s2fieldsofstudy: Biology Medicine

text:
Recombinant betatrophin (Angptl-8/lipasin) ameliorates streptozotocin-induced hyperglycemia and β-cell destruction in neonatal rats

Betatrophin [also known as lipasin, angiopoietin-like 8 (ANGPTL8), refeeding induced in fat and liver (RIFL), or hepatocellular carcinoma-associated gene TD26], a 22-kDa protein in the angiopoietin-like family, is a liver-derived hormone that promotes pancreatic β-cell proliferation and lipid metabolism. The aim of the present study was to investigate the effect of recombinant betatrophin on β-cell regeneration in a neonatal streptozotocin (STZ)-induced diabetic rat model. One-day-old Wistar rats were injected with STZ (100 mg/kg), followed by intraperitoneal administration of betatrophin to the STZ-injected rats for 6 days. Plasma glucose and body weight were monitored. On days 4 and 7, expression levels of pancreatic duodenal homeobox gene-1 (PDX-1), the Bax/B-cell lymphoma-2 (Bcl-2) ratio and plasma insulin were assessed, and the β-cell proliferation rate was determined. Pancreatic islet area and number were determined at 10 weeks. It was found that betatrophin treatment alleviated STZ-induced hyperglycemia, elevated pancreatic expression levels of Bcl-2, PDX-1, plasma insulin levels and the β-cell proliferation rate on days 4 and 7. Long-term betatrophin treatment improved glucose tolerance, associated with improved plasma insulin levels and β-cell mass. These results suggest that early administration of betatrophin promotes β-cell proliferation in STZ-induced diabetic neonates and prevents the development of diabetes in adults.

Introduction
diabetes mellitus (dM) is a complex metabolic disease, characterized by high blood glucose levels and dysfunctional lipid metabolism. DM is further classified as type 1 (TIDM) and type 2 (T2dM), caused by absolute and relative insulin insufficiency, respectively. in T1dM, inadequate mass of functional pancreatic β cells causes insulin deficiency (1). a variety of traditional treatments for diabetes, including insulin therapy, have limited ability to simulate insulin secretion and are frequently associated with severe hypoglycemic episodes (2,3). To overcome the limitations of traditional treatment, researchers have focused on replenishing the loss of insulin-producing cells and expansion of existing pancreatic β cells through regeneration (2).
The streptozotocin (STZ)-treated neonatal model is useful for investigating β-cell regeneration (4). it provides a better understanding of dM pathophysiology by exhibiting hyperglycemia, altered glucose tolerance, and reduced insulin secretion after neonatal injection of STZ (5,6).
Betatrophin is known to induce β-cell proliferation and to improve glucose tolerance in insulin resistance states (11). Jiao et al (12) found that elevated hepatic betatrophin expression increased the proliferation of β cells transplanted from mice. However, this finding is contentious. Cox et al reported that β-cell replication was not obviously altered after anGPTl8 overexpression in B6.129 mice (13). Since the initial discovery relied on cdna overexpression rather than direct treatment using the recombinant protein, we tested its direct effect on diabetes and β cells using a neonatal diabetes model. Furthermore, numerous clinical studies have demonstrated that betatrophin levels are significantly increased in individuals with obesity, who are pregnant (14), with T1dM (15), with newly identified type 2 diabetes mellitus (nT2DM), T2DM, and diabetic retinopathy (16,17). These facts suggest that betatrophin may be involved in compensatory mechanisms of enhanced insulin levels. in the present study, we investigated the short-and long-term effects of betatrophin in a neonatal STZ-induced diabetes mellitus model and the underlying mechanisms.

Materials and methods
Reagents. recombinant human betatrophin was purchased from creative Biomart (Shirley, nY, uSa), and STZ was purchased from Wako Pure chemicals (Sigma-aldrich; Merck KGaa). Animals (rat model of diabetes). Wistar rats (275.4±10.1 g per rat, n=5) at 16-18 days of pregnancy, were obtained from Qingdao institute for Food and drug control. They were kept in specific pathogen-free conditions in filtered cages and were fed standard chow diets and water in a 12-h light/dark cycle and housed in standard housing conditions (22-24˚C and 55±20% humidity). each litter of pups was randomly divided into four groups (STZ group n=13, STZ+betatrophin group n=11, untreated group n=13, untreated+betatrophin group n=18). For neonates within 10 h of birth, rats were injected intraperitoneally (i.p.) with a single dose of STZ (100 mg/kg, freshly dissolved in 0.1 M citrate buffer, pH 4.5), or citrate buffer alone. Male animals were used for further study only if their random glucose levels were higher than 11.1 mM on day 3 measured using a glucometer (B. Braun, Meilsungen, Germany). Betatrophin (300 mg/kg, freshly dissolved in normal saline) or normal saline alone was administered to the animals by i.p. injection for 6 days (days [1][2][3][4][5][6]. in the long term study, STZ and STZ+betatrophin groups were injected with a single dose of STZ (100 mg/kg) within 10 h of birth. Betatrophin (300 mg/kg) was administered to the STZ+betatrophin group by i.p. injection for 6 days (day 1-6). At least five rats in each group were maintained until the 10th week. The design of the study is presented in Fig. 1a.
Animals were sacrificed on days 2, 4, and 7 after birth by decapitation. Adult rats were sacrificed at 70 days after birth by bleeding following anesthesia with an i.p. injection of sodium pentobarbital (50 mg/kg). Blood samples were immediately collected and centrifuged at 20,000 x g for 2 min at 4˚C and then stored at -20˚C until assayed. The animal experimental protocol was approved by the ethics committee of the Medical department of Qingdao university (Qingdao, china). all experiments were conducted in accordance with the national institutes of Health Guide for the care and use of laboratory animals.
Measurement of body weight, blood glucose and plasma insulin levels. Blood glucose levels were measured with a glucometer from the foot pad. Body weights were measured with an electric balance (Pl1501-S; Mettler Toledo, china) each day of the study. Plasma insulin levels of the 4-and 7-day-old pups were measured using an enzyme-linked immunosorbent assay kit (eiaab Science co., Wuhan, china), following the manufacturer's protocol.
Glucose tolerance test (IPGTT). rats were fasted for 12 h prior to the intraperitoneal glucose tolerance test (iPGTT). Glucose levels were measured from the tail vein at 0, 30, 60 and 120 min, after an i.p. injection of glucose (2 g/kg), using a one Touch Basic glucose meter.
Immunohistochemistry of the pancreas. The pancreas of each pup was rapidly harvested, weighed and fixed in 4% paraformaldehyde for 24 h. immunohistochemistry and immunofluorescence staining analysis was performed as described previously (19). The tissues were subsequently dehydrated in graded concentrations of ethanol, cleared in xylene, embedded in paraffin and sectioned into 5-µm tissue sections. adjacent sections at a fixed interval throughout the block were immunostained for insulin using a technique adapted from the peroxidase indirect labeling method. The sections were incubated overnight with primary antibodies against insulin (ZSGB-Bio) after 1 h blocking with 1% bovine serum albumin. They were then incubated with biotinylated secondary antibody (PV6000; ZSGB-Bio) for 3 h. insulin positive staining was visualized with hematoxylin and eosin and mounted in 3,3'diaminobenzidine (daB). Histological images were captured using high-power light microscopy (dP72; olympus, Tokyo, Japan). Ten non-consecutive sections of different series per block were immunostained for insulin; at least six random islets (magnification, x400) from each section were counted for insulin-positive areas. The β-cell area ratio was quantified as the area of insulin-positive cells divided by the total tissue area using image J software (national institutes of Health, Bethesda, Md, uSa).
Immunofluorescence staining. The paraffin-embedded sections were deparaffinized and rehydrated using xylene, ethanol and PBS. antigen retrieval was performed using 10 mM citrate buffer (pH 6.0) in a microwave oven for two treatments of 10 min each. Sections were blocked in 10% normal donkey serum, 1.0% bovine serum albumin (BSa) for 2 h to prevent nonspecific binding. Incubation with the primary antibody mix was performed at 4˚C overnight in a wet chamber followed by incubation with the mixture of fluorophore-conjugated secondary antibody for 2 h in a wet chamber protected from light. The primary antibodies used were anti-insulin (dilution 1:1,000, e11d7; Merck Millipore) and anti-Ki67 (dilution 1:1,000, #2382594; Merck Millipore). corresponding secondary antibodies were Rhodamine-conjugated Affinipure goat anti-mouse, and Fluorescein-conjugated affinipure goat anti-rabbit made by ZSGB-Bio. Slides were mounted with coverslips with a drop of 50% glycerol. Fluorescence images were captured with a laser confocal microscope (FV500; olympus). Ten non-consecutive sections of different series per block were immunostained for insulin; at least five random islets from each section were measured to determine the proportion of insulin/Ki67 co-localized cells of the total β cells which was counted using imageJ software.
Statistical analysis. data are expressed as mean ± SeM and analyzed using ANOVA. The LSD (least significance difference) test was used as the post-hoc test, with the Student's t-test and the Fisher's exact test, with statistical significance set at P<0.05.

Results
Betatrophin treatment decreases STZ-promoted hyperglycemia in neonatal rats. in order to establish neonatal diabetes by specifically destroying β cells, STZ at 100 mg/kg was injected into newborn pups 10 h after birth, as previously described (20). as shown in Fig. 1B, compared to the untreated pups, STZ treatment caused a steady elevation in blood glucose level from 5 to 22 mM over 4 days. Glucose levels then gradually declined from 4 to 7 days to 13 mM, suggesting a partial recovery from diabetes. The expression of endogenous betatrophin in the liver doubled from day 2 in the STZ group compared to levels in untreated pups, suggesting possible involvement of betatrophin in diabetes (Fig. 1e).
Betatrophin+STZ treatments also caused substantial increases in glucose levels, however, to a significantly lesser extent especially on days 2, 4 and 7 and only peaked at 16 mM (Fig. 1B). Body weight was significantly different between the STZ and STZ+betatrophin groups on day 7 (12.81±0.37 g, n=9 vs. 13.82±0.25 g, n=11). There was a tendency of the STZ+betatrophin rats to grow faster from the 4th to the 7th day of age (Fig. 1c). STZ treatment caused a slight delay in weight gain (Fig. 1d) and a decrease in pancreatic weight, especially on day 7, both of which were prevented by betatrophin treatment ( Fig. 1 and Table i).
Betatrophin treatment reverses the depletion of plasma insulin and the mortality caused by STZ. With partial destruction of β cells, plasma insulin levels in neonatal rats were significantly lower by approximately 30% at 4 and 7 days after STZ injection, an effect that was completely reversed by the treatment of recombinant betatrophin ( Fig. 2a and B). Treatment with betatrophin alone in normal neonates did not significantly affect insulin levels.
STZ injection caused very severe hyperglycemia. The affected pups became pale and inactive, and 36% of them in fact died within 2-4 days ( Fig. 2c and d). This high mortality rate was once again completely prevented by co-treatment of betatrophin, supporting the notion that early administration of betatrophin protected the newborns from diabetes and mortality.
Betatrophin treatment promotes β-cell proliferation in STZ-treated rats. Betatrophin may protect neonatal pups by preventing β-cell death caused by STZ, or by promoting β-cell proliferation thereby replacing the lost cells. in order to determine whether the increase in plasma insulin level after betatrophin administration in the STZ+betatrophin rats was due to enhancement in β-cell replication, we performed immunofluorescence on pancreatic sections from 4-and 7-day-old pups. cell proliferation was labeled using nuclear protein Ki67 and colocalized to β cells using insulin (Fig. 3) The ratios of Ki67-positive β cells were calculated from representative images, and the results illustrated using bar graphs. it was found that, in 4-day-old pups, 23% of the β cells underwent proliferation normally; STZ treatment caused a 50% reduction to 12%, while betatrophin+STZ treatment resulted in higher than normal ratios of β-cell proliferation to 32% ( Fig. 3a and B, 4th vs. 3rd bar). The rate of β-cell proliferation was greater than restored, consistent with the restored insulin level. a similar result was obtained at 7 days, while a 20% decrease in β-cell proliferation by STZ treatment was more than fully compensated to 35% of the normal ratio ( Fig. 3c  and d, 4th vs. 3rd bar).
Betatrophin treatment increases PDX-1 and reduces the Bax/Bcl-2 ratio in STZ-treated neonatal pancreas. To identify the mechanism governing the restoration of β-cell proliferation and insulin production, we examined possible changes in expression of PdX-1, a key transcriptional factor involved in pancreatic development and β-cell function, as well as that of pro-apoptosis protein Bax and anti-apoptotic protein Bcl-2. Western blot analysis and densitometry showed that PdX-1 levels were only slightly decreased by STZ treatment at either 4 or 7 days (Fig. 4a, B, d and e, 3rd vs. 1st bars); betatrophin+STZ treatments significantly increased PdX-1 levels to 1.3 and 3-fold above STZ-treated levels, respectively (4th vs. 3rd bars). Betatrophin treatment itself had no effect on normal PdX-1 expression in young rats (2nd vs. 1st bars). at 4 and 7 days, betatrophin treatment significantly reduced Bax protein expression, while increased Bcl-2 protein level in the STZ-treated rats ( Fig. 4a and d). Thus, betatrophin caused inhibitory effect on the ratio of Bax/Bcl-2 (P<0.05, Fig. 4c and F, 4th vs. 3rd bars). no difference in the Bax/Bcl-2 ratio was observed between the untreated and untreated+betatrophin group (P>0.05, Fig. 4c and 4F, 1st vs. 2nd bars). The changes in PdX-1 and Bcl-2 levels indicate potential stimulation by the treatment of betatrophin and potential involvement in restoring β-cell mass, function and/or rescuing from diabetes.
Long-term effects on blood glucose, insulin levels, glucose tolerance and β-cell mass after neonatal treatments of STZ and betatrophin. To study the recovery from acute STZ and betatrophin treatments in the newborn period and in addition to studying the possible long-term influence of betatrophin administration, we followed a group of pups until they reached adulthood at 10 weeks. Fig. 5a illustrates the changes in overnight fasting blood glucose levels. There was hyperglycemia at 3, 4, 9 and 10 weeks with transient normalization to close-to-normal over 5-8 weeks. Betatrophin-treated mice displayed largely normalized glycemia from STZ, close to that of the untreated rats.
intraperitoneal glucose tolerance was assessed at 3, 5, 7 and 9 weeks (Fig. 5B). on both occasions, STZ-treated rats exhibited glucose intolerance as opposed to untreated animals. Those treated with betatrophin exhibited completely normalized responses, indistinguishable from those of the untreated rats, but significantly lower than those of STZ alone treated rats (Fig. 5c using auc). These results suggest that STZ treatment resulted in a long-term glucose intolerance that was corrected by treatment with betatrophin during the neonatal period. The effect was persistent.    The animals were then sacrificed at 10 weeks of age. As shown in Fig. 6a and B, STZ rats with glucose intolerance and hyperglycemia had significantly lower body weights (-15%) and elevated blood glucose levels (+15%). early treatment with betatrophin significantly improved body weight to 95% of the normal as well as normalizing blood glucose levels. Betatrophin treatment significantly increased serum insulin levels by 15% compared to the STZ group (Fig. 6c).
Finally, we assessed the islet morphology using immunohistochemistry (Fig. 6e). on average, STZ-treated rats exhibited smaller islets that were stained using insulin antibody. Treatment of betatrophin in addition to STZ caused significant normalization (Fig. 6D). STZ rats exhibited only 1/3 of the β-cell area of the untreated rats, that was increased to 55% by treatment with betatrophin. These results suggest that neonatal STZ administration causes reduced insulin production in the pancreas and reduced hyperglycemia from newborn to 10 weeks of age. Betatrophin treatment may prevent this deterioration via maintenance of insulin-positive cells and insulin production.

Discussion
The neonatal STZ-induced diabetes mellitus model is valuable to study the regeneration of β cells. Streptozotocin (STZ) administration with 100 mg/kg body weight in newborn rats causes severe destruction in β cells, followed by spontaneous remission. Several studies have reported that this partial recovery of β cells may be modulated by exogenous factors (20,21). in the present study, we investigated whether recombinant betatrophin has a potentially protective effect on neonatal STZ-induced diabetic rats. our results showed that administration of recombinant betatrophin during the neonatal period alleviated hyperglycemia by promoting β-cell proliferation, and exhibited anti-diabetic properties in adults in a neonatal STZ-induced diabetic rat model.
We found that endogenous betatrophin levels in the liver were higher in STZ rats than that in the untreated rats (Fig. 1e), consistent with the observation that serum betatrophin levels were increased in long-term T1dM patients (15). These observations suggest that betatrophin may participate in a compensatory mechanism. Further investigation of the effect of betatrophin in T1dM, it was found that betatrophin ameliorated hyperglycemia in neonatal STZ-induce diabetic rats (Fig. 1), in accordance with previous reports showing that betatrophin improved hyperglycemia (22,23). it was also found that STZ-induced diabetic rats gained significantly less weight in the first week than did the untreated rats (Fig. 1C), while betatrophin improved the body weight gain of diabetic rats from days 4 to 7 (Fig. 1d), suggesting an anti-diabetic effect of Figure 4. Betatrophin treatment increases PdX-1 levels and reduces the ratio of Bax/Bcl-2 in STZ-treated neonatal pancreas. Western blot analysis was performed on protein extracts obtained from pancreatic tissues from the (a) 4-and (d) 7-day-old rats. Graphs represent the densitometric analysis of (B and e) PdX-1 normalized to β-tubulin and (c and F) Bax/Bcl-2 ratio. on day 4, effects of betatrophin on (B) PdX-1 expression and (c) Bax/Bcl-2 ratio in the pancreas of each group. untreated rats (n=6); untreated + betatrophin rats (n=5); STZ rats (n=4); STZ+betatrophin rats (n=7). on day 7, effects of betatrophin on (e) PdX-1 expression and (F) Bax/Bcl-2 ratio in the pancreas of each group. untreated rats (n=7); untreated+betatrophin rats (n=6); STZ rats (n=9); STZ+betatrophin rats (n=11); Bars represent mean ± SeM. * P<0.05, ** P<0.01, STZ rats vs. STZ+betatrophin rats. STZ, streptozotocin; PdX-1, pancreatic duodenal homeobox gene-1; Bcl-2, B-cell lymphoma-2.  betatrophin in the increasing severity of the diabetic state. in Fig. 1B, the STZ treated rats exhibited insulin deficient acute diabetes mellitus 3-5 days after birth. The hyperglycemia observed in the neonates following STZ is only transient which is followed by spontaneous remission (24). Both high rates of replication and neogenesis are known to contribute to the increase in β-cell mass in the neonatal pancreas during the first week (25). Thus, a possible explanation for the decline in glucose level could be the compensatory proliferation of exciting β cells.
We measured plasma insulin levels on days 4 and 7 ( Fig. 2a and B), and found an increase in insulin levels after betatrophin treatment in the diabetic rats, consistent with the observed glucose changes (Fig. 1B). We also found an interesting phenomenon to the effect that neonates became pale and inactive after STZ administration. Betatrophin improved the survival rate from 64 to 100% on day 7, suggesting that early betatrophin treatment may protect neonates from death induced by acute hyperglycemia and liver damage. Zhang et al reported that betatrophin is a stress response protein that increases expression of early response transcription factor (egr1) (26). other studies reported marked elevation of betatrophin levels in cord blood and placental tissues (27,28). Taken together, these data suggest that betatrophin may play a key role in growth and development during the fetal and perinatal period.
Both high rates of replication and neogenesis contribute to the increase in β-cell mass in the neonatal pancreas during the first week of life (24). Betatrophin displayed dramatic effects on proliferation and expansion of pancreatic β cells (29). in the present study, betatrophin did not trigger the proliferation of β cells in normal neonates, but increased the proliferating β-cell number. nevertheless, this function of betatrophin on β-cell replication has been disputed in subsequent studies (13,30), that used ANGPTL8-deficient and ANGPTL8-overexpressing mice. This phenomenon can be explained as betatrophin promotes β-cell proliferation only under circumstances of β-cell deficiency. Another possible reason is that there are several interconnected compensatory mechanisms that regulate cell homeostasis in mice. We therefore hypothesized that betatrophin treatment would promote β-cell proliferation in STZ-induced diabetic neonates with insulin deficiency. in support of our hypothesis, we found increased Ki67-positive cells, representing an elevated rate of cell proliferation in response to betatrophin treatment at two different ages ( Fig. 3B and D). This result agrees with previous findings showing that betatrophin promotes β-cell proliferation and expansion (12,22,23).
We found that betatrophin upregulated the expression of PdX-1 and decreased the Bax/Bcl-2 ratio in the pancreas in neonatal STZ-induced diabetic rats. PdX-1 is a necessary transcription factor for pancreatic development and β-cell differentiation. β cells with reduced PdX-1 expression have an increased rate of apoptosis (31). Bcl-2 is an important anti-apoptotic protein, and Bax is an pro-apoptotic protein (32). in the present study, the upregulated pancreatic expression of PdX-1 and the decreased Bax/Bcl-2 ratio suggest that betatrophin may expand the β-cell mass by enhancing activation of anti-apoptotic mechanisms and promoting differentiation of stem cells into β cells as well as promoting β-cell proliferation. it was reported that betatrophin regulates inflammation via the NF-κB pathway (33)(34)(35). Inflammation is one of the factors leading to apoptosis. We assessed a pro-apoptosis marker with western blot analysis. The ratio of Bax/Bcl-2 indicates that inflammation may exist in the early stage, eventually leading to β-cell apoptosis. Betatrophin may reduce inflammation and eventually improve the apoptosis rate of β cells.
This study was the first to determine that betatrophin preserves islet cell mass and prevents diabetes in adult rats in a neonatal STZ-diabetic rat model. early administration of betatrophin showed anti-diabetic potential by reducing plasma glucose, elevating insulin levels, and improving body weight and glucose tolerance test (iPGTT) in adult rats (Fig. 5). it is likely that STZ has no long-acting effects on pancreatic islets. Therefore, at weeks 5 and 7, the result of the iPGTT was normal in the STZ group. Moreover, there was a higher demand for β-cell mass to maintain normal glucose tolerance. The regeneration and proliferation of β cells in the STZ group might account for the recovery of impaired glucose tolerance. although plasma insulin levels in the STZ group were equal to that of the untreated group, blood glucose levels of the STZ rats was higher than those of untreated rats (Fig. 6a and c). it is possible that newly regenerated islets in the STZ group are able to release similar amounts of insulin. However, the insulin responsiveness may have been impaired due to earlier diabetic damage. There may be other unaccounted compensatory changes behind this discovery. immunohistochemistry revealed that betatrophin increased pancreatic islet area (Fig. 6d). There were few large islets in the STZ-treated rats (Fig. 6e). These results strongly favor the conclusion that betatrophin prevents development of diabetes in adult rats by stimulating β-cell proliferation in the neonatal STZ-induced diabetes model. Betatrophin as an adipokine, played a beneficial role in β-cell proliferation and function. We previously reported that betatrophin (anGPTl8) is closely linked to T2dM and insulin resistance (17). In the present study, we confirmed that betatrophin improved glucose tolerance and promoted β-cell proliferation. Moreover, our group also found that betatrophin decreased the FFa level (36). Thus, betatrophin may be a promising and attractive target for the treatment of obesity and T2dM.
In summary, this study firstly illuminated that administration of recombinant betatrophin during the neonatal period promoted β-cell proliferation, and exhibited anti-diabetic properties in the adult rat in a neonatal STZ-induced diabetic rat model.

Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors' contributions
dZ and YJY designed and performed the experiments, and researched the data. dZ wrote the manuscript. JHY, rW, cSZ, lXW, Yl and lMS contributed to discussion of the experiments and analysis of the data and results. Jd and Jll directed the project, contributed to the discussion and analysis of the results, and reviewed and edited the manuscript. Jd as the corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. FSX interpreted the results and revised the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate
The protocol was approved by the ethics committee of the Medical department of Qingdao university (Qingdao, china). all experiments were conducted in accordance with the national institutes of Health Guide for the care and use of laboratory animals.

Patient consent for publication
not applicable.


extfieldsofstudy:
Medicine
Computer Science

text:
Touch DNA in forensic science: The use of laboratory-created eccrine fingerprints to quantify DNA loss

Touch samples typically contain a limited quantity of DNA, which can be further reduced during collection and analysis. It is not clear, however, at which point(s) the majority of the DNA is lost because there is not a reliable positive control to track the quantity of DNA through the analysis procedures. To take the first step in bridging this gap, we established a set of laboratory-created eccrine, or mock, fingerprints containing known quantities of DNA. Next, we defined a set of process controls to quantify loss at key fail points in the collection/extraction procedures, analyzing a total of 1200 mock fingerprints deposited on four different surfaces. We quantified DNA loss to the surface, the swab and at extraction, completing the evaluation with ANOVA. With better understanding of DNA yields and the mechanisms of loss, targeted process improvements will bring touch DNA samples into even more routine use with standardized, optimized procedures.

Introduction
The Locard Exchange Principle holds that, with contact between two items, there will be an exchange of material [1]: a concept central to the science of fingerprints. The fingers act as vectors of transmission, transferring sweat and oil as ridge detail that is the conventional information-bearing component of the exchange [2]. For the last two decades, however, forensic scientists have recognized the added capability of extracting "DNA fingerprints from fingerprints," [3] that is, the sweat and oil exchange contains a second information-bearing component in the DNA-containing cells that support genetic profiling: this is the science of touch DNA.
Touch samples contain DNA, not attributed to a particular body fluid, that is deposited when an object is handled or touched. The origins of the human DNA in a touch sample have not been definitively elucidated, but many lines of evidence indicate that they are likely to include shed corneocytes [4], endogenous or transferred nucleated epithelial cells [2,5e8], fragmented cells and nuclei [9e11], and cell-free DNA [12e14]. There is broad inter-and intraindividual variation in the quality and quantity of DNA contained in a touch sample, and it can vary based on disparate factors including activity of donor, sex, age, substrate, temperature and humidity [6,15e22]. Therefore, it is difficult to define a true fingerprint as the positive control for the collection and analysis of touch samples. To take the first steps in bridging this gap, the aims of the work described here were: (1) establish a method to generate standardized, laboratory-created control fingerprints containing a known quantity of DNA; (2) quantify loss at key fail points during collection and analysis, providing an empirical basis for the optimization of touch sample methodology; and (3) alter one of the variables (surface) to demonstrate the application of the mock fingerprint method.
Efforts have been made to standardize the deposition of the biological components in previous touch DNA experiments, but none have established a definitive positive control. In earlier studies, donors deposited touch samples by contacting sterile tubes, glass plates or another volunteer's hand for a defined period of time, e.g. 3, 10 or 60 s [15,21,23e26]. Other experimental protocols called for volunteers to rub their hands over a substrate or wear an article of clothing for a prescribed period of time and number of occasions [27,28]. However, because there is such great inter-and intra-person variability and even a single individual can be either a good or a bad shedder depending on his/her specific circumstances at the time of sampling [15], the DNA deposited is not consistent.
Approaches using non-epidermal cell types as a DNA source have been tested as well. Researchers suggested that, since individuals don't carry a consistent amount of cellular material in their fingerprints over time, it was not useful to standardize sampling with multiple collections from the same donor [29]. Other approaches have included the use of known volumes of other body fluids such as blood or saliva [6], or naked, quantified DNA. Such approaches have been employed by multiple groups [20,30e32], but a disadvantage is that these controls have a significantly different biology than touch samples. Differences in cell wall, size and nature of cells from those routinely deposited in true touch DNA cases could limit the applicability and extrapolation of results using these controls from research to crime lab casework.
A different strategy for the standardization of touch DNA controls involved producing the biological material by cell culture. Feine et al. [29] cultured skin-derived human dermal fibroblasts. DNA quantification was indirect; serial dilutions of cell suspensions were extracted and quantified. The quantification values were used to calculate the amount of DNA contained in the cell suspension, and the appropriate volumes were deposited on glass slides for collection by tape-lifting or swabbing. Actively dividing connective tissue cells, the DNA content of which has not been evaluated directly, may not be ideal for use as a control for a touch sample, however.
A challenge in defining a positive control for the collection and analysis of touch DNA lies in the nature of the sample itself e it is a complicated mixture of components that can vary over time [4,33]. In the work described here, we reduced this complexity by defining the basic components of an eccrine touch sample to include human diploid cells in an inorganic solution [34,35]. This simplification established a baseline set of conditions under which we could evaluate the effects of a simple eccrine background on DNA collection and loss. In future experiments, we can independently evaluate the effects of specific variables, such as the inclusion of fatty acids [36] or different sources of DNA, e.g. microbial or cellfree [12,13,37], in an effort to develop a better understanding of the optimal collection and analysis techniques.
The touch sample positive control described here is a laboratory-created, or mock, eccrine fingerprint. The general preparation scheme is: (1) prepare a suspension of human diploid cells; (2) count the number of cells per microliter; (3) use #cells/ml to calculate the volume of cell suspension containing the target quantity of DNA, e.g. add 2.85 ng to a mock fingerprint (475 cells x 0.006 ng/cell ¼ 2.85 ng DNA). If the count was 110 cells/ml, then 4.3 ml of suspension contained 475 cells, or 2.85 ng DNA; (4) combine the target suspension volume with an inorganic fingerprint solution; (5) deposit the mock fingerprint on a surface; (6) collect and analyze.
Through creation of a consistent reproducible mock fingerprint, the variability of human true fingerprints can be eliminated, thereby enabling improved evaluation of other variables on   recovery of touch DNA.

Fingerprint solution
The 1X fingerprint solution contained the major inorganic components identified in earlier studies: 0.197 M urea, 0.195 M NaCl, 0.0866 M KCl, 0.0678 M lactic acid in 98% sterile water [34,35].

Cell suspension
Samples from human subjects were collected with informed consent using the University of Illinois at Chicago protocol (2016_0431). Buccal epithelial cells were collected from multiple donors over the course of the study by swabbing the inside cheek with a sterile cotton-tipped swab (Puritan, Guilford, ME). The cotton tips were removed from the shaft to 500 ml of 1X Accumax™ Cell Dissociation Solution (Innovative Cell Technologies, San Diego, CA and incubated for 15 min at room temperature. The swab was removed from the tube and an additional 500 ml Accumax™ was added before a second 15-min incubation at room temperature.

Improved Neubauer hemocytometer
A cover slip was placed on the hemocytometer and 10 ml of the homogeneous suspension pipetted under the slip. The cells in the nine squares were counted and concentration determined: (Total # of cells/9 squares) x (1 square/0.1 ml) ¼ cells/ml. Two different aliquots from each suspension were used for counting, for a total of 18

LUNA™ Automated Cell Counter (logos biosystems, South Korea)
Cells were counted according to the manufacturer's no-dye protocol. Ten microliters of the cell suspension were added to the counting slide and placed into the cell counter. The operating parameters were: Dilution 1; Noise Reduction 6; Live detection sensitivity 2; Roundness 40; Min. cell size 5; Max cell size 60; Declustering level Medium. From a single suspension, three aliquots of 10 ml each were counted three times each, for a total of 9 data points.

Laboratory-created eccrine (mock) fingerprints
Each counting technique was considered individually. The eighteen (hemocytometer) or the nine (LUNA™) cell counts were averaged separately. The LUNA™ cell counts were used for the generation of the data presented here. The mean number of cells per microliter of suspension was converted to volume of suspension required to deliver a specific quantity of DNA (1 epithelial cell ¼ 6 pg DNA). The volume was brought to 18 ml in 1X PBS and combined with 2 ml of 10X Fingerprint Solution. The entire 20 ml volume was pipetted on a surface over an area of approximately 3.63 cm 2 and allowed to dry at room temperature (~1 h). To collect the mock fingerprint, a sterile, cotton-tipped swab was wetted with 20 ml 2% SDS and the area swabbed completely [38]. A total of 1200 mock fingerprints were generated and analyzed -300 for each of the four surfaces (glass slide, steering wheel, drug baggie, brass door plate).

Surfaces: decontamination
A total of four surfaces were included in this study. Glass microscope slides (Fisher Scientific, Norcross GA) were decontaminated by placing the slides in a beaker filled with a 10% bleach solution for at least 10 min, then rinsed in water for at least 5 min. The slides were then cleaned with 70% ethanol and air dried. Once they were completely dry, each slide was individually wrapped in foil, set out in a single layer, and sterilized in an autoclave.
The other three surfaces were: (1) a Nissan Altima OEM Steering Wheel (1-stopautoparts, https://www.ebay.com/str/1stopautoparts), (2)  For decontamination, these objects were placed in a biological safety cabinet and washed with RNase Away followed by 70% ethanol. Once dry, the surfaces were cleaned with sterile NanoPure water and allowed to air dry.

ATR FTIR
Fourier transform infrared spectroscopy with attenuated total reflectance was used to confirm that the drug baggies used in this study were similar to baggies collected as evidence by the Illinois State Police Department ( Supplementary Fig. 1). A FSC-C Nicolet iS10 FTIR with an ATR diamond crystal collected spectra from 4000 cm À1 to 450 cm À1 with resolution set to 4 cm À1 . A sample was compressed against the diamond cell and the spectrum was collected with a total of 36 scans.

Isolation and purification of DNA
DNA was extracted from samples using a standard phenol:chloroform method [39]. Briefly, the cotton tip was removed from a swab and incubated overnight at 56 C in 400 ml DNA extraction buffer (100 mM NaCl, 10 mM Tris-HCl pH 8.0, 25 mM EDTA, 0.5% SDS, 0.1 mg/ml Proteinase K). The swab was removed to a Spin-X filter (Corning, Tewksbury, MA) and the tube centrifuged. Four hundred microliters of 25:24:1 phenol/chloroform/isoamyl alcohol (Fisher, Scientific, Norcross, GA), were added, and the phases were separated in a Phase Lock Gel Tube (2 ml, heavy, Eppendorf, Boulder, CO) according to the manufacturer's protocol. DNA was precipitated for at least 1 h in 1 ml (2.5 vol) absolute ethanol at À20 C and pelleted by centrifugation. The pellet was washed twice with 1 ml (2.5 vol) 70% ethanol and dried in a 56 C incubator (~10e20 min). The DNA was re-solubilized in 30 ml sterile water by overnight incubation in a 56 C water bath (12e18 h).

Quantification
Human DNA was quantified by Alu-specific real-time PCR [40]. Table 2 DNA Loss: Glass Slides. Twenty replicate mock FP standard curves were produced for each of the three process controls (slide, swab, direct). DNA recovered was quantified by real-time PCR, and the values from a twenty replicate set were used to calculate the mean DNA recovery. Subtracting that value from total quantity deposited gave the mean DNA loss, to provide the average percent DNA loss as follows: ((mean DNA loss/total DNA deposited)*100).  Ten microliter reactions were prepared containing: 2 ml of purified DNA, 2.6 ml of nuclease-free water, 5 ml of 2X iTaq Universal SYBR Green Supermix (Bio-Rad, Hercules, California), and 0.4 mM each primer (forward-GTCAGGAGATCGAGACCATCCC; reverse-TCCT GCCTCAGCCTCCCAAG) (Sigma Aldrich, St. Louis, MO). The standard curve ranged from 0.0077 ng/ml to 16.7 ng/ml with a total of eight data points and was generated using a human genomic DNA standard (Bioline USA Inc., Taunton, MA). The cycling conditions Table 3 DNA Loss: Key Fail Points. The total percent DNA lost from glass slides was quantified by the surface process control. Loss resulting from the extraction procedure was the value from the direct process control. The quantity of DNA left on the surface was calculated as (percent loss: surface) e (percent loss: swab), and the amount retained on the swab was (percent loss: swab) e (percent loss: direct were: 95 C for 2 min; 35 cycles of 95 C for 15 s, 68 C for 1 min. A melt curve was generated from 65 C to 95 C to confirm the single PCR product.

Visualization of cells
Trypan Blue. Buccal epithelial cells were suspended in either 1X PBS (Fisher Scientific) or 1X Accumax™ (Innovative Cell Technologies, Inc, San Diego CA). Ten microliters of the cell suspension were added to an equal volume of 0.4% dye. After incubation for 3 min at room temperature, the entire volume was pipetted onto a clean glass slide and allowed to dry under a biosafety hood for 1 h. The slides were heat-fixed for 1.5 min at 105 C. After cooling, the slides were mounted in Permount™, allowed to dry overnight before visualization under a bright field microscope.
True fingerprints were deposited on clean glass slides. Prior to donation, volunteers carried on with their normal daily activities, but refrained from handwashing for at least an hour. Prints were collected from the thumb, index, and middle fingers. Donors placed their fingers on the glass slides and rolled them from side-to-side for 10 s. The slide was stained with 10 ml of 0.4% trypan blue and visualized immediately under the bright field microscope with 40X or 100X magnification. Hematoxylin

DNA amplification and genetic analysis
Purified DNA was profiled using the Ampf[STR® Identifiler ® Plus PCR Amplification Kit (ThermoFisher Scientific, Waltham, MA), according to the manufacturer's protocol. PCR product was analyzed using the 3130 Genetic Analyzer (ThermoFisher Scientific). One microliter of PCR product was combined with 0.5 ml GS LIZ 600 Lane Standard and 9.5 ml deionized formamide. Samples were electrophoresed on the 3130 Genetic Analyzer with the following run parameters: G5 dye set; Oven Temperature: 60 C; Polymer_-

Selection of human diploid cells
The outer layer of the hand's epidermis comprises tightly packed, keratinized, squamous epithelial cells that can be deposited as components of touch DNA [41e43]. These characteristics were considered when identifying the type of human diploid cells to include as the DNA source in the laboratory-created eccrine fingerprint, or mock fingerprint (MFP). Both isolated white blood cells and palmar scrapings were evaluated and discarded as the cell source. The white blood cell was too dissimilar to the epidermal epithelial cell, and palmar scrapings contained only a sparse population of anucleate cells.
The squamous epithelial cells lining the mucosa of the buccal cavity were similar to palmar cells but retained intact nuclei. To evaluate their use, cell suspensions were prepared from both true and mock fingerprints and deposited on glass slides. The cells were stained using both hematoxylin/eosin (H&E) and trypan blue and were visualized by bright field microscopy. The H&E stained true fingerprint contained flattened, irregularly-shaped, and mostly anucleate cells (Fig. 1A). In the dye exclusion test, the majority of  these cells took up trypan blue (Fig. 1B). The buccal cells in the MFPs had a similar morphology but retained their nuclei (Fig. 1C) and gave comparable results in the dye exclusion test (Fig. 1D). As a result of these similarities, buccal squamous epithelial cells were selected as the DNA source in the MFPs.

Laboratory-created (mock) eccrine fingerprints
Accurate cell counts were critical for the conversion of #cells/ml to ng DNA/ml. However, cells suspended in water or PBS formed large aggregates, or clumps, making accurate counting impossible (Fig. 2 A&B). Anti-clumping was achieved by suspending cells in Accumax™ Cell Dissociation Solution [44], a reagent optimized to replace trypsin and collagenase treatments in applications such as tissue dissociation, cell counting, and the dissolution of cell clumps (Fig. 2C&D).
To confirm the success of the anti-clumping protocol, reproducibility of the cell counting techniques were evaluated. Counts were completed for each of five different suspensions using either a manual (improved Neubauer hemocytometer) or an automated method (LUNA™ Automated Cell Counter). The eighteen (hemocytometer) or nine (LUNA™) replicate counts for each of the five suspensions were averaged and the standard deviations calculated (Table 1). Complete supporting data is provided as Supplementary Table 1 A&B. The averaged cell count values from each suspension differed, which was to be expected due to biological variation, but data points from a single suspension clustered around the mean, as demonstrated by strip chart (Fig. 3).
With the reproducibility of both manual and automated cell counting established, the #cells/ml of suspension could be used to calculate the volume containing the target DNA quantity, e.g. add 9 ng DNA to a mock fingerprint (1500 cells x 0.006 ng/cell ¼ 9 ng DNA). If the cell count was 168 cells/ml, then 8.9 ml of suspension contained 1500 cells, or 9 ng DNA, which were added to the Fingerprint Solution to produce a MFP.
The complete MFP procedure was: (1) generate a suspension of buccal epithelial cells in Accumax™; (2) count the # cells/ml and convert to ng DNA/ml; (3) add the volume of cell suspension containing the target DNA quantity to Fingerprint Solution; (4) pipet the MFP onto a substrate, air-dry and collect by swabbing; and (5) extract the DNA.
In the present study, we optimized mock eccrine fingerprints containing directly quantified amounts of DNA sourced from stratified squamous epithelial cells. Recent published studies [41e43] and our own work ( Figs. 1 and 2) have demonstrated that nucleated cells can be visualized in deposited fingerprints. The number of nucleated cells can be directly and reliably equated to DNA content for the purpose of tracking loss during collection/ extraction. Using these results as a baseline for comparison, we can selectively alter, add and/or remove various other organic and inorganic components of touch samples to evaluate the specific effects on DNA loss and provide an empirical rationale for targeted process improvements.

Tracking DNA loss
A careful evaluation of the steps of collection and extraction lead to the identification of three major bottlenecks, or key fail points, at which the DNA population in a sample could be reduced significantly: (1) remaining on the substrate; (2) retained on the swab; or (3) lost during the manipulations of DNA extraction. Three process controls were established to monitor loss: (a) depositing the MFP on a surface (surface sample); (b) pipetting the MFP onto a swab (swab sample); and (c) adding the MFP directly to the lysis buffer (direct sample). During protocol development and optimization, MFPs containing cells numbering from 0 to 8000 (0e48.0 ng DNA) were evaluated. Ultimately, we refined this to a five-point range encompassing the typical quantities of DNA recovered from true fingerprints in our hands; this could be extended to include higher numbers as method sensitivity increases with targeted process improvements. Each of the five points was defined by the number of cells, which translated to the nanograms of DNA deposited, and was given a unique identifier: Cells for the MFPs were drawn from five single-source  suspensions donated by one male and two female volunteers over the course of five days. Twenty replicates were generated for each of the five points, MFP1 through MFP5, and deposited on glass slides to produce a five-point, one-hundred sample set for each process control (surface, swab and direct). Negative controls including a clean swab, a swab of a clean slide, and a reagents-only sample were completely free from DNA in all experiments. The sets of MFPs were collected with cotton-tipped swabs wetted with 2% SDS. The DNA was extracted using a standard phenol:chloroform protocol and quantified by real-time PCR. Strip charts showed the twenty-point data sets for each of the process controls clustering around their respective means (Fig. 4). There was no DNA recovered from any of the zero-cell samples, and they were omitted from further analyses. We averaged the DNA extracted from the twenty replicates within each of the remaining sets to calculate the mean DNA recovery ( Table 2, complete data provided in Supplementary Table 2). Subtracting that value from total DNA deposited gave us the mean DNA loss, to provide the average percent DNA loss as follows: ((mean DNA loss/total DNA deposited)*100) ( Table 2). For the surface samples, the average DNA loss ranged from 69 to 77% (mean 73%, SD 3.6). The range for the swab samples was 55e61% (mean 59%, SD 2.9), and for the direct samples, 27e42% (mean 34%, SD 6.2). Further strengthening confidence in the data, plotting the data points as a standard curve of DNA recovered vs DNA deposited (Fig. 5) confirmed linearity, with R 2 values averaging 0.9933 (0.9896-surface; 0.9935-swab; 0.9968direct).
We used the mean DNA loss values for the three process controls to track the loss at each of the key fail points. The slide control accounted for DNA loss over the complete collection and extraction procedures, or total percent loss. The swab sample represented the quantity of DNA remaining on the swab plus the material that was lost during extraction. Loss solely due to the extraction procedure was defined by the direct sample. Therefore, the quantity of DNA remaining on the slide was calculated as: (surface) e (swab), and the amount retained of the swab was: (swab) e (direct). A summary of the data is included in Table 3.
An average of 73% (SD 3.9) of the total DNA deposited was lost during the complete collection and extraction procedures, which is generally in agreement with the published literature [45e47]. The mean DNA remaining on the slide after mock FP collection was 16% (SD 3.9), and an average of 24% (SD 4.9) of the DNA was retained on the swab. It was not clear at this point, however, whether these losses resulted from properties of the collection device or characteristics of the surface. Finally, an average of 34% (SD 6.2) of the DNA was lost during extraction. We chose the organic phenol:chloroform extraction because it has long been considered a gold standard [48,49], but it remains possible that the use of protocol enhancements, such as the inclusion of glycogen or carrier RNA [50e52], or of different extraction technologies would have resulted in a lower DNA loss and should be explored. Using the collection and extraction methods in this study, these results indicate that the majority of the DNA in a touch sample is lost during collection and analysis, reducing the value and utility of such evidence in an operational crime laboratory.
Together, the losses to the surface and the swab account for more than half of the total. Therefore, we began to further differentiate these key fail points by altering the surface variable. We selected three items, representative of surfaces where biological evidence might be deposited at a crime scene, to include further testing -a (Nissan Altima) steering wheel, drug baggies, and a brass door plate (Supplementary Fig. 2). Using the baseline protocol developed with the glass slides, we evaluated DNA loss with these surfaces at the key fail points. Twenty replicate mock FPs for of the five points comprising the standard curve (0.00, 1.50, 2.85, 4.95, 9.00 ng DNA) were deposited as the three process controls (surface,  swab and direct), resulting in one-hundred sample standard curves for each new surface. DNA recovered from the samples was quantified by real-time PCR, and the values averaged to calculate mean DNA recovered (Table 4, complete data is available in  Supplementary Table 3). From these values, we calculated the mean DNA loss per MFP set (DNA deposited minus DNA recovered) and mean percent DNA loss ((mean DNA loss/DNA deposited)*100) ( Table 4). Next, we calculated the average percent DNA loss from the four positive mock fingerprints -MFP2 through MFP5 -for each process control on each surface.
Steering Wheel. Strip charts were generated from the twentypoint data sets deposited on the steering wheel, on the swab and into the lysis buffer, showing the values for DNA recovered clustering around the mean (Fig. 6). Plotting the averaged data points as a standard curve of total DNA recovered vs DNA deposited confirmed the linearity of the data (Fig. 7), with R 2 values averaging 0.9950 (0.9965-surface; 0.9890-swab; 0.9996-direct). The averaged percent DNA loss across MFP2 through MFP5 within each of the three process control sets was relatively constant; 77% (SD 1.4) for the surface samples, 59% (SD 2.2) for the swab samples, and 31% (SD 1.4) for the direct samples.
Drug Baggie. Strip charts of the DNA recovered from MFPs that were deposited along the zip top closure, on the swab and directly into lysis buffer confirmed the clustering of the values (Fig. 8). A standard curve of total DNA recovered vs total DNA deposited confirmed linearity (Fig. 9); R 2 values averaged 0.9977 (0.9999surface; 0.9968-swab; 0.9965-direct). We averaged the percent DNA loss for MFP2 through MFP5 for each of the process controls, finding it to be relatively constant: 56% (SD 1.9) for the surface samples, 55% (SD 1.7) for the swab samples, and 32% (SD 1.2) for the direct samples.
Brass Door Plate. The DNA recovered from MFPs deposited on the brass door plate, on the swab and into the lysis buffer displayed as clustered strip charts (Fig. 10). The standard curves of total DNA recovered vs total DNA deposited showed the data fitting closely to Table 5 DNA Loss: Key Fail Points. Total percent loss from the steering wheel, drug baggies, and brass door plate was evaluated using the surface process control. Loss resulting from the extraction procedure was quantified with the direct process control. The quantity of DNA left on the surface was calculated as (percent loss: surface) e (percent loss: swab), and the amount retained on the swab was (percent loss: swab) e (percent loss: direct).  We tracked the mean DNA loss at each of the key fail points using the values collected for the process controls; they were: total percent loss (surface sample), percent loss at extraction (direct sample), percent retained on surface (surface minus swab), and percent retained on swab (swab minus direct). A summary of the data is included in Table 5. The major differences were detected in the mean percentages of DNA retained on the surfaces and total DNA lost. The drug baggies and the door plate retained between 3 and 18 times less DNA than the slide and steering wheel, and the total loss decreased by approximately 30%. To provide a further statistical evaluation of the data, we defined four treatments e slide, steering wheel, drug baggie, brass door plate. Within each treatment, we used the averaged percent loss for MFP2 e MFP5, and completed pairwise comparisons by ANOVA with post-Hoc Tukey HSD test (Table 6).
Variance was insignificant for both the % retained on the swab and % lost at extraction for all pairwise comparisons. This was not unexpected because the "swab" and "direct" procedures were not altered between sample sets. There were two treatment pairs with no statistically significant differences in total % loss: slide/steering wheel and baggie/door plate. The total percent DNA retained on the surface was not variable within the slide/steering wheel group, but was for the baggie/door plate. Significant variance in the total % loss was observed between: (1) slide and baggie; (2) slide and door plate; (3) steering wheel and baggie; and (4) steering wheel and door plate. The pairwise comparisons also showed significant differences in the % retained on the surface between: (1) slide and baggie; (2) slide and door plate; (3) steering wheel and baggie; (4) steering wheel and door plate; and (5) baggie and door plate.
Although the relative porosity and finish of the slide and the steering wheel were dissimilar, there was insignificant variance between their total % loss and the % retained on the surfaces. A closer look at the composition of the slides provided a likely explanation for the results. The majority of commercial glass, including microscope slides, is soda-lime glass. Typical components are: Na 2 O (soda, 12e16 w/t%), CaO (lime, 10e15 w/t%), and SiO 2 (silica, 70e75 w/t%) [53].
There was an insignificant variance between the total % losses from the baggie and the door plate. This was consistent with the nature of the materials; the baggies were made of polyethylenewaterproof and resistant to condensation -and the door plate was satin clear-coated brass, optimized to protect the surface and inhibit corrosion. The difference between the average percent retained on the individual surfaces was statistically significant, with 1% retention on the baggie and 6% on the door plate, but these numbers were in sharp contrast to those resulting from the slide and steering wheel.
As a final test, samples from each of the process control groups were amplified using the AmpF[STR® Identifiler® Plus PCR Kit to confirm that the mock fingerprints supported downstream DNA profiling. Complete profiles were generated for all samples; a representative sample is Fig. 12 (250 cell, surface control).
Collectively, these baseline results suggest that, as a starting point, the exploration of alternative collection devices, additional surfaces and different extraction techniques in future experiments is warranted. This information should help us optimize the collection and extraction protocols for touch DNA, taking into consideration the variables of each scenario.

Conclusions
The goal of forensic science is to maximize the value of evidence. Through examining the process flow to demonstrate key fail points, touch DNA will be better utilized to solve and prevent crimes. Published data and reports from operational scientists have indicated that up to 90% of the DNA in a sample can be lost during collection and analysis [46], however other studies average this loss at approximately 39% [47]. In the present study, we calculated percent DNA loss from touch DNA samples ranging from 56 to 77%. Considering any of these values, this means, from an operational stand-point, a vast amount of evidence and the answers it may have provided have potentially been lost. This is particularly problematic in cases of touch DNA, where sample is limited to begin with. It has been difficult to quantify this loss and evaluate improvements empirically because there has been no positive control since the DNA content in true fingerprints is extremely variable, thus a starting point cannot be established. In this work, we describe efforts to bridge this gap that are rooted in a collaboration between research and operational forensic scientists. This synergy has allowed each group to provide specific expertise to maximize the efforts and produce a valuable tool for future studies as well as enhance applicability to forensic casework.
As a positive control for the collection and analysis of touch DNA, a protocol for laboratory-created eccrine fingerprints containing a known quantity of DNA was developed and optimized. The complexity of a touch sample was reduced to establish a baseline set of conditions against which other variables, such as the addition of fatty acids or the effects of different collection devices and extraction procedures, can be independently evaluated in future studies. The three process controls allowed us to quantify DNA loss at key points in collection and analysis. Creation of a robust fingerprint standard curve enabled elimination of the large range of variation seen between individuals. In future experiments, this will enable the range of DNA deposited at a crime scene by sloughers and shedders to be framed, so that variables which impact the capture of DNA can be established.
An increase in understanding of the challenges in efficiency of each step in the DNA sample workflow has major ramifications in terms of potential improvement for all biological sample types, including semen, blood and saliva. Improvements in efficiency in obtaining samples from substrates and subsequent extraction will broaden the number of samples that will yield successful profiles, particularly when the starting quantities are low or environmentally challenged, as is the case with touch samples.
With better understanding of DNA yields and the mechanisms of loss, targeted process improvements will bring touch DNA samples into even more routine use with standardized optimized procedures. Depending on substrate type and porosity, it is a challenge to obtain all the available DNA, however these findings demonstrate key points of loss to be targeted by process optimization. This will translate to a wider variety of successful sample types and percentage success on similar case sample types. The results will be an improved achievement of the crime lab mission of maximization of evidentiary value.

Declaration of competing interest
None.


Dysregulation of the TOX-RUNX3 pathway in cutaneous T-cell lymphoma

Studies have examined gene expression changes in Sézary syndrome (SS), but disease pathogenesis remains largely unknown, and diagnosis and treatment are difficult. TOX is a transcription factor involved in CD4+ T-cell development with downstream effects on RUNX3, a known tumor suppressor gene. We sought to identify genes involved in SS disease pathogenesis with the potential to enable diagnosis and treatment. We utilized previously reported transcriptome sequencing data to construct a list of candidate genes, which was narrowed using pathway analysis. qRT-PCR confirmed TOX upregulation (>7 fold increase) in SS (n = 5), as well as two established markers, PLS3 and KIRD3DL2. We also evaluated expression of members of the TOX-RUNX3 pathway and confirmed downregulation of RUNX3 (0.59 fold decrease) and upregulation of GATA3 (2 fold increase). Moreover, TOX and RUNX3 expression were significantly inversely proportional. Using siRNA to suppress TOX, we demonstrated that TOX knockdown rescues RUNX3 expression and reduces cell viability. We evaluated TOX protein expression in paraffin-embedded skin biopsies with immunohistochemistry, showing nuclear staining of CTCL infiltrates, suggesting it is a candidate diagnostic biomarker. Further studies validating our findings and evaluating the TOX-RUNX3 pathway and the role of TOX as a disease marker and therapeutic target are warranted.

INTRODUCTION
Cutaneous T-cell lymphomas (CTCL) are a heterogeneous group of T-cell lymphoproliferative disorders involving the skin. The most common form of CTCL is mycosis fungoides (MF), which accounts for half of CTCL cases and classically presents with indolent skinlimited patches, plaques, and tumors [1]; however, disease progression and extracutaneous dissemination are possible [2,3]. Sézary syndrome (SS) is a rare leukemic variant of CTCL that has a high mortality rate and a median overall survival rate of 5.1 years, which decreases to as Sézary cell burden increases [4]. Sézary cells are neoplastic CD4+ lymphocytes found in skin, lymph nodes, and peripheral blood. Early detection of SS is associated with positive clinical outcome, but diagnosis is complicated by histological and clinical similarities between SS and other dermatoses [5].
Despite attempts to define gene expression in CTCL, the molecular biology and pathogenesis of the disease remain poorly understood. Genomic studies over the last ten years have attempted to characterize gene expression in CTCL [6]. These studies have aimed to establish biomarkers useful in diagnosis, to elucidate disease pathogenesis, and to discover targets for therapy. Several genes have been identified as upregulated in multiple studies including PLS3, DNM3, and Twist [7][8][9][10][11]. Despite the consensus on dysregulation of a small number of genes, the role of these dysregulated genes in pathogenically relevant pathways has not been well characterized. Further, little is known how the Research Paper effects of treatment and clinical responses correlate with dysregulated gene expression.
Recently, we and others have identified dysregulation of the gene TOX and its protein product, thymocyte selection-associated high mobility group box protein (TOX) in MF [12][13][14][15]. TOX is a transcription factor that contains an HMG box DNA binding domain function necessary for the development of CD4+ cell lineages and lymphoid tissue but not typically expressed in mature circulating CD4+ cells. [16] Overexpression of TOX was also found to have prognostic implications in CTCL as it correlated with thicker lesions, such as patches and plaques as well as disease progression and mortality. [14] TOX was also upregulated in lesional skin from SS patients [15] and in SS peripheral blood mononuclear cells by microarray analysis [11].
To further investigate gene dysregulation in SS, we pooled our previously reported next generation sequence-based transcriptome data comparing CD4+ malignant T-cells with non-malignant CD4+ cells from the same SS patient [17,18], and identified genes likely to be differentially expressed. A number of these genes were selected for validation and analysis, including TOX. After confirming dysregulation of TOX, we also sought to characterize the expression of its downstream targets and the effects of treatment on its expression.
Here, we present our results, confirming the differential expression of TOX and other identified genes, and we propose potential roles for a new pathway in disease pathogenesis.

Candidate gene prioritization and biomarker selection
To identify genetic signatures for SS, we utilized two different forms of transcriptome analysis, based on the results of our previously reported datasets. First, we isolated CD4+ T-cells from both SS patients and normal controls and compared gene expression between the two using next generation sequencing-based transcriptome analysis [18]. This analysis was also used to compare normal control CD4+ T-cells to lesional skin from MF patients [18]. Second, we isolated highly purified Sézary cells and matched non-malignant CD4+ T-cells from the same patient and compared gene expression in these two cell populations as we previously described [17]. The results of these two data collection methods were examined and differentially expressed genes were selected. Genes most likely to be biomarkers and oncogenes were identified with the use of Ingenuity and Metacore software. Finally, an exhaustive literature search of gene expression in CTCL was conducted and genes identified in previous publications were compared with our data. Based on the literature and software analysis, five genes were initially selected for validation: TOX, PLS3, PDCD6, KIR3DL2, and Integrin-β1. The expression levels of these genes using our sequence-based method as well as their biological relevance are displayed in Table 1. PLS3 and KIR3DL2 have been consistently reported as upregulated in SS, and their expression has been confirmed by flow cytometry [6,19,20]. For our initial and verifying studies, samples of purified CD4+ T cells were obtained from five SS patients (Supplemental table) and three healthy blood donors. Real-time PCR analysis confirmed statistically significant overexpression of TOX, PLS3, and KIR3DL2 in SS CD4+ T-cells compared to healthy blood donor samples (Figure 1). PLS3 and KIR3DL2 were over-expressed in all five patient samples in each set of experiments. TOX was over-expressed in four of the five patient samples in each set of experiments. As there has been little reported on the role of TOX in CTCL, we selected it for further analysis.

Gene expression analysis and immunohistochemical staining
Diagnosis of CTCL represents a significant challenge due to the absence of definitive disease markers. Uniquely expressed proteins are ideal candidates to serve as biomarkers of the disease, enabling its diagnosis and management. To evaluate TOX for utility as a diagnostic marker we employed immunohistochemical staining of routine tissue sections from four MF patients, two SS patients, and nine psoriasis controls using commercial antibodies chosen based on their established use in staining formalin fixed paraffin embedded tissues. As PLS3 has not been formally studied with IHC, it was included as well. Both TOX and PLS3 were detected in SS and MF samples ( Figure 2).

Treatment with romidepsin, but not pralatrexate, alters expression of selected genes
To characterize the effects of treatment of CTCL on gene expression, cells isolated from three CTCL patients with treatment-naïve disease were treated in culture. Romidepsin, a histone deacetylase inhibitor, and pralatrexate, an antifolate analogue were selected for study. PBMCs isolated from SS patients were treated in culture with either romidepsin (10nM, 100nM, and 4 μM) or pralatrexate (5 μM and 20 μM) for 48 hours. Gene expression analysis was then conducted using RNA isolated from treated samples. Analysis revealed that TOX and PLS3 expression normalizes with romidepsin treatment but not pralatrexate in CTCL PBMCs cultured for 48 hours (Figure 3a). In normal cells, a global decrease in gene expression was noted in response to treatment that was not specific to either drug (data not shown). Further, CD4+ T-cells were banked from two patients with active disease and from the same two patients following treatment with romidepsin and partial or complete resolution of disease. qRT-PCR analysis of these samples showed TOX and PLS3 expression also normalize in CD4+ T-cells isolated from patients with disease resolution (Figure 3b).

The TOX-RUNX3 pathway is dysregulated in SS
Because TOX is a transcription factor, we sought to examine expression of its known downstream targets, particularly RUNX3, a tumor suppressor gene frequently deleted or transcriptionally silenced in cancer [21,22]. TOX knockdown was recently shown to decrease the expression of ThPOK/ZBTB7B, a transcriptional regulator which serves as an intermediary in the TOX-RUNX3 pathway [23] and is also activated by GATA3 [24]. This pathway is involved in CD4/CD8 fate selection in T-cell development [16,23], and RUNX3 suppression is associated with Th2 skewing [25], which is frequently observed in patients with MF and is associated with advanced stage of disease. TOX was also recently shown to be associated with increased cell viability in malignant Sézary cells [26]. Our sequence-based transcriptome analysis indicated that RUNX3 is downregulated in CD4+ cells from SS patients as compared with those from TOX is a transcription factor highly expressed in the thymus necessary for the development of CD4+ cells but not normally expressed in mature CD4+ cells [16].
Killer cell Ig-like receptor 3DL2 (KIR3DL2) 19.67 n/a KIR3DL2 inhibits natural killer-mediated lysis after interaction with HLA-A, may prevent elimination of tumor cells [36].
Integrins play a role in cellular shape, motility and the cell cycle [37]. In SS, ITGB1 may increase skin homing [38].
Programmed Cell Death 6 (PDCD6) 13 0.16 PDCD6 product participates in T-cell receptor-programmed cell death and may have a role in cancer survival pathways [39].
Ratios of overexpression comparing SS CD4+ cells to normal CD4+ cells as well as MF lesional skin to normal CD4+ cells as determined by previously reported sequence-based analysis are displayed as well as biological significance.  Figure 4d). Importantly, TOX has been hypothesized to play a role in PLS3 upregulation in SS [11]; however, our data did not demonstrate any significant correlation between TOX and PLS3 expression (not shown). Knockdown of TOX expression was performed using two different siRNA constructs (Figure 5a). Cell viability was studied following TOX siRNA knockdown with a resultant decrease in viability following treatment compared with cells treated with negative control siRNA and untreated cells (Figure 5b). Moreover, RUNX3 expression in cells treated with TOX siRNA was measured and was rescued following siRNA treatment (Figure 5c).

DISCUSSION
TOX or thymocyte selection-associated high mobility group box is a transcription factor that contains an HMG-box DNA binding domain function. TOX is necessary for the development of CD4+ cell lineages and lymphoid tissue, but is not typically expressed in mature circulating CD4+ cells. [16] TOX indirectly suppresses  [35]. IHC staining for TOX shows strong, nonuniform nuclear staining in CTCL infiltrate but not psoriasis. All images are 40X and were captured using a Zeiss Mirax Midi Slide Scanner with Pannoramic MIDI/Viewer software. www.oncotarget.com RUNX3, a tumor suppressor implicated in many cancers, including solid organ malignancies, leukemia, and primary central nervous system lymphomas [21,27,28]. RUNX3 modulates the strength of Wnt signaling by complexing with β-catenin and T-Cell Factor 4 [22]. Our data, including transcriptome analysis and qRT-PCR results demonstrate that TOX is upregulated and RUNX3 is downregulated in SS patients. Moreover, knockdown of   was carried out using two constructs and confirmed with qRT-PCR analysis. b. TOX knockdown decreases cell viability more than negative control knockdown determined using a luminescence assay. 100% represents the viability of the untreated group at each respective time point. c. TOX knockdown also produced increased expression of RUNX3 based on qRT-PCR analysis. All pooled data is shown as mean +\− SEM. www.oncotarget.com TOX was associated with increase in RUNX3 expression levels, indicating that TOX may act to decrease RUNX3′s tumor suppressor functions in SS. Importantly, TOX knockdown was associated with decreased cell viability, suggesting that it may play an important role in maintaining the malignant phenotype. Further studies on the effects of TOX expression on RUNX3 and cellular function included evasion of apoptosis and cell migration are warranted.
We examined regulation of RUNX3 by TOX in malignant CD4+ cells derived from PMBCs of Sézary syndrome patients. Interestingly, both TOX and GATA3, which was also previously demonstrated to be overexpressed in CTCL [11], are the negative regulators of RUNX3 expression. GATA3 and TOX proteins may exert their action on RUNX3 through epigenetic or posttranslational mechanisms, because a known intermediary, ThPOK, was not changed in our studies. In support of our conclusions, a ThPOKindependent mechanism of GATA3 effects on RUNX3 was recently reported [29]. McGirt et al. suggests that TOX itself may be upregulated following downregulation of microRNA-223, which is underexpressed in MF and has a binding site in the 3′UTR region of TOX [30]. Huang et al. recently demonstrated that TOX levels correlate with disease-specific mortality in SS patients, an observation that suggests the in vitro results achieved here are correlated to clinical pathogenesis and outcomes [26]. In light of the recent findings by our group and others, the role this pathway plays in pathogenesis of SS is an important area of continued study.
It has been previously suggested that TOX may upregulate PLS3 in SS patients [11]. The overexpression of PLS3 in SS peripheral blood mononuclear cells and SS CD4+ cells has been a single consistently reported finding through many studies [7][8][9]. In our nextgeneration sequence analysis, PLS3 was significantly upregulated in purified malignant CD4+ cells from Sézary patients (83 times in SS compared to both MF patients and normal controls). Such significant and consistent upregulation of a gene not normally expressed in lymphocytes is suggestive of its pathological role in SS. In fact, PLS3 has been implicated in increasing resistance to apoptosis and SS cell migration toward chemokines [31]. However, we did not find any correlation between TOX and PLS3 expression levels, and our data does not support a relationship between TOX and PLS3.
There are no markers currently available for definitive diagnosis of SS and MF. The diagnosis is based on a constellation of morphological, histological, and immunochemical parameters together with clinicpathological correlation. Diagnosis of MF and SS is especially difficult in early stages of the diseases. We hypothesized that overexpression of PLS3 and TOX may result in high and specific expression of corresponding proteins that could be used diagnostically.
To evaluate TOX and PLS3 diagnostic markers, we performed IHC staining of routine paraffin embedded MF and SS biopsy specimens. Using psoriasis samples as negative control, we observed specific positive staining of TOX and PLS3 in SS and MF. Importantly, we have previously demonstrated that TOX and CD4+ stain the same cells in CTCL samples using immunofluorescence [32]. Taken together, our observations indicate that TOX and PLS3 are strong candidates for future prospective biomarker validation studies.
In summary, we have described a novel pathway, the TOX-RUNX3 pathway, in SS and have demonstrated an inverse relationship between TOX, an established marker in CTCL, and a tumor suppressor gene RUNX3, suggestive of an important role of this pathway in disease pathogenesis. Further functional studies are necessary to confirm the role of each individual component of this pathway, including potential role of GATA3. Our results both contribute to the growing body of data defining multicomponent pathways important in disease etiology and pathogenesis, and discovering novel markers for diagnosis and potential therapeutic targets.

Transcriptome analysis
Transcriptome data was analyzed from two sources. A single patient's malignant CD4+ cells were compared to the same patient's non-malignant CD4+ cells as we have previously described. [17] Next generation sequenced-based transcriptome analysis was conducted comparing both CD4+ T-cells from three SS patients and MF skin samples with CD4+ T-cells from three normal controls as we have previously described [18]. These data were analyzed using Ingenuity Pathways Analysis (IPA, http://www .ingenuity.com) and Metacore (Thomson Reuters, http:// thomsonreuters.com) to determine oncogenic potential of upregulated genes.

Cell sample collection, purification, and RNA and protein isolation
For validation of gene expression as well as drug and cell viability studies, peripheral blood was collected from nine histologically confirmed SS patients and four normal controls in total. Using Ficoll-Paque TM gradient centrifugation (Amersham Biosciences Corp, Piscataway, NF), peripheral blood mononuclear cells (PBMCs) were selected. The CD4+ cells were then isolated from whole PBMCs using MACS MicroBeads magnetic beads separation (Miltenyi Biotec, Inc., Auburn, CA). Purity of the resulting population of cells was checked with flow cytometry. From the CD4+ cells, RNA and protein were isolated using the RNeasy kit (Qiagen, Valencia, CA). For cDNA synthesis, total RNA (2 μg) was used for Reverse Transcription (RT) with Superscript II reverse transcriptase (Invitrogen, Karlsruhe, Germany) using oligo dT primers according to the recommendations of the manufacturer. The obtained cDNA was diluted 1:10 with ddH2O and 1 μl was used for each PCR reaction.

qRT-PCR
Quantitative reverse transcription PCR was performed using TaqMan PCR master mix (Applied Biosystems, Grand Island, NY) together with TaqMan probes and primers (Applied Biosystems) using standard conditions. Human B2M was used as an internal control. The experiments were performed on a StepOnePlus™ Real-Time PCR System (Applied Biosystems). The expression levels of the studied genes were normalized to B2M expression. Experiments were carried out three separate days in triplicate. Each assay included a negative control that was lacking template DNA. Relative expression of RNAs was calculated using the two ΔC T method [33]. Statistical analysis was performed using the student's t-test.

Immunohistochemistry
Histologically confirmed, formalin fixed paraffin embedded (FFPE) MF (n = 4) and SS (n = 2) tumor biopsies collected from our institutional tissue bank in accordance with an IRB-approved protocol were used for immunohistochemical analysis of candidate CTCL biomarkers, with FFPE psoriasis (n = 9) lesions selected for use as negative controls. Human esophagus and small intestine were used as positive controls for PLS3 and TOX respectively. Commercial antibodies were acquired for PLS3 (

Treatment with romidepsin and pralatrexate
To study the effects of treatment on gene transcription, two strategies were used. First, patient PBMCs from patients with active CTCL were collected as above. PBMCs were then cultured overnight in RPMI 1640 medium supplemented with interleukin-2 (BD Biosciences, San Jose, CA) 10 U/ml and interleukin-7 (BD Biosciences, San Jose, CA) 10 ng/ml both in a humidified incubator with 5% CO2 at 37°C and the next day divided into treatment groups: 4 μM, 100 nM, and 10 nM romidepsin and 20 μM and 5 μM pralatrexate. Romidepsin and pralatrexate were provided by the UPMC pharmacy. Romidepsin was dissolved in diluent composed of 80% propylene glycol and 20% dehydrated alcohol to a stock concentration of 2 mM and stored at −20°C. Dilutions of 100 and 10uM were made in RPMI 1640 and stored at −20°C for no more than 2 months. Pralatrexate was stored at a concentration of 20 mg/mL in −20°C at for no more than two months and was diluted as needed in RPMI 1640; these dilutions were used within one week. Each treatment was added 24 hours following culture initiation and carried out for 48 hours. Following treatment and prior to gene expression analysis, we performed flow cytometry to ensure that CD4+ cells comprised a similar percentage of each sample, ensuring that subsequent changes in gene expression were not the result of cell death or and altered population.
As described, RNA was isolated with RNAprotect and RNeasy products (Qiagen). Additionally, patient samples were banked from the same patients during active disease and after partial or complete clinical clearance of disease with romidepsin treatment. CD4+ cells were isolated from these samples using MACS magnetic beads (Miltenyi) and RNA was isolated as described. Finally, qRT-PCR was performed using the Quantitect reverse transcription kit (Qiagen) and TaqMan primers and PCR master mix (Applied Biosystems) on all samples. Relative expression of RNAs was calculated using the two ΔC T method [33]. Statistical analysis was performed using the student's t-test.

Gene knockdown
To study the effects of TOX knockdown, siRNA knockdown was used. Two Silencer ® Select siRNA constructs (IDs s18841 and s18840, Ambion, Grand Island, NY) were transfected using TransIT-siQUEST ® Transfection Reagent (Mirus Bio, Madison, WI) according to manufacturer's instructions. Freshly harvested SS PBMCs were plated in a 24-well plate and 0.5 μl of the transfection reagent was added to 50 μl of Opti-MEM I Reduced-Serum Medium (life technologies, Grand Island, NY) then to each well. siRNA was added to a final concentration of 10nM. Incubation was carried out for 24-36 hours. Knockdown was confirmed with qRT-PCR as described above, and expression of RUNX3 was determined.