Design of the cross-over clinical study

The study was conducted at the Department of Endocrinology of Heidelberg University Hospital, and was approved by the local ethics committee (Ethics Committee of the Medical Faculty of Heidelberg: Trial Code Number S-675/2015). The study was registered at ClinicalTrials.gov with identifier NCT02957838. Study participants provided written informed consent.

The study size was designed in consultation with a biometrician, Johannes Krisam (in the Acknowledgements), based on data from a pilot study, and using formulas for cross-over studies from ref. 24. These calculations showed that for reaching a significance of 0.01 and a power of 95%, 10 participants per group are required. We therefore screened 284 outpatients of the Department of Endocrinology (see Supplementary Fig. 1), 108 of which were eligible and thus were contacted. Assuming there would be roughly a 50% drop-out rate, we recruited 20 subjects per group who gave oral consent. In the end 12 healthy controls and 11 type-2-diabetics gave written consent. The recruited type-2 diabetic patients did not require insulin treatment and did not have severe complications yet. Neither the type-2-diabetics nor the control participants suffered from other severe diseases such as cancer or anemia. The baseline characteristics of the groups are provided in Supplementary Data 1–2. Two healthy controls preferred not to repeat the second arm of the cross-over study, but did not withdraw consent concerning data generated in the first round. Hence data from the remaining 10 healthy controls that completed both arms of the study were analyzed.

Basal blood samples were collected at 9 a.m. after subjects had been eating a regular diet, followed by an overnight starvation and no breakfast. The subjects were then asked to follow a low-fat, vegan diet (low C18:0 diet) for 2 days and to maintain a diary of the food and drink they consumed, thereby allowing participants to self-report violations of the diet rules. On the day of the first timecourse, “0 h” blood samples were collected at 9 a.m. after an overnight fast and no breakfast. Immediately afterwards the subjects received a banana milk shake with or without 24 g C18:0 (see below for the recipe). At 12 p.m., the “3 h” blood samples were collected and the subjects then received a standardized low-fat vegan lunch. At 3 p.m., “6 h” blood samples were collected. Each subject underwent the whole procedure twice for the cross-over timecourse, once with the C18:0 milk shake and once with the mock milk shake lacking C18:0, in a randomized order and with a wash-out phase of at least 3 days between experiments. The timecourse intervals were determined based on ref. 20. The timecourse was performed with a maximum of three subjects per day because the blood samples had to be processed and imaged fresh and soon after collection. The blood samples were labeled with codes and only the person who drew the blood samples knew the identity of the samples. The whole study was performed in a double-blind fashion—i.e., the people who processed the samples did not have any information about the samples. After all data were collected and all analyses were performed, the data were unblinded.

Preparation of the banana shakes

For the C18:0 drink, 24 g of C18:0 intended for human consumption (stearic acid, Sigma-Aldrich W303518) were mixed with 100 ml of low-fat milk. This amount of C18:0 was selected by calculating the C18:0 content of a high fat meal19. The mixture was microwaved to emulsify the fatty acid. One small banana was added and the whole mixture was homogenized with a hand blender. The volume was completed to 250 ml with more low-fat milk. The mock drink was prepared the same way without fatty acids. For the C16:0 drink, 21.56 g (an equal molar amount to 24 g of C18:0) of C16:0 intended for human consumption (palmitic acid, Sigma-Aldrich W283207) was added instead. Milkshakes were prepared approximately 90 min before consumption.

Sample collection

Blood was drawn with butterfly needle sets at each timepoint from a different location. Several tubes were filled with different blood amounts for the following purposes: (1) one was filled with 4.5 ml to extract a leukocyte pellet after erythrocyte lysis, which was stored at −80 °C, (2) a smaller EDTA tube (Sarstedt S-Monovette® 2.7 ml K3E) was filled with 1 ml of blood for mitochondrial morphology scoring via fluorescence microscopy, (3) to keep serum samples, 4 ml of blood were drawn into a Sarstedt S-Monovette® 7.5 ml Z tube, then centrifuged at 2500g for 10 min, aliquoted and stored at −80 °C, (4) for analysis of insulin, 2 ml of blood were drawn into a Sarstedt S-Monovette® 7.5 ml Z-Gel tube, and (5) for other serum parameters 2 ml of blood were put into a Sarstedt S-Monovette® 7.5 ml LH-Gel. Both tubes #4 and #5 were submitted to the high-throughput analysis facilities of the Heidelberg University Central Laboratory, which is accredited according to DIN EN ISO 15189. On the “basal” day, an additional Sarstedt S-Monovette® 2.7 ml K3E tube was filled with 2 ml for high throughput cell counting via a Siemens ADVIA 120 Hematology system and measurement of HbA1c by a Biorad Variant II Turbo.

Staining and imaging of neutrophil mitochondrial morphology

Blood was collected into EDTA containing tubes (Sarstedt S-Monovette® 2.7 ml K3E). An aliquot of 100 μL whole blood was put into a 1.7 ml tube and the following antibodies and dyes were added: CD15-FITC (BD Pharmingen 555401, Lot: 5267530, 1:10 dilution), CD16-BV421 (BD Pharmingen 562878, Lot: 6007759, 1:20 dilution), Mitotracker Red (Cell Signaling #9082, 200 nM final) and DRAQ5 (Abcam ab108410, 10 μM final). CD15 and CD16 are neutrophil cell surface markers and DRAQ5 is a nuclear stain. Mitotracker red was used to image mitochondria. Staining was performed at room temperature for 15 min. Afterwards, 10 μL stained blood was put on a glass slide and covered with a coverslip. The resulting smear was immediately visualized with a fluorescence microscope. Importantly, this method allowed us to score mitochondrial morphology within 30 min of blood collection. Mitochondrial morphology of approximately 50 CD15, CD16+ neutrophils per subject per timepoint were scored. Cells containing a single large interconnected network were scored as “fused”, cells containing individual dots were score as “fragmented”, and all other cells were scored as “intermediate”. To ensure consistency of scoring between samples, all blood samples in this paper were scored in a blinded fashion by one person. Four samples were also scored independently by a second person, arriving at qualitatively similar results (Supplementary Fig. 7).

Calculation of mitochondrial fusion factor

The fraction of neutrophils with fragmented, intermediate, and fused mitochondria were calculated and then the following formula was used: mitochondrial fusion factor = 1 × fraction of neutrophils with intermediate mitochondria + 2 × fraction of neutrophils with fused mitochondria.

Statistical analyses

Data sampling: Data from the two healthy subjects who did not complete both arms of the study were not used. Otherwise, for all statistical analyses, all available data were used and none were excluded.

Student t-tests were used to test significance in Figs. 1c–i, 2a–d, 3a, b, 4a–d, Supplementary Fig. 3, Supplementary Fig. 4, Supplementary Fig. 5, and Supplementary Fig. 6f. For all these figures except Fig. 4b–d, this was done using a 2-tailed, paired t-test because the comparisons are between two timepoints for the same subject (i.e., paired). For Fig. 4b–d, a 2-tailed unpaired student’s t-test was used because the comparison is between subjects. For Fig. 1c–h, and Supplementary Fig. 6f, 55–60 neutrophils were scored for mitochondrial morphology per blood sample. These data were used to calculate the percentage of neutrophils in that sample with fragmented, intermediate or fused morphology. These percentages from the various samples were combined to generate the plots shown in figures. For instance, in Fig. 1c at 0 h, the “fragmented” bar represents the average of 21 datapoints, corresponding to the percentage of neutrophils with fragmented mitochondria from the 21 subjects, and the error bars represent the standard deviation of these 21 datapoints. Significance was tested by applying the student t-test to the “fragmented” category, comparing the 3 h or the 6 h timepoints to the 0 h timepoint (i.e., 21 datapoints for the 3 h or the 6 h timepoint, compared to the 21 datapoints for the 0 h timepoint.) For Figs. 1i, 2a–d, and 4a, b, a “mitochondrial fusion factor” was calculated per sample as described above, thereby yielding a single datapoint per sample (shown as individual dots in the figures). The t-tests were then applied to these datapoints.

The significance of the changes seen in Fig. 1c, e, g was confirmed by using simplex plots (Supplementary Fig. 2). Simplex plots allow the depiction of data with multiple variables which sum to a constant. In this case, the fractions of neutrophils with fragmented, intermediate or fused mitochondria from one blood sample sum to 1. In the plots, each individual is color coded with a particular color, which is kept the same across timepoints (Supplementary Fig. 2). With an R package that is described in refs. 25,26, centered planar transformations were applied to map the data isometrically to a 1-dimensional Euclidian vector space, and then a linear mixed effect model was fitted for each composite to test the effect of the drinks (C18:0 vs mock). This method directly assesses the statistical significance of the difference between the C18:0 and the mock drinks in terms of changes in mitochondrial morphology across timepoints. (n = 21 subjects, of which 10 healthy and 11 type-2 diabetic.)

The Mann–Whitney test was used to test for significance in Supplementary Figures 6a,b,g,h and Supplementary Figure 7, since each of these figure panels represents data from a single subject. For each blood sample, 60 neutrophils were scored as follows: 1 (fragmented), 2 (intermediate), and 3 (fused). The non-parametric Mann–Whitney test was then applied in Microsoft Excel to assess the significance in the change in neutrophil score distribution between samples. Hence in these panels only, the statistical test was applied on the distribution of scores of individual neutrophils.

For Figs. 2e–i and 3c, d, correlations and their significance (two-tailed p) were calculated with Pearson’s test in GraphPad Prism.

The significance of the lack of mitochondrial fusion caused by C16:0 was tested as follows. The null-hypothesis to be rejected was that the effect of C16:0 ingestion is non-inferior to that of C18:0 ingestion. C18:0 caused mitochondrial fusion in 19 of the 21 subjects. (Mitochondrial fusion was defined as an increase in the mitochondrial fusion factor (mff) by at least 0.19, which is 1.64 standard deviations of the mitochondrial fusion factors observed at 0 h, corresponding to a false-discovery rate of 5%.) Since 90% of all subjects (19 out of 21) responded to C18:0 ingestion, there is a 10% probability of a subject not fusing their mitochondria upon C18:0 ingestion. If C16:0 behaves like C18:0, we would expect 10% of subjects to not fuse their mitochondria by chance upon C16:0 ingestion. Instead, 5 out of 5 subjects did not fuse their mitochondria after C16:0 ingestion, which has a probability of happening of (10%)5 = 10−5. Hence we reject the null hypothesis that C16:0 causes mitochondrial fusion like C18:0.

Multivariate linear regression analysis was performed with SPSS statistical analysis software with mitochondrial fusion factor as the dependent variable and all parameters shown in Supplementary Data 3 as independent variables using default parameters and confidence interval = 95%.

Quantification of lipids with GC/MS

Lipids were extracted from 400 μL of serum by adding 600 μL of KH 2 PO 4 followed by 1 ml of methanol (Sigma 646377) and finally 3 ml of chloroform (Sigma 650471) in a 7 ml screw top tube (SLS TUB1202). Internal standards were added in the chloroform and were as follows: FFAs, deuterated tridecanoic acid (C13D25O2H, Cambridge Isotopes DLM1392), 20 μg; Triglycerides 1,2,3-Triheptadecanoylglycerol (Sigma), 40 μg; Phospholipids, 1,2-diundecanoyl-sn-glycero-3-phosphocholine (Avanti polar lipids), 40 μg. Samples were vortexed for 2 min then centrifuged for 10 min at 720 g. The lower layer was collected and transferred to a new 7 ml glass tube and dried under nitrogen.

Lipid classes were separated by solid phase extraction. To carry out the solid phase extraction, the lipids were resuspended in 1 ml chloroform and transferred to aminopropyl (NH 2 ) BondElut solid-phase extract columns (Agilent, 12113014). The flowthrough was collected along with two washes of 1 ml chloroform and dried under the nitrogen stream. The flowthrough contained the neutral lipid fraction. Phospholipids were eluted from the column by addition of 2 ml of 60:40 chloroform methanol. Finally FFAs were eluted using 100:2:2 Chloroform:Methanol:Glacial acetic acid. All fractions were dried under nitrogen.

To derivatize the samples into fatty acid methyl esters, 875 μL of a mixture of chloroform (Sigma 650471): methanol (Sigma 646377): boron trifluoride-methanol solution (Sigma 134821) (15:19:1 v/v/v) was added to the dried lipids in 7 ml glass tubes. The tubes were then sealed and incubated in an oven at 80 °C for 90 min. After cooling the samples, 1 ml of hexane (Sigma 34859) and 500 μL of water (Sigma 34877) were added, and the samples were vortexed and centrifuged at 720g at room temperature for 5 min. The upper organic layer was transferred into glass autosampler vials and dried under a nitrogen stream. The samples were reconstituted in 1 ml hexane prior to the gas chromatography analysis.

Gas chromatography was performed on an Agilent 7890B GC using a Thermo Scientific TR-FAME column (length: 30 m, internal diameter: 0.25 mm, film size: 0.25 µm) with helium as carrier gas (1.9 ml/min). FAMEs were detected using a 5977A MSD. Inlet and MSD temperature were set at 230 °C. The oven program temperature steps used were as follows.

The column was held at 100 °C for 2 min, then the temperature was increased to 150 °C at a rate of 25 °C/min. The temperature was further increased to 162 °C at a rate of 2.5 °C/min, with a hold time of 3.8 min. Subsequently, the temperature was increased to 173 °C at a 4.5 °C/min rate, followed by a hold time of 5 min. The column temperature was further increased to 210 °C with a 5 °C/min rate. Finally, the temperature was increased to 230 °C with a 40°C/min rate, followed by a hold time of 0.5 min. The transfer line temperature was set at 240 °C, and the ion source was at 250 °C, operating at 70 eV for electron ionization (EI). The detector was initiated after 240 s, and full scan spectra were collected over a range of 50–650 m/z.

To identify the FAME peaks, retention times of peaks in the samples were compared with those in external standards (Restek 35077 Food industry FAME mix and Supelco 46904 Vaccenic Methyl ester) using MS Quantitative Analysis (Agilent). The areas of specific ions for each fatty acid were used for quantification, with the background subtracted to the values of blank samples. The quantity of a given fatty acid methyl ester was determined using a standard curve generated using the external standard and normalized to the relevant internal standard for the given fraction. Data is expressed as molar%, which was calculated by dividing any individual fatty acid methyl ester by the all the detected fatty acids in a given sample.

Quantification of acylcarnitines

Acylcarnitines were determined in serum by electrospray ionization tandem mass spectrometry (ESI-MS/MS) according to a modified method as previously described27, using a Quattro Ultima triple quadrupole mass spectrometer (Micromass, Manchester, UK) equipped with an electrospray ion source and a Micromass MassLynx data system. In particular, 5 µl of plasma were placed on a 4.7 mm filter paper punch, dried at room temperature overnight and extracted with 100 µl of deuterium-labeled standard solution in methanol27.

Other blood and serum measurements

Methylglyoxal was measured according to ref. 28. Human serum hepcidin was measured using the “Bioactive hepcidin 25 ELISA kit” (DRG International) following manufacturer’s instructions. The hepcidin concentration was extrapolated against a standard curve by using the four parameters logistic model of the Graphpad Prism v7 software. All other blood parameters were measured by the clinical analysis facilities of the Heidelberg University Hospital Central Laboratory, which is accredited according to DIN EN ISO 15189.

Data availability

The authors declare that the data supporting the findings of this study are available within the paper and its supplementary information files.