Automated Flow Cytometry Research Articles

Integration of a fully automated flow cytometry system with high robustness into a Screening Station

In recent years, there has been an increasing demand for the detection of rare cells in drug discovery research, such as cells that have differentiated off-purpose or are required for immunogenicity evaluation. Since detection and quantification limits depend on the robustness of the experiment, inter-human differences in technique have a significant impact on the performance of the assay system. Here, we integrated flow cytometry into a cell experiment platform, Screening Station, to construct a robust assay system, examined each step of the flow cytometric pretreatment using Jurkat cells, and finally evaluated the overall assay performance. Cell detection rate when the experiment was performed manually was 48.8 % ± 5.7 % (CV=11.6 %) versus 73.7 %±2.0 % (CV=2.8 %) with the automated method. To further clarify the analytical performance of the automated method, 1–100 PD-1 expressing Jurkat cells were spiked with 1 × 105 Jurkat cells, and the lower limit of detection, linearity, and CV% were evaluated. Average detection rate was 69 %, decision count was 0.985, and lower limit of detection was 4 cells (0.004 %). We evaluated the CV% value of the number of detected cells per spiked cell and found our system to be highly robust, approximating a binomial distribution with a 69 % recovery rate. In conclusion, we have integrated the Novocyte flow cytometry system into an automated experimental platform, Screening Station, to create a fully automated flow cytometric assay system with high robustness. Our platform can fulfill the technology needs of drug discovery for rare cell detection, which have intensified in recent years.

Limited impact of traumatic brain injury on the post-traumatic inflammatory cellular response.

Trauma triggers a systemic inflammatory cellular response due to tissue damage, potentially leading to a secondary immune deficiency. Trauma severity is quantified by the Injury Severity Score (ISS). Severe Traumatic Brain Injury (TBI) is associated with high ISSs due to high lethality, despite limited tissue damage. Therefore, ISS might overestimate the post-traumatic inflammatory cellular response. This study investigated the effect of TBI on the occurrence of different systemic neutrophil phenotypes as alternative read-out for systemic inflammation. A single-center retrospective cohort study was conducted at a level-1 trauma center. Patients aged ≥ 18 years, admitted between 01-03-2021-01-11-2022 and providing a diagnostic blood sample were included. Four groups were created: isolated TBI, isolated non-TBI, multitrauma TBI and multitrauma non-TBI. Primary outcome was occurrence of different neutrophil phenotypes determined by automated flow cytometry. Secondary outcome was infectious complications. In total, 404 patients were included. TBI and non-TBI patients demonstrated similar occurrences of different neutrophil phenotypes. However, isolated TBI patients had higher ISSs than their isolated non-TBI controls who suffered similar post-traumatic inflammatory cellular responses. Regardless of the type of injury, patients exhibiting higher systemic inflammation had a high infection risk. When TBI is involved, ISS tends to be higher compared to similar patients in the absence of TBI. However, TBI patients did not demonstrate an increased inflammatory cellular response compared to non-TBI patients. Therefore, TBI does not add much to the inflammatory cellular response in trauma patients. The degree of the inflammatory response was related to the incidence of infectious complications.

Correlation between peripheral immature platelet level and coronary immature platelet levels in coronary artery disease: an observational study in cardiac referral centre in East Java, Indonesia.

To investigate the correlation between peripheral and coronary immature platelet, and factors that may predict coronary immature platelet levels. The cross-sectional, observational, analytical study was conducted at the Cardiovascular Diagnostic and Intervention Centre of Dr Soetomo General Academic Hospital, Surabaya, Indonesia, from November 2017 to January 2018, and comprised patients of either gender with coronary artery disease. Peripheral and coronary blood samples were retrieved during coronary catheterisation. Immature platelet fraction was acquired by examining whole blood samples analysed through automated flow cytometry. Relationship between peripheral and coronary immature platelet fractions and counts were analysed using parametric correlation test, followed by linear regression analysis model of variables that influenced coronary immature platelet fraction. The statistical analysis was carried out using SPSS Statistics for Windows, Version 25.0 (IBM Corp, Armonk, NY, USA). Of the 70 patients, 55(78.6%) were males and 15(21.4%) were females. The overall mean age was 57±5.32 years. There were 35(50%) patients with a history of smoking, and 34(48.6%) had hypertension and dyslipidaemia. Mean peripheral immature platelet fraction was 3.86±1.84% and mean coronary immature platelet fraction was 3.63±1.7%. There was a robust positive and significant correlation (r=0.882; p<0.001) between immature platelet levels in peripheral and coronary blood. Peripheral immature platelet and glycated haemoglobin >7.5 were independent predictors of coronary immature platelet (p=0.001). There was a strong correlation between immature platelet levels in peripheral and coronary blood.

New automation-friendly 96-well plate ready-to-use 8-color dry antibody panel for basic phenotyping of human whole blood and peripheral blood mononuclear cells using flow cytometry

Abstract Automation-friendly 96-well plate flow cytometry solutions are ideal for pharmaceutical, academic, and CRO laboratories that perform testing on large numbers of samples and/or large number of test conditions. Our ready-to-use pre-formulated dry antibody panel in 96-well plate format provide researchers all the reagents within the wells of the plate where the test is conducted in a stable dry format, resulting in dependable reagent performance and reduction of manual pipetting steps with the added benefit of time and material (reagent and sample) savings. In addition, the 96-well plate format is compatible with automated liquid handlers for walk-away flexibility and higher-throughput sample processing. Here we show flow cytometry data for both whole blood and PBMC samples stained with the first ready-to-use DURAClone IM Phenotyping BASIC plate (RUO) in a shallow 96-well plate containing a dry reagent antibody panel to identify major lymphocyte and monocyte subpopulations for the following markers: CD45, CD16, CD56, CD19, CD14, CD3, CD4 and CD8. Processing of whole blood samples using the shallow 96-well plate format was achieved using FLEXLyse, a lysing solution with low volume ratio of lysis/whole blood, applicable for no-wash and wash protocols. Our experiments were performed using automation on the Biomek i7 liquid handling automated workstation integrated with a CytoFLEX LX flow cytometer and microplate centrifuge demonstrating a fully automated flow cytometry workflow.

Assessment of CD4, CD8 and White Cell Parameters Amongst HIV Seronegative Pregnant Subjects in Port Harcourt, Nigeria

Pregnancy involves maternal immunological adjustments to accommodate the fetus and maintain a strong immune defense against potential pathogens. The present study evaluated the changes in CD4, CD8, white blood cell (WBC) and total lymphocyte count (TLC) amongst HIV seronegative pregnant subjects in Port Harcourt, Nigeria. A total of 302 female subjects (18-39 years) were recruited for the study. They consisted of 205 pregnant subjects and 97 non-pregnant subjects which served as the control. All subjects were screened for HIV type 1 and type 2 using standard test kits. Total and differential white blood cell counts were determined using a haematology auto analyzer while the total lymphocyte count (TLC) was obtained by multiplying total white blood cell count (TWC) with percentage lymphocyte count. The CD4 and CD8 cell counts were analyzed using the automated flow cytometry analyzer while the CD4:CD8 cell count ratio was obtained by dividing the CD4 cell count value by that of CD8. The result of the study shows a statistically significant decrease in CD4 and CD8 cell counts, lymphocyte and total lymphocyte counts and an increase in neutrophil count in all the trimesters of pregnancy when compared to the non-pregnant control (p&amp;lt;0.05). Also, there was a significant increase in WBC during the third trimester and a similar decrease in monocyte count in the first and third trimesters of pregnancy. The evidence from the present study concludes that pregnancy modifies the maternal immune response to ensure fetal survival and the protection of the mother from invading pathogens as reported in the increase in total WBC, neutrophil and monocyte counts and a reduction in TLC, CD4 and CD8 counts. The study recommends routine assessments of these crucial cellular immune markers for pregnant women during antenatal visits.

Flow Cytometry as an Alternative to Microscopy for the Differentiation of BAL Fluid Leukocytes

Microscopy is currently the gold standard to differentiate BAL fluid (BALF) leukocytes. However, local expertise for microscopic BALF leukocyte differentiation is often unavailable in clinical practice. Can automated flow cytometry be used instead of microscopy to differentiate BALF leukocytes? A new automated flow cytometric method for BALF leukocyte differentiation, using four antibodies (anti-CD45, anti-CD66b, anti-HLA-DR, anti-CD52) given to human BALF in one tube, was developed and prospectively validated in 745 unselected subsequent BALF samples from patients with interstitial lung diseases (455 patients), infectious diseases (196 patients), and other diseases (94 patients). Flow cytometry and traditional microscopy were performed by separate investigators in a double-anonymized fashion. Results were compared using Spearman correlation, Deming regression, and Bland-Altman analysis. There was a strong correlation between flow cytometric and microscopic results regarding macrophage/monocyte, lymphocyte, eosinophil, and neutrophil percentages in BALF (P< .001 for all leukocyte subpopulations). Bland-Altman analyses showed that the mean differences between the methods were≤ 2%for all four cell types. Flow cytometric results differed less than 20%from microscopic results in more than 95%of all samples. Subgroup analyses confirmed that these results were independent from total leukocyte counts in BALF. We report, to our knowledge, the first validated flow cytometric method for BALF leukocyte differentiation, which can be used in clinical settings where local expertise for microscopic analysis is unavailable and which can be combined easily with lymphocyte surface marker analysis.

Value of Reticulocyte Count, Absolute Reticulocyte Count and Platelet Count for Bone Marrow Recovery Status on Remission Induction Phase

Reticulocyte count performed on a supravitally stained blood film is a initial and common laboratory method of determining early hematological recovery. This method is rapidly replaced by automated flow cytometry methods which have the advantage of much greater precision, before other test become positive after chemotherapy. A prospective observational study was carried out in the Department of Laboratory Medicine in collaboration with Paediatric Haematology and Oncology, Bangabandhu Sheikh Mujib Medical University during a period of one year to evaluate the bone marrow recovery in children with acute lymphoblastic leukemia by automated reticulocyte analysis over platelet count. Total fifty patients were enrolled in this study on remission induction phase. All patients were between 8 months to 15 years’ age range with a mean age of 5.5 ± 3.2. At the end of the study out of 50 cases, Ret% and Abs ret count showed early recovery in a median of 6 days before the platelet count recovery and concluded that reticulocyte parameter showed earlier haematopoietic recovery than the platelet count recovery.

Identification of neutrophil phenotype categories in geriatric hip fracture patients aids in personalized medicine.

The number of geriatric hip fracture patients is high and expected to rise in the coming years, and many are frail and at risk for adverse outcomes. Early identification of high-risk patients is crucial to balance treatment and optimize outcome, but remains challenging. Previous research in patients with multitrauma suggested that neutrophil phenotype analysis could aid in early identification of high-risk patients. This pilot study investigated the feasibility and clinical value of neutrophil phenotype analysis in geriatric patients with a hip fracture. A prospective study was conducted in a regional teaching hospital in the Netherlands. At the emergency department, blood samples were collected from geriatric patients with a hip fracture and analyzed using automated flow cytometry. Flow cytometry data were processed using an automated clustering algorithm. Neutrophil activation data were compared with a healthy control cohort. Neutrophil phenotype categories were assessed based on two-dimensional visual assessment of CD16/CD62L expression. Blood samples from 45 geriatric patients with a hip fracture were included. Neutrophils showed an increased activation profile and decreased responsiveness to formyl peptides when compared to healthy controls. The neutrophil phenotype of all patients was categorized. The incidence of severe adverse outcome was significantly different between the different categories (P = 0.0331). Moreover, patients with neutrophil phenotype category 0 developed no severe adverse outcomes. Using point-of-care fully automated flow cytometry to analyze the neutrophil compartment in geriatric hip fracture patients is feasible and holds clinical value in determining patients at risk for adverse outcome. This study is a first step toward immuno-based precision medicine for identifying geriatric hip fracture patients that are deemed fit for surgery.

Can Haematological Parameters Discriminate COVID-19 from Influenza?

Symptoms of COVID-19 are similar to the influenza virus, but because treatments and prognoses are different, it is important to accurately and rapidly differentiate these diseases. The aim of this study was to evaluate whether the analysis of complete blood count (CBC), including cellular population (CPD) data of leukocytes and automated flow cytometry analysis, could discriminate these pathologies. In total, 350 patients with COVID-19 and 102 patients with influenza were included between September 2021 and April 2022 in the tertiary hospital of Suresnes (France). Platelets were lower in patients with influenza than in patients with COVID-19, whereas the CD16pos monocyte count and the ratio of the CD16pos monocytes/total monocyte count were higher. Significant differences were observed for 9/56 CPD of COVID-19 and flu patients. A logistic regression model with 17 parameters, including among them 11 CPD, the haemoglobin level, the haematocrit, the red cell distribution width, and B-lymphocyte and CD16pos monocyte levels, discriminates COVID-19 patients from flu patients. The sensitivity and efficiency of the model were 96.2 and 86.6%, respectively, with an area under the curve of 0.862. Classical parameters of CBC are very similar among the three infections, but CPD, CD16pos monocytes, and B-lymphocyte levels can discriminate patients with COVID-19.

Development of a novel medium throughput flow-cytometry based micro-neutralisation test for SARS-CoV-2 with applications in clinical vaccine trials and antibody screening.

Quantifying neutralising capacity of circulating SARS-COV-2 antibodies is critical in evaluating protective humoral immune responses generated post-infection/post-vaccination. Here we describe a novel medium-throughput flow cytometry-based micro-neutralisation test to evaluate Neutralising Antibody (NAb) responses against live SARS-CoV-2 Wild Type and Variants of Concern (VOC) in convalescent/vaccinated populations. Flow Cytometry-Based Micro-Neutralisation Test (Micro-NT) was performed in 96-well plates using clinical isolates WT-B, WT-B.1.177.18 and/or VOCs Beta and Omicron. Plasma samples (All Ireland Infectious Diseases (AIID) Cohort) were serially diluted (8 points, half-log) from 1:20 and pre-incubated with SARS-CoV-2 (1h, 37°C). Virus-plasma mixture were added onto Vero E6 or Vero E6/TMPRSS2 cells for 18h. Percentage infected cells was analysed by automated flow cytometry following trypsinisation, fixation and SARS-CoV-2 Nucleoprotein intracellular staining. Half-maximal Neutralisation Titres (NT50) were determined using non-linear regression. Our assay was compared to Plaque Reduction Neutralisation Test (PRNT) and validated against the First WHO International Standard for anti-SARS-CoV-2 immunoglobulin. Both Micro-NT and PRNT achieved comparable NT50 values. Further validation showed adequate correlation with PRNT using a panel of secondary standards of clinical convalescent and vaccinated plasma samples. We found the assay to be reproducible through measuring both repeatability and intermediate precision. Screening 190 convalescent samples and 11 COVID-19 naive controls (AIID cohort) we demonstrated that Micro-NT has broad dynamic range differentiating NT50s <1/20 to >1/5000. We could also characterise immune-escape VOC Beta and Omicron BA.5, achieving fold-reductions in neutralising capacity similar to those published. Our flow cytometry-based Micro-NT is a robust and reliable assay to quantify NAb titres, and has been selected as an endpoint in clinical trials.

B-142 Development and Clinical Validation of Artificial Intelligence Assisted Flow Cytometry Diagnosis for Acuteleukemia

Abstract Background Flow cytometry is one of the most commonly used diagnostic tools in hematopathology. Manual flow cytometry data analysis is vulnerable to substantial inter-operator variation and typically takes a technologist 20 min to analyze a case. In the last decade, artificial intelligence (AI) technology has advanced dramatically and become widely used in image processing. Previously, we created an AI-assisted workflow for classifying white blood cell subsets in peripheral blood. The goal of this study is to evaluate the automated flow cytometry analysis system for diagnosing acute leukemia. Methods A total of 117 cases were retrieved from the archived diagnostic cases, consisting of three diagnostic categories: 20 normal cases, 37 acute lymphoblastic leukemia and 60 acute myeloid leukemia. Flow cytometry data manually analyzed by a pathologist is the gold standard. The same flow cytometry data was processed by the flow cytometry analysis software DeepFlow® using proprietary AI algorithm. The final diagnosis and blast cell count of AI and manual analysis are compared by Pearson correlation coefficient. Results The AI-assisted blast cell enumeration showed moderate correlation as compared to manual evaluation (r = 0.8, Fig. 1). Manual adjustment for enumeration of CD34 negative blast population with uncommon immunophenotype is required for 7 cases, including 4 CD34−/CD117+ acute myeloid leukemia and 3 CD34−/TDT+ lymphoblastic leukemia. The AI analysis effectively recognized cell populations and provided correct diagnoses on 94% of cases (110/117). With pathologists’ review, all cases were classified into the correct diagnostic categories. Conclusion Our study demonstrated that AI can accurately recognize the flow cytometry pattern of leukemia and make the proper diagnosis. Additional training for CD34 negative blast gating and other uncommon blast immunophenotypes is being conducted. Ultimately, AI will decrease the demand on manual analysis by technologists and pathologists, standardize the analysis process, and provide accurate diagnosis.

Development of an Automated Online Flow Cytometry Method to Quantify Cell Density and Fingerprint Bacterial Communities.

Cell density is an important factor in all microbiome research, where interactions are of interest. It is also the most important parameter for the operation and control of most biotechnological processes. In the past, cell density determination was often performed offline and manually, resulting in a delay between sampling and immediate data processing, preventing quick action. While there are now some online methods for rapid and automated cell density determination, they are unable to distinguish between the different cell types in bacterial communities. To address this gap, an online automated flow cytometry procedure is proposed for real-time high-resolution analysis of bacterial communities. On the one hand, it allows for the online automated calculation of cell concentrations and, on the other, for the differentiation between different cell subsets of a bacterial community. To achieve this, the OC-300 automation device (onCyt Microbiology, Zürich, Switzerland) was coupled with the flow cytometer CytoFLEX (Beckman Coulter, Brea, USA). The OC-300 performs the automatic sampling, dilution, fixation and 4',6-diamidino-2-phenylindole (DAPI) staining of a bacterial sample before sending it to the CytoFLEX for measurement. It is demonstrated that this method can reproducibly measure both cell density and fingerprint-like patterns of bacterial communities, generating suitable data for powerful automated data analysis and interpretation pipelines. In particular, the automated, high-resolution partitioning of clustered data into cell subsets opens up the possibility of correlation analysis to identify the operational or abiotic/biotic causes of community disturbances or state changes, which can influence the interaction potential of organisms in microbiomes or even affect the performance of individual organisms.

Detection of early-stage lung cancer in sputum using automated flow cytometry and machine learning

BackgroundLow-dose spiral computed tomography (LDCT) may not lead to a clear treatment path when small to intermediate-sized lung nodules are identified. We have combined flow cytometry and machine learning to develop a sputum-based test (CyPath Lung) that can assist physicians in decision-making in such cases.MethodsSingle cell suspensions prepared from induced sputum samples collected over three consecutive days were labeled with a viability dye to exclude dead cells, antibodies to distinguish cell types, and a porphyrin to label cancer-associated cells. The labeled cell suspension was run on a flow cytometer and the data collected. An analysis pipeline combining automated flow cytometry data processing with machine learning was developed to distinguish cancer from non-cancer samples from 150 patients at high risk of whom 28 had lung cancer. Flow data and patient features were evaluated to identify predictors of lung cancer. Random training and test sets were chosen to evaluate predictive variables iteratively until a robust model was identified. The final model was tested on a second, independent group of 32 samples, including six samples from patients diagnosed with lung cancer.ResultsAutomated analysis combined with machine learning resulted in a predictive model that achieved an area under the ROC curve (AUC) of 0.89 (95% CI 0.83–0.89). The sensitivity and specificity were 82% and 88%, respectively, and the negative and positive predictive values 96% and 61%, respectively. Importantly, the test was 92% sensitive and 87% specific in cases when nodules were < 20 mm (AUC of 0.94; 95% CI 0.89–0.99). Testing of the model on an independent second set of samples showed an AUC of 0.85 (95% CI 0.71–0.98) with an 83% sensitivity, 77% specificity, 95% negative predictive value and 45% positive predictive value. The model is robust to differences in sample processing and disease state.ConclusionCyPath Lung correctly classifies samples as cancer or non-cancer with high accuracy, including from participants at different disease stages and with nodules < 20 mm in diameter. This test is intended for use after lung cancer screening to improve early-stage lung cancer diagnosis.Trial registration ClinicalTrials.gov ID: NCT03457415; March 7, 2018

Leukocyte cell population data in patients with cardiac surgery and cardiopulmonary bypass: A potential readily available tool to monitor immunity.

Cardiac surgery with cardiopulmonary bypass triggers sterile inflammation that is responsible for post-operative morbidity. Automated flow cytometry devices used for leucocyte count provide cell population data (CPD) regarding fluorescence intensity, size and granularity of leukocytes that have never been studied in the context of sterile inflammation. Our objective was to explore leukocyte cell population data in patients undergoing cardiac surgery with cardiopulmonary bypass in order to determine whether CPD could be used to monitor immune cell activation. This is an ancillary study of a cohort of patients undergoing cardiac surgery with cardiopulmonary bypass. Cell population data (CPD) extracted from a routine automated flow cytometer were analyzed (Fluorescence targeted to nucleic acids). The time points of interest were: pre-operative, postoperative and 5 days after surgery. The variations in those parameters were studied. Data were then compared between patients according to the occurrence of a composite criteria (supra-ventricular arrythmia, stroke, acute renal failure, and/or death). Data from 1453 patients were analyzed. The neutrophil count, fluorescence granularity (NE-SCC), intensity (NE-SFL) and size (NE-FSC) increased with surgery. Heterogeneity of neutrophils decreased in terms of fluorescence granularity (NE-WX) and size (NE-WZ) but increased in terms of intensity (NE-WY). The lymphocyte count decreased with surgery. While fluorescence granularity (LY-X) and size increased (LY-Z), Lymphocyte intensity decreased (LY-Y). Lymphocytes were less heterogeneous in terms of their granularity, size and intensity after surgery (LY-WX, LY-WY, LY-WZ). Patients who developed the composite complication criteria had a higher pre-operative neutrophil count (5.08 [3.89;6.95] vs 4.76 [3.60;6.13], p = 0.02; AUC = 0.56 [0.51;0.60]), and more heterogeneous neutrophils in terms of fluorescence granularity (NE-WX, AUC = 0.57 [0.52;0.62]) and intensity (NE-WY, AUC 0.61 [0.56;0.65]). Those patients also had lower pre-operative lymphocyte count (1.49 [1.10;1.14] vs 1.81 [1.39;2.39], p<0.01, AUC = 0.61 [0.57;0.66]) and fluorescence granularity (LY-X, AUC = 0.57 [0.53;0.62]). NE-WX, NE-WY and LY-X were associated with post-operative complications after adjustment on the EuroSCORE 2 (adjusted odd ratio of 1.01 [1.00;1.02]; 1.01 [1.00;1.01] and 1.08 [1.02;1.15] respectively). Cardiac surgery with cardiopulmonary bypass was associated with substantial alterations of CPD probably reflecting leukocytes activation in sterile inflammation. Pre-operative NE-WX, NE-WY and LY-X biomarkers levels were associated with post-operative complications, independently of the EuroSCORE 2. Such routine, unexploited and low cost parameters might represent useful tools likely to monitor immune function and predict outcomes for patients undergoing cardiac surgery. Our findings requires validation on a larger external cohort.

Phytoplankton reaction to an intense storm in the north-western Mediterranean Sea

Abstract. The study of extreme weather events and their impact on ocean physics and biogeochemistry is challenging due to the difficulty involved with collecting in situ data. However, recent research has pointed out the major influence of such physical forcing events on microbiological organisms. Moreover, the occurrence of such intense events may increase in the future in the context of global change. In May 2019, an intense storm occurred in the Ligurian Sea (north-western Mediterranean Sea) and was captured during the FUMSECK (Facilities for Updating the Mediterranean Submesoscale – Ecosystem Coupling Knowledge) cruise. In situ multi-platform (vessel-mounted acoustic Doppler current profiler, thermosalinometer, fluorometer, flow cytometer, a moving vessel profiler equipped with a multi-sensor towed vehicle, and a glider) measurements along with satellite data and a 3D atmospheric model were used to characterise the fine-scale dynamics occurring in the impacted oceanic zone. The most affected area was marked by a lower water temperature (1 ∘C colder), a factor of 2 increase in surface chlorophyll a, and a factor of 7 increase in the nitrate concentration, exhibiting strong gradients with respect to the surrounding waters. Our results show that this storm led to a deepening of the mixed-layer depth from 15 to 50 m and a dilution of the deep chlorophyll maximum. As a result, the surface biomass of most phytoplankton groups identified by automated flow cytometry increased by up to a factor of 2. Conversely, the carbon / chlorophyll ratio of most phytoplankton groups decreased by a factor of 2, evidencing significant changes in the phytoplankton cell composition. These results suggest that the role of storms on the biogeochemistry and ecology of the Mediterranean Sea may be underestimated and highlight the need for high-resolution measurements during these events coupling physics and biology.

Automated flow cytometry as a tool to obtain a fine-grain picture of marine prokaryote community structure along an entire oceanographic cruise.

On a standard oceanographic cruise, flow cytometry data are usually collected sparsely through a bottle-based sampling and with stations separated by kilometers leading to a fragmented view of the ecosystem; to improve the resolution of the datasets produced by this technique here it is proposed the application of an automatic method of sampling and staining. The system used consists of a flow-cytometer (Accuri-C6) connected to an automated continuous sampler (OC-300) that collects samples of marine surface waters every 15 min. We tested this system for five days during a brief Mediterranean cruise with the aim of estimating the abundance, relative size and phenotypic diversity of prokaryotes. Seawater was taken by a faucet linked to an inlet pump (ca. 5 m depth). Once the sample was taken, the Oncyt-300 stained it and sent it to the flow cytometer. A total of 366 samples were collected, effectively achieving a fine-grained scale view of microbial community composition both through space and time. A significative positive relationship was found comparing data obtained with the automatic method and 10 samples collected from the faucet but processed with the standard protocol. Abundance values retrieved varied from 3.56·105 cell mL-1 in the coastal area till 6.87 105 cell mL-1 in open waters, exceptional values were reached in the harbor area where abundances peaked to 1.28 106 cell mL-1. The measured features (abundance and size) were associated with metadata (temperature, salinity, conductivity) also taken in continuous, of which conductivity was the one that better explained the variability of abundance. A full 24 h measurement cycle was performed resulting in slightly higher median bacterial abundances values during daylight hours compared to night. Alpha diversity, calculated using computational cytometry techniques, showed a higher value in the coastal area above 41° of latitude and had a strong inverse relationship with both salinity and conductivity. This is the first time to our knowledge that the OC-300 is directly applied to the marine environment during an oceanographic cruise; due to its high-resolution, this set-up shows great potential both to cover large sampling areas, and to monitor day-night cycles in situ.

Avoiding the All-or-None Response in Gene Expression During E. coli Continuous Cultivation Based on the On-Line Monitoring of Cell Phenotypic Switching Dynamics.

Different expression vectors are available for the effective production of recombinant proteins by bacterial populations. However, the productivity of such systems is limited by the inherent noise of the gene circuits used for the synthesis of recombinant products. An extreme case of cell-to-cell heterogeneity that has been previously reported for the ara- and lac-based expression systems in E. coli is the all-or-none response. According to this mode of response, two subpopulations of cells are generated, i.e., a "low-" subpopulation exhibiting a shallow expression level and a "high-" subpopulation exhibiting a high-expression level. The "low-" subpopulation can be considered as a cluster of non-producing cells contributing to the loss of productivity. Here we describe the setup, design, and operation of a continuous culture where inducer addition is operated based on microbial population dynamics. The determination of population dynamics is done based on an automated flow cytometry (FC) procedure previously denoted as segregostat. We illustrate how this setup can be used to control the activation of an ara-based expression system and avoid phenotypic diversification leading to an all-or-none response. Upon the determination of the natural frequency of the gene circuit used as an expression system, our current protocol can be set up without the requirement of a feedback controller.

Karenia selliformis bloom dynamics and growth rate estimation in the Sfax harbour (Tunisia), by using automated flow cytometry equipped with image in flow, during autumn 2019

A Karenia selliformis bloom event in the Gulf of Gabès (Mediterranean Sea), was monitored over 9 days at high frequency during fall 2019, by using an automated flow cytometer (Cytosense, Cytobuoy b.v.) with an image-in-flow attachment. The instrument recorded the shape of the optical signals that lead to the resolution of six cell groups of pico-, nano- and microphytoplankton, during the Harmful Algal Bloom (HAB). K. selliformis cell dimensions derived from the hourly records, enabled to estimate the daily division rate over the bloom period. Results revealed that K. selliformis was the only bloom-forming species and it reached its highest mean abundance the fourth day of the survey. A shift in the nutrient composition occurred with a potential P limitation during the bloom growth and N limitation during the bloom collapse. The co-inertia analysis revealed opposite patterns for K. selliformis and heterotrophic prokaryotes suggesting trophic interactions and possible mixotrophic behaviour of K. selliformis at the end of the bloom. K. selliformis exhibited low growth rates generally < 1 division day−1, which could not explain the observed high abundance. The tide played a crucial role in the dynamics of K. selliformis at a semi-diurnal scale and at spring-neap tide scale and was probably enhancing K. selliformis accumulation.

Ex Vivo Drug Sensitivity Correlates with Clinical Response and Supports Personalized Therapy in Pediatric AML.

Acute myeloid leukemia (AML) is a heterogeneous disease that accounts for ~20% of all childhood leukemias, and more than 40% of children with AML relapse within three years of diagnosis. Although recent efforts have focused on developing a precise medicine-based approach towards treating AML in adults, there remains a critical gap in therapies designed specifically for children. Here, we present ex vivo drug sensitivity profiles for children with de novo AML using an automated flow cytometry platform. Fresh diagnostic blood or bone marrow aspirate samples were screened for sensitivity in response to 78 dose conditions by measuring the reduction in leukemic blasts relative to the control. In pediatric patients treated with conventional chemotherapy, comprising cytarabine, daunorubicin and etoposide (ADE), ex vivo drug sensitivity results correlated with minimal residual disease (r = 0.63) and one year relapse-free survival (r = 0.70; AUROC = 0.94). In the de novo ADE analysis cohort of 13 patients, AML cells showed greater sensitivity to bortezomib/panobinostat compared with ADE, and comparable sensitivity between venetoclax/azacitidine and ADE ex vivo. Two patients showed a differential response between ADE and bortezomib/panobinostat, thus supporting the incorporation of ex vivo drug sensitivity testing in clinical trials to further evaluate the predictive utility of this platform in children with AML.

1057. Development of a Flow Cytometry-Based Micro-Neutralisation Assay to Evaluate Humoral Immunity Against SARS-CoV-2 Variants of Concern in Vaccine Trials

Abstract Background Quantifying neutralising capacity of circulating SARS-COV-2 antibodies is critical in evaluating protective humoral immune responses generated post-infection/post-vaccination. Here we describe a novel medium-throughput flow cytometry based micro-neutralisation assay to evaluate Neutralising Antibody (NAb) responses against live SARS-CoV-2 Wild Type (D641G) and Variants of Concern (VoC) in convalescent/vaccinated populations. Methods Micro-Neutralisation assay (Micro-NT) was performed in 96-well plates using clinical isolate 2019-nCoV/Italy-INMI1, D641G (SARS-CoV-2/human/IRL/AIIDV1446/2020) and/or VOCs Beta (SARS-CoV-2/human/IRL/AIIDV1752/2021) and Omicron (SARS-Cov-2/human/IRL/AIIDV2326/2021). Plasma samples (All Ireland Infectious Diseases (AIID) Cohort) were serially diluted (8 points, half-log) from 1/20 and pre-incubated with SARS-CoV-2 (1h, 37°C). Virus-plasma mixture were added onto VERO E6/VERO-E6 TMPRSS2 cells for 18h. Percentage infected cells was analysed by automated flow cytometry following trypsinisation, fixation and SARS-CoV-2 Nucleoprotein intracellular staining. Half-maximal Neutralisation Titres (NT50) was determined using four-parameter logistic regression. Our assay was compared to Plaque Reduction Neutralisation Test (PRNT) and validated against WHO anti-SARS-CoV-2 Immunoglobulin Standards. Results Using WHO Standards with low, medium or high anti-SARS-CoV-2 IgG, both Micro-NT and PRNT achieved comparable NT50 values (Table 1). Micro-NT was found to be highly reproducible (inter-assay CV of 11.39%). Screening 190 convalescent samples and 11 COVID-19 naive controls (AIID cohort) we achieved an assay sensitivity of 90% and specificity of 81%. We demonstrated that Micro-NT has broad dynamic range differentiating NT50s &amp;lt; 1/20 to &amp;gt; 1/5000 (Figure 1). We could also characterise immune-escape VoC, observing up to 10-fold reduction in NT50 against Beta (Figure 2). Table 1:NT50s of Low, Medium and High Titre Anti-SARS-CoV-2 IgG Standards measured against Live SARS-CoV-2 using PRNT and Micro-NT Neutralising Capacity of low, medium and high-titre anti-SARS-CoV-2 IgG (WHO, International Standards) against live SARS-CoV-2 (2019-nCoV/Italy-INMI1) measured using PRNT and Micro-NT Assays on Vero E6 cells, as well as the potency of NAbs in each sample in International Units (IU/ml) as determined by the WHO. Figure 1:Dynamic Range of Micro-NT Micro-NT has a broad Dynamic Range, distinguishing low (A), medium (B) and high (C) neutralising plasma samples against live SARS-CoV-2 (2019-nCoV/Italy-INMI1) from a cohort of COVID-19 convalescent individuals (AIID cohort), as well as negative samples from COVID-19 naïve samples (D). Graphs show 3 representative samples of each NT50 range. (E) shows the population distribution of 190 Convalescent plasma samples as measured by Micro-NT on Vero E6 cells. Figure 2:Reduced Neutralisation Capacities measured against SARS-CoV-2 VoC using Micro-NT Low (A), Medium (B) and High (C) anti-SARS-CoV-2 IgG (WHO Standards) show different neutralising capacities against WT (D614G) SARS-CoV-2 and variants Beta and Omicron, measured using Micro-NT on Vero-E6-TMPRSS2 cells. Conclusion Our flow-cytometry-based Micro-NT is a robust and reliable assay to quantify NAb titres, an important evaluation endpoint in clinical trials. It has higher throughput (96 well format versus 12 well) and reduced infection time (18h vs 48-96h) compared to the gold standard PRNT. Disclosures All Authors: No reported disclosures.