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Toxicol Sci. 2016 August; 152(2): 257–261.
Published online 2016 July 20. doi:  10.1093/toxsci/kfw113
PMCID: PMC4960913

From the Editor’s Desk, Editor’s Highlights, Letters to the Editor

From the Editor’s Desk

PubPeer, F1000, and other outlets are encouraging postpublication review of science. I appreciate scientific scrutiny at all levels, including pre- and postpublication peer review. For Toxicological Sciences, our Letters to the Editor section has been the primary outlet for postpublication discussion. In this issue, we have broken from tradition and permitted a concerned reader to include data to make a point and, as always, allowed the original authors to respond. We should encourage the rigorous analysis of our science before and after publication. While we do not yet have an online outlet for postpublication discussion, this is a concept we will pursue as we transition to a new web platform over the next year. As always, I encourage you to look inside ToxSci for the best original research in the field of toxicology. – Gary W. Miller

Editor’s Highlights

Embryonic stem cells for toxicity testing

Embryonic stem cells are an attractive tool for the identification of teratogenic compounds because they are cost-effective and compatible with high-throughput screening methods. Kugler et al. (pp. 382–394) recently developed a Wnt/β-Catenin-reporter embryonic stem cell line that differentiates into cardiomyocytes within 12 days. They used this reporter cell line to quantify the dose- and time-dependent effects of teratogenic chemicals. The authors determined that valproic acid reduced reporter activity on day 7 and retinoic acid induced reporter activity on day 5 at concentrations similar to those known to inhibit the formation of functional cardiomyocytes. The authors also showed that selected teratogenic chemicals exhibit different dose-response curves and cytotoxic effects in the Wnt/β-Catenin-reporter embryonic stem cell line compared to a previously described Bmp-reporter embryonic stem cell line. Collectively, these findings indicate that the authors have developed a new Wnt/β-Catenin-reporter embryonic stem cell line, which provides a complementary tool for the identification and analysis of potentially teratogenic compounds. View Abstract—Jodi A. Flaws

Computational approaches for big toxicology data

In the NRC report Toxicity Testing in the 21st century the use of in vitro assays to support humans risk assessment has been extensively discussed. As a result, the ToxCast and Tox 21 programs have been initiated with the idea that the integrated results of these assays can provide a basis to determine adverse outcome pathways or modes of action. Judson et al. (pp. 323–339) studied responses of 1060 chemicals with diverse biological activities in 815 in vitro assays. This provided a large data set and showed that responses could be divided in 2 categories. The first group includes chemicals that interact with specific biomolecular pathways or targets, whereas in the second group a more generalized disruption of the cellular homeostasis occurred. The authors expect that their data will further improve the use of in vitro models for prediction of in vivo hazard. View Abstract—Martin van den Berg

miR mirrors retinal toxicity

Drug-induced ocular toxicity is a common obstacle in the clinical development of a drug. The current diagnostic options for detecting retinal injuries are limited to invasive and inconvenient methodologies such as electroretinography and histopathology. Lack of early predictive biomarkers with high specificity and sensitivity still remains a major limitation in assessing retinal toxicity. In this issue, Peng et al. (pp. 273–283) demonstrate elevated circulating retina-enriched plasma miRNAs using 2 different models of retinal toxicity: NaIO3-induced retinal toxicity and laser-induced choroidal neovascularization injury models. Following the induction of retinal injuries, the authors found that circulating plasma miR-183/96/182 clusters and miR-124 were significantly elevated in these 2 models. Notably, the increase in plasma miRNAs (miR-183 cluster and miR-124) appeared to be dose- and time-dependent, suggesting these retina-enriched miRNAs could serve as potential biomarkers for retinal toxicity. Further validation of these newly identified circulating miRNA biomarkers in other commonly used preclinical species should prove their utility in assessing ocular toxicity during drug discovery. View Abstract—Anumantha G. Kanthasamy

p53 and organogenesis

The p53 protein is well known in the field of carcinogenesis for its role as a tumor suppressor and is considered critical in the protection of the genome. In this issue, El Husseini et al. (pp. 297–308) reveal a novel role of p53 in the response to exposure to a teratogen. The authors exposed timed-pregnant female mice to the well-characterized teratogen hydroxyurea and then performed a transcriptomic analysis on mouse embryos (gestational day 9) 3 h after exposure. The analysis revealed a dramatic change in p53 expression as well as in genes regulated by p53. Moreover, Western blot analysis confirmed an increase in the phosphorylated form of p53 and confocal microscopy demonstrated translocation of the p53 protein to the nucleus. These findings show that the p53 pathway plays an important role in the stress response to teratogens and suggests that p53 has a fundamental role in embryonic development. View Abstract—Gary W. Miller

Letter to the Editor

In Vivo Mn Exposure Does Not Affect Adult Neurogenesis in Rats

A recent article by Fu et al. (2015b) presents a 40% decrease in Cu levels of the subventricular zone (SVZ) in rats as measured by atomic absorption spectroscopy (AAS) attributed to subchronic manganese exposure. Furthermore, Fu et al. (2015b) report a statistically significant increase in SVZ and rostral migratory stream (RMS) neurogenesis measured via fluorescence intensity of antibodies for bromodeoxyuridine (BrdU). While these results are of interest to both the Mn neurotoxicity community and those studying neurogenesis, we bring into the question relevance of hand dissection for isolation of the SVZ and/or RMS, regions which are a few hundred microns wide, for the reported AAS measurements. Furthermore, quantification of fluorescence intensity to measure neurogenic activity does not appear to provide any additional advantages over the established approach of direct cell counting. Consequently, we sought to verify the decrease in Cu using X-ray fluorescence microscopy (XRF) with resolution of 25 × 25 μm2 using the same set of samples as in Fu et al. (2015b). In contrast to the results of Fu et al. (2015b), our data show a small, significant increase in Cu concentration in the SVZ following Mn treatment but only in areas with elevated Cu content. The RMS shows no changes in Cu concentration. Additionally, we quantified Ki67+ cell density in the SVZ and RMS, which is expressed in actively dividing cells, by cell counting. Our data show no indication of changes in the cell cycle suggesting that Mn exposure does not affect neural cell division in the adult SVZ or RMS.

All rats analyzed for this letter were from the same treatment groups analyzed in (Fu et al., 2015b); as such they were age-matched and underwent identical injection regiments. X-ray maps were generated from 30 μm thick sections (sagittal planes, lateral 1.90 mm, n = 5 per group) imaged at beamline 8-BM at the Advanced Photon Source (Argonne, Illinois) and data analysis and Cu quantitation was done as previously described (Pushkar et al., 2013; Vogt, 2003). As the majority of Cu in the SVZ and RMS lies primarily within a single cell layer, these regions can be spatially isolated by applying a concentration filter. To achieve this, lines drawn along the SVZ and RMS were expanded to a 7 × 7 pixel box for each pixel in the line and pixels above 8.5 μg/g were considered (Figure 1C–F). The threshold of 8.5 μg/g was determined as it is the lowest concentration within 1 standard deviation of the mean concentration of unthresholded pixels the SVZ and RMS. Prior to applying the threshold, no significant differences in Cu concentrations are observed. Only after applying a threshold filter is a small, statistically significant increase in the Cu level in the SVZ of Mn-treated animals was observed in comparison to controls (P < .05). Cu concentrations in the RMS showed no changes (P = .40; Figure 1B). The difference is likely due to limited reproducibility of the dissection protocol. Note that data with almost a 20-fold discrepancy (0.928 μg/g vs. 17.8 μg/g) in Cu content in SVZ have been reported by the same group (Fu et al., 2015a, b).

FIG. 1
(A) Diagram of a sagittal section at lateral ~1.90 mm with the approximate location of the displayed XRF scan indicated by the cyan box. (B) Summary of Cu concentrations in the SVZ and RMS for control (white) and treated (gray) groups ...

For quantification of Ki67+ cells, 10 μm thick sagittal sections from n = 4 rats per group were stained and quantified with Ki67 following our laboratory’s previously published protocol (Pushkar, et al., 2013). Note that the BrdU protocol used in Fu et al. and Ki67 stains have been demonstrated to be equivalent measures of neurogenesis (Kee et al., 2002). Briefly, the number of Ki67+ cells was blindly counted and then normalized to the length of the SVZ or RMS to account for any variability in the size of the brain area. Sequential images with 10× magnification of the RMS and SVZ were stitched using the ImageJ plugin by Preibisch et al. (2009) with a regression threshold of 0.3 and fusion done by maximum pixel intensity. No statistically significant difference between Mn-treated and control groups was observed for either region (Figure 2D). This conflicts with Fu et al. (2015b) who report an increased neurogenesis as measured by bulk fluorescence quantification of labeled antibodies sensitive to BrdU, recently supplemented by direct cell counting (Fu et al., 2016). Direct cell counting is preferred as it removes variabilities such as ROI selection, image stitching techniques, and excitation light intensity; the only source of ambiguity comes from overlapping fluorescing nuclei which are rare in 10 μm thick sections (Figure 2C). The reported increase in neurogenesis from BrdU quantification may be an artifact of BrdU’s uptake into the brain if the blood brain barrier’s or blood cerebrospinal fluid barrier’s integrity is compromised following Mn exposure. Santos et al. (2012), for instance, report differential amino acid concentrations in rat brain tissue following Mn exposure, suggesting the possibility of compromised barriers increasing BrdU uptake. Increased brain availability may be particularly important at the 50 mg/kg dose falls on the low end of the dose-effect curve (Cameron and Mckay, 2001; Hancock et al., 2009). In this regime, BrdU labeling is limited by uptake into the brain; increased permeability due to Mn exposure would result in increased BrdU+ cell labeling which would be misinterpreted as increased neurogenesis. The use of exogenous markers like Ki67 avoids this issue.

FIG. 2
(A) Representative Ki67 stain of the SVZ and RMS for a control rat and (B) representative Ki67 stain for a Mn-treated rat. Magnification 10×. (C) High magnification (40×) view of the RMS in a control rodent. (D) Quantitation of neurogenesis ...

In conclusion, using animals from the same treatment groups our data disagree with the reports of Fu et al. (2015b) in that XRF does not verify a ~40% decrease in Cu but shows a small increase in SVZ Cu with differences limited to areas with high Cu content and counting of Ki67+ cells shows no statistically significant increase neural cell division. The discrepancy regarding metal concentrations is likely due to XRF’s ability to provide spatial information which can be used to more precisely isolate the SVZ and RMS. Differences in quantification regarding neurogenesis likely stem from the sensitivity of the measurement to the ROI selection and the use of BrdU despite compromised brain barriers. The connection between Cu and Mn levels also appears to be rather tenuous. For instance, a prior report on changes in Cu content in large areas in the brain (Zheng et al., 2009) has not been verified (Robison et al., 2012).

SUPPLEMENTARY DATA

Supplementary data are available online at http://toxsci.oxfordjournals.org/.

ACKNOWLEDGMENTS

The authors acknowledge Dr Lydia Finney and Evan Maxey for their assistance operating APS beamline 8-BM and Dr Stefan Vogt for his assistance with the MAPS program.

FUNDING

This study was supported by the National Institute of Environmental Health Sciences at the National Institutes of Health (Grant no. R01 ES008146-14). The use of the Advanced Photon Source, an Office of Science User Facility operated for the U.S. Department of Energy (DOE) Office of Science by Argonne National Laboratory, was supported by the U.S. DOE under (Contract no. DE-AC02-06CH11357).

REFERENCES

Available as a Supplementary File.

Brendan Sullivan, Gregory Robison, Martin Kay, and Yulia Pushkar1

Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana

1To whom correspondence should be addressed. E-mail: ude.eudrup@rakhsupy.

doi: 10.1093/toxsci/kfw091

© The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Response Letter to the Editor

Approaches in Evaluating In Vivo Mn Effect on Adult Neurogenesis

In the referred Letter to the Editor, Sullivan and his coworkers have confused the utility and limitation of Ki67 with those of BrdU in tracing adult neurogenesis. The critical piece of evidence on which they concluded the lack of effect of Mn exposure on adult neurogenesis was based on a solo Ki67 staining and dubious cell counting (Figure 2 of the Letter). The statement, as quoted that “the BrdU protocol used in Fu et al. and Ki67 stains have been demonstrated to be equivalent measures of neurogenesis (Kee et al., 2002)”, is incorrect and out of context of the original Kee paper. The concept of adult neurogenesis involves the cell proliferation, migration, survival, differentiation, and integration of newborn cells into the existing neuronal circuits (Gage et al., 2008). As Ki67 is a cell cycle protein which expresses only temporally during most of the cell cycle phases, staining with Ki67 can only reflect the proliferation but cannot provide unambiguous information when the newly generated neural stem/progenitor cells (NSPCs) exit the cell cycle and begin their maturation process in the later phases of adult neurogenesis. In fact, Kee et al. (2002) in their paper explicitly point out that their study “provides evidence for Ki67 to be used as a marker of proliferation in the initial phase of adult neurogenesis”. In contrast, BrdU is incorporated into DNA during the S-phase of the mitotic process. Pulse-labeling newly generated cells with BrdU and tracing these labeled cells in the entire neurogenesis process have been used extensively to determine the time of origin, migration, lineage and fate of adult-born NSPCs (Cameron et al., 1993; Lois and Alcarez-Buylla, 1994; Miller and Nowakowski, 1988; Palmer et al., 2000; Taupin et al., 2000). Thus, the experiment using Ki67 staining, as used by Sullivan et al. in the Letter, provides the limited information on cell proliferation, but cannot depict the fate of newborn NSPCs during the entire process of adult neurogenesis.

Another concern pertains to the data provided by Sullivan et al. in Figure 2 of the Letter. The authors studied rather limited regions or sections of the subventricular zone (SVZ) and rostral migratory stream (RMS), but not the entire SVZ and RMS. Newly generated cells are not evenly distributed throughout SVZ and RMS. To truly reflect the proliferation of NSPCs, one must count all proliferating cells in a whole series of brain sections that cover the entire distances of the lateral ventricles and RMS; this is precisely what we have accomplished and reported in our newly published paper (Fu et al., 2016). Multiple staining against BrdU and other neuronal markers which represent the stages from differentiation to matured neurons can provide valuable information to distinguish the phenotypes and the fate of newborn NSPCs. In their Letter, however, Sullivan et al. did not examine the maturation and integration of adult-born cells in the olfactory bulb (OB), which is an indispensable step to evaluate whether or not the neurogenesis process is successfully completed. Moreover, the authors did not count the cells from images with Z-stack scanning under higher magnifications. Thus, the cell overlay with indistinguishable fluorescent signals would compromise the true cell numbers that were labeled with Ki67 (hence, leading to an underestimation of cell populations). Noticeably also, they did not co-stain Ki67 with any nuclear marker, such as DAPI. Without co-localizing Ki67 with DAPI to distinguish the healthy proliferating cell bodies for their cell counting, their results were likely tainted with non-specific staining. Taking into account these shortcomings, ie, the limitation of Ki67 in reflecting the entire neurogenesis process, their improper approaches in selecting brain sections and counting the cells, and their very limited experimental data which were presented only in one figure, we strongly suspect that their conclusion, as quoted in the title that “in vivo Mn exposure does not affect adult neurogenesis in rats”, is premature and not supported by scientifically sound experimental proofs.

Having realized the limitation of Ki67 and related insufficient signal quantification techniques, we have made significant improvements after our initial report by Fu et al. (2015b). These improvements are exemplified in our newly published paper (Fu et al., 2016), including the use of better-designed BrdU labeling paradigms, adapting Z-stack imaging to improve cell counting confidence, and tracing BrdU-labeled NSPCs toward their maturation and integration in the OB. We designed one protocol to study the origin and proliferation of NSPCs and the other protocol to track the fate of BrdU pre-labeled NSPCs from SVZ, along RMS, to OB, following in vivo Mn exposure (Figure 1A and B in Fu et al., 2016). Our new data in Fu et al. (2016) clearly indicate that Mn exposure initially enhances the cell proliferation in adult SVZ, which is consistent with the observation in our initial report (Fu et al., 2015b). In the OB, however, Mn exposure significantly reduces the surviving adult-born cells and markedly inhibits their differentiation into mature neurons, resulting in an overall decreased adult neurogenesis in the OB (Fu et al., 2016).

Sullivan et al. did raise an interesting point that the disrupted blood-brain barrier (BBB) permeability as a result of Mn exposure may increase the uptake of BrdU to the brain, leading to a possible artificial increase of BrdU labeling. They also suggested that the BrdU we used (50 mg/kg) was too low to allow for an effective labeling of cells in the SVZ. Based on the literature search, for adult rodents and non-human primates, a BrdU dose range between 50 and 100 mg/kg (ip) has been used by most investigators to study neurogenesis (Corotto et al., 1993; Gould et al., 2001; Kornack and Rakic, 2001; Kuhn et al., 1996; Seki and Arai, 1993; van Praag et al., 1999). We had tested both BrdU doses at 50 and 100 mg/kg in our preliminary studies, and found that the labeled cell numbers in the SVZ were consistent and comparable between 2 dose regimens. Moreover, the BrdU fluorescent signals from the pulse labeling (50 mg/kg) before the Mn treatment remained sufficiently detectable in the OB even at 4 weeks after Mn treatment. We thus chose the lower dose of 50 mg/kg for the purpose of reducing the possible BrdU-associated toxicity. Thus, regardless what reports suggest in the literature, the dose (50 mg/kg) as tested by our own hands was proven useful and effective in our studies.

As to the brain barrier systems, Mn exposure is known to alter iron and copper transport across the BBB and blood-CSF barrier (BCB) (Fu et al., 2014; Li et al., 2006). This group has been conducting brain barrier research for the past 25 years. However, to the best of our knowledge, there is no evidence to suggest that Mn exposure in the current dose regimen can cause any structural damage leading to an increased BBB or BCB permeability. The question raised by Sullivan et al. is reasonable, but speculative at the best and without any experimental proofs.

Another disputable point by Sullivan et al. pertains to the contrast results of Cu contents in the SVZ following Mn exposure by comparing the measurements between atomic absorption spectrophotometry (AAS) and synchrotron X-ray fluorescence (XRF) analyses. Admittedly, the SVZ dissection skill in our initial attempt to investigate Mn effect on SVZ Cu was in its infancy; inclusion of some surrounding tissues may cause the contamination and therefore lead to a large discrepancy in Cu quantitation (Fu et al., 2015a,b). However, after training by the expert in adult neurogenesis (Dr. Jinhui Chen from Indiana University School of Medicine) and persistent practice, using the dissection microscope, and employing rat brain slicers and matrices, our dissection technique has improved significantly and become mature among lab crews. The data reported in the later paper (Fu et al., 2015a) reflect our improved skill and quality in SVZ dissection and metal analysis.

We do have our own reservation on the usefulness of the synchrotron XFR technique to quantify metal concentrations in bulk brain tissues. We have no doubts regarding the technical operation and analysis by synchrotron XRF conducted by Sullivan et al. Our concern stemmed mainly from 3 observed facts. First, the section used for synchrotron XRF analysis (sagittal planes, lateral 1.90 mm), whereas not entirely random, is rather subjective, because it is impossible to ascertain if metal distribution and accumulation are typically aligned with this 1.90-mm thin section. Metals, particularly Cu, are not evenly distributed in brain tissues (Becker et al., 2005; Davies et al., 2013, 2014; Dobrowolska et al., 2008; Lech and Sadlik, 2007; Ramos et al., 2014). The XRF data from this peculiar thin slice of brain area cannot truthfully reflect the metal accumulation in the entire region of research interest, which includes areas above or below, near or far from this 1.90-mm coordinate. Second, from our early experience with the synchrotron XRF quantification, the large day-to-day variations became a major concern; one day’s outcome could be entirely opposite to the other day’s conclusion. It was truly this uncertainty that prompted us to seek for more traditional and reliable means, such as AAS, to quantify metal concentrations in brain tissues. Finally, there is a serious concern on the biological consistency for tissues from different treatment groups for synchrotron XRF analysis. The cryosectioned brain tissues could preserve the cellular and subcellular proteins and maintain overall cell integrity without using chemical fixatives. However, during the process of XRF scanning, the snap-frozen, ultra-thin sections are exposed to the air and analyzed under room temperature, which inevitably triggers the protein degradation via autolytic and/or proteolytic processes and causes the collapse of cellular and subcellular structure, leading to the dissociation of protein-bounded metals which in turn leak toward extracellular compartments or adjacent regions. This issue may be less crucial if the comparison is made within the same brain section under the same experimental conditions such as the study published by Pushkar et al. (2013). However, it can become a severe interference when the comparison is made between brain tissues from different groups that undergo different metal exposure paradigms, assorted sample collection and processing procedures, and varying time frames under synchrotron XRF operation. Thus, the question as to how accurately the XRF quantification can reflect the in situ quantity of brain metals between different animal treatment groups remains elusive.

Finally, we would like to point out that the statement made by Sullivan et al., as quoted that “All rats analyzed for this letter were from the same treatment groups analyzed in (Fu et al., 2015b); as such they were age-matched and underwent identical injection regiments”, is untrue. The brain tissues from animals receiving BrdU injections in our report (Fu et al., 2015b) were never provided to the XRF group for synchrotron XRF study; otherwise, Sullivan et al. could have used the same BrdU staining approach to verify the results in Fu et al., 2015b paper. According to our record, the brain samples provided to the XRF group, which were used in their Letter, were taken from an earlier and entirely different rat cohort before we fine-toned our experimental approaches in study design and technical procedure for our subsequent adult neurogenesis study. Thus, we respectfully question the authors of the Letter for the reliability of their experimental record, the validity of the comparisons made between the Letter and our reports (Fu et al., 2015b, 2016), and the soundness of their ensuing “no effect” conclusion presented in the Letter.

SUPPLEMENTARY DATA

Supplementary data are available online at http://toxsci.oxfordjournals.org/.

FUNDING

National Institute of Environmental Health Sciences, (Grant/Award Number: ES008146).

REFERENCES

Available as a Supplementary File.

Sherleen Fu,* Daniel Cholger,* and Wei Zheng,*,1

*School of Health Sciences, Purdue University, West Lafayette, Indiana 47907

1To whom correspondence should be addressed at Professor of Neurotoxicology, School of Health Sciences, Purdue University, 550 Stadium Mall Drive, Room 1169, West Lafayette, IN 47907. Tel: 765 496-6447; Fax: 765 496-1377; E-mail: ude.eudrup@gnehzw.

doi: 10.1093/toxsci/kfw095

© The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Supplementary Material

Supplementary Data:

Articles from Toxicological Sciences are provided here courtesy of Oxford University Press