The qpcR library is an add-on to the free R statistical environment performing sigmoidal model selection in real-time quantitative polymerase chain reaction (PCR) data analysis. Additionally, the ...package implements the most commonly used algorithms for real-time PCR data analysis and is capable of extensive statistical comparison for the selection and evaluation of the different models based on several measures of goodness of fit. Availability: www.dr-spiess.de/qpcR.html. Contact: a.spiess@uke.uni-hamburg.de Supplementary Information: Statistical evaluations of the implemented methods can be found at www.dr-spiess.de under ‘Supplemental Data’.
Human spermatogonial markers von Kopylow, Kathrein; Spiess, Andrej-Nikolai
Stem cell research,
December 2017, 2017-Dec, 2017-12-00, 20171201, 2017-12-01, Letnik:
25, Številka:
C
Journal Article
Recenzirano
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In this review, we provide an up-to-date compilation of published human spermatogonial markers, with focus on the three nuclear subtypes Adark, Apale and B. In addition, we have extended our recently ...published list of putative spermatogonial markers with protein expression and RNA-sequencing data from the Human Protein Atlas and supported these by literature evidence. Most importantly, we have put substantial effort in acquiring a comprehensive list of new and potentially interesting markers by refiltering the raw data of 15 published germ cell expression datasets (four human, eleven rodent) and subsequent building of intersections to acquire a robust, cross-species set of spermatogonia-enriched or -specific transcripts.
•Spermatogonia-specific markers are diverse and do not correlate with classical A dark / A pale nuclear morphology.•The same spermatogonial subtype can exist with or without expression of a certain marker, and only a few markers are expressed in all spermatogonial subtypes.•The reanalysis of 15 gene expression studies provided a plethora of novel and putative spermatogonial markers.•A robust set of spermatogonia-specific markers was obtained by intersection of the reanalysis results.
Measurement of cell surface coverage has become a common technique for the assessment of growth behavior of cells. As an indirect measurement method, this can be accomplished by monitoring changes in ...electrode impedance, which constitutes the basis of electric cell-substrate impedance sensing (ECIS). ECIS typically yields growth curves where impedance is plotted against time, and changes in single cell growth behavior or cell proliferation can be displayed without significantly impacting cell physiology. To provide better comparability of ECIS curves in different experimental settings, we developed a large toolset of R scripts for their transformation and quantification. They allow importing growth curves generated by ECIS systems, edit, transform, graph and analyze them while delivering quantitative data extracted from reference points on the curve. Quantification is implemented through three different curve fit algorithms (smoothing spline, logistic model, segmented regression). From the obtained models, curve reference points such as the first derivative maximum, segmentation knots and area under the curve are then extracted. The scripts were tested for general applicability in real-life cell culture experiments on partly anonymized cell lines, a calibration setup with a cell dilution series of impedance versus seeded cell number and finally IPEC-J2 cells treated with 1% and 5% ethanol.
New methods are used to compare seven qPCR analysis methods for their performance in estimating the quantification cycle (Cq) and amplification efficiency (E) for a large test data set (94 samples ...for each of 4 dilutions) from a recent study. Precision and linearity are assessed using chi-square (χ2), which is the minimized quantity in least-squares (LS) fitting, equivalent to the variance in unweighted LS, and commonly used to define statistical efficiency. All methods yield Cqs that vary strongly in precision with the starting concentration N0, requiring weighted LS for proper calibration fitting of Cq vs log(N0). Then χ2 for cubic calibration fits compares the inherent precision of the Cqs, while increases in χ2 for quadratic and linear fits show the significance of nonlinearity. Nonlinearity is further manifested in unphysical estimates of E from the same Cq data, results which also challenge a tenet of all qPCR analysis methods — that E is constant throughout the baseline region. Constant-threshold (Ct) methods underperform the other methods when the data vary considerably in scale, as these data do.
Fitting four-parameter sigmoidal models is one of the methods established in the analysis of quantitative real-time PCR (qPCR) data. We had observed that these models are not optimal in the fitting ...outcome due to the inherent constraint of symmetry around the point of inflection. Thus, we found it necessary to employ a mathematical algorithm that circumvents this problem and which utilizes an additional parameter for accommodating asymmetrical structures in sigmoidal qPCR data.
The four-parameter models were compared to their five-parameter counterparts by means of nested F-tests based on the residual variance, thus acquiring a statistical measure for higher performance. For nearly all qPCR data we examined, five-parameter models resulted in a significantly better fit. Furthermore, accuracy and precision for the estimation of efficiencies and calculation of quantitative ratios were assessed with four independent dilution datasets and compared to the most commonly used quantification methods. It could be shown that the five-parameter model exhibits an accuracy and precision more similar to the non-sigmoidal quantification methods.
The five-parameter sigmoidal models outperform the established four-parameter model with high statistical significance. The estimation of essential PCR parameters such as PCR efficiency, threshold cycles and initial template fluorescence is more robust and has smaller variance. The model is implemented in the qpcR package for the freely available statistical R environment. The package can be downloaded from the author's homepage.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Monte Carlo simulations are used to examine the bias and loss of precision that result from experimental error and analysis procedures in real-time quantitative polymerase chain reaction (PCR). In ...the limit of small copy numbers (N 0), Poisson statistics govern the dispersion in estimates of the quantification cycle (C q) for replicate experiments, permitting the estimation of N 0 from the C q variance, which is inversely proportional to N 0. We derive corrections to expressions given previously for this determination. With increasing N 0, the Poisson contribution decreases and other effects, like pipet volume uncertainty (typically >3%), dominate. Cycle-to-cycle variability in the amplification efficiency E produces scale dispersion similar to that for variability in the sensitivity of fluorescence detection. When this E variability is proportional to just the amplification (E – 1), there is insignificant effect on C q if scale-independent definitions are used for this marker. Single-reaction analysis methods based on the exponential growth equation are inherently low-biased in E and high-biased in N 0, and these biases can amount to factor-of-4 or greater error in N 0. For estimating C q, their greatest limitation is use of a constant absolute threshold, making them inefficient for data that exhibit scale variability.
Abstract
STUDY QUESTION
Is it possible to induce in vitro reorganization of primary human testis cells from testicular sperm extraction (TESE) biopsies, maintain their long-term cultivation in a 2D ...system and identify cellular compositions?
SUMMARY ANSWER
In vitro reorganization of primary human testis cells from TESE biopsies and their long-term cultivation on uncoated cell culture dishes is feasible and the cellular compositions can be uncovered through gene expression and microscopic analyses.
WHAT IS KNOWN ALREADY
It has been shown in the rodent model that mixtures of testicular cell types are able to reassemble into clusters when cultivated on different kinds of surfaces or three-dimensional matrices. Two recent publications demonstrated the ability of primary human testicular cells to assemble into testicular organoids and their cultivation for a period of 3–4 weeks.
STUDY DESIGN SIZE, DURATION
Primary human testis cells from TESE biopsies from 16 patients were reorganized in vitro and the clusters were cultivated long term on uncoated cell culture dishes, providing a solid ground for in vitro spermatogenesis. Gene expression analysis as well as fluorescence/transmission electron microscopy (TEM) were employed to uncover the cellular composition of the clusters.
PARTICIPANTS/MATERIALS, SETTING, METHODS
Testis biopsies from adult, normogonadotropic patients displaying full spermatogenesis (n = 11), hypospermatogenesis (n = 2), predominantly full spermatogenesis with some hypospermatogenic tubules (n = 1), meiotic arrest (n = 1) or mixed atrophy (n = 1) were enzymatically digested and dispersed cells were cultivated on 96-well plates or chamber dishes as aggregate-free cell suspensions. Time-lapse imaging of cluster formation was performed over a period of 48 h. For receptor tyrosine kinase inhibition of cluster formation, cells were treated twice with K252a within 2–3 days. Immunofluorescence staining and confocal microscopy was carried out on clusters after 1–3 weeks of cultivation to identify the presence of Sertoli cells (SC) (SOX9), peritubular myoid cells (SMA), Leydig cells (LC) (STAR), undifferentiated spermatogonia (FGFR3), differentiating spermatogonia/spermatocytes (DDX4) and postmeiotic germ cells (PRM1). Single clusters from four patients and a pool of eight larger clusters from another patient were manually picked and subjected to quantitative real-time PCR to evaluate the presence of SC (SOX9, AR), LC (INSL3, STAR, HSD3B1), peritubular myoid cells (ACTA2), fibroblasts (FSP1), endothelial cells (CD34), macrophages (CD68), undifferentiated spermatogonia (FGFR3), differentiating spermatogonia/spermatocytes (DDX4) and postmeiotic germ cells (PRM1). Finally, an ultrastructural investigation was conducted based on TEM of clusters from six different patients, among them 3-month cultivated large clusters from two patients.
MAIN RESULTS AND THE ROLE OF CHANCE
Quantitative PCR-based analysis of single-picked testicular cell clusters identified SC, peritubular myoid cells, endothelial cells, fibroblasts, macrophages, spermatids and LC after 1, 2 or 3 weeks or 3 months of cultivation. Immunofluorescence positivity for SC and peritubular myoid cells corroborated the presence of these two kinds of testis niche cells. In addition, round as well as elongated spermatids were frequently encountered in 1 and 2 weeks old clusters. Transmission electron microscopical classification confirmed all these cell types together with a few spermatogonia. Macrophages were found to be of the proinflammatory M1 subtype, as revealed by CD68+/CD163−/IL6+ expression. Time-lapse imaging uncovered the specific dynamics of cluster fusion and enlargement, which could be prevented by addition of protein kinase inhibitor K252a.
LARGE SCALE DATA
N/A.
LIMITATIONS REASON FOR CAUTION
Cell composition of the clusters varied based on the spermatogenic state of the TESE patient. Although spermatids could be observed with all applied methods, spermatogonia were only detected by TEM in single cases. Hence, a direct maintenance of these germ cell types by our system in its current state cannot be postulated. Moreover, putative dedifferentiation and malignant degeneration of cells in long-term cluster cultivation needs to be investigated in the future.
WIDER IMPLICATIONS OF THE FINDINGS
This work demonstrates that the reorganization of testicular cells can be achieved with TESE biopsies obtained from men enroled in a standard clinical assisted reproduction program. The formed clusters can be cultivated for at least 3 months and are composed, to a large extent, of the most important somatic cell types that are essential to support spermatogenesis. These findings may provide the cellular basis for advances in human in vitro spermatogenesis and/or the possibility for propagation of spermatogonia within a natural stem cell niche-like environment.
STUDY FUNDING AND COMPETING INTERESTS
The project was funded by a DFG grant to K.v.K. (KO 4769/2-1). The authors declare they have no conflicts of interest.
The quantification cycle (C q) is widely used for calibration in real-time quantitative polymerase chain reaction (qPCR), to estimate the initial amount, or copy number (N 0), of the target DNA. C q ...may be defined several ways, including the cycle where the detected fluorescence achieves a prescribed threshold level. For all methods of defining C q, the standard deviation from replicate experiments is typically much greater than the estimated standard errors from the least-squares fits used to obtain C q. For moderate-to-large copy number (N 0 > 102), pipet volume uncertainty and variability in the amplification efficiency (E) likely account for most of the excess variance in C q. For small N 0, the dispersion of C q is determined by the Poisson statistics of N 0, which means that N 0 can be estimated directly from the variance of C q. The estimation precision is determined by the statistical properties of χ2, giving a relative standard deviation of ∼(2/n)1/2, where n is the number of replicates, for example, a 20% standard deviation in N 0 from 50 replicates.
BACKGROUND A key step in studying the biology of spermatogonia is to determine their global gene expression profile. However, disassociation of these cells from the testis may alter their profile to ...a considerable degree. To characterize the molecular phenotype of human spermatogonia, including spermatogonial stem cells (SSCs), within their cognate microenvironment, a rare subtype of human defective spermatogenesis was exploited in which spermatogonia were the only germ cell type. METHODS The global expression profile of these samples was assessed on the Affymetrix microarray platform and compared with tissues showing homogeneous Sertoli-cell-only appearance; selected genes were validated by quantitative real-time PCR and immunohistochemistry on disparate sample sets. RESULTS Highly significant differences in gene expression levels correlated with the appearance of spermatogonia, including 239 best candidates of human spermatogonially expressed genes. Specifically, fibroblast growth factor receptor 3 (FGFR3), desmoglein 2 (DSG2), E3 ubiquitin ligase c-CBL (casitas B-cell lymphoma), cancer/testis antigen NY-ESO-1 (CTAG1A/B), undifferentiated embryonic cell transcription factor 1 (UTF1) and synaptosomal-associated protein, 91 kDa homolog (SNAP91) were shown to represent specific biomarkers of human spermatogonia. CONCLUSIONS These biomarkers, specifically the surface markers FGFR3 and DSG2, may facilitate the isolation and enrichment of human stem and/or progenitor spermatogonia and thus lay a foundation for studies of long-term maintenance of human SSCs/progenitor cells, spermatogonial self-renewal, clonal expansion and differentiation.
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