Proteomic study uncovers molecular principles of single-cell-level phenotypic heterogeneity in lipid storage of Nannochloropsis oceanica

Abstract Background Nannochloropsis oceanica belongs to a large group of photoautotrophic eukaryotic organisms that play important roles in fixation and cycling of atmospheric CO2. Its capability of storing solar energy and carbon dioxide in the form of triacylglycerol (TAG) of up to 60% of total weight under nitrogen deprivation stress sparked interest in its use for biofuel production. Phenotypes varying in lipid accumulation among an N. oceanica population can be disclosed by single-cell analysis/sorting using fluorescence-activated cell sorting (FACS); yet the phenomenon of single cell heterogeneity in an algae population remains to be fully understood at the molecular level. In this study, combination of FACS and proteomics was used for identification, quantification and differentiation of these heterogeneities on the molecular level. Results For N. oceanica cultivated under nitrogen deplete (−N) and replete (+N) conditions, two groups differing in lipid content were distinguished. These differentiations could be recognized on the population as well as the single-cell levels; proteomics uncovered alterations in carbon fixation and flux, photosynthetic machinery, lipid storage and turnover in the populations. Although heterogeneity patterns have been affected by nitrogen supply and cultivation conditions of the N. oceanica populations, differentiation itself seems to be very robust against these factors: cultivation under +N, −N, in shaker bottles, and in a photo-bioreactor all split into two subpopulations. Intriguingly, population heterogeneity resumed after subpopulations were separately recultivated for a second round, refuting the possible development of genetic heterogeneity in the course of sorting and cultivation. Conclusions This work illustrates for the first time the feasibility of combining FACS and (prote)-omics for mechanistic understanding of phenotypic heterogeneity in lipid-producing microalgae. Such combinatorial method can facilitate molecular breeding and design of bioprocesses

Patients with Type 1 Diabetes Treated with Insulin Pumps Need Widely Heterogeneous Basal Rate Profiles Ranging from Negligible to Pronounced Diurnal Variability

Background: Pump-treated patients with type 1 diabetes have widely differing basal insulin infusion profiles. We analyzed consequences of such heterogeneity for glycemic control under fasting conditions. Methods: Data from 339 adult patients with type 1 diabetes on insulin pump therapy undergoing a 24-hour fast (basal rate test) were retrospectively analyzed. Hourly programmed basal insulin infusion rates and plasma glucose concentrations as well as their proportions within, below, or above arbitrarily defined target ranges were assessed for specific periods of the day (eg, 1-7 hours, “dawn” period, 16-19 hours, “dusk” period, reference period 20-1 hours/10-14 hours), by tertiles of a predefined “dawn” index (mean basal insulin infusion rate during the “dawn” divided by the reference periods). Results: The “dawn” index varied interindividually from 0.7 to 4.4. Basal insulin infusion profiles exhibited substantial differences ( P = .011), especially overnight. Despite higher insulin infusion rates at 4 and 6.45 hours, patients with the most pronounced “dawn” phenomenon exhibited higher plasma glucose concentrations at those time points ( P &lt; .012). Patients with a marked “dawn” phenomenon exhibited a lower probability for low (&lt;4.4 mmol/L) and a higher probability of high values (&gt;7.2 mmol/L) during the dawn period (all P values &lt;.01). Conclusions: We observe substantial interindividual heterogeneity in the “dawn” phenomenon. However, widely different empirically derived basal insulin infusion profiles appear appropriate for individual patients, as indicated by similar plasma glucose concentrations, mainly in the target range, during a 24-hour fasting period. </jats:sec

Unklare Lymphadenopathie mit Panzytopenie bei einer Patientin mit rezidivierenden Hypoglykämien

ZusammenfassungEine Patientin wurde aufgrund rezidivierender postprandialer Hypoglykämien nach Roux-en-Y-Magenbypass mit Diazoxid behandelt, nachdem eine Ernährungsumstellung keine Symptomlinderung erzielt hatte. Nach Eindosierung von Diazoxid mit guter Akutverträglichkeit wurde die Patientin entlassen. Eine Woche nach Therapieeinleitung kam es zu einer Lymphadenopathie und Panzytopenie. Es fanden sich keine Hinweise auf das Vorliegen eines Infekts. Nach Absetzen von Diazoxid sistierten die Beschwerden. Unser Fallbericht weist auf seltene unerwünschte hämatologische Arzneimittelwirkungen unter Diazoxid hin.</jats:p

Twenty-Four Hour Fasting (Basal Rate) Tests to Achieve Custom-Tailored, Hour-by-Hour Basal Insulin Infusion Rates in Patients With Type 1 Diabetes Using Insulin Pumps (CSII).

BACKGROUND: Twenty-four hour fasting periods are being used to scrutinize basal insulin infusion rates for pump-treated patients with type 1 diabetes. METHODS: Data from 339 consecutive in-patients with adult type 1 diabetes on insulin pump therapy undergoing a 24-hour fast as a basal rate test were retrospectively analyzed. Hourly programmed basal insulin infusion rates and plasma glucose concentrations within, below, or above arbitrarily defined target ranges were assessed for periods of the day of special interest (eg, 01:00-07:00 am, "dawn" period, 04:00-07:00 pm, and "dusk" period). Statistics: χ2-tests, paired t-tests were used. RESULTS: Basal rates (mean: 0.90 ± 0.02 IU/h) showed circadian variations with peaks corresponding to "dawn" (1.07 ± 0.02 IU/h from 01:00 to 07:00 am) and, less prominently, "dusk" (0.95 ± 0.02 IU/h from 03:00 to 07:00 pm). Individual mean plasma glucose concentrations averaged 6.6 ± 0.1 mmol/L, with 53.1% in the predefined "strict" (4.4-7.2 mmol/L) target range. Interestingly, during the "dawn" period, plasma glucose was significantly higher (by 0.5 ± 0.1 mmol/L [95% confidence interval: 0.3-0.8 mmol/L; P < .0001]) and the odds ratio for hypoglycemia was significantly lower compared to the reference period. INTERPRETATION: Twenty-four hour fasting periods as basal rate tests frequently unravel periods with inappropriate basal insulin infusion rates potentially responsible for fasting hyper- or hypoglycemia. Notably, the higher basal insulin infusion rate found during the "dawn" period seems to be justified and may need to be accentuated.status: publishe

Twenty-Four Hour Fasting (Basal Rate) Tests to Achieve Custom-Tailored, Hour-by-Hour Basal Insulin Infusion Rates in Patients With Type 1 Diabetes Using Insulin Pumps (CSII)

Background: Twenty-four hour fasting periods are being used to scrutinize basal insulin infusion rates for pump-treated patients with type 1 diabetes. Methods: Data from 339 consecutive in-patients with adult type 1 diabetes on insulin pump therapy undergoing a 24-hour fast as a basal rate test were retrospectively analyzed. Hourly programmed basal insulin infusion rates and plasma glucose concentrations within, below, or above arbitrarily defined target ranges were assessed for periods of the day of special interest (eg, 01:00-07:00 am, “dawn” period, 04:00-07:00 pm, and “dusk” period). Statistics: χ2-tests, paired t-tests were used. Results: Basal rates (mean: 0.90 ± 0.02 IU/h) showed circadian variations with peaks corresponding to “dawn” (1.07 ± 0.02 IU/h from 01:00 to 07:00 am) and, less prominently, “dusk” (0.95 ± 0.02 IU/h from 03:00 to 07:00 pm). Individual mean plasma glucose concentrations averaged 6.6 ± 0.1 mmol/L, with 53.1% in the predefined “strict” (4.4-7.2 mmol/L) target range. Interestingly, during the “dawn” period, plasma glucose was significantly higher (by 0.5 ± 0.1 mmol/L [95% confidence interval: 0.3-0.8 mmol/L; P &lt; .0001]) and the odds ratio for hypoglycemia was significantly lower compared to the reference period. Interpretation: Twenty-four hour fasting periods as basal rate tests frequently unravel periods with inappropriate basal insulin infusion rates potentially responsible for fasting hyper- or hypoglycemia. Notably, the higher basal insulin infusion rate found during the “dawn” period seems to be justified and may need to be accentuated. </jats:sec

InsulinPumpSupplement290719 – Supplemental material for Twenty-Four Hour Fasting (Basal Rate) Tests to Achieve Custom-Tailored, Hour-by-Hour Basal Insulin Infusion Rates in Patients With Type 1 Diabetes Using Insulin Pumps (CSII)

Supplemental material, InsulinPumpSupplement290719 for Twenty-Four Hour Fasting (Basal Rate) Tests to Achieve Custom-Tailored, Hour-by-Hour Basal Insulin Infusion Rates in Patients With Type 1 Diabetes Using Insulin Pumps (CSII) by Michael A. Nauck, Anna M. Lindmeyer, Chantal Mathieu and Juris J. Meier in Journal of Diabetes Science and Technology</p

Prediction of Individual Basal Rate Profiles From Patient Characteristics in Type 1 Diabetes on Insulin Pump Therapy

Background: Basal rate profiles in patients with type 1 diabetes on insulin pump therapy are subject to enormous inter-individual heterogeneity. Tools to predict basal rates based on clinical characteristics may facilitate insulin pump therapy. Methods: Data from 339 consecutive in-patients with adult type 1 diabetes on insulin pump therapy were collected. Basal rate tests were performed over 24 hours. A mathematical algorithm to predict individual basal rate profiles was generated by relating the individual insulin demand to selected clinical characteristics in an exploratory cohort of 170 patients. The predicted insulin pump profiles were validated in a confirmatory cohort of 169 patients. Findings: Basal rates (0.27 ± 0.01 IU.d−1.kg−1) showed circadian variations with peaks corresponding to the “dawn” and “dusk” phenomena. Age, gender, duration of pump treatment, body-mass-index, HbA1c, and triacylglycerol concentrations largely predicted the individual basal insulin demand per day (IU/d; exploratory vs prospective cohorts: r2 = 0.518, P &lt; .0001). Model-predicted and actual basal insulin rates were not different (exploratory cohort: Δ 0.1 (95% CI −0.9; 1.0 U/d; P = .95; prospective cohort: Δ −0.5 (95% CI −1.5; 0.6 IU/d; P = .46). Similarly, precise predictions were possible for each hour of the day. Actual and predicted “dawn” index correlated significantly in the exploratory but not in the confirmatory cohort. Interpretation: Clinical characteristics predict 52% of the variation in individual basal rate profiles, including their diurnal fluctuations. The multivariate regression model can be used to initiate or optimize insulin pump treatment in patients with type 1 diabetes. </jats:sec

Whole-cell microtiter plate screening assay for terminal hydroxylation of fatty acids by P450s

A readily available galactose oxidase (GOase) variant was used to develop a whole cell screening assay. This endpoint detection system was applied in a proof-of-concept approach by screening a focussed mutant library. This led to the discovery of the thus far most active P450 Marinobacter aquaeolei mutant catalysing the terminal hydroxylation of fatty acids.</p

Copy number variability of expression plasmids determined by cell sorting and Droplet Digital PCR

BACKGROUND: Plasmids are widely used for molecular cloning or production of proteins in laboratory and industrial settings. Constant modification has brought forth countless plasmid vectors whose characteristics in terms of average plasmid copy number (PCN) and stability are rarely known. The crucial factor determining the PCN is the replication system; most replication systems in use today belong to a small number of different classes and are available through repositories like the Standard European Vector Architecture (SEVA). RESULTS: In this study, the PCN was determined in a set of seven SEVA-based expression plasmids only differing in the replication system. The average PCN for all constructs was determined by Droplet Digital PCR and ranged between 2 and 40 per chromosome in the host organism Escherichia coli. Furthermore, a plasmid-encoded EGFP reporter protein served as a means to assess variability in reporter gene expression on the single cell level. Only cells with one type of plasmid (RSF1010 replication system) showed a high degree of heterogeneity with a clear bimodal distribution of EGFP intensity while the others showed a normal distribution. The heterogeneous RSF1010-carrying cell population and one normally distributed population (ColE1 replication system) were further analyzed by sorting cells of sub-populations selected according to EGFP intensity. For both plasmids, low and highly fluorescent sub-populations showed a remarkable difference in PCN, ranging from 9.2 to 123.4 for ColE1 and from 0.5 to 11.8 for RSF1010, respectively. CONCLUSIONS: The average PCN determined here for a set of standardized plasmids was generally at the lower end of previously reported ranges and not related to the degree of heterogeneity. Further characterization of a heterogeneous and a homogeneous population demonstrated considerable differences in the PCN of sub-populations. We therefore present direct molecular evidence that the average PCN does not represent the true number of plasmid molecules in individual cells. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12934-016-0610-8) contains supplementary material, which is available to authorized users