CLANet: A comprehensive framework for cross-batch cell line identification using brightfield images.

Cell line authentication plays a crucial role in the biomedical field, ensuring researchers work with accurately identified cells. Supervised deep learning has made remarkable strides in cell line identification by studying cell morphological features through cell imaging. However, biological batch (bio-batch) effects, a significant issue stemming from the different times at which data is generated, lead to substantial shifts in the underlying data distribution, thus complicating reliable differentiation between cell lines from distinct batch cultures. To address this challenge, we introduce CLANet, a pioneering framework for cross-batch cell line identification using brightfield images, specifically designed to tackle three distinct bio-batch effects. We propose a cell cluster-level selection method to efficiently capture cell density variations, and a self-supervised learning strategy to manage image quality variations, thus producing reliable patch representations. Additionally, we adopt multiple instance learning(MIL) for effective aggregation of instance-level features for cell line identification. Our innovative time-series segment sampling module further enhances MIL's feature-learning capabilities, mitigating biases from varying incubation times across batches. We validate CLANet using data from 32 cell lines across 93 experimental bio-batches from the AstraZeneca Global Cell Bank. Our results show that CLANet outperforms related approaches (e.g. domain adaptation, MIL), demonstrating its effectiveness in addressing bio-batch effects in cell line identification.

Short tandem repeat profiling via next-generation sequencing for cell line authentication.

Cell lines are indispensable models for modern biomedical research. A large part of their usefulness derives from the ability of a cell line to proliferate over multiple passages (often indefinitely), allowing multiple experiments to be performed. However, over time, cell line identity and purity can be compromised by human errors. Cross-contamination from other cell lines and complete misidentification are both possible. Routine cell line authentication is a necessary preventive measure and has become a requirement for many funding applications and publications. Short tandem repeat (STR) profiling is the most common method for cell line authentication and is usually carried out using standard polymerase chain reaction-capillary electrophoresis analysis (STR-CE). Here, we evaluated next-generation sequencing (NGS)-based STR profiling of human and mouse cell lines at 18 and 15 loci, respectively, in a high-throughput format. Using the Python program STRight, we demonstrate that NGS-based analysis (STR-NGS) is superior to standard STR-CE in terms of the ability to report the sequence context of repeat motifs, sensitivity and flexible multiplexing capability. STR-NGS is thus a valuable alternative for cell line authentication.

Rat Hepatic Stellate Cell Line CFSC-2G: Genetic Markers and Short Tandem Repeat Profile Useful for Cell Line Authentication.

Hepatic stellate cells (HSCs) are also known as lipocytes, fat-storing cells, perisinusoidal cells, or Ito cells. These liver-specific mesenchymal cells represent about 5% to 8% of all liver cells, playing a key role in maintaining the microenvironment of the hepatic sinusoid. Upon chronic liver injury or in primary culture, these cells become activated and transdifferentiate into a contractile phenotype, i.e., the myofibroblast, capable of producing and secreting large quantities of extracellular matrix compounds. Based on their central role in the initiation and progression of chronic liver diseases, cultured HSCs are valuable in vitro tools to study molecular and cellular aspects of liver diseases. However, the isolation of these cells requires special equipment, trained personnel, and in some cases needs approval from respective authorities. To overcome these limitations, several immortalized HSC lines were established. One of these cell lines is CFSC, which was originally established from cirrhotic rat livers induced by carbon tetrachloride. First introduced in 1991, this cell line and derivatives thereof (i.e., CFSC-2G, CFSC-3H, CFSC-5H, and CFSC-8B) are now used in many laboratories as an established in vitro HSC model. We here describe molecular features that are suitable for cell authentication. Importantly, chromosome banding and multicolor spectral karyotyping (SKY) analysis demonstrate that the CFSC-2G genome has accumulated extensive chromosome rearrangements and most chromosomes exist in multiple copies producing a pseudo-triploid karyotype. Furthermore, our study documents a defined short tandem repeat (STR) profile including 31 species-specific markers, and a list of genes expressed in CFSC-2G established by bulk mRNA next-generation sequencing (NGS).

Genetic Characterization of Rat Hepatic Stellate Cell Line HSC-T6 for In Vitro Cell Line Authentication.

Immortalized hepatic stellate cells (HSCs) established from mouse, rat, and humans are valuable in vitro models for the biomedical investigation of liver biology. These cell lines are homogenous, thereby providing consistent and reproducible results. They grow more robustly than primary HSCs and provide an unlimited supply of proteins or nucleic acids for biochemical studies. Moreover, they can overcome ethical concerns associated with the use of animal and human tissue and allow for fostering of the 3R principle of replacement, reduction, and refinement proposed in 1959 by William M. S. Russell and Rex L. Burch. Nevertheless, working with continuous cell lines also has some disadvantages. In particular, there are ample examples in which genetic drift and cell misidentification has led to invalid data. Therefore, many journals and granting agencies now recommend proper cell line authentication. We herein describe the genetic characterization of the rat HSC line HSC-T6, which was introduced as a new in vitro model for the study of retinoid metabolism. The consensus chromosome markers, outlined primarily through multicolor spectral karyotyping (SKY), demonstrate that apart from the large derivative chromosome 1 (RNO1), at least two additional chromosomes (RNO4 and RNO7) are found to be in three copies in all metaphases. Additionally, we have defined a short tandem repeat (STR) profile for HSC-T6, including 31 species-specific markers. The typical features of these cells have been further determined by electron microscopy, Western blotting, and Rhodamine-Phalloidin staining. Finally, we have analyzed the transcriptome of HSC-T6 cells by mRNA sequencing (mRNA-Seq) using next generation sequencing (NGS).

Get law enforcement out of biospecimen authentication.

Use of D NA markers in research that are used in law enforcement risks undermining public trust and participation.

Cell line authentication: a necessity for reproducible biomedical research.

Immortalized or continuous cell lines are invaluable tools in basic and preclinical research. However, the widespread use of misidentified cell lines is a serious threat to scientific reproducibility. Based on the experiences of mandatory cell line authentication at the International Journal of Cancer (IJC), we provide an overview of the issues pertinent to misidentified cell lines and discuss available solutions. We also summarize the lessons learned, revealing that at least 5% of the human cell lines used in manuscripts considered for peer review are misidentified. About 4% of the considered manuscripts are rejected for severe cell line problems, and most are subsequently published in other journals. In order to diminish such malpractice and its consequences for the scientific record, we postulate that strict multi-layered quality control is essential. Besides journals and publishers, we encourage scientists, research institutions, and funders to take action on the matter and revise their respective policies. Hence, we provide concrete recommendations on introducing regular authentication schemes and staff training, and discuss future steps for enhancing good cell culture practices.

An automated cell line authentication method for AstraZeneca global cell bank using deep neural networks on brightfield images.

Cell line authentication is important in the biomedical field to ensure that researchers are not working with misidentified cells. Short tandem repeat is the gold standard method, but has its own limitations, including being expensive and time-consuming. Deep neural networks achieve great success in the analysis of cellular images in a cost-effective way. However, because of the lack of centralized available datasets, whether or not cell line authentication can be replaced or supported by cell image classification is still a question. Moreover, the relationship between the incubation times and cellular images has not been explored in previous studies. In this study, we automated the process of the cell line authentication by using deep learning analysis of brightfield cell line images. We proposed a novel multi-task framework to identify cell lines from cell images and predict the duration of how long cell lines have been incubated simultaneously. Using thirty cell lines' data from the AstraZeneca Cell Bank, we demonstrated that our proposed method can accurately identify cell lines from brightfield images with a 99.8% accuracy and predicts the incubation durations for cell images with the coefficient of determination score of 0.927. Considering that new cell lines are continually added to the AstraZeneca Cell Bank, we integrated the transfer learning technique with the proposed system to deal with data from new cell lines not included in the pre-trained model. Our method achieved excellent performance with a precision of 97.7% and recall of 95.8% in the detection of 14 new cell lines. These results demonstrated that our proposed framework can effectively identify cell lines using brightfield images.

A silver lining in cell line authentication: Short tandem repeat analysis of 1373 cases in China from 2010 to 2019.

Continuous cell lines are practical models that are widely used in the study of disease mechanisms and particularly cancers. However, the issue of cell line cross-contamination has existed since the 1960s, despite repeated advocation for cell line authentication by many experts. Furthermore, cell line abuse has been underestimated and underreported. The China Center for Type Culture Collection (CCTCC) received 1373 cell samples for authentication from 2010 to 2019, and has found that the quality of cell lines has improved during this time, offering a positive outlook for the future.

Transposable element profiles reveal cell line identity and loss of heterozygosity in Drosophila cell culture.

Cell culture systems allow key insights into biological mechanisms yet suffer from irreproducible outcomes in part because of cross-contamination or mislabeling of cell lines. Cell line misidentification can be mitigated by the use of genotyping protocols, which have been developed for human cell lines but are lacking for many important model species. Here, we leverage the classical observation that transposable elements (TEs) proliferate in cultured Drosophila cells to demonstrate that genome-wide TE insertion profiles can reveal the identity and provenance of Drosophila cell lines. We identify multiple cases where TE profiles clarify the origin of Drosophila cell lines (Sg4, mbn2, and OSS_E) relative to published reports, and also provide evidence that insertions from only a subset of long-terminal repeat retrotransposon families are necessary to mark Drosophila cell line identity. We also develop a new bioinformatics approach to detect TE insertions and estimate intra-sample allele frequencies in legacy whole-genome sequencing data (called ngs_te_mapper2), which revealed loss of heterozygosity as a mechanism shaping the unique TE profiles that identify Drosophila cell lines. Our work contributes to the general understanding of the forces impacting metazoan genomes as they evolve in cell culture and paves the way for high-throughput protocols that use TE insertions to authenticate cell lines in Drosophila and other organisms.

High-throughput sequencing for species authentication and contamination detection of 63 cell lines.

Cell lines are widely used in research and for diagnostic tests and are often shared between laboratories. Lack of cell line authentication can result in the use of contaminated or misidentified cell lines, potentially affecting the results from research and diagnostic activities. Cell line authentication and contamination detection based on metagenomic high-throughput sequencing (HTS) was tested on DNA and RNA from 63 cell lines available at the Canadian Food Inspection Agency's National Centre for Foreign Animal Disease. Through sequence comparison of the cytochrome c oxidase subunit 1 (COX1) gene, the species identity of 53 cell lines was confirmed, and eight cell lines were found to show a greater pairwise nucleotide identity in the COX1 sequence of a different species within the same expected genus. Two cell lines, LFBK-αvß6 and SCP-HS, were determined to be composed of cells from a different species and genus. Mycoplasma contamination was not detected in any cell lines. However, several expected and unexpected viral sequences were detected, including part of the classical swine fever virus genome in the IB-RS-2 Clone D10 cell line. Metagenomics-based HTS is a useful laboratory QA tool for cell line authentication and contamination detection that should be conducted regularly.

Cell Coding Arrays Based on Fluorescent Glycan Nanoparticles for Cell Line Identification and Cell Contamination Evaluation.

Cell lines are applied on a large scale in the field of biomedicine, but they are susceptible to issues such as misidentification and cross-contamination. This situation is becoming worse over time due to the rapid growth of the biomedical field, and thus there is an urgent need for a more effective strategy to address the problem. As described herein, a cell coding method is established based on two types of uniform and stable glycan nanoparticles that are synthesized using the graft-copolymerization-induced self-assembly (GISA) method, which further exhibit distinct fluorescent properties due to elaborate modification with fluorescent labeling molecules. The different affinity between each nanoparticle and various cell lines results in clearly distinguishable differences in their endocytosis degrees, thus resulting in distinct characteristic fluorescence intensities. Through flow cytometry measurements, the specific signals of each cell sample can be recorded and turned into a map divided into different regions by statistical processing. Using this sensing array strategy, we have successfully identified six human cell lines, including one normal type and five tumor types. Moreover, cell contamination evaluation of different cell lines with HeLa cells as the contaminant in a semiquantitative analysis has also been successfully achieved. Notably, the whole process of nanoparticle fabrication and fluorescent testing is facile and the results are highly reliable.

Traceability Methods for Cell Line Authentication and Mycoplasma Detection.

Many laboratories struggle with mycoplasma contamination and cell line misidentification when growing cells in culture. These well-documented issues affect the scientific research community and have detrimental downstream effects. Research published with suspect cultures can produce misleading results. There is increasing pressure to verify the integrity of experimental and established cell lines before publishing. Therefore, laboratories need to define how and when to perform these critical tests, analyze the results, and determine action plans if disparities exist. Our laboratory is committed to producing cell lines of the highest quality for use in experiments; thus, we created a surveillance strategy for these potential problems. We developed processes for both testing and tracing cell line authentication and mycoplasma detection data. Using these methods, we can protect the integrity of our patient and commercial cell lines, maintaining reliable cultures for our research.

Characterization of genetically defined sporadic and hereditary type 1 papillary renal cell carcinoma cell lines.

Renal cell carcinoma (RCC) is not a single disease but is made up of several different histologically defined subtypes that are associated with distinct genetic alterations which require subtype specific management and treatment. Papillary renal cell carcinoma (pRCC) is the second most common subtype after conventional/clear cell RCC (ccRCC), representing ~20% of cases, and is subcategorized into type 1 and type 2 pRCC. It is important for preclinical studies to have cell lines that accurately represent each specific RCC subtype. This study characterizes seven cell lines derived from both primary and metastatic sites of type 1 pRCC, including the first cell line derived from a hereditary papillary renal carcinoma (HPRC)-associated tumor. Complete or partial gain of chromosome 7 was observed in all cell lines and other common gains of chromosomes 16, 17, or 20 were seen in several cell lines. Activating mutations of MET were present in three cell lines that all demonstrated increased MET phosphorylation in response to HGF and abrogation of MET phosphorylation in response to MET inhibitors. CDKN2A loss due to mutation or gene deletion, associated with poor outcomes in type 1 pRCC patients, was observed in all cell line models. Six cell lines formed tumor xenografts in athymic nude mice and thus provide in vivo models of type 1 pRCC. These type 1 pRCC cell lines provide a comprehensive representation of the genetic alterations associated with pRCC that will give insight into the biology of this disease and be ideal preclinical models for therapeutic studies.

Novel immortalized human vocal fold epithelial cell line: In vitro tool for mucosal biology.

Study of vocal fold (VF) mucosal biology requires essential human vocal fold epithelial cell (hVFE) lines for use in appropriate model systems. We steadily transfected a retroviral construct containing human telomerase reverse transcriptase (hTERT) into primary normal hVFE to establish a continuously replicating hVFE cell line. Immortalized hVFE across passages have cobblestone morphology, express epithelial markers cytokeratin 4, 13 and 14, induced hTERT gene and protein expression, have similar RNAseq profiling, and can continuously grow for more than 8 months. DNA fingerprinting and karyotype analysis demonstrated that immortalized hVFE were consistent with the presence of a single cell line. Validation of the hVFE, in a three-dimensional in vitro VF mucosal construct revealed a multilayered epithelial structure with VF epithelial cell markers. Wound scratch assay revealed higher migration capability of the immortalized hVFE on the surface of collagen-fibronectin and collagen gel containing human vocal fold fibroblasts (hVFF). Collectively, our report demonstrates the first immortalized hVFE from true VFs providing a novel and invaluable tool for the study of epithelial cell-fibroblast interactions that dictate disease and health of this specialized tissue.

Short tandem repeat profiling for the authentication of cancer stem-like cells.

Colorectal and glioblastoma cancer stem-like cells (CSCs) are essential for translational research. Cell line authentication by short tandem repeat (STR) profiling ensures reproducibility of results in oncology research. This technique enables to identify mislabeling or cross-contamination of cell lines. In our study, we provide a reference dataset for a panel of colorectal and glioblastoma CSCs that allows authentication. Each cell line was entered into the cell Line Integrated Molecular Authentication database 2.1 to be compared to the STR profiles of 4485 tumor cell lines. This article also provides clinical data of patients from whom CSCs arose and data on the parent tumor stage and mutations. STR profiles and information of our CSCs are also available in the Cellosaurus database (ExPASy) as identified by unique research resource identifier codes.

Establishment and Characterization of a Sclerosing Spindle Cell Rhabdomyosarcoma Cell Line with a Complex Genomic Profile.

Sclerosing spindle cell rhabdomyosarcoma (SSRMS) is a rare rhabdomyosarcomas (RMS) subtype. Especially cases bearing a myogenic differentiation 1 (MYOD1) mutation are characterized by a high recurrence and metastasis rate, often leading to a fatal outcome. SSRMS cell lines are valuable in vitro models for studying disease mechanisms and for the preclinical evaluation of new therapeutic approaches. In this study, a cell line established from a primary SSRMS tumor of a 24-year-old female after multimodal chemotherapeutic pretreatment has been characterized in detail, including immunohistochemistry, growth characteristics, cytogenetic analysis, mutation analysis, evaluation of stem cell marker expression, differentiation potential, and tumorigenicity in mice. The cell line which was designated SRH exhibited a complex genomic profile, including several translocations and deletions. Array-comparative genomic hybridization (CGH) revealed an overall predominating loss of gene loci. The mesenchymal tumor origin was underlined by the expression of mesenchymal markers and potential to undergo adipogenic and osteogenic differentiation. Despite myogenic marker expression, terminal myogenic differentiation was inhibited, which might be elicited by the MYOD1 hotspot mutation. In vivo tumorigenicity could be confirmed after subcutaneous injection into NOD/SCID/γcnull mice. Summarized, the SRH cell line is the first adult SSRMS cell line available for preclinical research on this rare RMS subtype.

Effect of a Lens Protein in Low-Temperature Culture of Novel Immortalized Human Lens Epithelial Cells (iHLEC-NY2).

The prevalence of nuclear cataracts was observed to be significantly higher among residents of tropical and subtropical regions compared to those of temperate and subarctic regions. We hypothesized that elevated environmental temperatures may pose a risk of nuclear cataract development. The results of our in silico simulation revealed that in temperate and tropical regions, the human lens temperature ranges from 35.0 °C to 37.5 °C depending on the environmental temperature. The medium temperature changes during the replacement regularly in the cell culture experiment were carefully monitored using a sensor connected to a thermometer and showed a decrease of 1.9 °C, 3.0 °C, 1.7 °C, and 0.1 °C, after 5 min when setting the temperature of the heat plate device at 35.0 °C, 37.5 °C, 40.0 °C, and 42.5 °C, respectively. In the newly created immortalized human lens epithelial cell line clone NY2 (iHLEC-NY2), the amounts of RNA synthesis of αA crystallin, protein expression, and amyloid ß (Aß)1-40 secreted into the medium were increased at the culture temperature of 37.5 °C compared to 35.0 °C. In short-term culture experiments, the secretion of Aß1-40 observed in cataracts was increased at 37.5 °C compared to 35.0 °C, suggesting that the long-term exposure to a high-temperature environment may increase the risk of cataracts.

Towards image-based cancer cell lines authentication using deep neural networks.

Although short tandem repeat (STR) analysis is available as a reliable method for the determination of the genetic origin of cell lines, the occurrence of misauthenticated cell lines remains an important issue. Reasons include the cost, effort and time associated with STR analysis. Moreover, there are currently no methods for the discrimination between isogenic cell lines (cell lines of the same genetic origin, e.g. different cell lines derived from the same organism, clonal sublines, sublines adapted to grow under certain conditions). Hence, additional complementary, ideally low-cost and low-effort methods are required that enable (1) the monitoring of cell line identity as part of the daily laboratory routine and 2) the authentication of isogenic cell lines. In this research, we automate the process of cell line identification by image-based analysis using deep convolutional neural networks. Two different convolutional neural networks models (MobileNet and InceptionResNet V2) were trained to automatically identify four parental cancer cell line (COLO 704, EFO-21, EFO-27 and UKF-NB-3) and their sublines adapted to the anti-cancer drugs cisplatin (COLO-704rCDDP1000, EFO-21rCDDP2000, EFO-27rCDDP2000) or oxaliplatin (UKF-NB-3rOXALI2000), hence resulting in an eight-class problem. Our best performing model, InceptionResNet V2, achieved an average of 0.91 F1-score on tenfold cross validation with an average area under the curve (AUC) of 0.95, for the 8-class problem. Our best model also achieved an average F1-score of 0.94 and 0.96 on the authentication through a classification process of the four parental cell lines and the respective drug-adapted cells, respectively, on a four-class problem separately. These findings provide the basis for further development of the application of deep learning for the automation of cell line authentication into a readily available easy-to-use methodology that enables routine monitoring of the identity of cell lines including isogenic cell lines. It should be noted that, this is just a proof of principal that, images can also be used as a method for authentication of cancer cell lines and not a replacement for the STR method.

Advantages of a 21-loci short tandem repeat method for detection of cross-contamination in human cell lines.

Cross-contamination of cell lines is a highly relevant and pervasive problem. The analysis of short tandem repeats (STR) is a simple and commercially available technique to authenticate cell lines for more than two decades. At present, STR multiple amplification kits have been developed up to 21 loci while the current STR databases only provide 9-loci STR profiles. Here, we compared the advantages of 21-loci STR methodology using the same algorithm as 9-loci method. The 21-loci method reduced the uncertainty ratio for authentications by 97.5% relative to the 9-loci method and exclude effectively false positive. We show that the additional 12 loci helped to greatly reduce sample-site marker specificity arising from genetic isolation and the occurrence of null alleles, suggesting that inclusion of additional loci in these databases will ultimately improve the efficiency and accuracy of authentication of cell lines. Taken together, we demonstrate the utility of a 21-loci method in human cells, providing a novel marker panel for use as a valuable alternative to 9-loci analyses to minimize cell line authentication errors and reduce costs due to erroneous experiments.