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Technical Pitfalls and Biases in Molecular Biology

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biology".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 32829

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Pharmazentrum Frankfurt, Dept. of Clinical Pharmacology, Goethe-University of Frankfurt, Theodor Stern Kai 7, Bd. 74, 4th Fl, 60590 Frankfurt am Main, Germany
Interests: nerve injury and neuropathic pain; pain and aging; central adaptations to chronic pain; multiple sclerosis; neuroinflammation; neuro-immunologic communication; redox signaling; nitric oxide; endocannabinoids and other lipid signaling molecules; progranulin; autophagy
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Special Issue Information

Dear Colleagues,

The enormous progress of research techniques and tools and a steadily growing wealth of data increases the risk of putative technical errors, analytical biases, and erroneous analysis or mal-interpretation of research data. This Special Issue offers a platform to publish such errors and biases to increase the awareness and to improve the measures against such biases. For example, the off-target effects of gene manipulation or pharmacological interventions may produce unexpected effects, transgenic models may turn out to be something else, antibodies may un-specifically detect other proteins, alternative methods for normalization of omics data may yield controversial results, DNA/RNA extraction procedures may have a stronger effect on results than genotype or treatment, and differences between labs or day-to-day variability may be greater than the biological variability.

This Special Issue aims to gather a unique collection of original research articles and reviews, that address the occurrence, recognition, and avoidance of biases and errors and sharpen the awareness of experimental and data-analysis-based pitfalls. We welcome the submission of articles that cover, but are not limited to, the following topics:

  • Analytical biases owing to sample handling or pre-analytical processing
  • Impact of extraction procedures for DNA/RNA, proteins, metabolites, etc.
  • Off-target effects of drugs or gene/protein manipulations
  • Un-specificity of immune – or RNA-based detection and quantification methods
  • Data-analysis based biases owing to normalization, data transformation, low expression genes/protein, low sample sizes, use of statistical methods, etc.
  • Variability between labs or researchers versus biological variability
  • Confounding influences of environmental factors
  • Methods for visualizing biases

Prof. Dr. Irmgard Tegeder
Guest Editor

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Keywords

  • analytical and technical biases
  • molecular biology
  • reproducibility
  • biological versus technical variability
  • agreement of continuous variables
  • artifacts

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Published Papers (12 papers)

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14 pages, 7661 KiB  
Article
Comparison of Four Methods of RNA Extraction and cDNA Synthesis from The Venom of Peruvian Snakes of the Genus Bothrops of Clinical Importance
by Daniel Torrejón, Javier Cárdenas, Diana Juárez, Jordano Espinoza, Alex Proleón, Andrés Agurto-Arteaga, Fanny Lazo, Mariana Leguía, Félix A. Urra, Eladio F. Sánchez, Carlos Chávez-Olortegui, Dan E. Vivas-Ruiz and Armando Yarlequé
Int. J. Mol. Sci. 2023, 24(13), 11161; https://doi.org/10.3390/ijms241311161 - 6 Jul 2023
Cited by 1 | Viewed by 2418
Abstract
RNA purification and cDNA synthesis represents the starting point for molecular analyses of snake venom proteins-enzymes. Usually, the sacrifice of snakes is necessary for venom gland extraction to identify protein-coding transcripts; however, the venom can be used as a source of transcripts. Although [...] Read more.
RNA purification and cDNA synthesis represents the starting point for molecular analyses of snake venom proteins-enzymes. Usually, the sacrifice of snakes is necessary for venom gland extraction to identify protein-coding transcripts; however, the venom can be used as a source of transcripts. Although there are methods for obtaining RNA from venom, no comparative analysis has been conducted in the Bothrops genus. In the present study, we compared four commercial methods for RNA purification and cDNA synthesis from venom (liquid, lyophilized, or long-term storage) of four clinically relevant species of Peruvian Bothrops. Our results show that the TRIzol method presents the highest yield of RNA purified from venom (59 ± 11 ng/100 µL or 10 mg). The SuperScript First-Strand Synthesis System kit produced high amounts of cDNA (3.2 ± 1.2 ng cDNA/ng RNA), and the highest value was from combination with the Dynabeads mRNA DIRECT kit (4.8 ± 2.0 ng cDNA/ng RNA). The utility of cDNA was demonstrated with the amplification of six relevant toxins: thrombin-like enzymes, P-I and P-III metalloproteinases, acid and basic phospholipases A2, and disintegrins. To our knowledge, this is the first comparative study of RNA purification and cDNA synthesis methodologies from Bothrops genus venom. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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18 pages, 29198 KiB  
Article
Single and Joined Behaviour of Circulating Biomarkers and Metabolic Parameters in High-Fit and Low-Fit Healthy Females
by Joëlle J. E. Janssen, Bart Lagerwaard, Arie G. Nieuwenhuizen, Xavier Escoté, Núria Canela, Josep M. del Bas, Vincent C. J. de Boer and Jaap Keijer
Int. J. Mol. Sci. 2023, 24(4), 4202; https://doi.org/10.3390/ijms24044202 - 20 Feb 2023
Cited by 4 | Viewed by 1613
Abstract
Biomarkers are important in the assessment of health and disease, but are poorly studied in still healthy individuals with a (potential) different risk for metabolic disease. This study investigated, first, how single biomarkers and metabolic parameters, functional biomarker and metabolic parameter categories, and [...] Read more.
Biomarkers are important in the assessment of health and disease, but are poorly studied in still healthy individuals with a (potential) different risk for metabolic disease. This study investigated, first, how single biomarkers and metabolic parameters, functional biomarker and metabolic parameter categories, and total biomarker and metabolic parameter profiles behave in young healthy female adults of different aerobic fitness and, second, how these biomarkers and metabolic parameters are affected by recent exercise in these healthy individuals. A total of 102 biomarkers and metabolic parameters were analysed in serum or plasma samples from 30 young, healthy, female adults divided into a high-fit (V̇O2peak ≥ 47 mL/kg/min, N = 15) and a low-fit (V̇O2peak ≤ 37 mL/kg/min, N = 15) group, at baseline and overnight after a single bout of exercise (60 min, 70% V̇O2peak). Our results show that total biomarker and metabolic parameter profiles were similar between high-fit and low-fit females. Recent exercise significantly affected several single biomarkers and metabolic parameters, mostly related to inflammation and lipid metabolism. Furthermore, functional biomarker and metabolic parameter categories corresponded to biomarker and metabolic parameter clusters generated via hierarchical clustering models. In conclusion, this study provides insight into the single and joined behavior of circulating biomarkers and metabolic parameters in healthy females, and identified functional biomarker and metabolic parameter categories that may be used for the characterisation of human health physiology. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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13 pages, 3763 KiB  
Article
Robust Classification Using Posterior Probability Threshold Computation Followed by Voronoi Cell Based Class Assignment Circumventing Pitfalls of Bayesian Analysis of Biomedical Data
by Alfred Ultsch and Jörn Lötsch
Int. J. Mol. Sci. 2022, 23(22), 14081; https://doi.org/10.3390/ijms232214081 - 15 Nov 2022
Viewed by 1686
Abstract
Bayesian inference is ubiquitous in science and widely used in biomedical research such as cell sorting or “omics” approaches, as well as in machine learning (ML), artificial neural networks, and “big data” applications. However, the calculation is not robust in regions of low [...] Read more.
Bayesian inference is ubiquitous in science and widely used in biomedical research such as cell sorting or “omics” approaches, as well as in machine learning (ML), artificial neural networks, and “big data” applications. However, the calculation is not robust in regions of low evidence. In cases where one group has a lower mean but a higher variance than another group, new cases with larger values are implausibly assigned to the group with typically smaller values. An approach for a robust extension of Bayesian inference is proposed that proceeds in two main steps starting from the Bayesian posterior probabilities. First, cases with low evidence are labeled as “uncertain” class membership. The boundary for low probabilities of class assignment (threshold ε) is calculated using a computed ABC analysis as a data-based technique for item categorization. This leaves a number of cases with uncertain classification (p < ε). Second, cases with uncertain class membership are relabeled based on the distance to neighboring classified cases based on Voronoi cells. The approach is demonstrated on biomedical data typically analyzed with Bayesian statistics, such as flow cytometric data sets or biomarkers used in medical diagnostics, where it increased the class assignment accuracy by 1–10% depending on the data set. The proposed extension of the Bayesian inference of class membership can be used to obtain robust and plausible class assignments even for data at the extremes of the distribution and/or for which evidence is weak. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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12 pages, 1515 KiB  
Article
Non-Reproducibility of Oral Rotenone as a Model for Parkinson’s Disease in Mice
by Ellen Niederberger, Annett Wilken-Schmitz, Christine Manderscheid, Yannick Schreiber, Robert Gurke and Irmgard Tegeder
Int. J. Mol. Sci. 2022, 23(20), 12658; https://doi.org/10.3390/ijms232012658 - 21 Oct 2022
Cited by 1 | Viewed by 2230
Abstract
Oral rotenone has been proposed as a model for Parkinson’s disease (PD) in mice. To establish the model in our lab and study complex behavior we followed a published treatment regimen. C57BL/6 mice received 30 mg/kg body weight of rotenone once daily via [...] Read more.
Oral rotenone has been proposed as a model for Parkinson’s disease (PD) in mice. To establish the model in our lab and study complex behavior we followed a published treatment regimen. C57BL/6 mice received 30 mg/kg body weight of rotenone once daily via oral administration for 4 and 8 weeks. Motor functions were assessed by RotaRod running. Immunofluorescence studies were used to analyze the morphology of dopaminergic neurons, the expression of alpha-Synuclein (α-Syn), and inflammatory gliosis or infiltration in the substantia nigra. Rotenone-treated mice did not gain body weight during treatment compared with about 4 g in vehicle-treated mice, which was however the only robust manifestation of drug treatment and suggested local gut damage. Rotenone-treated mice had no deficits in motor behavior, no loss or sign of degeneration of dopaminergic neurons, no α-Syn accumulation, and only mild microgliosis, the latter likely an indirect remote effect of rotenone-evoked gut dysbiosis. Searching for explanations for the model failure, we analyzed rotenone plasma concentrations via LC-MS/MS 2 h after administration of the last dose to assess bioavailability. Rotenone was not detectable in plasma at a lower limit of quantification of 2 ng/mL (5 nM), showing that oral rotenone had insufficient bioavailability to achieve sustained systemic drug levels in mice. Hence, oral rotenone caused local gastrointestinal toxicity evident as lack of weight gain but failed to evoke behavioral or biological correlates of PD within 8 weeks. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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18 pages, 7530 KiB  
Article
Single-Step Fast Tissue Clearing of Thick Mouse Brain Tissue for Multi-Dimensional High-Resolution Imaging
by Youngjae Ryu, Yoonju Kim, Hye Ryeong Lim, Hyung-Joon Kim, Byong Seo Park, Jae Geun Kim, Sang-Joon Park and Chang Man Ha
Int. J. Mol. Sci. 2022, 23(12), 6826; https://doi.org/10.3390/ijms23126826 - 19 Jun 2022
Cited by 1 | Viewed by 3801
Abstract
Recent advances in optical clearing techniques have dramatically improved deep tissue imaging by reducing the obscuring effects of light scattering and absorption. However, these optical clearing methods require specialized equipment or a lengthy undertaking with complex protocols that can lead to sample volume [...] Read more.
Recent advances in optical clearing techniques have dramatically improved deep tissue imaging by reducing the obscuring effects of light scattering and absorption. However, these optical clearing methods require specialized equipment or a lengthy undertaking with complex protocols that can lead to sample volume changes and distortion. In addition, the imaging of cleared tissues has limitations, such as fluorescence bleaching, harmful and foul-smelling solutions, and the difficulty of handling samples in high-viscosity refractive index (RI) matching solutions. To address the various limitations of thick tissue imaging, we developed an Aqueous high refractive Index matching and tissue Clearing solution for Imaging (termed AICI) with a one-step tissue clearing protocol that was easily made at a reasonable price in our own laboratory without any equipment. AICI can rapidly clear a 1 mm thick brain slice within 90 min with simultaneous RI matching, low viscosity, and a high refractive index (RI = 1.466), allowing the imaging of the sample without additional processing. We compared AICI with commercially available RI matching solutions, including optical clear agents (OCAs), for tissue clearing. The viscosity of AICI is closer to that of water compared with other RI matching solutions, and there was a less than 2.3% expansion in the tissue linear morphology during 24 h exposure to AICI. Moreover, AICI remained fluid over 30 days of air exposure, and the EGFP fluorescence signal was only reduced to ~65% after 10 days. AICI showed a limited clearing of brain tissue >3 mm thick. However, fine neuronal structures, such as dendritic spines and axonal boutons, could still be imaged in thick brain slices treated with AICI. Therefore, AICI is useful not only for the three-dimensional (3D) high-resolution identification of neuronal structures, but also for the examination of multiple structural imaging by neuronal distribution, projection, and gene expression in deep brain tissue. AICI is applicable beyond the imaging of fluorescent antibodies and dyes, and can clear a variety of tissue types, making it broadly useful to researchers for optical imaging applications. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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9 pages, 779 KiB  
Article
Binding of Citrate-Fe3+ to Plastic Culture Dishes, an Artefact Useful as a Simple Technique to Screen for New Iron Chelators
by Jiro Ogura, Toshihiro Sato, Kei Higuchi, Sathish Sivaprakasam, Jonathan Kopel, Yangzom D. Bhutia and Vadivel Ganapathy
Int. J. Mol. Sci. 2022, 23(12), 6657; https://doi.org/10.3390/ijms23126657 - 15 Jun 2022
Viewed by 1491
Abstract
NaCT mediates citrate uptake in the liver cell line HepG2. When these cells were exposed to iron (Fe3+), citrate uptake/binding as monitored by the association of [14C]-citrate with cells increased. However, there was no change in NaCT expression and [...] Read more.
NaCT mediates citrate uptake in the liver cell line HepG2. When these cells were exposed to iron (Fe3+), citrate uptake/binding as monitored by the association of [14C]-citrate with cells increased. However, there was no change in NaCT expression and function, indicating that NaCT was not responsible for this Fe3+-induced citrate uptake/binding. Interestingly however, the process exhibited substrate selectivity and saturability as if the process was mediated by a transporter. Notwithstanding these features, subsequent studies demonstrated that the iron-induced citrate uptake/binding did not involve citrate entry into cells; instead, the increase was due to the formation of citrate-Fe3+ chelate that adsorbed to the cell surface. Surprisingly, the same phenomenon was observed in culture wells without HepG2 cells, indicating the adsorption of the citrate-Fe3+ chelate to the plastic surface of culture wells. We used this interesting phenomenon as a simple screening technique for new iron chelators with the logic that if another iron chelator is present in the assay system, it would compete with citrate for binding to Fe3+ and prevent the formation and adsorption of citrate-Fe3+ to the culture well. This technique was validated with the known iron chelators deferiprone and deferoxamine, and with the bacterial siderophore 2,3-dihydroxybenzoic acid and the catechol carbidopa. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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19 pages, 25620 KiB  
Article
Efficient Isolation and Functional Characterization of Niche Cells from Human Corneal Limbus
by Naresh Polisetti, Lyne Sharaf, Ursula Schlötzer-Schrehardt, Günther Schlunck and Thomas Reinhard
Int. J. Mol. Sci. 2022, 23(5), 2750; https://doi.org/10.3390/ijms23052750 - 2 Mar 2022
Cited by 10 | Viewed by 2700
Abstract
The fate decision of limbal epithelial progenitor cells (LEPC) at the human corneal limbus is determined by the surrounding microenvironment with limbal niche cells (LNC) as one of its essential components. Research on freshly isolated LNC which mainly include limbal mesenchymal stromal cells [...] Read more.
The fate decision of limbal epithelial progenitor cells (LEPC) at the human corneal limbus is determined by the surrounding microenvironment with limbal niche cells (LNC) as one of its essential components. Research on freshly isolated LNC which mainly include limbal mesenchymal stromal cells (LMSC) and limbal melanocytes (LM) has been hampered by a lack of efficient protocols to isolate and purify these cells. We devised a protocol for rapid retrieval of pure LMSC, LM and LEPC populations by collagenase digestion of limbal tissue and subsequent fluorescence-activated cell sorting (FACS) using antibodies against CD90 and CD117. The sorted cells were characterized by immunophenotyping and functional assays. The effects of LMSC and LM on LEPC were studied in 3D co-cultures and LEPC differentiation status was assessed by immunohistochemistry. Enzymatic digestion and flow sorting yielded pure populations of LMSC (CD117CD90+), LM (CD117+CD90), and LEPC (CD117CD90). The LMSC exhibited self-renewal capacity (55.0 ± 4.6 population doublings), expressed mesenchymal stem cell markers (CD73, CD90, CD105, and CD44), and transdifferentiated to adipocytes, osteocytes, or chondrocytes. The LM exhibited self-renewal capacity and sustained melanin production. The sorted LEPC expressed epithelial progenitor markers (CK14, CK19, and CK15) and showed a colony-forming ability. Co-cultivation of LMSC and LM with LEPC resulted in a 4–5-layered stratified epithelium and supported the preservation of a LEPC phenotype, as reflected by increased p63+ and Ki67+ cells and decreased CK12+ cells compared with LEPC monocultures. A highly efficient isolation of pure LM, LMSC, and LEPC populations from a single preparation may allow for direct transcriptomic and proteomic profiling as well as functional studies on native unpassaged LNC, which can be considered as proper equivalents of LNC in vivo. The developed biomimetic 3D co-culture method could provide an experimental model for investigating the functional role of LNC in the limbal stem cell niche. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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14 pages, 3568 KiB  
Article
Failure of Diphtheria Toxin Model to Induce Parkinson-Like Behavior in Mice
by Lucie Valek and Irmgard Tegeder
Int. J. Mol. Sci. 2021, 22(17), 9496; https://doi.org/10.3390/ijms22179496 - 31 Aug 2021
Cited by 5 | Viewed by 4153
Abstract
Rodent models of Parkinson’s disease are based on transgenic expression of mutant synuclein, deletion of PD genes, injections of MPTP or rotenone, or seeding of synuclein fibrils. The models show histopathologic features of PD such as Lewi bodies but mostly only subtle in [...] Read more.
Rodent models of Parkinson’s disease are based on transgenic expression of mutant synuclein, deletion of PD genes, injections of MPTP or rotenone, or seeding of synuclein fibrils. The models show histopathologic features of PD such as Lewi bodies but mostly only subtle in vivo manifestations or systemic toxicity. The models only partly mimic a predominant loss of dopaminergic neurons in the substantia nigra. We therefore generated mice that express the transgenic diphtheria toxin receptor (DTR) specifically in DA neurons by crossing DAT-Cre mice with Rosa26 loxP-STOP-loxP DTR mice. After defining a well-tolerated DTx dose, DAT-DTR and DTR-flfl controls were subjected to non-toxic DTx treatment (5 × 100 pg/g) and subsequent histology and behavioral tests. DAT protein levels were reduced in the midbrain, and tyrosine hydroxylase-positive neurons were reduced in the substantia nigra, whereas the pan-neuronal marker NeuN was not affected. Despite the promising histologic results, there was no difference in motor function tests or open field behavior. These are tests in which double mutant Pink1−/−SNCAA53T Parkinson mice show behavioral abnormalities. Higher doses of DTx were toxic in both groups. The data suggest that DTx treatment in mice with Cre/loxP-driven DAT-DTR expression leads to partial ablation of DA-neurons but without PD-reminiscent behavioral correlates. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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10 pages, 1559 KiB  
Communication
Evaluation of Stable LifeAct-mRuby2- and LAMP1-NeonGreen Expressing A549 Cell Lines for Investigation of Aspergillus fumigatus Interaction with Pulmonary Cells
by Natalia Schiefermeier-Mach, Violetta Moresco, Stephan Geley, Lea Heinrich, Lukas Lechner, Heidi Oberhauser and Susanne Perkhofer
Int. J. Mol. Sci. 2021, 22(11), 5965; https://doi.org/10.3390/ijms22115965 - 31 May 2021
Viewed by 2477
Abstract
Inhaled Aspergillus fumigatus spores can be internalized by alveolar type II cells. Cell lines stably expressing fluorescently labeled components of endocytic pathway enable investigations of intracellular organization during conidia internalization and measurement of the process kinetics. The goal of this report was to [...] Read more.
Inhaled Aspergillus fumigatus spores can be internalized by alveolar type II cells. Cell lines stably expressing fluorescently labeled components of endocytic pathway enable investigations of intracellular organization during conidia internalization and measurement of the process kinetics. The goal of this report was to evaluate the methodological appliance of cell lines for studying fungal conidia internalization. We have generated A549 cell lines stably expressing fluorescently labeled actin (LifeAct-mRuby2) and late endosomal protein (LAMP1-NeonGreen) following an evaluation of cell-pathogen interactions in live and fixed cells. Our data show that the LAMP1-NeonGreen cell line can be used to visualize conidia co-localization with LAMP1 in live and fixed cells. However, caution is necessary when using LifeAct-mRuby2-cell lines as it may affect the conidia internalization dynamics. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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13 pages, 8269 KiB  
Article
Current Projection Methods-Induced Biases at Subgroup Detection for Machine-Learning Based Data-Analysis of Biomedical Data
by Jörn Lötsch and Alfred Ultsch
Int. J. Mol. Sci. 2020, 21(1), 79; https://doi.org/10.3390/ijms21010079 - 20 Dec 2019
Cited by 15 | Viewed by 2619
Abstract
Advances in flow cytometry enable the acquisition of large and high-dimensional data sets per patient. Novel computational techniques allow the visualization of structures in these data and, finally, the identification of relevant subgroups. Correct data visualizations and projections from the high-dimensional space to [...] Read more.
Advances in flow cytometry enable the acquisition of large and high-dimensional data sets per patient. Novel computational techniques allow the visualization of structures in these data and, finally, the identification of relevant subgroups. Correct data visualizations and projections from the high-dimensional space to the visualization plane require the correct representation of the structures in the data. This work shows that frequently used techniques are unreliable in this respect. One of the most important methods for data projection in this area is the t-distributed stochastic neighbor embedding (t-SNE). We analyzed its performance on artificial and real biomedical data sets. t-SNE introduced a cluster structure for homogeneously distributed data that did not contain any subgroup structure. In other data sets, t-SNE occasionally suggested the wrong number of subgroups or projected data points belonging to different subgroups, as if belonging to the same subgroup. As an alternative approach, emergent self-organizing maps (ESOM) were used in combination with U-matrix methods. This approach allowed the correct identification of homogeneous data while in sets containing distance or density-based subgroups structures; the number of subgroups and data point assignments were correctly displayed. The results highlight possible pitfalls in the use of a currently widely applied algorithmic technique for the detection of subgroups in high dimensional cytometric data and suggest a robust alternative. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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19 pages, 2156 KiB  
Article
Discrimination of DNA Methylation Signal from Background Variation for Clinical Diagnostics
by Robersy Sanchez, Xiaodong Yang, Thomas Maher and Sally A. Mackenzie
Int. J. Mol. Sci. 2019, 20(21), 5343; https://doi.org/10.3390/ijms20215343 - 27 Oct 2019
Cited by 9 | Viewed by 3902
Abstract
Advances in the study of human DNA methylation variation offer a new avenue for the translation of epigenetic research results to clinical applications. Although current approaches to methylome analysis have been helpful in revealing an epigenetic influence in major human diseases, this type [...] Read more.
Advances in the study of human DNA methylation variation offer a new avenue for the translation of epigenetic research results to clinical applications. Although current approaches to methylome analysis have been helpful in revealing an epigenetic influence in major human diseases, this type of analysis has proven inadequate for the translation of these advances to clinical diagnostics. As in any clinical test, the use of a methylation signal for diagnostic purposes requires the estimation of an optimal cutoff value for the signal, which is necessary to discriminate a signal induced by a disease state from natural background variation. To address this issue, we propose the application of a fundamental signal detection theory and machine learning approaches. Simulation studies and tests of two available methylome datasets from autism and leukemia patients demonstrate the feasibility of this approach in clinical diagnostics, providing high discriminatory power for the methylation signal induced by disease, as well as high classification performance. Specifically, the analysis of whole biomarker genomic regions could suffice for a diagnostic, markedly decreasing its cost. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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12 pages, 3396 KiB  
Protocol
Efficient Isolation and Expansion of Limbal Melanocytes for Tissue Engineering
by Naresh Polisetti, Thomas Reinhard and Günther Schlunck
Int. J. Mol. Sci. 2023, 24(9), 7827; https://doi.org/10.3390/ijms24097827 - 25 Apr 2023
Cited by 1 | Viewed by 1496
Abstract
Limbal melanocytes (LMs) are found in the corneoscleral limbus basal epithelial layer and interact with neighboring limbal epithelial progenitor cells. The difficulty of isolating and cultivating LMs is due to the small fraction of LMs in the overall limbal population and the frequent [...] Read more.
Limbal melanocytes (LMs) are found in the corneoscleral limbus basal epithelial layer and interact with neighboring limbal epithelial progenitor cells. The difficulty of isolating and cultivating LMs is due to the small fraction of LMs in the overall limbal population and the frequent contamination of primary cultures by other cell types. This has limited the research on freshly isolated LMs and the investigation of their biological significance in the maintenance of the limbal stem cell niche. Here, we describe an optimized protocol for the efficient isolation and expansion of LMs from cadaveric corneal limbal tissue using CD90 and CD117 as selective markers in fluorescence-activated cell sorting to obtain a pure population of LMs (CD90 CD117+) with self-renewal capacity and sustained melanin production. The isolation of pure LMs from a single preparation enables direct transcriptomic and proteomic analyses, as well as functional studies on freshly isolated LMs, which can be considered the proper counterparts of LMs in vivo and have potential applications in tissue engineering. Full article
(This article belongs to the Special Issue Technical Pitfalls and Biases in Molecular Biology)
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