Transformation of multicolour flow cytometry data with OTflow prevents misleading multivariate analysis results and incorrect immunological conclusions.

The rapid evolution of the flow cytometry field, currently allowing the measurement of 30-50 parameters per cell, has led to a marked increase in deep multivariate information. Manual gating is insufficient to extract all this information. Therefore, multivariate analysis (MVA) methods have been developed to extract information and efficiently analyze the high-density multicolour flow cytometry (MFC) data. To aid interpretation, MFC data are often logarithmically transformed before MVA. We studied the consequences of different transformations of flow cytometry data in datasets containing negative intensities caused by background subtractions and spreading error, as logarithmic transformation of negative data is impossible. Transformations such as logicle or hyperbolic arcsine transformations allow linearity around zero, whereas higher (positive and negative) intensities are logarithmically transformed. To define the linear range, a parameter (or cofactor) must be chosen. We show how the chosen transformation parameter has great impact on the MVA results. In some cases, peak splitting is observed, producing two distributions around zero in an actual homogeneous population. This may be misinterpreted as the presence of multiple cell populations. Moreover, when performing arbitrary transformation before MVA analysis, biologically relevant and statistically significant information might be missed. We present a new algorithm, Optimal Transformation for flow cytometry data (OTflow), which uses various statistical methods to optimally choose the parameter of the transformation and prevent artifacts such as peak splitting. Arbitrary or unconsidered transformation can lead to wrong conclusions for the MVA cluster methods, dimensionality reduction methods, and classification methods. We recommend transformation of flow cytometry data by using OTflow-defined parameters estimated per channel, in order to prevent peak splitting and other artifacts in the data.

The trans-activator RNF12 and cis-acting elements effectuate X chromosome inactivation independent of X-pairing.

X chromosome inactivation (XCI) in female placental mammals is a vital mechanism for dosage compensation between X-linked and autosomal genes. XCI starts with activation of Xist and silencing of the negative regulator Tsix, followed by cis spreading of Xist RNA over the future inactive X chromosome (Xi). Here, we show that XCI does not require physical contact between the two X chromosomes (X-pairing) but is regulated by trans-acting diffusible factors. We found that the X-encoded trans-acting and dose-dependent XCI-activator RNF12 acts in concert with the cis-regulatory region containing Jpx, Ftx, and Xpr to activate Xist and to overcome repression by Tsix. RNF12 acts at two subsequent steps; two active copies of Rnf12 drive initiation of XCI, and one copy needs to remain active to maintain XCI toward establishment of the Xi. This two-step mechanism ensures that XCI is very robust and fine-tuned, preventing XCI of both X chromosomes.

A field-applicable method for flow cytometric analysis of granulocyte activation: Cryopreservation of fixed granulocytes.

Upon activation granulocytes upregulate several adhesion molecules (CD11b) and granule proteins (CD35, CD66b) and shed surface l-selectin (CD62L). These changes in expression, as assessed by flow cytometry, can be used as markers for activation. Whereas these markers are usually studied in fresh blood samples, a new method is required when samples are collected at a field site with no direct access to a flow cytometer. Therefore, we developed and tested a field-applicable method in which fixed leukocytes were cryopreserved. Using this method, the intensity of granulocyte activation markers was compared to samples that were either stained fresh, or fixed prior to staining but not cryopreserved. In addition, the response to an in vitro stimulation with fMLF was determined. While we observed differences in marker intensities when comparing fresh and fixed granulocytes, similar intensities were found between fixed cells that had been cryopreserved and fixed cells that did not undergo cryopreservation. Although fixation using FACS lysing solution might lead to membrane permeabilization, activation markers, and the responsiveness to fMLF or eotaxin could still be clearly measured. This method will, therefore, enable future studies of granulocyte activation in settings with limited resources and will allow simultaneous analysis of samples collected at different time points. © 2018 International Society for Advancement of Cytometry.

Kinetics of Neutrophil Subsets in Acute, Subacute, and Chronic Inflammation.

At homeostasis the vast majority of neutrophils in the circulation expresses CD16 and CD62L within a narrow expression range, but this quickly changes in disease. Little is known regarding the changes in kinetics of neutrophils phenotypes in inflammatory conditions. During acute inflammation more heterogeneity was found, characterized by an increase in CD16dim banded neutrophils. These cells were probably released from the bone marrow (left shift). Acute inflammation induced by human experimental endotoxemia (LPS model) was additionally accompanied by an immediate increase in a CD62Llow neutrophil population, which was not as explicit after injury/trauma induced acute inflammation. The situation in sub-acute inflammation was more complex. CD62Llow neutrophils appeared in the peripheral blood several days (>3 days) after trauma with a peak after 10 days. A similar situation was found in the blood of COVID-19 patients returning from the ICU. Sorted CD16low and CD62Llow subsets from trauma and COVID-19 patients displayed the same nuclear characteristics as found after experimental endotoxemia. In diseases associated with chronic inflammation (stable COPD and treatment naive HIV) no increases in CD16low or CD62Llow neutrophils were found in the peripheral blood. All neutrophil subsets were present in the bone marrow during homeostasis. After LPS rechallenge, these subsets failed to appear in the circulation, but continued to be present in the bone marrow, suggesting the absence of recruitment signals. Because the subsets were reported to have different functionalities, these results on the kinetics of neutrophil subsets in a range of inflammatory conditions contribute to our understanding on the role of neutrophils in health and disease.

Multi-set Pre-processing of Multicolor Flow Cytometry Data.

Flow Cytometry is an analytical technology to simultaneously measure multiple markers per single cell. Ten thousands to millions of single cells can be measured per sample and each sample may contain a different number of cells. All samples may be bundled together, leading to a 'multi-set' structure. Many multivariate methods have been developed for Flow Cytometry data but none of them considers this structure in their quantitative handling of the data. The standard pre-processing used by existing multivariate methods provides models mainly influenced by the samples with more cells, while such a model should provide a balanced view of the biomedical information within all measurements. We propose an alternative 'multi-set' preprocessing that corrects for the difference in number of cells measured, balancing the relative importance of each multi-cell sample in the data while using all data collected from these expensive analyses. Moreover, one case example shows how multi-set pre-processing may benefit removal of undesired measurement-to-measurement variability and another where class-based multi-set pre-processing enhances the studied response upon comparison to the control reference samples. Our results show that adjusting data analysis algorithms to consider this multi-set structure may greatly benefit immunological insight and classification performance of Flow Cytometry data.

A novel data fusion method for the effective analysis of multiple panels of flow cytometry data.

Multicolour flow cytometry (MFC) is used to measure multiple cellular markers at the single-cell level. Cellular markers may be coloured with different panels of fluorescently-labelled antibodies to enable cell identification or the detection of activated cells in pre-defined, 'gated' specific cell subsets. The number of markers that can be used per measurement is technologically limited however, requiring every panel to be analysed in a separate aliquot measurement. The combined analyses of these dedicated panels may enhance the predictive ability of these measurements and could enrich the interpretation of the immunological information. Here we introduce a fusion method for MFC data, based on DAMACY (Discriminant Analysis of Multi-Aspect Cytometry data), which can combine information from complementary panels. This approach leads to both enhanced predictions and clearer interpretations in comparison with the analysis of separate measurements. We illustrate this method using two datasets: the response of neutrophils evoked by a systemic endotoxin challenge and the activated immune status of the innate cells, T cells and B cells in obese versus lean individuals. The data fusion approach was able to detect cells that do not individually show a difference between clinical phenotypes but do play a role in combination with other cells.

Trovafloxacin-Induced Liver Injury: Lack in Regulation of Inflammation by Inhibition of Nucleotide Release and Neutrophil Movement.

The fluoroquinolone trovafloxacin (TVX) is associated with a high risk of drug-induced liver injury (DILI). Although part of the liver damage by TVX+TNF relies on neutrophils, we have recently demonstrated that liver recruitment of monocytes and neutrophils is delayed by TVX. Here we show that the delayed leukocyte recruitment is caused by a combination of effects which are linked to the capacity of TVX to block the hemichannel pannexin 1. TVX inhibited find-me signal release in apoptotic HepG2 hepatocytes, decelerated freshly isolated human neutrophils toward IL-8 and f-MLF, and decreased the liver expression of ICAM-1. In blood of TVX+TNF-treated mice, we observed an accumulation of activated neutrophils despite an increased MIP-2 release by the liver. Depletion of monocytes and neutrophils caused increased serum concentrations of TNF, IL-6, and MIP-2 in TVX-treated mice as well as in mice treated with the fluoroquinolone levofloxacin, known to have a lower DILI-inducing profile. This supports the idea that early leukocyte recruitment regulates inflammation. In conclusion, disrupted regulation by leukocytes appears to constitute a fundamental step in the onset of TVX-induced liver injury, acting in concert with the capability of TVX to induce hepatocyte cell death. Interference of leukocyte-mediated regulation of inflammation represents a novel mechanism to explain the onset of DILI.

Submaximal heart rate seems inadequate to prescribe and monitor intensified training.

The aim of this study is to investigate whether the change in (sub)maximal heart rate after intensified training is associated with the change in performance. Thirty subjects were recruited who performed cardiopulmonary exercise tests to exhaustion 2 weeks before (pre), 1 week after (post) and 5 weeks after (follow-up) an 8-day non-competitive amateur cycling event (TFL). The exercise volume during the TFL was 7.7 fold the volume during the preparation period. Heart rate and cardiopulmonary parameters were obtained at standardised absolute submaximal workloads (low, medium and high intensity) and at peak level each test. Subjects were classified as functionally overreached (FOR) or acute fatigued (AF) based on the change in performance. No differences between FOR and AF were observed for heart rate (P = .51). On total group level (AF + FOR), post-TFL heart rate decreased significantly at low (-4.4 beats·min-1, 95% CI [-8.7, -0.1]) and medium (-5.5 beats·min-1 [-8.5, -2.4]), but not at high intensity. Peak heart rate decreased -3.4 beats·min-1 [-6.1, -0.7]. O2pulse was on average 0.49 ml O2·beat-1 [0.09, 0.89] higher at all intensities after intensified training. No changes in ⩒O2 (P = .44) or the ventilatory threshold (P = .21) were observed. Pearson's correlation coefficients revealed negative associations between heart rate and O2pulse at low (r = -.56, P < .01) and medium intensity (r = -.54, P < .01), but not with ⩒O2 or any other submaximal parameter. (Sub)maximal heart rate decreased after the TFL. However, this decrease is unrelated to the change in performance. Therefore, heart rate seems inadequate to prescribe and monitor intensified training.

Changes in Choice Reaction Time During and After 8 Days Exhaustive Cycling Are Not Related to Changes in Physical Performance.

PURPOSE: Reaction time has been proposed as a training monitoring tool, but to date, results are equivocal. Therefore, it was investigated whether reaction time can be used as a monitoring tool to establish overreaching. METHODS: The study included 30 subjects (11 females and 19 males, age: 40.8 [10.8] years, VO2max: 51.8 [6.3] mL/kg/min) who participated in an 8-day cycling event. The external exercise load increased approximately 900% compared with the preparation period. Performance was measured before and after the event using a maximal incremental cycling test. Subjects with decreased performance after the event were classified as functionally overreached (FOR) and others as acutely fatigued (AF). A choice reaction time test was performed 2 weeks before (pre), 1 week after (post), and 5 weeks after (follow-up), as well as at the start and end of the event. RESULTS: A total of 14 subjects were classified as AF and 14 as FOR (2 subjects were excluded). During the event, reaction time at the end was 68 ms (95% confidence interval, 46-89) faster than at the start. Reaction time post event was 41 ms (95% confidence interval, 12-71) faster than pre event and follow-up was 55 ms faster (95% confidence interval, 26-83). The time by class interaction was not significant during (P = .26) and after (P = .43) the event. Correlations between physical performance and reaction time were not significant (all Ps > .30). CONCLUSIONS: No differences in choice reaction time between AF and FOR subjects were observed. It is suggested that choice reaction time is not valid for early detection of overreaching in the field.

Automated flow cytometric identification of disease-specific cells by the ECLIPSE algorithm.

Multicolor Flow Cytometry (MFC)-based gating allows the selection of cellular (pheno)types based on their unique marker expression. Current manual gating practice is highly subjective and may remove relevant information to preclude discovery of cell populations with specific co-expression of multiple markers. Only multivariate approaches can extract such aspects of cell variability from multi-dimensional MFC data. We describe the novel method ECLIPSE (Elimination of Cells Lying in Patterns Similar to Endogeneity) to identify and characterize aberrant cells present in individuals out of homeostasis. ECLIPSE combines dimensionality reduction by Simultaneous Component Analysis with Kernel Density Estimates. A Difference between Densities (DbD) is used to eliminate cells in responder samples that overlap in marker expression with cells of controls. Thereby, subsequent data analyses focus on the immune response-specific cells, leading to more informative and focused models. To prove the power of ECLIPSE, we applied the method to study two distinct datasets: the in vivo neutrophil response induced by systemic endotoxin challenge and in studying the heterogeneous immune-response of asthmatics. ECLIPSE described the well-characterized common response in the LPS challenge insightfully, while identifying slight differences between responders. Also, ECLIPSE enabled characterization of the immune response associated to asthma, where the co-expressions between all markers were used to stratify patients according to disease-specific cell profiles.

Multi-dimensional flow cytometry analysis reveals increasing changes in the systemic neutrophil compartment during seven consecutive days of endurance exercise.

Endurance exercise is associated with a transient increase in neutrophil counts in the peripheral blood. Here we investigate the impact of intensified endurance exercise on the neutrophil compartment. We hypothesized that intensified endurance exercise leads to mobilization of neutrophil subsets, which are normally absent in the blood. Furthermore, we followed the potential build-up of neutrophil activation and the impact on overnight recovery of the neutrophil compartment during a seven-day cycling tour. The neutrophil compartment was studied in 28 healthy amateur cyclists participating in an eight-day strenuous cycling tour. Blood samples were taken at baseline, after 4 days and after 7 days of cycling. The neutrophil compartment was analyzed in terms of numbers and its phenotype by deep phenotyping of flow cytometry data with the multi-dimensional analysis method FLOOD. Repeated endurance exercise led to a gradual increase in total neutrophil counts over the days leading to a 1.26 fold-increase (95%CI 1.01-1.51 p = 0.0431) in the morning of day 8. Flow cytometric measurements revealed the appearance of 2 additional neutrophil subsets: CD16brightCD62Ldim and CD16dimCD62Lbright. A complex change in neutrophil phenotypes was present characterized by decreased expression of both CD11b and CD62L and marked increased expression of LAIR-1, VLA-4 and CBRM1/5. The changes in expression were found on all neutrophils present in the blood. Strikingly, in strong contrast to our findings during acute inflammation evoked by LPS challenge, these neutrophils did not upregulate classical degranulation markers. In fact, our FLOOD analysis revealed that the exercise induced neutrophil phenotype did not overlap with the neutrophil subsets arising upon acute inflammation. In conclusion, during multiple days of endurance exercise the neutrophil compartment does not regain homeostasis overnight. Thereby our study supports the concept of a build-up of inflammatory cues during repeated endurance exercise training, causing a prolonged change of the systemic neutrophil compartment.

Novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype.

Multicolour Flow Cytometry (MFC) produces multidimensional analytical data on the quantitative expression of multiple markers on single cells. This data contains invaluable biomedical information on (1) the marker expressions per cell, (2) the variation in such expression across cells, (3) the variability of cell marker expression across samples that (4) may vary systematically between cells collected from donors and patients. Current conventional and even advanced data analysis methods for MFC data explore only a subset of these levels. The Discriminant Analysis of MultiAspect CYtometry (DAMACY) we present here provides a comprehensive view on health and disease responses by integrating all four levels. We validate DAMACY by using three distinct datasets: in vivo response of neutrophils evoked by systemic endotoxin challenge, the clonal response of leukocytes in bone marrow of acute myeloid leukaemia (AML) patients, and the complex immune response in blood of asthmatics. DAMACY provided good accuracy 91-100% in the discrimination between health and disease, on par with literature values. Additionally, the method provides figures that give insight into the marker expression and cell variability for more in-depth interpretation, that can benefit both physicians and biomedical researchers to better diagnose and monitor diseases that are reflected by changes in blood leukocytes.

Prediction of Functional Overreaching From Subjective Fatigue and Readiness to Train After Only 3 Days of Cycling.

PURPOSE: To investigate whether monitoring of easily measurable stressors and symptoms can be used to distinguish early between acute fatigue (AF) and functional overreaching (FOR). METHODS: The study included 30 subjects (11 female, 19 male; age 40.8 ± 10.8 y, VO2max 51.8 ± 6.3 mL · kg-1 · min-1) who participated in an 8-d cycling event over 1300 km with 18,500 climbing meters. Performance was measured before and after the event using a maximal incremental test. Subjects with decreased performance after the event were classified as FOR, others as AF. Mental and physical well-being, internal training load, resting heart rate, temperature, and mood were measured daily during the event. Differences between AF and FOR were analyzed using mixed-model ANOVAs. Logistic regression was used to determine the best predictors of FOR after 3 and 6 d of cycling. RESULTS: Fifteen subjects were classified as FOR and 14 as AF (1 excluded). Although total group changes were observed during the event, no differences between AF and FOR were found for individual monitoring parameters. The combination of questionnaire-based changes in fatigue and readiness to train after 3 d cycling correctly predicted 78% of the subjects as AF or FOR (sensitivity = 79%, specificity = 77%). CONCLUSIONS: Monitoring changes in fatigue and readiness to train, using simple visual analog scales, can be used to identify subjects likely to become FOR after only 3 d of cycling. Hence, we encourage athlete support staff to monitor not only fatigue but also the subjective integrated mental and physical readiness to perform.