Infection of Human Macrophage-Like Cells by African Swine Fever Virus

BACKGROUND

The African swine fever (ASF) virus (ASFV) and ASF-like viral sequences were identified in human samples and sewage as well as in different water environments. Pigs regularly experience infections by the ASFV. The considerable stability of the virus in the environment suggests that there is ongoing and long-term contact between humans and the ASFV. However, humans exhibit resistance to the ASFV, and the decisive factor in developing infection in the body is most likely the reaction of target macrophages to the virus. Therefore, this study aimed to characterize the responses of human macrophages to the virus and explore the distinct features of the viral replication cycle within human macrophages.

METHODS

The ASFV Armenia/07 strain was used in all experiments. In this study, quantitative real-time polymerase chain reaction (qRT-PCR) was used to determine the ASFV gene expression; flow cytometry analysis was performed to evaluate the effects of the inactive and active ASFV (inASFV and aASFV) treatments on the phenotype of THP-1-derived macrophages (Mφ0) and inflammatory markers. Moreover, other methods such as cell viability and apoptosis assays, staining techniques, phagocytosis assay, lysosome-associated membrane protein (LAMP-1) cytometry, and cytokine detection were used during experiments.

RESULTS

Our findings showed that the virus initiated replication by entering human macrophages. Subsequently, the virus shed its capsid and initiated the transcription of numerous viral genes, and at least some of these genes executed their functions. In THP-1-derived macrophages (Mφ0), the ASFV implemented several functions to suppress cell activity, although the timing of their implementation was slower compared with virus-sensitive porcine alveolar macrophages (PAMs). Additionally, the virus could not complete the entire replication cycle in human Mφ0, as indicated by the absence of viral factories and a decrease in infectious titers of the virus with each subsequent passage. Overall, the infection of Mφ0 with the ASFV caused significant alterations in their phenotype and functions, such as increased TLR2, TLR3, CD80, CD36, CD163, CXCR2, and surface LAMP-1 expression. Increased production of the tumor necrosis factor (TNF) and interleukin (IL)-10 and decreased production of interferon (IFN)-α were also observed. Taken together, the virus enters human THP-1-derived macrophages, starts transcription, and causes immunological responses by target cells but cannot complete the replicative cycle.

CONCLUSION

These findings suggest that there may be molecular limitations within human macrophages that at least partially restrict the complete replication of the ASFV. Understanding the factors that hinder viral replication in Mφ0 can provide valuable insights into the host-virus interactions and the mechanisms underlying the resistance of human macrophages to the ASFV.

Cell-type specific molecular expression levels by restricted-dimensional cytometry

BACKGROUND

Cytometric analysis has been commonly used to delineate distinct cell subpopulations among peripheral blood mononuclear cells by the differential expression of surface receptors. This capability has reached its apogee with high-dimensional approaches such as mass cytometry and spectral cytometry that include simultaneous assessment of 20-50 analytes. Unfortunately, this approach also engenders significant complexity with analytical and interpretational pitfalls.

METHODS

Here, we demonstrate a complementary approach with restricted-dimensionality to assess cell-type specific intracellular molecular expression levels at exceptional levels of precision. The expression of five analytes was individually assessed in four mononuclear cell-types from peripheral blood.

RESULTS

Distinctions in expression levels were seen between cell-types and between samples from different donor groups. Mononuclear cell-type specific molecular expression levels distinguished pregnant from nonpregnant women and G-CSF-treated from untreated persons. Additionally, the precision of our analysis was sufficient to quantify a novel relationship between two molecules-Rel A and translocator protein-by correlational analysis.

CONCLUSIONS

Restricted-dimensional cytometry can provide a complementary approach to define characteristics of cell-type specific intracellular protein and phosphoantigen expression in mononuclear cells.

IL-8 Instructs Macrophage Identity in Lateral Ventricle Contacting Glioblastoma

Adult IDH-wildtype glioblastoma (GBM) is a highly aggressive brain tumor with no established immunotherapy or targeted therapy. Recently, CD32+ HLA-DRhi macrophages were shown to have displaced resident microglia in GBM tumors that contact the lateral ventricle stem cell niche. Since these lateral ventricle contacting GBM tumors have especially poor outcomes, identifying the origin and role of these CD32+ macrophages is likely critical to developing successful GBM immunotherapies. Here, we identify these CD32+ cells as M_IL-8 macrophages and establish that IL-8 is sufficient and necessary for tumor cells to instruct healthy macrophages into CD32+ M_IL-8 M2 macrophages. In ex vivo experiments with conditioned medium from primary human tumor cells, inhibitory antibodies to IL-8 blocked the generation of CD32+ M_IL-8 cells. Finally, using a set of 73 GBM tumors, IL-8 protein is shown to be present in GBM tumor cells in vivo and especially common in tumors contacting the lateral ventricle. These results provide a mechanistic origin for CD32+ macrophages that predominate in the microenvironment of the most aggressive GBM tumors. IL-8 and CD32+ macrophages should now be explored as targets in combination with GBM immunotherapies, especially for patients whose tumors present with radiographic contact with the ventricular-subventricular zone stem cell niche.

High-Dimensional Methods of Single-Cell Microglial Profiling to Enhance Understanding of Neuropathological Disease

Microglia are the innate myeloid cells of the central nervous system (CNS) parenchyma, functionally implicated in almost every defined neuroinflammatory and neurodegenerative disorder. Current understanding of disease pathogenesis for many neuropathologies is limited and/or lacks reliable diagnostic markers, vaccines, and treatments. With the increasing aging of society and rise in neurogenerative diseases, improving our understanding of their pathogenesis is essential. Analysis of microglia from murine disease models provides an investigative tool to unravel disease processes. In many neuropathologies, bone-marrow-derived monocytes are recruited to the CNS, adopting a phenotype similar to that of microglia. This significantly confounds the accurate identification of cell-type-specific functions and downstream therapeutic targeting. The increased capacity to analyze more phenotypic markers using spectral-cytometry-based technologies allows improved separation of microglia from monocyte-derived cells. Full-spectrum profiling enables enhanced marker resolution, time-efficient analysis of >40 fluorescence parameters, and extraction of cellular autofluorescence parameters. Coupling this system with additional cytometric technologies, including cell sorting and high-parameter imaging, can improve the understanding of microglial phenotypes in disease. To this end, we provide detailed, step-by-step protocols for the analysis of murine brain tissue by high-parameter ex vivo cytometric analysis using the Aurora spectral cytometer (Cytek), including best practices for unmixing and autofluorescence extraction, cell sorting for single-cell RNA analysis, and imaging mass cytometry. Together, this provides a toolkit for researchers to comprehensively investigate microglial disease processes at protein, RNA, and spatial levels for the identification of therapeutic targets in neuropathology. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Processing the mouse brain into a single-cell suspension for microglia isolation Basic Protocol 2: Staining single-cell mouse brain suspensions for microglial phenotyping by spectral cytometry Basic Protocol 3: Flow cytometric sorting of mouse microglia for ex vivo analysis Basic Protocol 4: Processing the mouse brain for imaging mass cytometry for spatial microglia analysis.

Immune response variation in mild and severe COVID-19 patients

Sixty patients with COVID-19 infection were categorized into mild and severe groups, and their immune response was analyzed using flow cytometry and complete blood count. An observed increase in immune activation parameters, notably a higher percentage of CD4 lymphocytes co-expressing CD69 and CD25 molecules, and enhanced activity of the macrophage-monocyte cell line was noted in the mild group. Although Group 2 (severe COVID) had fewer CD4 cells, significant migration and proliferation were evident, with increased CD4CD69, CD8 HLA-DR+, and CD8CD69 lymphocytes. The CD4 to CD8 ratio in Group 1 suggested potential autoimmune reactions, while Group 2 indicated potential immunosuppression from severe infection and employing immunosuppressive drugs. Additionally, Group 2 exhibited an increased neutrophil count, hinting at possible bacterial co-infection. Group 1 showed differences in CD4RO and CD8RA lymphocyte populations, implying that cellular immunity plays a role in developing efficient postinfectious immunity. This intimation suggests that vaccination might mitigate the severity of the coronavirus infection and prevent complications, including long-term COVID-19.

Joint transcriptomic and cytometric study of peanut allergic children reveals molecular and cellular cross-talk in reaction thresholds

BACKGROUND

Reaction thresholds in peanut allergy are highly variable. Elucidating causal relationships between molecular and cellular processes associated with variable thresholds could point to therapeutic pathways for raising thresholds.

OBJECTIVE

To characterize molecular and cellular systemic processes associated with reaction threshold in peanut allergy and causal relationships between them.

METHODS

105 children ages 4 to 14 years with suspected peanut allergy underwent double-blind, placebo-controlled food challenges to peanut. The cumulative peanut protein quantity eliciting allergic symptoms was considered the reaction threshold for each child. Peripheral blood samples collected at 0, 2, and 4 hours after challenge start were used for RNA sequencing, whole blood staining, and cytometry. Statistical and network analyses were performed to identify associations and causal mediation between the molecular and cellular profiles and peanut reaction threshold.

RESULTS

Within the cohort (n=105), 81 (77%) experienced allergic reactions after ingesting varying quantities of peanut, ranging from 43 to 9043 mg cumulative peanut protein. Peripheral blood expression of transcripts (e.g., IGF1R, FDR=5.4e-5 and PADI4, FDR=5.4e-5) and neutrophil abundance (FDR=9.5e-4) were associated with peanut threshold. Co-expression network analyses revealed that the threshold-associated transcripts were enriched in modules for FcγR-mediated phagocytosis (FDR=3.2e-3) and TLR (FDR=1.4e-3) signaling. Bayesian network, key driver, and causal mediation analyses identified key drivers (AP5B1, KLHL21, VASP, TPD52L2 and IGF2R) within these modules involved in bi-directional causal mediation relationships with neutrophil abundance.

CONCLUSION

Key driver transcripts in FcγR-mediated phagocytosis and TLR signaling bi-directionally interact with neutrophils in peripheral blood and are associated with reaction threshold in peanut allergy.

mirna-383-5p Functions as an Anti-oncogene in Glioma through the Akt/mTOR Signaling Pathway by Targeting VEGFA

BACKGROUND

Previously, we have screened 59 differentially expressed miRNAs and 419 mRNAs in the glioblastoma samples that have been compared to the peritumoral tissues using bioinformatics analyses, which included miRNA-383-5p and vascular endothelial growth factor A (VEGFA). miRNA-383-5p and VEGFA/Akt/mTOR pathway play important regulatory roles in the malignant biological behavior of glioma.

METHODS

Glioma cell lines, U87 and U251, were collected for in vitro experiments. miRNA-383-5p and VEGFA expression levels were detected with qRT-PCR and WB. The protein expressions of Akt, mTOR, and VEGFR in U87 and U251 were detected with WB. The effect of miRNA-383-5p on the VEGFA activity was verified by dual-luciferase reporter assay. CCK-8 was used to examine the U87 and U251 cells' inhibition. Flow cytometry and transwell assays were used to detect cell apoptosis and invasion, respectively.

RESULTS

Our research data indicated overexpression of miRNA-383-5p to suppress malignant biological behavior, which was manifested as promoting the apoptosis of U87 and U251 cells and inhibiting invasion, proliferation, and metastasis. VEGFA is one of the downstream target genes of miRNA-383- 5p. miRNA-383-5p could inhibit the expression of VEGFA and Akt/mTOR signaling pathways. Overexpression of VEGFA can reverse the inhibitory effect of miRNA-383-5p and reactivate the Akt/mTOR signaling pathway.

CONCLUSION

Our results indicate that miRNA-383-5p functions as an anti-oncogene by inhibiting the VEGFA/Akt/mTOR signaling pathway in glioma cells. These data provide potential therapeutic targets for glioblastoma.

Nanosensor Chemical Cytometry: Advances and Opportunities in Cellular Therapy and Precision Medicine

With the definition of therapeutics now encompassing transplanted or engineered cells and their molecular products, there is a growing scientific necessity for analytics to understand this new category of drugs. This Perspective highlights the recent development of new measurement science on label-free single cell analysis, nanosensor chemical cytometry (NCC), and their potential for cellular therapeutics and precision medicine. NCC is based on microfluidics integrated with fluorescent nanosensor arrays utilizing the optical lensing effect of a single cell to real-time extract molecular properties and correlate them with physical attributes of single cells. This new class of cytometry can quantify the heterogeneity of the multivariate physicochemical attributes of the cell populations in a completely label-free and nondestructive way and, thus, suggest the vein-to-vein conditions for the safe therapeutic applications. After the introduction of the NCC technology, we suggest the technological development roadmap for the maturation of the new field: from the sensor/chip design perspective to the system/software development level based on hardware automation and deep learning data analytics. The advancement of this new single cell sensing technology is anticipated to aid rich and multivariate single cell data setting and support safe and reliable cellular therapeutics. This new measurement science can lead to data-driven personalized precision medicine.

Changes in immune cell populations following KappaMab, lenalidomide and low-dose dexamethasone treatment in multiple myeloma

Objectives

Lenalidomide (LEN) is used to treat multiple myeloma (MM) and shows in vitro synergy with KappaMab (KM), a chimeric antibody specific for Kappa Myeloma antigen, an antigen exclusively expressed on the surface of kappa-restricted MM cells. Lenalidomide, dexamethasone (DEX) and KM control MM via multiple immunomodulatory mechanisms; however, there are several additional effects of the drug combination on immune cells. Lenalidomide can increase T cell and NKT cell cytotoxicity and dendritic cell (DC) activation in vitro. We investigated the immune cell populations in bone marrow of patients treated with KM, LEN and low-dose DEX in kappa-restricted relapsed/refractory MM ex vivo and assessed association of those changes with patient outcome.

Methods

A cohort (n = 40) of patients with kappa-restricted relapsed/refractory MM, treated with KM, LEN and low-dose DEX, was analysed using a mass cytometry panel that allowed identification of immune cell subsets. Clustering analyses were used to determine significant changes in immune cell populations at time periods after treatment.

Results

We found changes in five DC and 17 T-cell populations throughout treatment. We showed an increase in activated conventional DC populations, a decrease in immature/precursor DC populations, a decrease in activated CD4 T cells and an increase in effector-memory CD4 T cells and effector CD8 T cells, indicating an activated immune response.

Conclusion

These data characterise the effects of LEN, DEX, and KM treatment on non-target immune cells in MM. Treatment may support destruction of MM cells by both direct action and indirect mechanisms via immune cells.

BODIPY Dye Derivative for Irreversible Fluorescent Labeling of Eukaryotic Cells and Their Simultaneous Cytometric Analysis

In this work, we synthesized a green fluorescent dye derivative, 1,3,5,7-tetramethyl-BODIPY, with a heptyl substituent at the 8-position. The obtained highly hydrophobic compound was able to rapidly and irreversibly bind to eukaryotic cells. Incubation of cells with the dye over different periods of time or at different concentrations allowed us to control the degree of cell labeling and the level of fluorescence. This made it possible to modulate the fluorescence level of different eukaryotic cell cultures and then distinguish them by their level of fluorescence signal in the green channel in cytometric experiments. The labeled cells can be combined and further analyzed in the same test tube under identical conditions using the channels in which the dye does not fluoresce. This approach has been tested on a number of tumor cell cultures containing the HER2 receptor on their surface. The representation of the receptor in these cells was analyzed in one test tube in one run using a HER2-specific ligand based on the hybrid protein DARPin9_29-mCherry, which fluoresces in the red region of the spectrum.

Advancing Understanding of Non-Small Cell Lung Cancer with Multiplexed Antibody-Based Spatial Imaging Technologies

Non-small cell lung cancer (NSCLC) remains a cause of significant morbidity and mortality, despite significant advances made in its treatment using immune checkpoint inhibitors (ICIs) over the last decade; while a minority experience prolonged responses with ICIs, benefit is limited for most patients. The development of multiplexed antibody-based (MAB) spatial tissue imaging technologies has revolutionised analysis of the tumour microenvironment (TME), enabling identification of a wide range of cell types and subtypes, and analysis of the spatial relationships and interactions between them. Such study has the potential to translate into a greater understanding of treatment susceptibility and resistance, factors influencing prognosis and recurrence risk, and identification of novel therapeutic approaches and rational treatment combinations to improve patient outcomes in the clinic. Herein we review studies that have leveraged MAB technologies to deliver novel insights into the TME of NSCLC.

The Effect of Potassium Canrenoate (Mineralocorticoid Receptor Antagonist) on the Markers of Inflammation in the Treatment of COVID-19 Pneumonia and Fibrosis-A Secondary Analysis of Randomized Placebo-Controlled Clinical Trial

In March 2020, the World Health Organization (WHO) announced a global pandemic of coronavirus disease 2019 (COVID-19) that presented mainly as an acute infection of the lower respiratory tract (pneumonia), with multiple long-term consequences, including lung fibrosis. The aim of this study was to evaluate the influence of potassium canrenoate on inflammatory markers in the treatment of COVID-19 pneumonia. A randomized clinical trial (RCT) of intravenous potassium canrenoate vs. placebo was performed between December 2020 and November 2021. This study is a secondary analysis of that RCT. In the final analysis, a total of 49 hospitalized patients were included (24 allocated to the potassium canrenoate group and 25 to the placebo group). Patients were assessed by serum testing and blood cell cytometry on day 1 and day 7 of the intervention. Age, sex, and body mass index were not significantly different between the placebo group and intervention group. Although there was a significantly higher rate of ischemic heart disease in the placebo group, rates of other preexisting comorbidities were not significantly different. There were no significant differences in the inflammatory parameters between the potassium canrenoate and placebo groups on day 1 and day 7. However, the intragroup comparisons using Wilcoxon's test showed significant differences between day 1 and day 7. The CD3% for potassium canrenoate increased significantly between day 1 and day 7 (12.85 ± 9.46; 11.55 vs. 20.50 ± 14.40; 17.80; p = 0.022), while the change in the placebo group was not significant (15.66 ± 11.39; 12.65 vs. 21.16 ± 15.37; 16.40; p = 0.181). The IL-1ß total count [%] increased over time for both potassium canrenoate (0.68 ± 0.58; 0.45 vs. 1.27 ± 0.83; 1.20; p = 0.004) and placebo (0.61 ± 0.59; 0.40 vs. 1.16 ± 0.91; 1.00; p = 0.016). The TNF-α total count (%) decreased significantly between day 1 and day 7 for potassium canrenoate (0.54 ± 0.45; 0.40 vs. 0.25 ± 0.23; 0.10; p = 0.031), but not for placebo (0.53 ± 0.47; 0.35 vs. 0.26 ± 0.31; 0.20; p = 0.056). Interleukin-6 (pg/mL) showed a significant decrease between day 1 and day 7 for potassium canrenoate (64.97 ± 72.52; 41.00 vs. 24.20 ± 69.38; 5.30; p = 0.006), but not the placebo group. This RCT has shown that the administration of potassium canrenoate to patients with COVID-19-induced pneumonia may be associated with significant changes in certain inflammatory markers (interleukin-6, CD3%, TNF-α), potentially related to pulmonary fibrosis. Although some positive trends were observed in the potassium canrenoate group, none of these observations reached statistical significance. Any possible benefits from the use of potassium canrenoate as an anti-inflammatory or antifibrotic drug in COVID-19 patients require further investigation.

Rapid and Efficient Computation of Cell Paths During Ultrasonic Focusing

This biophysical analysis explores the first-principles physics of movement of white blood cell sized particles, suspended in an aqueous fluid and experiencing progressive or standing waves of acoustic pressure. In many current applications the cells are gradually nudged or herded toward the nodes of the standing wave, providing a degree of acoustic focusing and concentration of the cells in layers perpendicular to the direction of sound propagation. Here the underlying biomechanics of this phenomenon are analyzed specifically for the viscous regime of water and for small diameter microscopic spheroids such as living cells. The resulting mathematical model leads to a single algebraic expression for the creep or drift velocity as a function of sound frequency, amplitude, wavelength, fluid viscosity, boundary dimensions, and boundary reflectivity. This expression can be integrated numerically by a simple and fast computer algorithm to demonstrate net movement of particles as a function of time, providing a guide to optimization in a variety of emerging applications of ultrasonic cell focusing.

Clinical Application of In Vitro Tests for COVID-19 Vaccine Delayed Hypersensitivity Diagnostics

Drug hypersensitivity reactions can be classified as immediate or delayed. While diagnostic options for immediate reactions are well developed and standardized, delayed reactions (in many cases type IV according to Gell and Coombs) are a challenge for allergy work-up. In recent years, some in vitro markers have been proposed and used for delayed reactions, such as contact dermatitis. Primary strategy: Avoidance is difficult to achieve, especially for COVID-19 vaccinations, when immunity against infection is extremely important. The aim of our study was to evaluate the application of in vitro delayed hypersensitivity tests in COVID-19 vaccines. Seven patients with a positive history of severe delayed drug allergy were enrolled. Vein blood was collected to stimulate cells with the tested vaccines (Comirnaty, Janssen, Spikevax) and excipients with the assessment of CD40L, CD69, IL-2, IL-4, IL-6, IL-10, IFNgamma, TNFalfa, and intracellular markers: granulysin and INFgamma. In addition, basophile activation tests, patch tests, skin prick tests, and intradermal tests were performed with the tested vaccine. Finally, the decision was made to either administer a vaccine or resign. Two out of seven patients were considered positive for drug hypersensitivity in the in vitro test according to the high vaccine stimulation index measured with CD69 (6.91 and 12.18) and CD40L (5.38 and 15.91). All patch tests, BATs, and skin tests were negative. Serum interleukin measurements were inconclusive as the impact of the vaccine itself on the immunity system was high. Intracellular markers gave uncertain results due to the lack of stimulation on the positive control. CD69 and CD40L could be reliable in vitro markers for delayed hypersensitivity to COVID-19 vaccines. Patch tests, skin tests, BATs, and serum interleukins did not confirm their usefulness in our study.

Integrated Cytometry With Machine Learning Applied to High-Content Imaging of Human Kidney Tissue for In Situ Cell Classification and Neighborhood Analysis

The human kidney is a complex organ with various cell types that are intricately organized to perform key physiological functions and maintain homeostasis. New imaging modalities, such as mesoscale and highly multiplexed fluorescence microscopy, are increasingly being applied to human kidney tissue to create single-cell resolution data sets that are both spatially large and multidimensional. These single-cell resolution high-content imaging data sets have great potential to uncover the complex spatial organization and cellular makeup of the human kidney. Tissue cytometry is a novel approach used for the quantitative analysis of imaging data; however, the scale and complexity of such data sets pose unique challenges for processing and analysis. We have developed the Volumetric Tissue Exploration and Analysis (VTEA) software, a unique tool that integrates image processing, segmentation, and interactive cytometry analysis into a single framework on desktop computers. Supported by an extensible and open-source framework, VTEA's integrated pipeline now includes enhanced analytical tools, such as machine learning, data visualization, and neighborhood analyses, for hyperdimensional large-scale imaging data sets. These novel capabilities enable the analysis of mesoscale 2- and 3-dimensional multiplexed human kidney imaging data sets (such as co-detection by indexing and 3-dimensional confocal multiplexed fluorescence imaging). We demonstrate the utility of this approach in identifying cell subtypes in the kidney on the basis of labels, spatial association, and their microenvironment or neighborhood membership. VTEA provides an integrated and intuitive approach to decipher the cellular and spatial complexity of the human kidney and complements other transcriptomics and epigenetic efforts to define the landscape of kidney cell types.

Polymeric Micelles Formulation of Combretastatin Derivatives with Enhanced Solubility, Cytostatic Activity and Selectivity against Cancer Cells

Combretastatin derivatives is a promising class of antitumor agents, tubulin assembly inhibitors. However, due to poor solubility and insufficient selectivity to tumor cells, we believe, their therapeutic potential has not been fully realized yet. This paper describes polymeric micelles based on chitosan (a polycation that causes pH and thermosensitivity of micelles) and fatty acids (stearic, lipoic, oleic and mercaptoundecanoic), which were used as a carrier for a range of combretastatin derivatives and reference organic compounds, demonstrating otherwise impossible delivery to tumor cells, at the same time substantially reduced penetration into normal cells. Polymers containing sulfur atoms in hydrophobic tails form micelles with a zeta potential of about 30 mV, which increases to 40-45 mV when cytostatics are loaded. Polymers with tails of oleic and stearic acids form poorly charged micelles. The use of polymeric 400 nm micelles provides the dissolution of hydrophobic potential drug molecules. Micelles could significantly increase the selectivity of cytostatics against tumors, which has been shown using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay, Fourier transform infrared (FTIR) spectroscopy, flow cytometry and fluorescence microscopy. Atomic force microscopy presented the difference between the unloaded micelles and those loaded with the drug: the size of the former was 30 nm on average, while the latter had a "disc-like" shape and a size of about 450 nm. The loading of drugs into the core of micelles was confirmed by UV and fluorescence spectroscopy methods; shifts of absorption and emission maxima into the long-wavelength region by tens of nm was observed. With FTIR spectroscopy, a high interaction efficiency of micelles with the drug on cells was demonstrated, but at the same time, selective absorption was observed: micellar cytostatics penetrate into A549 cancer cells 1.5-2 times better than the simple form of the drugs. Moreover, in normal HEK293T, the penetration of the drug is reduced. The proposed mechanism for reducing the accumulation of drugs in normal cells is the adsorption of micelles on the cell surface and the preservation of cytostatics to penetrate inside the cells. At the same time, in cancer cells, due to the structural features of the micelles, they penetrate inside, merging with the membrane and releasing the drug by pH- and glutathione-sensitive mechanisms. From a methodological point of view, we have proposed a powerful approach to the observation of micelles using a flow cytometer, which, in addition, allows us to quantify the cells that have absorbed/adsorbed cytostatic fluorophore and distinguish between specific and non-specific binding. Thus, we present polymeric micelles as drug delivery systems in tumors using the example of combretastatin derivatives and model fluorophore-cytostatic rhodamine 6G.

Selection of Cell Populations with High or Low Surface Marker Expression Using Magnetic Sorting

Magnetic cell sorting technology stands out because of its speed, simplicity, and ability to process large cell numbers. However, it also suffers from a number of drawbacks, in particular low discrimination power, which results in all-or-none selection outcomes limited to a bulk separation of cell populations into positive and negative fractions, as well as the modest purity of the selected cells and the inability to select subpopulations of cells with high expression of a surface marker. In the present study, we developed a simple solution to this problem and confirmed the effectiveness of this approach by multiple experiments with the magnetic selection of transduced cell populations. Murine NIH 3T3 cells were transduced with the bicistronic retroviral vector constructs co-expressing fluorescent reporter proteins EGFP (enhanced green fluorescent protein) or DsRed-Express 2 and LNGFR (low-affinity nerve growth factor receptor) as surface selection markers. The effects of the magnetic selection of transduced cells with anti-LNGFR Micro Bead (MB) doses ranging from 0.5 to 80 µL have been assessed. Low doses of MBs favored the depletion of weakly positive cells from the population, resulting in the higher expression levels of EGFP or DsRed-Express2 reporters in the selected cell fractions. Low MB doses also contributed to the increased purity of the selected population, even for samples with a low initial percentage of positive cells. At the same time, high MB doses resulted in the increased yield and a more faithful representation of the original expression profiles following selection. We further demonstrate that for populations with fairly narrow distribution of expression levels, it is possible to achieve separation into high- and low-expressing subsets using the two-stage selection scheme based on the sequential use of low and high doses of MBs. For populations with broad expression distribution, a one-stage selection with low or high doses of MBs is sufficient for a clear separation of low- and high-expressing subsets in the column-retained and flow-through fractions, respectively. This study substantially extends the potential of magnetic cell sorting, and may open new possibilities in a number of biomedical applications.

A Method for Rapid, Quantitative Evaluation of Particle Sorting in Microfluidics Using Basic Cytometry Equipment

This paper describes, in detail, a method that uses flow cytometry to quantitatively characterise the performance of continuous-flow microfluidic devices designed to separate particles. Whilst simple, this approach overcomes many of the issues with the current commonly utilised methods (high-speed fluorescent imaging, or cell counting via either a hemocytometer or a cell counter), as it can accurately assess device performance even in complex, high concentration mixtures in a way that was previously not possible. Uniquely, this approach takes advantage of pulse processing in flow cytometry to allow quantitation of cell separation efficiencies and resulting sample purities on both single cells as well as cell clusters (such as circulating tumour cell (CTC) clusters). Furthermore, it can readily be combined with cell surface phenotyping to measure separation efficiencies and purities in complex cell mixtures. This method will facilitate the rapid development of a raft of continuous flow microfluidic devices, will be helpful in testing novel separation devices for biologically relevant clusters of cells such as CTC clusters, and will provide a quantitative assessment of device performance in complex samples, which was previously impossible.

Differentiating single cervical cells by mitochondrial fluorescence imaging and deep learning-based label-free light scattering with multi-modal static cytometry

Cervical cancer is a high-risk disease that threatens women's health globally. In this study, we developed the multi-modal static cytometry that adopted different features to classify the typical human cervical epithelial cells (H8) and cervical cancer cells (HeLa). With the light-sheet static cytometry, we obtain brightfield (BF) images, fluorescence (FL) images and two-dimensional (2D) light scattering (LS) patterns of single cervical cells. Three feature extraction methods are used to extract multi-modal features based on different data characteristics. Analysis and classification of morphological and textural features demonstrate the potential of intracellular mitochondria in cervical cancer cell classification. The deep learning method is used to automatically extract deep features of label-free LS patterns, and an accuracy of 76.16% for the classification of the above two kinds of cervical cells is obtained, which is higher than the other two single modes (BF and FL). Our multi-modal static cytometry uses a variety of feature extraction and analysis methods to provide the mitochondria as promising internal biomarkers for cervical cancer diagnosis, and to show the promise of label-free, automatic classification of early cervical cancer with deep learning-based 2D light scattering.

Co-Transplantation of Barcoded Lymphoid-Primed Multipotent (LMPP) and Common Lymphocyte (CLP) Progenitors Reveals a Major Contribution of LMPP to the Lymphoid Lineage

T cells have the potential to maintain immunological memory and self-tolerance by recognizing antigens from pathogens or tumors. In pathological situations, failure to generate de novo T cells causes immunodeficiency resulting in acute infections and complications. Hematopoietic stem cells (HSC) transplantation constitutes a valuable option to restore proper immune function. However, delayed T cell reconstitution is observed compared to other lineages. To overcome this difficulty, we developed a new approach to identify populations with efficient lymphoid reconstitution properties. To this end, we use a DNA barcoding strategy based on the insertion into a cell chromosome of a lentivirus (LV) carrying a non-coding DNA fragment named barcode (BC). These will segregate through cell divisions and be present in cells' progeny. The remarkable characteristic of the method is that different cell types can be tracked simultaneously in the same mouse. Thus, we in vivo barcoded LMPP and CLP progenitors to test their ability to reconstitute the lymphoid lineage. Barcoded progenitors were co-grafted in immuno-compromised mice and their fate analyzed by evaluating the BC composition in transplanted mice. The results highlight the predominant role of LMPP progenitors for lymphoid generation and reveal valuable novel insights to be reconsidered in clinical transplantation assays.

Immunopathological Mechanisms of Bird-Related Hypersensitivity Pneumonitis

Bird-related hypersensitivity pneumonitis (BRHP) is an interstitial lung disease induced by avian proteins. The immunopathological pathways involved in the disease are still unknown. This study assesses the cellular immune response and the cytokine pattern in a mouse model of BRHP. On days -3 and -1, mice were intraperitoneally sensitized with commercial pigeon serum (PS) or saline. Intranasal instillations with PS or saline were carried out on three consecutive days/week over either 3 weeks (Group 1) or 12 weeks (Group 2). Leukocyte and cytokine patterns in lung tissue and pulmonary inflammation in bronchoalveolar lavage (BAL) were analysed. Both groups presented increases in resident monocytes, interstitial macrophages and type 2 dendritic cells (DCs), but also reductions in inflammatory monocytes, alveolar macrophages and tolerogenic DCs compared with their control groups. Group 1 had increased levels of eosinophils and T cells with reductions in neutrophils and B cells, while Group 2 showed high levels of B cells. Both groups exhibited increases in Th1 and Th2 cytokines. Group 2 also showed increased levels of IL-23, a Th17 cytokine. Increased levels of neutrophils, eosinophils and lymphocytes were observed in BAL samples of both groups compared with controls. In the first stages of BRHP, there is a mixed Th1/Th2 immune response, while during the progression of the disease, although there is a Th1 response, the cytokine levels seem to indicate a switch towards a Th2/Th17 mixed response.

Cell-Molecular Interactions of Nano- and Microparticles in Dental Implantology

The role of metallic nano- and microparticles in the development of inflammation has not yet been investigated. Soft tissue biopsy specimens of the bone bed taken during surgical revisions, as well as supernatants obtained from the surface of the orthopedic structures and dental implants (control), were examined. Investigations were performed using X-ray microtomography, X-ray fluorescence analysis, and scanning electron microscopy. Histological studies of the bone bed tissues were performed. Nanoscale and microscale metallic particles were identified as participants in the inflammatory process in tissues. Supernatants containing nanoscale particles were obtained from the surfaces of 20 units of new dental implants. Early and late apoptosis and necrosis of immunocompetent cells after co-culture and induction by lipopolysaccharide and human venous blood serum were studied in an experiment with staging on the THP-1 (human monocytic) cell line using visualizing cytometry. As a result, it was found that nano- and microparticles emitted from the surface of the oxide layer of medical devices impregnated soft tissue biopsy specimens. By using different methods to analyze the cell-molecule interactions of nano- and microparticles both from a clinical perspective and an experimental research perspective, the possibility of forming a chronic immunopathological endogenous inflammatory process with an autoimmune component in the tissues was revealed.

Correlation Between Serum and Urine Biomarkers and the Intensity of Acute Radiation Cystitis in Patients Treated With Radiation Therapy for Localized Prostate Cancer: Protocol for the Radiotoxicity Bladder Biomarkers (RABBIO) Study

BACKGROUND

Despite improvements in radiation techniques, pelvic radiotherapy is responsible for acute and delayed bladder adverse events, defined as radiation cystitis. The initial symptoms of bladder injury secondary to pelvic irradiation are likely to occur during treatment or within 3 months of radiotherapy in approximately 50% of irradiated patients, and have a significant impact on their quality of life. The pathophysiology of radiation cystitis is not well understood, particularly because of the risk of complications associated with access to bladder tissue after irradiation, which limits our ability to study this process and develop treatments.

OBJECTIVE

It is an original study combining digital data collection to monitor patients' symptoms and biological markers during irradiation. The main objective of our study is to evaluate the correlation of biological biomarkers with the intensity of acute radiation cystitis and the quality of life of patients, assessed with the digital telemonitoring platform Cureety.

METHODS

Patients with intermediate-risk localized prostate cancer who are eligible for localized radiotherapy will be included. Inflammatory biomarkers will be analyzed in urine and blood samples before the start of radiotherapy and at weeks 4, 12, and 48 of irradiation, through quantitative methods such as a multiplex Luminex assay, flow cytometry, and enzyme-linked immunosorbent assay. We will also characterize the patients' gut and urine microbiota composition using 16S ribosomal RNA sequencing technology. Between sample collection visits, patients will complete various questionnaires related to radiation cystitis symptoms (using the International Prostate Symptom Score), adverse events, and quality of life (using the Functional Assessment of Cancer Therapy-Prostate questionnaire), using the Cureety digital remote monitoring platform. Upon receipt of the questionnaires, an algorithm will process the information and classify patients in accordance with the severity of symptoms and adverse events reported on the basis of Common Terminology Criteria for Adverse Events and International Prostate Symptom Score standards. This will allow us to correlate levels of urinary, blood, and fecal biomarkers with the severity of acute radiation cystitis symptoms and patient-reported quality of life.

RESULTS

The study started in March 2022. We estimate a recruitment period of approximately 18 months, and the final results are expected in 2024.

CONCLUSIONS

This prospective study is the first to explore the overexpression of inflammatory proteins in fluid biopsies from patients with symptoms of acute radiation cystitis. In addition, the 1-year follow-up after treatment will allow us to predict which patients are at risk of late radiation cystitis and to refer them for radioprotective treatment. The results of this study will allow us to develop strategies to limit radiation damage to the bladder and improve the quality of life of patients.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05246774; https://clinicaltrials.gov/ct2/show/NCT05246774?term=NCT05246774.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/38362.

TrackSOM: Mapping immune response dynamics through clustering of time-course cytometry data

Mapping the dynamics of immune cell populations over time or disease-course is key to understanding immunopathogenesis and devising putative interventions. We present TrackSOM, a novel method for delineating cellular populations and tracking their development over a time- or disease-course cytometry datasets. We demonstrate TrackSOM-enabled elucidation of the immune response to West Nile Virus infection in mice, uncovering heterogeneous subpopulations of immune cells and relating their functional evolution to disease severity. TrackSOM is easy to use, encompasses few parameters, is quick to execute, and enables an integrative and dynamic overview of the immune system kinetics that underlie disease progression and/or resolution.

Methods for assessment of the tumour microenvironment and immune interactions in non-small cell lung cancer. A narrative review

Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer death worldwide. Immunotherapy with immune checkpoint inhibitors (ICI) has significantly improved outcomes in some patients, however 80-85% of patients receiving immunotherapy develop primary resistance, manifesting as a lack of response to therapy. Of those that do have an initial response, disease progression may occur due to acquired resistance. The make-up of the tumour microenvironment (TME) and the interaction between tumour infiltrating immune cells and cancer cells can have a large impact on the response to immunotherapy. Robust assessment of the TME with accurate and reproducible methods is vital to understanding mechanisms of immunotherapy resistance. In this paper we will review the evidence of several methodologies to assess the TME, including multiplex immunohistochemistry, imaging mass cytometry, flow cytometry, mass cytometry and RNA sequencing.

Spatial statistics is a comprehensive tool for quantifying cell neighbor relationships and biological processes via tissue image analysis

Automated microscopy and computational image analysis has transformed cell biology, providing quantitative, spatially resolved information on cells and their constituent molecules from the sub-micron to the whole-organ scale. Here we explore the application of spatial statistics to the cellular relationships within tissue microscopy data and discuss how spatial statistics offers cytometry a powerful yet underused mathematical tool set for which the required data are readily captured using standard protocols and microscopy equipment. We also highlight the often-overlooked need to carefully consider the structural heterogeneity of tissues in terms of the applicability of different statistical measures and their accuracy and demonstrate how spatial analyses offer a great deal more than just basic quantification of biological variance. Ultimately, we highlight how statistical modeling can help reveal the hierarchical spatial processes that connect the properties of individual cells to the establishment of biological function.

High-Dimensional Cytometry Dissects Immunological Fingerprints of Idiopathic Inflammatory Myopathies

Chronic inflammation of skeletal muscle is the common feature of idiopathic inflammatory myopathies (IIM). Given the rarity of the disease and potential difficulty of routinely obtaining target tissue, i.e., standardized skeletal muscle, our understanding of immune signatures of the IIM spectrum remains incomplete. Further insight into the immune topography of IIM is needed to determine specific treatment targets according to clinical and immunological phenotypes. Thus, we used high-dimensional flow cytometry to investigate the immune phenotypes of anti-synthetase syndrome (ASyS), dermatomyositis (DM) and inclusion-body myositis (IBM) patients as representative entities of the IIM spectrum and compared them to healthy controls. We studied the CD8, CD4 and B cell compartments in the blood aiming to provide a contemporary overview of the immune topography of the IIM spectrum. ASyS was characterized by altered CD4 composition and expanded T follicular helper cells supporting B cell-mediated autoimmunity. For DM, unsupervised clustering identified expansion of distinct B cell subtypes highly expressing immunoglobulin G4 (IgG4) and CD38. Lastly, terminally differentiated, cytotoxic CD8 T cells distinguish IBM from other IIM. Interestingly, these terminally differentiated CD8 T cells highly expressed the integrin CD18 mediating cellular adhesion and infiltration. The distinct immune cell topography of IIM might provide the framework for targeted treatment approaches potentially improving therapeutic outcomes.

Calibration-Aimed Comparison of Image-Cytometry- and Flow-Cytometry-Based Approaches of Ploidy Analysis

Ploidy analysis is the fundamental method of measuring DNA content. For decades, the principal way of conducting ploidy analysis was through flow cytometry. A flow cytometer is a specialized tool for analyzing cells in a solution. This is convenient in laboratory environments, but prohibits measurement reproducibility and the complete detachment of sample preparation from data acquisition and analysis, which seems to have become paramount with the constant decrease in the number of pathologists per capita all over the globe. As more open computer-aided systems emerge in medicine, the demand for overcoming these shortcomings, and opening access to even more (and more flexible) options, has also emerged. Image-based analysis systems can provide an alternative to these types of workloads, placing the abovementioned problems in a different light. Flow cytometry data can be used as a reference for calibrating an image-based system. This article aims to show an approach to constructing an image-based solution for ploidy analysis, take measurements for a basic comparison of the data produced by the two methods, and produce a workflow with the ultimate goal of calibrating the image-based system.

Droplet Microfluidic Technology for the Early and Label-Free Isolation of Highly-Glycolytic, Activated T-Cells

A label-free, fixation-free and passive sorting method is presented to isolate activated T-cells shortly after activation and prior to the display of activation surface markers. It uses a recently developed sorting platform dubbed "Sorting by Interfacial Tension" (SIFT) that sorts droplets based on pH. After polyclonal (anti-CD3/CD28 bead) activation and a brief incubation on chip, droplets containing activated T-cells display a lower pH than those containing naive cells due to increased glycolysis. Under specific surfactant conditions, a change in pH can lead to a concurrent increase in droplet interfacial tension. The isolation of activated T-cells on chip is hence achieved as flattened droplets are displaced as they encounter a micro-fabricated trench oriented diagonally with respect to the direction of flow. This technique leads to an enrichment of activated primary CD4+ T-cells to over 95% from an initial mixed population of naive cells and cells activated for as little as 15 min. Moreover, since the pH change is correlated to successful activation, the technique allows the isolation of T-cells with the earliest activation and highest glycolysis, an important feature for the testing of T-cell activation modulators and to determine regulators and predictors of differentiation outcomes.

Monocyte Phenotypes and Physical Activity in Patients with Carotid Atherosclerosis

Atherosclerosis is associated with low-grade inflammation involving circulating monocytes. It has been shown that the levels of intermediate pro-inflammatory monocytes are associated with cardiovascular mortality and risk of ischemic stroke. It also has been shown that physical activity (PA) decreases inflammation markers, incidence of strokes, and mortality. In this cross-sectional study, we tested the effect of PA on circulating monocytes phenotype rate. A total of 29 patients with a carotid stenosis > 50% were recruited. Levels of physical activity (MET.min/week) were measured by the GPAQ questionnaire, arterial samples of blood were collected to analyze monocyte phenotype (classical, intermediate and non-classical) assessed by flow cytometry, and venous blood samples were used to dose antioxidant activity and oxidative damage. Antioxidant capacity was reduced and oxidative damage increased in patients. There was a significant decrease in the percentage of classical and intermediate monocytes in moderately active patients as compared with non-active and highly active patients. Inversely, the rate of non-classical monocytes increased in moderately active patients. Intense PA appears to blunt the beneficial effects of moderate PA. Our study also suggests that PA could be beneficial in such patients by reducing the rate of intermediate monocytes known to predict the risk of ischemic stroke and by increasing the non-classical monocytes involved in lesions’ healing. Nevertheless, a longitudinal study would be necessary to confirm this hypothesis.

Needle in a Whey-Stack: PhRACS as a Discovery Tool for Unknown Phage-Host Combinations

The field of metagenomics has rapidly expanded to become the go-to method for complex microbial community analyses. However, there is currently no straightforward route from metagenomics to traditional culture-based methods of strain isolation, particularly in (bacterio)phage biology, leading to an investigative bottleneck. Here, we describe a method that exploits specific phage receptor binding protein (RBP)-host cell surface receptor interaction enabling isolation of phage-host combinations from an environmental sample. The method was successfully applied to two complex sample types-a dairy-derived whey sample and an infant fecal sample, enabling retrieval of specific and culturable phage hosts. IMPORTANCE PhRACS aims to bridge the current divide between in silico genetic analyses (i.e., phageomic studies) and traditional culture-based methodology. Through the labeling of specific bacterial hosts with fluorescently tagged recombinant phage receptor binding proteins and the isolation of tagged cells using flow cytometry, PhRACS allows the full potential of phageomic data to be realized in the wet laboratory.

Size and density measurements of single sickle red blood cells using microfluidic magnetic levitation

Single cells have unique biophysical signatures that can rapidly change during various disease states. For instance, cellular density is an inherent property differing between cell types. Characterizing changes in fundamental density properties down to the single-cell level can reveal sub-populations in pathological states. Here, we have developed a microfluidic, magnetic levitation-based assay (MagDense) that detects minute density differences of individual red blood cells (RBCs) down to 0.0001 g mL^-1 resolution. This assay fractionates RBCs based on their density profiles in a non-ionic paramagnetic medium flowing in a capillary microchannel placed between magnets with same poles facing each other. Based on precisely measured levitation height and density of individual RBCs at their specific equilibrium state, we demonstrated that MagDense can accurately analyze the density of sickle hemoglobin (HbS)-containing RBCs and normal hemoglobin (HbA)-containing RBCs. In addition, the precise density and cell size measurements at the single cell level showed three different sub-populations of RBCs in blood samples from individuals with homozygous sickle cell disease receiving blood transfusions; where less dense, HbA-containing RBCs levitated higher, while the denser, HbS-containing RBCs levitated lower. We compared the mean RBC densities of sickle cell disease subjects with healthy controls and found distinctly separated bands of RBC density for each group denoting the likely range of cell densities seen in the blood samples. The high resolution of our method enabled measurement of deviation from the mean RBC density. Moreover, we introduced a new term as a measure of density dispersion, "RBC levitational density width, RLDW". Mean RBC density in sickle cell disease associated with hemoglobin from complete blood count (p = 0.032, linear regression) and RLDW associated with absolute reticulocyte count (ARC) and RBC distribution width (RDW) from complete blood count (p = 0.002 for ARC and p = 003 for RDW, linear regression). Our magnetic levitation-based assay enables rapid, accurate, density-based imaging, profiling and label-free monitoring of single RBCs. Our approach can be broadly applicable to investigate blood cell disorders and the effects of emerging pharmacological and curative therapies in patient outcomes.

Strategies to improve the survival of probiotic Lacticaseibacillus rhamnosus R0011 during the production and storage of granola bars

The goal of this study was to evaluate the effectiveness of two approaches to protect the viability of probiotic cells during granola bar manufacturing and storage: microencapsulation (ME) and inclusion in chocolate chips. In the process used, hot honey (138 °C) was blended with cereal ingredients, resulting in an initial blend temperature of 52 °C. Chocolate chips carrying probiotics were added; however, when the blend was cooled to 42 °C. The viability of Lacticaseibacillus rhamnosus R0011 probiotic was assessed by flow cytometry (FC) and plating (CFU). There was an uneven distribution of inoculated probiotic bacteria throughout the cereal bars, resulting in variability in the CFU data. By providing total and viable counts, FC assessed the correct number of inoculated cells in the sample, which enabled the accurate calculation of survival levels. Spray coating with ME increased survival during manufacturing, but ME in alginate particles was detrimental. Including the cultures in chocolate improved the stability of the probiotics during storage at 25 °C, but only in the first 4 weeks. FC analyses showed that viability losses during bar manufacturing could be linked to damage to the cell membrane, but less so during storage.

Random Lasing from Label-Free Living Cells for Rapid Cytometry of Apoptosis

A random laser carrying the scattering information on a biological host is a promising tool for the characterization of biophysical properties. In this work, random lasing from label-free living cells is proposed to achieve rapid cytometry of apoptosis. Random lasing is achieved by adding biocompatible gain medium to a confocal dish containing cells under optically pumped conditions. The random lasing characteristics are distinct at different stages of cell apoptosis after drug treatment. By analyzing the power Fourier transform results of the random lasing spectra, the percentage of apoptotic cells could be distinguished within two seconds, which is more than an order of magnitude faster than traditional flow cytometry. These results provide a label-free approach for rapid cytometry of apoptosis, which is advantageous for further research of random lasers in the biological field.

Application of Machine Learning for Cytometry Data

Modern cytometry technologies present opportunities to profile the immune system at a single-cell resolution with more than 50 protein markers, and have been widely used in both research and clinical settings. The number of publicly available cytometry datasets is growing. However, the analysis of cytometry data remains a bottleneck due to its high dimensionality, large cell numbers, and heterogeneity between datasets. Machine learning techniques are well suited to analyze complex cytometry data and have been used in multiple facets of cytometry data analysis, including dimensionality reduction, cell population identification, and sample classification. Here, we review the existing machine learning applications for analyzing cytometry data and highlight the importance of publicly available cytometry data that enable researchers to develop and validate machine learning methods.

A simple strategy for sample annotation error detection in cytometry datasets

Mislabeling samples or data with the wrong participant information can affect study integrity and lead investigators to draw inaccurate conclusions. Quality control to prevent these types of errors is commonly embedded into the analysis of genomic datasets, but a similar identification strategy is not standard for cytometric data. Here, we present a method for detecting sample identification errors in cytometric data using expression of human leukocyte antigen (HLA) class I alleles. We measured HLA-A*02 and HLA-B*07 expression in three longitudinal samples from 41 participants using a 33-marker CyTOF panel designed to identify major immune cell types. 3/123 samples (2.4%) showed HLA allele expression that did not match their longitudinal pairs. Furthermore, these same three samples' cytometric signature did not match qPCR HLA class I allele data, suggesting that they were accurately identified as mismatches. We conclude that this technique is useful for detecting sample-labeling errors in cytometric analyses of longitudinal data. This technique could also be used in conjunction with another method, like GWAS or PCR, to detect errors in cross-sectional data. We suggest widespread adoption of this or similar techniques will improve the quality of clinical studies that utilize cytometry.

A systematic comparison of novel and existing differential analysis methods for CyTOF data

Cytometry techniques are widely used to discover cellular characteristics at single-cell resolution. Many data analysis methods for cytometry data focus solely on identifying subpopulations via clustering and testing for differential cell abundance. For differential expression analysis of markers between conditions, only few tools exist. These tools either reduce the data distribution to medians, discarding valuable information, or have underlying assumptions that may not hold for all expression patterns. Here, we systematically evaluated existing and novel approaches for differential expression analysis on real and simulated CyTOF data. We found that methods using median marker expressions compute fast and reliable results when the data are not strongly zero-inflated. Methods using all data detect changes in strongly zero-inflated markers, but partially suffer from overprediction or cannot handle big datasets. We present a new method, CyEMD, based on calculating the earth mover's distance between expression distributions that can handle strong zero-inflation without being too sensitive. Additionally, we developed CYANUS - CYtometry ANalysis Using Shiny - a user-friendly R Shiny App allowing the user to analyze cytometry data with state-of-the-art tools, including well-performing methods from our comparison. A public web interface is available at https://exbio.wzw.tum.de/cyanus/.

Impact of Cryopreservation on Motile Subpopulations and Tyrosine-Phosphorylated Regions of Ram Spermatozoa during Capacitating Conditions

Simple Summary

Spermatozoa go through diverse changes to achieve their fertilizing potential (capacitation) and develop a specific motility pattern (hyperactivation). However, to ensure a greater reproductive success, not all the spermatozoa present in an ejaculate react equally or at the same time. Therefore, a comparative analysis was performed in the present study to improve our current understanding about how cryopreservation may affect the heterogeneous nature of fresh ejaculates during these two events. Among the four motile sperm subpopulations identified in fresh and frozen-thawed ram semen, one of them developed a hyperactivated-like movement and was the main group involve in those changes associated with sperm capacitation based on the marked increase and the positive correlation with mitochondrial activity and tyrosine phosphorylation, two relevant parameters that usually increase during capacitation. In addition, cryopreservation altered the distribution of the motile sperm subpopulations. Although the subpopulation with hyperactivated-like movement increased at the beginning of incubation in frozen-thawed samples, this subpopulation together with the subpopulation of rapid and progressive spermatozoa were replaced after a prolonged incubation by the subpopulation of slow spermatozoa with the lowest mitochondrial activity, which clearly indicate the reduction in sperm quality. These findings will aid to optimize the current cryopreservation and in vitro fertilization protocols.

Abstract

The heterogeneous nature of ejaculates highlights the relevance of studying the behavior of different sperm subpopulations. Changes in sperm motility and the increase in tyrosine phosphorylation are key events that usually occur during capacitation and can be modified by the cryopreservation process. However, the relationship between both events remains poorly defined throughout capacitation in the different sperm subpopulations. Fresh and frozen-thawed spermatozoa were incubated in capacitating (CAP) and non-capacitating (NC) media up to 240 min. Sperm kinematics, tyrosine phosphorylation and mitochondrial activity were measured by the CASA system and imaging flow cytometry. Four motile sperm subpopulations (SP) were identified in fresh and frozen-thawed ram semen after the cluster analysis. Incubation under CAP conditions over time led to greater changes in the percentage of spermatozoa included in each subpopulation compared to NC conditions, being different between fresh and frozen-thawed spermatozoa. The SP1, characterized by slow spermatozoa, progressively increased after 15 min in frozen-thawed samples incubated in both media but not in fresh ones. The SP4, characterized by fast and non-linear spermatozoa, showed a marked increase during CAP, but not under NC conditions, occurring more rapidly in frozen-thawed spermatozoa. This subpopulation (SP4) was also the only one positively and strongly correlated with mitochondrial activity and all phosphorylated sperm regions during capacitation, either in fresh or frozen-thawed samples. Our results indicated that in vitro capacitation induced significant changes in the distribution of motile sperm subpopulations, being affected by cryopreservation. Notwithstanding, the subpopulation which probably represents hyperactivated-like spermatozoa (SP4) also increased in frozen-thawed samples, occurring faster and simultaneously to the increment of mitochondrial activity and tyrosine phosphorylation of different sperm regions.

B6 Mouse Strain: The Best Fit for LPS-Induced Interstitial Cystitis Model

Interstitial cystitis (IC) is a chronic inflammatory disease characterized by bladder pain and increased urinary frequency. Although the C57BL/6J (B6) and FVB/NJ (FVB) mouse strains are commonly used as animal models for studies involving the urinary system, few reports have compared their lower urinary tract anatomy, despite the importance of such data. Our study aimed to characterize bladder function changes in FVB and B6 mouse strains with lipopolysaccharide (LPS)-induced IC, to understand mouse model-based bladder research. The bladder function parameters were measured by cystometrogram. Histological assay was examined by hematoxylin and eosin stain, Masson’s trichrome stain, and immunofluorescence staining. Results indicated that the two strains in the control group exhibited different bladder structures and functions, with significant anatomical differences, including a larger bladder size in the FVB than in the B6 strain. Furthermore, cystometry tests revealed differences in bladder function pressure. LPS-treated B6 mice presented significant changes in peak pressure, with decreased intercontraction intervals; these results were similar to symptoms of IC in humans. Each strain displayed distinct characteristics, emphasizing the care required in choosing the appropriate strain for bladder-model studies. The results suggested that the B6 mouse strain is more suitable for IC models.

Recent progress in cytometric technologies and their applications in ecotoxicology and environmental risk assessment

Environmental toxicology focuses on identifying and predicting impact of potentially toxic anthropogenic chemicals on biosphere at various levels of biological organization. Presently there is a significant drive to gain deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity. Most notable is increased focus on elucidation of cellular-response networks, interactomes, and greater implementation of cell-based biotests using high-throughput procedures, while at the same time decreasing the reliance on standard animal models used in ecotoxicity testing. This is aimed at discovery and interpretation of molecular pathways of ecotoxicity at large scale. In this regard, the applications of cytometry are perhaps one of the most fundamental prospective analytical tools for the next generation and high-throughput ecotoxicology research. The diversity of this modern technology spans flow, laser-scanning, imaging, and more recently, Raman as well as mass cytometry. The cornerstone advantages of cytometry include the possibility of multi-parameter measurements, gating and rapid analysis. Cytometry overcomes, thus, limitations of traditional bulk techniques such as spectrophotometry or gel-based techniques that average the results from pooled cell populations or small model organisms. Novel technologies such as cell imaging in flow, laser scanning cytometry, as well as mass cytometry provide innovative and tremendously powerful capabilities to analyze cells, tissues as well as to perform in situ analysis of small model organisms. In this review, we outline cytometry as a tremendously diverse field that is still vastly underutilized and often largely unknown in environmental sciences. The main motivation of this work is to highlight the potential and wide-reaching applications of cytometry in ecotoxicology, guide environmental scientists in the technological aspects as well as popularize its broader adoption in environmental risk assessment.

Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy

For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrait of the cells reacting to a novel virus before disease-specific knowledge and tools are established. However, single cell analysis tools can struggle to reveal rare cells that are under 0.1% of the population. Here, the machine learning workflow Tracking Responders EXpanding (T-REX) was created to identify changes in both rare and common cells across human immune monitoring settings. T-REX identified cells with highly similar phenotypes that localized to hotspots of significant change during rhinovirus and SARS-CoV-2 infections. Specialized MHCII tetramer reagents that mark rhinovirus-specific CD4+ cells were left out during analysis and then used to test whether T-REX identified biologically significant cells. T-REX identified rhinovirus-specific CD4+ T cells based on phenotypically homogeneous cells expanding by ≥95% following infection. T-REX successfully identified hotspots of virus-specific T cells by comparing infection (day 7) to either pre-infection (day 0) or post-infection (day 28) samples. Plotting the direction and degree of change for each individual donor provided a useful summary view and revealed patterns of immune system behavior across immune monitoring settings. For example, the magnitude and direction of change in some COVID-19 patients was comparable to blast crisis acute myeloid leukemia patients undergoing a complete response to chemotherapy. Other COVID-19 patients instead displayed an immune trajectory like that seen in rhinovirus infection or checkpoint inhibitor therapy for melanoma. The T-REX algorithm thus rapidly identifies and characterizes mechanistically significant cells and places emerging diseases into a systems immunology context for comparison to well-studied immune changes.

High-Dimensional Image Analysis using Histocytometry

Histocytometry is a technique for processing multiparameter microscopy images using computational approaches to identify and quantify cellular phenotypes. It allows for spatial analyses of cellular phenotypes in relation to each other and within defined spatial regions. The benefit of this technique over manual annotation and characterization of cells is a high degree of automation/throughput, significantly decreased user bias, and increased reproducibility. Recently, an increase in freely available software amenable to or deliberately designed for histocytometry has resulted in these complex analyses being available to a broader base of users who have amassed multi-component microscopic imaging data. This article provides an overview of a histocytometry pipeline, focusing on the strategic planning and software requirements to allow readers to perform cell segmentation, phenotyping, and spatial analyses to advance their research outputs. © 2021 Wiley Periodicals LLC.

Evaluating Very Deep Convolutional Neural Networks for Nucleus Segmentation from Brightfield Cell Microscopy Images

Advances in microscopy have increased output data volumes, and powerful image analysis methods are required to match. In particular, finding and characterizing nuclei from microscopy images, a core cytometry task, remains difficult to automate. While deep learning models have given encouraging results on this problem, the most powerful approaches have not yet been tested for attacking it. Here, we review and evaluate state-of-the-art very deep convolutional neural network architectures and training strategies for segmenting nuclei from brightfield cell images. We tested U-Net as a baseline model; considered U-Net++, Tiramisu, and DeepLabv3+ as latest instances of advanced families of segmentation models; and propose PPU-Net, a novel light-weight alternative. The deeper architectures outperformed standard U-Net and results from previous studies on the challenging brightfield images, with balanced pixel-wise accuracies of up to 86%. PPU-Net achieved this performance with 20-fold fewer parameters than the comparably accurate methods. All models perform better on larger nuclei and in sparser images. We further confirmed that in the absence of plentiful training data, augmentation and pretraining on other data improve performance. In particular, using only 16 images with data augmentation is enough to achieve a pixel-wise F1 score that is within 5% of the one achieved with a full data set for all models. The remaining segmentation errors are mainly due to missed nuclei in dense regions, overlapping cells, and imaging artifacts, indicating the major outstanding challenges.

Sheath fluid impacts the depletion of cellular metabolites in cells afflicted by sorting induced cellular stress (SICS)

Flow cytometrists have long observed a spectrum of cell‐type‐specific changes ranging from minor functional defects to outright cell destruction after purification of cells using conventional droplet cell sorters. We have described this spectrum of cell perturbations as sorter induced cellular stress, or SICS (Lopez and Hulspas, Cytometry, 2020, 97, 105–106). Despite the potential impact of this issue and ubiquitous anecdotes, little has been reported about this phenomenon in the literature, and the underlying mechanism has been elusive. Inspired by others' observations (Llufrio et al., Redox Biology, 2018, 16, 381–387 and Binek et al., Journal of Proteome Research, 2019, 18, 169–181), we set out to examine SICS at the metabolic level and use this information to propose a working model. Using representative suspension (Jurkat) and adherent (NIH/3T3) cell lines we observed broad and consistent metabolic perturbations after sorting using a high‐speed droplet cell sorter. Our results suggest that the SICS metabolic phenotype is a common cell‐type‐independent manifestation and may be the harbinger of a wide‐range of functional defects either directly related to metabolism, or cell stress response pathways. We further demonstrate a proof of concept that a modification to the fluidic environment (complete media used as sheath fluid) in a droplet cell sorter can largely rescue the intracellular markers of SICS, and that this rescue is not due to a contribution of metabolites found in media. Future studies will focus on characterizing the potential electro‐physical mechanisms inherent to the droplet cell sorting process to determine the major contributors to the SICS mechanism.

Apoptotic Bodies in the Pancreatic Tumor Cell Culture Media Enable Label-Free Drug Sensitivity Assessment by Impedance Cytometry

The ability to rapidly and sensitively predict drug response and toxicity using in vitro models of patient-derived tumors is essential for assessing chemotherapy efficacy. Currently, drug sensitivity assessment for solid tumors relies on imaging adherent cells or by flow cytometry of cells lifted from drug-treated cultures after fluorescent staining for apoptotic markers. Subcellular apoptotic bodies (ABs), including microvesicles that are secreted into the culture media under drug treatment can potentially serve as markers for drug sensitivity, without the need to lift cells under culture. However, their stratification to quantify cell disassembly is challenging due to their compositional diversity, with tailored labeling strategies currently needed for the recognition and cytometry of each AB type. It is shown that the high frequency impedance phase versus size distribution of ABs determined by high-throughput single-particle impedance cytometry of supernatants in the media of gemcitabine-treated pancreatic tumor cultures exhibits phenotypic resemblance to lifted apoptotic cells and enables shape-based stratification within distinct size ranges, which is not possible by flow cytometry. It is envisioned that this tool can be applied in conjunction with the appropriate pancreatic tumor microenvironment model to assess drug sensitivity and toxicity of patient-derived tumors, without the need to lift cells from cultures.

ImmunoCluster provides a computational framework for the nonspecialist to profile high-dimensional cytometry data

High-dimensional cytometry is an innovative tool for immune monitoring in health and disease, and it has provided novel insight into the underlying biology as well as biomarkers for a variety of diseases. However, the analysis of large multiparametric datasets usually requires specialist computational knowledge. Here, we describe ImmunoCluster (https://github.com/kordastilab/ImmunoCluster), an R package for immune profiling cellular heterogeneity in high-dimensional liquid and imaging mass cytometry, and flow cytometry data, designed to facilitate computational analysis by a nonspecialist. The analysis framework implemented within ImmunoCluster is readily scalable to millions of cells and provides a variety of visualization and analytical approaches, as well as a rich array of plotting tools that can be tailored to users' needs. The protocol consists of three core computational stages: (1) data import and quality control; (2) dimensionality reduction and unsupervised clustering; and (3) annotation and differential testing, all contained within an R-based open-source framework.