-cm(-1) combination spectral range. Calibration models were generated with both the full spectral range and optimized spectral ranges. In both cases, the number of model factors was optimized and model validity was determined by comparing analyte concentrations predicted from a series of independent and unaltered samples that were obtained during a subsequent cultivation of the PC-3 cells. Similar analytical performance was achieved with fewer model factors when the optimized spectral range was used. The lowest standard errors of prediction were 0.82, 0.94, 0.55, and 0.76 mM for glucose, lactate, glutamine, and ammonia, respectively. Different spectral ranges were optimal for each analyte and the optimized spectral range coincided with the distinguishing spectral features of the analyte. The results of this study demonstrate that NIR spectroscopy can be used effectively in the off-line measurement of important nutrients (glucose and glutamine) and byproducts (lactate and ammonia) in a serum-based animal cell culture medium.     

基于近红外光谱实时监测乙醇发酵过程多组分参数

生物量、葡萄糖浓度和乙醇浓度是乙醇发酵过程的重要参数,传统的方法通常对发酵液取样作离线测量,不仅需要采用多种仪器进行测试分析,而且耗时耗力,成为实时过程调控和优化的障碍。文中针对这些重要过程参数提出了一个基于近红外光谱技术的原位实时检测方法。通过采用浸入式近红外光谱仪对发酵溶液进行原位测量,基于多输出最小二乘支持向量机回归(MLS-SVR)方法建立了利用近红外光谱同时分析葡萄糖浓度、生物量和乙醇浓度的多输出预测模型。实验结果表明,该方法能实时准确地检测乙醇发酵过程中的葡萄糖浓度、生物量和乙醇浓度,而且相对于现有的偏最小二乘法(PLS)分别对各组分建模和预测,能明显提高测量准确性和可靠性。     

Monitoring,treatment and control of blood glucose and lipids in Ontario First Nations people with diabetes

BACKGROUND:Indigenous people worldwide are disproportionately affected by diabetes and its complications. We aimed to assess the monitoring, treatment and control of blood glucose and lipids in First Nations people in Ontario.METHODS:We conducted a longitudinal population-based study using administrative data for all people in Ontario with diabetes, stratified by First Nations status. We assessed age- and sex-specific rates of completion of recommended monitoring for low-density lipoprotein (LDL) and glycated hemoglobin (A_1c) from 2001/02 to 2014/15. We used data from 2014/15 to conduct a cross-sectional analysis of rates of achievement of A_1c and LDL targets and use of glucose-lowering medications.RESULTS:The study included 22 240 First Nations people and 1 319 503 other people in Ontario with diabetes. Rates of monitoring according to guidelines were 20%–50% for A_1c and 30%–70% for lipids and were lowest for younger First Nations men. The mean age- and sex-adjusted A_1c level was higher among First Nations people than other people (7.59 [95% confidence interval (CI) 7.57 to 7.61] v. 7.03 [95% CI 7.02 to 7.03]). An A_1c level of 8.5% or higher was observed in 24.7% (95% CI 23.6 to 25.0) of First Nations people, compared to 12.8% (95% CI 12.1 to 13.5) of other people in Ontario. An LDL level of 2.0 mmol/L or less was observed in 60.3% (95% CI 59.7 to 61.6) of First Nations people, compared to 52.0% (95% CI 51.1 to 52.9) of other people in Ontario. Among those aged 65 or older, a higher proportion of First Nations people than other Ontarians were using insulin (28.1% v. 15.1%), and fewer were taking no medications (28.3% v. 40.1%).INTERPRETATION:As of 2014/15, monitoring and achievement of glycemic control in both First Nations people and other people in Ontario with diabetes remained suboptimal. Interventions to support First Nations patients to reach their treatment goals and reduce the risk of complications need further development and study.

Diabetes and its related complications are major contributors to morbidity and mortality worldwide.^1–3 Indigenous populations in Canada and around the world are disproportionately affected by diabetes owing to the complex relations among colonization, social disadvantage, stress, trauma and metabolic health.^4–7 In addition to our own work showing persistently higher rates of peripheral vascular disease, stroke, cardiac disease, renal dysfunction and ophthalmologic complications in Ontario First Nations,^8–12 other Canadian and international studies also showed higher complication rates in diverse Indigenous populations.^6,7,13–15Glycemic control is fundamental to the management of diabetes and the prevention of complications.¹⁶ Glycated hemoglobin (A_1c) is a reliable way to estimate the average level of glucose in the blood.¹⁷ Since A_1c levels higher than 7.0% have been associated with an increased risk of microvascular complications,^18–20 treatment guidelines suggest A_1c should be measured every 3–6 months to ensure that glycemic goals are being met or maintained.²¹ Since people with diabetes also have an elevated risk for cardiovascular disease,^22–24 management and control of cardiovascular risk factors, particularly lipids such as low-density lipoprotein (LDL) cholesterol, are also important.^25–27 Guidelines further recommend that a full lipid profile be measured every 1–3 years, depending on cardiovascular risk, and suggest that LDL be consistently less than 2.0 mmol/L.²⁸ Control of A_1c and lipids has been shown to be associated with reduced morbidity and mortality in patients with diabetes.^18,29–32One possible reason for the high burden of complications among Indigenous people with diabetes may be failure to achieve control of these 2 key clinical parameters. We examined differences between Status First Nations people with diabetes in Ontario and all other Ontario residents with diabetes in rates of monitoring of A_1c and lipids, achievement of targets for A_1c and LDL outlined in clinical guidelines, and patterns of medication use to help attain these targets.     

Granular detail of β cell structures for insulin secretion

Pancreatic β cells secrete insulin in response to increased glucose concentrations. Müller et al. (2021. J. Cell Biol. https://doi.org/10.1083/jcb.202010039) use 3D FIB-SEM to study the architecture of these cells and to elucidate how glucose stimulation remodels microtubules to control insulin secretory granule exocytosis.

The pancreatic islet β cell is a prototypical model for regulated protein secretion, which has been studied extensively because of its importance for diabetes in humans. Upon stimulation by increased glucose concentrations, β cells mobilize insulin-containing secretory vesicles to the cell surface. These “insulin secretory granules” fuse at the plasma membrane to release insulin into the circulation. Insulin then acts on the liver to inhibit glucose production and on muscle and fat cells to stimulate glucose uptake, thus returning blood glucose concentrations to a narrow physiological range. During the development of diabetes, this negative feedback system fails. In type 1 diabetes, β cells are destroyed by an autoimmune process; in type 2 diabetes, attenuated insulin action (“insulin resistance”) occurs together with impaired β cell function. In both cases, blood glucose concentrations rise above the normal range. Overall, glucose homeostasis requires a delicate balance between glucose-stimulated insulin secretion from β cells and insulin-stimulated effects on glucose metabolism in liver, muscle, fat, and other cell types.Each β cell contains 5,000 to ≥10,000 insulin secretory granules, and acute glucose stimulation causes exocytosis of only 1–2% of this pool (1, 2). Both readily releasable and reserve pools of granules contribute to insulin secretion. Classically, the readily releasable pool has been considered as vesicles that are docked at the plasma membrane; the reserve pool, which is larger and more important, resides deeper within the cell and relies on microtubule-based transport to reach the cell surface. Yet, other data show that newly synthesized insulin is preferentially released, and aged insulin granules are targeted for degradation in lysosomes, implying that microtubules play a more complicated role in granule trafficking (3). In the setting of insulin resistance, the flux of insulin through the secretory pathway is increased. Demands are placed upon the machinery for folding of the insulin precursor, proinsulin, for its proteolytic conversion to produce insulin, and for insulin secretory granule maturation. As well, in type 2 diabetes, lipids and other metabolites act directly on β cells to impair glucose-stimulated insulin secretion. What steps are affected by this critical pathophysiologic insult is not well understood, in part because basic mechanisms by which glucose stimulation remodels microtubules to promote insulin release remain undefined.To better understand these processes, Müller et al. used focused ion beam scanning electron microscopy (FIB-SEM) to image microtubules, insulin secretory granules, and other organelles in whole primary mouse β cells and to study the effects of glucose stimulation on these structures (4). Together with advances in sample preparation, image segmentation, and analysis, FIB-SEM is uniquely suited to this task. The resulting 3D images have a voxel size of 4 × 4 × 4 nm and encompass volumes of 20–30 µm in x, y, and z dimensions. This is sufficient to image microtubules, which have an outer diameter of ~25 nm, in whole β cells, which are 10–20 µm in diameter. Moreover, the imaging was performed on intact islets, rather than on dissociated cells, which may better preserve insulin secretory granule dynamics. The images captured seven β cells in all, three in a low-glucose (unstimulated) condition and four in the glucose-stimulated state. Finally, the images were quantified in a way that controlled for the overall geometry of the cells.The data show that the β cell microtubule network is nonradial, dense, tortuous, and mostly not connected to either centrioles or the Golgi complex, so that microtubules appear to be freely positioned in the cytosol (Fig. 1). This is similar to other differentiated cells (5) but in contrast to previous data suggesting that in β cells most microtubules originate at the Golgi (6). The microtubule cytoskeleton negatively regulates insulin granule exocytosis in unstimulated cells (7). Yet, the FIB-SEM data suggest that the effect of glucose is not simply to disinhibit this effect. Glucose stimulated an approximately threefold increase in the number of microtubules and an approximately threefold decrease in the average length of each microtubule, so that total tubulin polymer density remained unchanged (4). The images also show that microtubule ends and insulin secretory granules are enriched near the plasma membrane and indicate an important role for microtubules in positioning the granules for exocytosis. Intriguingly, glucose stimulation did not cause any marked change in the association of secretory granules with microtubules, suggesting that it may act by other mechanisms to increase microtubule-based transport (3). The data also demonstrate an increase in the number of secretory granules near the Golgi in glucose-stimulated cells, raising the possibility that glucose may promote budding of nascent secretory vesicles at the trans-Golgi network. If so, it is not yet clear whether this is a direct effect or if it is secondary to increased flux through the secretory pathway.Open in a separate windowFigure 1.Regulation of β cell architecture by glucose. In low-glucose conditions (left panel), microtubules form a dense, nonradial network. The tubules are mostly not anchored to the Golgi complex or to centrosomes but are associated with insulin secretory granules near the plasma membrane (PM). After stimulation with high-glucose concentrations (right panel), the microtubules are shorter and more numerous, and an increased density of vesicles near the Golgi was observed.The observation that glucose stimulation results in shorter, more numerous microtubules, without changing tubulin polymer density, suggests a possible role for severing enzymes such as katanin, spastin, or fidgetin (8). Whether and how such enzymes may be stimulated by glucose is not known. Glucose stimulates insulin secretion by increasing the ATP/ADP ratio, in part due to local ATP generation by pyruvate kinase, as well as by oxidative phosphorylation (9). Although these microtubule-severing enzymes are AAA ATPases, it is not clear that ATP availability acts physiologically to regulate their activities. Other data show that in β cells, glucose-responsive kinases phosphorylate tau, causing it to dissociate from microtubule plus ends to destabilize microtubules and to promote remodeling (10). Could such kinases regulate severing enzymes as well?The technological achievements of Müller et al. are impressive, and the work will serve as a model for the analysis of cellular architecture in other cell types. In β cells, the results may be extended by using FIB-SEM to study effects of various genetic manipulations, by using EM-visible tags, and by examining diabetes models. It may be informative to image granules of different ages or to use drugs to manipulate microtubules or membrane lipids, or that act on β cells to enhance insulin secretion (3). In this study, Müller and colleagues used a 1-h high-glucose stimulation, but it may be interesting to test other time points to determine the effects of more acute versus chronic glucose exposure. Although FIB-SEM can image only fixed, static cells, the work will complement other studies using super-resolution imaging and live cell microscopy. Aside from these future directions, it is worthwhile to pause and celebrate the present work, which is the first to reconstruct the entire 3D architecture of the microtubule network in a primary mammalian cell during interphase. The movies in the supplement are gorgeous. The work bodes well for the future of FIB-SEM and will stimulate new directions to understand both diabetes physiology and regulated protein secretion.