Cytometry Part A最新文献

The advent of single-cell cytometric technologies, in conjunction with advances in single-cell biology, has significantly propelled forward the field of geroscience, enhancing our comprehension of the mechanisms underlying age-related diseases. Given that aging is a primary risk factor for numerous chronic health conditions, investigating the dynamic changes within the physiological landscape at the granularity of single cells is crucial for elucidating the molecular foundations of biological aging. Utilizing hallmarks of aging as a conceptual framework, we review current literature to delineate the progression of single-cell cytometric techniques and their pivotal applications in the exploration of molecular alterations associated with aging. We next discuss recent advancements in single-cell cytometry in terms of the development in instrument, software, and reagents, highlighting its promising and critical role in driving future breakthrough discoveries in aging research.

Optofluidic time-stretch imaging flow cytometry (OTS-IFC) provides a suitable solution for high-precision cell analysis and high-sensitivity detection of rare cells due to its high-throughput and continuous image acquisition. However, transferring and storing continuous big data streams remains a challenge. In this study, we designed a high-speed streaming storage strategy to store OTS-IFC data in real-time, overcoming the imbalance between the fast generation speed in the data acquisition and processing subsystem and the comparatively slower storage speed in the transmission and storage subsystem. This strategy, utilizing an asynchronous buffer structure built on the producer-consumer model, optimizes memory usage for enhanced data throughput and stability. We evaluated the storage performance of the high-speed streaming storage strategy in ultra-large-scale blood cell imaging on a common commercial device. The experimental results show that it can provide a continuous data throughput of up to 5891 MB/s.

Fairooz Sahir, Jericha Miles Mateo, Martin Steinhoff, Kodappully Sivaraman Siveen (2020), Development of a 43 color panel for the characterization of conventional and unconventional T-cell subsets, B cells, NK cells, monocytes, dendritic cells, and innate lymphoid cells using spectral flow cytometry. Cytometry Part A, https://doi.org/10.1002/cyto.a.24288.

This Expression of Concern is for the above article, published online on 18 December 2020 in Wiley Online Library (https://onlinelibrary.wiley.com/doi/10.1002/cyto.a.24288), and has been published by agreement between the journal's Editor-in-Chief, Attila Tárnok, the International Society for Advancement of Cytometry, and Wiley Periodicals, LLC.

The Expression of Concern has been agreed due to concerns raised by the cytometry community about the validity and reproducibility of the results, and overinterpretation of the data by the authors. However, the premise of the manuscript is that a 43-color panel is possible, with the conclusion that although not optimized, it nonetheless establishes an attempt at demonstrating the possibility of analyses at this depth of dimension.

With respect to panel design and assay optimization, the authors do not provide sufficient information regarding criteria for fluorochrome selection, spillover spread characterization, unmixing control optimization, unmixing accuracy, and differences in resolution between the single stained controls and the corresponding marker in the multicolor tube. The authors mention specific metrics used for panel design without explaining their meaning or relevance. In some instances, the gating strategy was found non-standard and the positioning of the gates arbitrary. Several populations display unusual patterns compared to what is expected in normal donors, and this may result from incorrect labeling of populations, poor data quality or limited familiarity with the tools used for analysis (e.g., high percentage of cells labeled as “MAIT”, and too close proximity of monocyte and dendritic cell populations in Suppl. Fig. 1). As the settings for the algorithms used have not been provided, reproducibility and verification of the accuracy of the data proves challenging. Lastly, the discussion of the figures and supplementary data is inaccurate or overinterpreted, in particular concerning the claims of satisfactory resolution using highly overlapping dyes when comparing the fully stained sample to the single-color stained sample (Suppl. Fig. 2).

The authors were informed about the concerns raised and asked to provide an explanation. Unfortunately, the concerns have not been satisfactorily addressed by the authors in the course of the investigation. Therefore, the journal has decided to issue an Expression of Concern to inform and alert the readers.

We introduce a 35-marker imaging mass cytometry (IMC) panel for a detailed examination of immune cell populations and HIV RNA in formalin fixed paraffin embedded (FFPE) human intestinal tissue. The panel has broad cell type coverage and particularly excels in delineating subsets of mononuclear phagocytes and T cells. Markers for key tissue structures are included, enabling identification of epithelium, blood vessels, lymphatics, and musculature. The described method for HIV RNA detection can be generalized to other low abundance RNA targets, whether endogenous or pathogen derived. As such, the panel presented here is useful for high parameter spatial mapping of intestinal immune cells and their interactions with pathogens such as HIV.

To achieve high-sensitivity cell measurements (<1 in 10⁵ cells) by flow cytometry (FCM), the minimum number of acquired cells must be considered and conventional immunophenotyping protocols fall short of these numbers. The bulk lysis (BL) assay is a standardized erythrocyte lysing approach that allows the analysis of the millions of cells required for high-sensitivity measurable residual disease (MRD) detection. However, this approach has been associated with significant cell loss, along with potential over or underestimates of rare cells when using this method. The aim of this study was to evaluate bulk lysis protocols and compare them with minimal sample perturbation (MSP) protocols, which are reported to better preserve the native cellular state and avoid significant cell loss due to washing steps. To achieve this purpose, we first generated an MRD model by spiking fresh peripheral blood with K562 cells, stably expressing EGFP, at known percentages of EGFP positive cells to leukocytes. Samples were then prepared with BL and MSP protocols and analyzed using FCM. For all percentages of K562 cells established and evaluated, a significant decrease of this population was detected in BL samples compared with MSP samples, even at low K562 cell percentages. Significant decreases for non-necrotic cells were also observed in BL samples relative to MSP samples. In conclusion, the evaluation of the potential effects of BL protocols in obtaining the final count is of great interest, especially for over- or under-estimation of target cells, as in the case of measurable residual disease. Since conventional flow cytometry or minimal sample perturbation assays fall short in obtaining the minimum numbers required to reach high sensitivity measurements, significant efforts may be needed to improve bulk lysis solution reagents.

Since its inception in the 1970s flow cytometry has been a valuable tool to study the characteristics of cells. Technical advancements lead to a rapid increase in the number of lasers and detectors, enabling assessment of an expanding number of parameters. As every flow cytometry user has experienced the frustration of not being able to fit all markers of interest into their panel, the prevailing mindset seemingly became the bigger the better. So, when spectral flow cytometers became commercially available, their ability to combine spectrally similar fluorophores, measure cellular autofluorescence and utilize the full light spectrum more effectively was received with enthusiasm. These attributes make spectral cytometry particularly applicable for limited or precious (clinical) material.

The recent paper from Dott et al. describes the development of a standardized protocol for sample handling, staining and acquisition, for the application of two large spectral panels in a cohort study using the ID7000™ Spectral Cell Analyzer (Sony Biotechnology).¹ The authors specifically address the repeatability and reproducibility of staining over time, which is relevant in the context of cohort studies. By combining a 34- and 35-color spectral panel, the authors were able to quantify and identify 182 cell phenotypes in whole blood samples.

Our expanding immunological knowledge of rare and unique subsets through deep profiling has necessitated the increasing number of cellular parameters required in a single panel for accurate cell identification. However, a new set of challenges arise with increasing panel size. Although the principle of panel design and analysis remain similar, assessing data quality, defining cell populations and translating phenotypic changes into biological insight become increasingly difficult. While many papers have addressed one of these challenges, Dott et al. touch upon all three of these concerns.¹

Paula Niewold: Conceptualization; writing – original draft.

The most commonly used flow cytometric (FCM) analysis of cellular DNA content relies on ethanol fixation followed by RNA digestion and propidium iodide (PI) intercalation into double-stranded DNA. This is a laborious and time-consuming procedure that is subject to systematic errors due to centrifugation and washing steps associated with sample preparation. It can adversely affect the reliability of the results. Here, we present a modified concept of DNA quantification in adherent cell lines by FCM that involves neither ethanol fixation nor any washing and cell transferring steps. Our high throughput assay of adherent cell lines reduces sample-processing time, requires minimal workload, provides a possibility for automation, and, if needed, also allows a significant reduction in the size of individual samples. Working with a well-proven commercial tool—The BD Cycletest™ Plus DNA Reagent Kit—primarily designed for cell cycle analysis and aneuploidy determination in experimental and clinical samples, we suggest a novel, very efficient, and robust approach for DNA research in adherent cell cultures.

Flow cytometry and fluorescence-activated cell sorting are widely used to study endothelial cells, for which the generation of viable single-cell suspensions is an essential first step. Two enzymatic approaches, collagenase A and dispase, are widely employed for endothelial cell isolation. In this study, the utility of both enzymatic approaches, alone and in combination, for endothelial cell isolation from juvenile and adult mouse lungs was assessed, considering the number, viability, and subtype composition of recovered endothelial cell pools. Collagenase A yielded an 8-12-fold superior recovery of viable endothelial cells from lung tissue from developing mouse pups, compared to dispase, although dispase proved superior in efficiency for epithelial cell recovery. Single-cell RNA-Seq revealed that the collagenase A approach yielded a diverse endothelial cell subtype composition of recovered endothelial cell pools, with broad representation of arterial, capillary, venous, and lymphatic lung endothelial cells; while the dispase approach yielded a recovered endothelial cell pool highly enriched for one subset of general capillary endothelial cells, but poor representation of other endothelial cells subtypes. These data indicate that tissue dissociation markedly influences the recovery of endothelial cells, and the endothelial subtype composition of recovered endothelial cell pools, as assessed by single-cell RNA-Seq.

Bladder cancer is one of the most common cancers with a high recurrence rate. Patients undergo mandatory yearly scrutinies, including cystoscopies, which makes bladder cancer highly distressing and costly. Here, we aim to develop a non-invasive, label-free method for the detection of bladder cancer cells in urine samples, which is based on interferometric imaging flow cytometry. Eight urothelial carcinoma and one normal urothelial cell lines, along with red and white blood cells, imaged quantitatively without staining by an interferometric phase microscopy module while flowing in a microfluidic chip, and classified by two machine-learning algorithms, based on deep-learning semantic segmentation convolutional neural network and extreme gradient boosting. Furthermore, urine samples obtained from bladder-cancer patients and healthy volunteers were imaged, and classified by the system. We achieved accuracy and area under the curve (AUC) of 99% and 97% for the cell lines on both machine-learning algorithms. For the real urine samples, the accuracy and AUC were 96% and 96% for the deep-learning algorithm and 95% and 93% for the gradient-boosting algorithm, respectively. By combining label-free interferometric imaging flow cytometry with high-end classification algorithms, we achieved high-performance differentiation between healthy and malignant cells. The proposed technique has the potential to supplant cystoscopy in the bladder cancer surveillance and diagnosis space.