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Nutrient Interactions and Toxicity

Contrasting and Cooperative Effects of Copper and Iron Deficiencies in Male Rats Fed Different Concentrations of Manganese and Different Sources of Sulfur Amino Acids in an AIN-93G-Based Diet¹

U.S. Department of Agriculture, ARS, Grand Forks Human Nutrition Research Center, Grand Forks, ND 58203 and ^* Energy and Environmental Research Center, University of North Dakota, Grand Forks, ND 58202

²To whom correspondence should be addressed. E-mail: preeves{at}gfhnrc.ars.usda.gov.

	ABSTRACT

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Dietary nutrient interactions are important factors to consider in the study of nutrient status and requirements. Here, the effects of dietary interactions among copper (Cu), iron (Fe), manganese (Mn) and sulfur amino acids (SAA) on blood cell characteristics and enzyme activities were observed. Male rats (n = 8) were used in a 2 x 2 x 2 x 2 factorial design and fed an AIN-93G-based diet containing dietary Cu (<1 and 5 mg/kg), Fe (10 and 35 mg/kg), Mn (10 and 50 mg/kg) and either L-cystine (LCys) or DL-methionine (DLMet). Blood was analyzed by automated hematology cell counting and by flow cytometry. Severe Cu deficiency was verified by reductions in the activities of serum ceruloplasmin (1% of control), RBC superoxide dismutase (SOD1) (14% of control), liver cytochrome c oxidase activity (25% of control) and serum extracellular SOD (SOD3) activity (20% of controls). Because Cu is required for Fe utilization, many physiologic responses that require Fe were affected by both deficiencies, including lowered blood hemoglobin (Hgb), lower RBC volume and Hgb concentration, and an increased number of reticulocytes. Cu and Fe deficiencies together worsened some conditions, i.e., lower Hgb, lower RBC Hgb, increased RBC distribution width, increased number of reticulocytes and nucleated RBC, and a higher platelet count. Increasing dietary Mn had little effect on most variables, except to reduce serum Cu when dietary Cu was adequate but not when it was low, and to reduce RBC SOD1 activity when dietary Fe was low but not when it was adequate. Hgb concentrations were higher (P < 0.002) in Cu-deficient rats fed LCys than in those fed DLMet. There was no effect in Cu-adequate rats. Hgb was higher (P < 0.004) in Fe-adequate rats fed LCys than in those fed DLMet, with no effect in Fe-deficient rats. Although the anemia of Cu deficiency in AIN-93G-fed rats was not as pronounced as that reported in rats fed the AIN-76A-based diet, other manifestations of the deficiency were prominent.

KEY WORDS: • copper • iron • manganese • AIN-93G diet • rats

In nutritional biochemistry studies, the diet formula is one of the most important factors that could affect the outcomes of experiments. Not only do investigators have to consider the concentration and form of the particular nutrient in question, but they must also have knowledge about the nutrient’s interactions with other components in the diet that affect its absorption and utilization. In 1993 formulations of the AIN-93G and M diets were published for use in studies involving laboratory rodents (1,2). These diets were designed to replace the AIN-76A diet that had been in use for a number of years but was associated with problems related to kidney calcification in female rats and survival rate during long-term studies. The AIN-93G diet has been used successfully in short-term studies innumerable times since its inception, and the AIN-93M diet has even been used with success in studies of up to 2 y in duration (3). However, we observed that rats fed the AIN-93G diet low in copper (Cu) are less severely anemic than rats fed the AIN-76A diet with similar concentrations of Cu (unpublished data). Changes in the AIN-93G and M diets that might relate to these findings include the following: 1) lowering the amount of dietary sucrose from 50% to only 10% by replacing it with starch, 2) lowering the Mn content from 50 to 10 mg/kg of diet, and 3) changing the sulfur amino acid (SAA)³ supplement from DL-methionine (DLMet) to L-cystine (LCys).

The dietary carbohydrate source has a pronounced effect on signs of Cu deficiency in male rats. Johnson and Hove (4) found that the severity of Cu deficiency anemia was greater in rats fed sucrose-based diets than in rats fed starch-based diets. Thus, the change in dietary carbohydrate source between the AIN-93G and the AIN-76A alone might be responsible for the less severe anemia reported by some investigators.

However, the other two changes also might affect Cu utilization. Work by Kato et al. (5) and Nielsen (6) suggested that dietary cystine facilitates indirect defects of Cu deficiency by impairing the mobilization of Fe from the liver (7). Similarly, changing the concentration of Mn in the diet could affect Cu deficiency anemia indirectly by affecting Fe absorption and utilization. There is a physiologic interaction between Mn and Fe in which one affects the intestinal absorption of the other, likely because each uses the same divalent metal ion transporter (DMT1) (8). Thus, lowering the dietary Mn from 50 to 10 mg/kg might enhance Fe absorption, thereby ameliorating some of the signs of altered hemopoiesis in Cu deficiency. However, a Cu/Mn interaction also exists that could affect Cu utilization. Johnson and Korynta (9) showed that rats fed 50 mg Mn/kg of AIN-76A diet and adequate Cu had lower plasma Cu concentrations than rats fed 1 mg Mn/kg and adequate Cu. This discovery suggests that 50 mg Mn/kg diet reduces the absorption of Cu because Davis and Feng (10) later found no difference in plasma Cu in rats fed the AIN-93G diet with 0.6 and 17 mg Mn/kg. Thus a number of changes in formulation of the AIN-93 diets compared with the AIN-76A diet might contribute to the attenuation of biochemical markers of Fe utilization induced by Cu deficiency. To test whether dietary Fe, Mn, and/or SAA interactions might affect the hemopoietic and other indices of Cu deficiency, we designed a study with rats in which these dietary ingredients were presented in a multiple factorial design.

	MATERIALS AND METHODS

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
This study was approved by the Animal Use Committee of the USDA-ARS, Grand Forks Human Nutrition Research Center and was in accordance with the guidelines of the NIH on the experimental use of laboratory animals (11). The experimental design was a 2 x 2 x 2 x 2 factorial in which the dietary variables were Cu, <1 and 6 mg/kg; Fe, 10 and 35 mg/kg; Mn, 10 and 50 mg/kg; and SAA as either DLMet or LCys, each at 3 g/kg to meet the NRC amino acid requirement of growing rats (12). The basal diet was similar to the AIN-93G (1). Weanling male Sprague-Dawley rats [strain: SAS:VAF (SD), Charles River/Sasco, Wilmington, MA] were used beginning at 3 wk of age. There were 8 rats/treatment and they had free access to their diets and deionized drinking water for a period of 6 wk. At the end of the experiment, rats were anesthetized with a 1.37:1 mixture of ketamine:xylazine (1 mL/kg body weight, i.p.) [Ketamine HCl (Ketaset), Fort Dodge Animal Health, Fort Dodge, Iowa; Xylazine (Xyla-Ject), Phoenix Scientific, St. Joseph, MO], and blood was withdrawn from the abdominal aorta into tubes prepared with an EDTA anticoagulant (30 µL of a solution containing 121 mmol disodium EDTA/L, pH 7.4, per mL of whole blood). Blood samples were analyzed within 2 h of the collection.

Erythrocyte and platelet indices were assessed with a Cell-Dyn 3500 automated hematology cell counter (Abbott Laboratories, Abbott Park, IL) and with a three-color Coulter Epics XL-MCL flow cytometer (Beckman-Coulter, Miami, FL). Reticulocyte count was determined by flow cytometry using thiazole orange (TO; Aldrich Chemical, Milwaukee, WI) as the fluorescent marker for RNA (13–15). Whole rat blood (10 µL) treated with EDTA was pipetted into 2 mL of a solution containing one part TO solution (1 mg TO was dissolved in 1 mL of methanol) to 10,000 parts PBS containing 2 mmol/L EDTA and 0.02% sodium azide, pH 7.4. On binding to RNA, TO increases fluorescence by a factor of 3000, which implies a high signal-to-noise ratio, giving a reliable reticulocyte count and maturity index (16). An individual control tube was made for each sample by pipetting 10 µL of whole rat blood into 2 mL of PBS. Both the control tube and the TO-stained sample tube were gently mixed and incubated at 20°C for 1 h. Cells were analyzed within 100 min of the start of the incubation on the flow cytometer equipped with a 15-mW argon laser operating at 488 nm as the excitation source. TO fluorescence emission was determined by using a filter with a 525-nm band pass. To separate RBC from platelets, a logarithmic histogram was constructed with side scatter on the x-axis and forward scatter on the y-axis. A rectangular gate was then placed around the RBC in this histogram. The control tube was analyzed first by collecting 25,000 events in the RBC gate. The TO-stained cells were then analyzed by collecting a minimum of 75,000 events in the RBC gate.

After sample collection, data were processed off line by using WinList flow cytometry software (Verity Software, Topsham, ME). A logarithmic histogram was constructed with side scatter on the x-axis and forward scatter on the y-axis to separate the RBC from the platelets and large white blood cells. On this histogram, the dot plot of the cells was divided into 13 regions of equal size. Region 1 was set at a height on the y-axis to include the largest, most complex cells based on forward and side scatter characteristics. Region 2 was set below and adjacent to region 1 and so on through region 13, which contained the smallest and least complex cells.

To calculate the number of nucleated RBC (nRBC), a histogram was created with the log of TO intensity on the x-axis and the number of cells counted on the y-axis. A region was drawn to count the number of cells that had a TO intensity in the fourth decade of the x-axis. These cells were called the TO bright cells (TO dim cells were considered to be reticulocytes) and in theory would include nRBC and WBC. To separate these two populations of cells, the percentage of WBC number, as determined by the Cell-Dyn, was multiplied by the total number of events counted on the flow cytometer. This is the number of WBC that passed through the flow cytometer during the data collection. This calculated number of WBC was then subtracted from the number of TO bright cells to obtain the number of nRBC in the sample, which was then multiplied by the total number of cells counted on the Cell-Dyn; this number was then divided by the total number of cells counted to give the final value of nRBC/µL of whole blood. The tabulated values were converted to the number of nRBC/10⁹ RBC.

A second blood sample was collected from the abdominal aorta and treated to obtain serum. The serum was then analyzed for ceruloplasmin amine oxidase (Cp) activity (17), extracellular superoxide dismutase (SOD3; EC 1.15.1.1) activity at pH 10.0 (18) and Cu, Fe and Mn concentration. RBC were analyzed for SOD1 at pH 8.2 (18), and liver for cytochrome c oxidase (Co1) (19).

The procedures used to prepare and analyze tissue samples for mineral content were similar to those outlined by Reeves and Chaney (20). To ensure adequate quality control, samples of bovine liver with certified concentrations of minerals were analyzed with each batch of tissues [certified ranges; Cu, 152–168 µg/g; Fe, 169–199 µg/g; and Mn, 8.8–12.2 µg/g (National Institutes of Standards and Technology, Gaithersburg, MD)]. Representative assayed values were within the acceptable ranges (mean ± SD, n = 6); Cu, 154 ± 1 µg/g; Fe, 182 ± 4 µg/g; and Mn, 10.1 ± 0.2 µg/g. Serum (0.5 mL) was diluted with 0.5 mL of 3 mol HCl/L and 1.5 mL of 10% TCA. The samples were centrifuged (2000 x g) and Cu and Fe were determined on the supernatant by inductively coupled argon plasma analysis. Manganese was determined on whole serum diluted twofold with deionized water by graphite furnace atomic absorption spectrometry with Zeeman background correction. To ensure adequate quality control, samples of control serum for Cu and Mn were analyzed with each batch of sera (normal ranges; Cu, 0.85–1.2 mg/L and Mn, 1.1–1.7 µg/L; UTAK Laboratories, Valencia, CA). The Fe control serum was from Medical Analysis Systems, (ChemTrack Plus, Camarillo, CA) (normal range; Fe, 1.21–1.64 mg/L). Representative assayed values were within the acceptable ranges (mean ± SD, n = 6); Cu, 1.15 ± 0.01 mg/L; Fe, 1.28 ± 0.03 mg/L; and Mn, 1.65 ± 0.03 µg/L.

The statistical analysis was carried out by using the StatView Statistical Computer Program, Version 5 (SAS Institute, Cary, NC), in a 2 x 2 x 2 x 2 factorial design in which main effects and interactions were computed. Line plots were used to observe differences between treatments when interactions among variables were significant. Main effects and interactions were considered significant when P 0.05.

	RESULTS

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
The values for many of the parameters measured were similar to those found previously by other investigators. Both Cu deficiency and Fe deficiency reduced body weight gain by 5% over the 6-wk period of the experiment (data not shown). Cu deficiency severely reduced (P < 0.001) serum Cu concentration, but Fe deficiency had no effect on serum Cu (Table 1). Overall, serum Fe concentrations were reduced (P < 0.001) to a similar extent in both Cu-deficient and Fe-deficient rats (Table 1). However, when rats were deficient in both Cu and Fe, serum Fe was reduced even further (P < 0.001). There was a slight interaction (P < 0.03) in which serum Fe was lower in Fe-adequate rats fed DLMet than in those fed LCys; however, there was no effect of SAA in Fe-deficient rats (Table 1). Feeding diets with 10 or 50 mg Mn/kg had very little physiologic effect on serum Mn; however, rats fed low Cu, adequate Fe, and 50 mg Mn/kg had slightly higher (P < 0.003) serum Mn than all other groups (Table 1).

Cu concentration in the duodenum of Cu-deficient rats was reduced to 30% of the control values (Table 2). There was an interaction (P < 0.005) between Cu and Fe in which low dietary Fe slightly elevated duodenal Cu in Cu-deficient rats, but reduced it in Cu-adequate rats. Duodenal Cu in Cu-adequate rats fed 50 mg Mn/kg of diet was reduced by 10% compared with that in similar rats fed 10 mg Mn/kg diet (Table 2). There was no effect of Mn on duodenal Cu in Cu-deficient rats. Duodenal Fe was 50% higher (P < 0.001) in Cu-deficient rats than in controls, but in Fe-deficient rats, it was reduced to 50% (P < 0.001) of values found in Fe-adequate rats. Even in the Fe-deficient rats, duodenal Fe was enhanced (P < 0.01) by Cu deficiency.

An interaction (P < 0.001) between Fe and Cu showed that liver Cu concentrations were higher (P < 0.001) in Fe-deficient rats than in Fe-adequate rats when dietary Cu was adequate, but there was no effect of Fe deficiency on liver Cu when dietary Cu was low (Table 3). In Cu-adequate rats, liver Cu was slightly higher (P < 0.003) when they also were fed DLMet, compared with LCys. There was no effect of SAA in Cu-deficient rats. Liver Fe was twice as high (P < 0.001) in Cu-deficient rats as in controls, but in Fe-deficient rats, liver Fe was lower (P < 0.001) than controls (Table 3). Feeding LCys as the SAA supplement decreased liver Fe compared with those fed DLMet, but only when dietary Cu was inadequate (P < 0.009).

Liver Co1 activity is a sensitive indicator of Cu status (21) and overall, Cu deficiency reduced its activity to only 25% of normal (Table 3). There was a complicated 4-way interaction (P < 0.001) among Cu-Fe-Mn-SAA for this variable. The main elements in the interaction occurred in the Cu-deficient rats, showing that when Fe was adequate, 10 mg Mn/kg of diet lowered Co1 activity, but activity was higher in rats fed LCys compared with those fed DLMet. Similar effects were found when dietary Fe was low, but when dietary Mn was at 50 mg/kg, feeding LCys had no effect on activity.

Reduced hematocrit (Hct) and low blood hemoglobin concentration (Hgb) are indicators of both Cu and Fe deficiencies; thus their responses to these dietary factors in the current study were similar (Table 4). Both Hct and Hgb were lower in both Cu- and Fe-deficient rats, but Fe deficiency had a greater effect in Cu-adequate rats than in Cu-deficient rats (P < 0.001). Hgb and Hct were slightly but significantly lower (P < 0.006 and <0.011, respectively) in Cu-deficient rats fed 10 mg Mn/kg diet than in those fed 50 mg/kg, but there were no differences in Cu-adequate rats. Hgb and Hct values were lower in Cu-deficient rats fed DLMet than LCys, but there was no effect of SAA when rats were fed adequate Cu. There was no effect of SAA in Fe-deficient rats, but Hgb and Hct were lower in Fe-adequate rats fed DLMet than those fed LCys (P < 0.004 and <0.009, respectively).

RBC SOD1 activity is a prime marker for Cu deficiency in rats (21) (Table 4). Overall, SOD1 activity was lower in Cu-deficient than in adequate rats, and higher in Fe deficiency (P < 0.002). However, a slight interaction (P < 0.03) between dietary Cu and Mn showed that RBC SOD1 activity was not affected by Mn in Cu-deficient rats, but in Cu-adequate rats, the activity was lower in those fed 50 mg Mn/kg diet than in those fed 10 mg Mn/kg.

The reticulocyte count, expressed as a percentage of the total number of RBC, was about twice as high in Fe-deficient and Cu-deficient rats as in controls (P < 0.001). However, when the two deficiencies were combined, the increase in reticulocyte number was nearly fivefold higher than the controls. There was an interaction (P < 0.008) between Cu and SAA where the reticulocyte count was lower in Cu-deficient rats fed LCys than in those fed DLMet. There was no effect of SAA in Cu-adequate rats. Because many of the individual values were zero for nucleated RBC (nRBC), it was not possible to perform an accurate statistical analysis on these data. However, the number of nRBC was increased manyfold with combined deficiencies of Cu and Fe, compared with the other groups (Table 4).

Platelet count recorded by the blood analyzer was not affected directly by Cu deficiency, but it was 50% higher (P < 0.001) in Fe-deficient than in Fe-adequate rats (Table 4). The difference in platelet count between rats fed 10 and 35 mg Fe/kg diet was much greater in rats fed adequate Cu than in those fed insufficient Cu (P < 0.001). Cu deficiency was reported to increase mean platelet volume (MPV) (22,23); however, we did not observe this effect. Nonetheless, data from the blood analyzer indicated that the MPV was increased (P < 0.001) by Fe deficiency alone, but not by >5% of that in Fe-adequate rats (Table 4).

Figure 1A–D shows graphic outputs from the flow cytometer. A logarithmic histogram was constructed with cell size [side scatter (SS)] on the x-axis and complexity [forward scatter (FS)] on the y-axis. Each graph represents 85,000 events from a single rat in each of four test groups only. RBC (upper) and platelet (lower) regions were separated in the control rats (Fig. 1A); however, when rats were fed Fe-deficient diets, the population of RBC had expanded and migrated down into the platelet population, which was more diffuse than the control (Fig. 1B). Similarly, but to a lesser extent, the RBC region of Cu-deficient rats was larger than that of controls and seemed to have migrated into the platelet region as well (Fig. 1C). However, this platelet region resembled that of the controls. When rats were both Cu and Fe deficient (Fig. 1D), the platelet region was more diffuse than either deficiency alone, and the space between the platelet and RBC regions seemed to be more populated than that for Fe deficiency alone (Fig. 1B). As a result, more cells were counted as platelets in the Fe-deficient rats than in controls. As discussed below, this seems to be an artifact caused by the inability of electronic blood analyzers to discriminate between microcytic RBC and platelets.

View larger version (35K): [in this window] [in a new window]   FIGURE 1 Blood cell size distribution is affected by Cu and Fe deficiency in rats. A logarithmic histogram was constructed with cell size [side scatter (SS)] on the x-axis and complexity [forward scatter (FS)] on the y-axis. Each graph represents 85,000 events from a single rat in each of four test groups, and is for observational purposes only. In this graph, the output from the flow cytometer is depicted as contour colors, which illustrate increasing cell number to the RBC and platelet center peaks (red). In panel A (dietary Cu, 6 mg/kg; Fe, 35 mg/kg), the RBC population (upper region) was clearly separated from the platelet population. In panel B (dietary Cu, 6 mg/kg; Fe, 10 mg/kg), the change in shape of the RBC population was interpreted as an increase in the number of smaller RBC caused by Fe deficiency compared with Fe adequacy (panel A). Many of these cells flowed into the platelet region (lower region) and likely were counted as platelets on automatic cell counters, thus increasing the platelet count. In panel C (dietary Cu, <1 mg/kg; Fe, 35 mg/kg) Cu deficiency also seemed to increase the number of smaller RBC; however, the change in distribution was not as great as in Fe deficiency (panel B). In panel D (dietary Cu <1 mg/kg; Fe, 10 mg/kg), it seems that both Cu and Fe deficiencies together accentuated the problem, but this was not borne out in the representation in Figure 2 in which all of the data are represented.

View larger version (34K): [in this window] [in a new window]   FIGURE 2 Erythrocyte and platelet size distribution is affected by Cu and Fe deficiency in rats. On this histogram, the contour plot (Fig. 1) of the cells was divided into 13 regions of equal size. Region 1 was set at a height on the y-axis to include the largest, most complex cells based on forward and side scatter characteristics. Region 2 was set below and adjacent to region 1, and so on through region 13, which contained the smallest and least complex cells. The cell counts were then determined in each of the 13 regions of this histogram. It can be seen that Fe deficiency caused a shift in RBC size (compare regions 4 and 5 in panels 1–4 with similar regions in panels 5–8). Cu deficiency also caused in RBC size to shift, but it was not as great as with Fe deficiency. The two deficiencies together seemed not to be greater than Fe deficiency alone (panels 12–16). Each point is the mean of 8 observations. SAA, sulfur amino acid.

	DISCUSSION

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

Some of the more prominent manifestations of Cu deficiency found in this study included low serum Cp activity and low serum Cu and Fe concentrations; low liver Cu, but elevated liver iron; altered hematology indices, including microcytic, hypochromic anemia, reduced Hct and Hgb concentrations, a reduced number of RBC, a reduced mean corpuscular Hgb concentration (MCHC), and an elevated RBC distribution width. Cu-deficient rats also had an elevated reticulocyte count and low RBC SOD1 activity, as well as low liver SOD1 and Co1 activities. All of these changes strongly suggest that a rodent diet with the AIN-93G base and low Cu content will produce alterations in the hematological profile as noted previously in rats fed other types of purified diets with low Cu. However, based on findings from past studies, the signs of Cu deficiency shown here might be less severe when compared side-by-side with those found in rats fed an AIN-76A-based diet containing a high concentration of sucrose. Johnson and Hove (4) compared Cu-deficient diets based on 65% of either sucrose or starch and found that after only 20 d of feeding, the hematocrit was lower in rats fed the sucrose diet than in those fed the starch diet. However, other signs of Cu deficiency, such as Cu concentration in liver, heart and spleen, were not affected by the type of carbohydrate. Johnson and Saari (21) fed rats Cu-deficient diets that contained 38% sucrose and 30% cornstarch as the carbohydrate sources. They found that after only 2 wk, plasma Cu and Fe, and blood Hgb concentration were significantly lower than controls. After 6 wk, the Hgb concentration was reduced to 48 g/L in Cu-deficient rats, whereas the control value was 140 g/L. Saari (24) fed similar diets and found 25% hematocrit in Cu-deficient rats and 41% in controls after 6 wk of treatment. For comparisons, in the current study in which the diet contained only 10% sucrose, Hgb values were 110 g/L in Cu-deficient vs. 150 g/L in controls; hematocrit values were 34 and 44%, respectively.

The Cu/Fe connection.

Many of the manifestations of Fe deficiency are similar to those of Cu deficiency. This is primarily because Cu is required for the efficient utilization of Fe. Normally, Fe is not absorbed unless needed; however, in growing animals, a considerable amount of Fe must be absorbed to support the demands for increase in body size and for Hgb synthesis as the blood volume expands. In the current study, the control rats gained 240 g during the experimental period and would have had to absorb 8.6 mg of Fe for Hgb synthesis alone.

Nonheme Fe is absorbed from the intestinal lumen into the circulation through a series of steps beginning with uptake into the enterocyte by the apical membrane transporter DMT1 (25). This step requires Fe in the reduced state, which is carried out by a reductase, duodenal cytochrome b, located in the enterocyte apical membrane (26). The Fe taken into the cell likely equilibrates with various Fe pools. Fe is exported from the enterocyte to the circulation by the basolateral membrane transporter, ferroportin (27), which apparently can transport Fe only in the oxidized state. To accomplish this, a Cu-dependent ferroxidase, hephaestin (Hp) (28), in the intestinal enterocytes, is thought to oxidize Fe²⁺ to Fe³⁺. Fe³⁺ is then transported into the circulation and is bound to apo-transferrin (Tf). If Hp is inactivated in Cu deficiency, the same as Cp, then Fe would not be oxidized and efficiently transported, and might accumulate in the enterocytes. As shown in the current study, duodenal Fe concentrations were nearly 50% higher in Cu-deficient rats than Cu-adequate rats with and without Fe deficiency. If Fe cannot be efficiently absorbed in Cu deficiency, the body Fe stores would not be filled during growth, and serum Fe would be reduced, as observed in the current study. The initial effect of Cu deficiency on plasma Fe seems to occur rather quickly, because Johnson and Saari (21) showed that it was 50% of normal after only 1 wk of consuming the Cu-deficient diet.

Based on studies showing that Cu-deficient pigs (29) and rats (30) have reduced Fe absorption, the above scenario seems logical. However, more recent evidence suggests that this is not the mechanism in rats. Thomas and Oates (31) showed that Fe absorption actually was enhanced in Cu-deficient rats. They suggested that the ferroxidase activity of Hp is unimportant in the release of Fe from the enterocytes and that the protein functions in some other capacity for Fe release.

Absorbed Fe is taken up by the liver through the Tf-Tf receptor mechanism. However, as shown numerous times before, Cu deficiency does not lead to low liver Fe in rats, but to high liver Fe instead (21,32–34). Theoretically, for Fe to be released from the liver cells, it must be oxidized by Cp, a Cu-dependent ferroxidase (35,36). Cu-deficient rats have very low Cp ferroxidase activity; thus, oxidization and release Fe from the liver cells cannot occur. Then, Fe accumulates in the liver as shown in the current study in which the values were twice as high in Cu-deficient rats compared with Cu-adequate rats, even in the presence of Fe deficiency. Some aspects of this theory are unclear when we consider the data presented by Johnson and Saari (21). Although they found that plasma Fe was reduced within 1 wk of initiating Cu deficiency in rats, Cp activity was not significantly reduced until wk 3, and liver Fe was not increased significantly until after wk 5. Alfaro and Heaton (37) also showed similar effects on liver Fe in the Cu-deficient rat model.

It is believed that most of the Fe in plasma comes from continuous recycling of heme from senescent RBC through the reticuloendothelial system (38,39). The RBC of Cu-deficient rats (40) and pigs (41) tend to be more fragile and their lifespan is shorter. As a result, one might expect that plasma Fe would remain normal or increase for a period of time after initiation of Cu deficiency, unless the excess Fe released from heme degradation was quickly removed by the liver, bone marrow and spleen. However, Johnson and Saari (21) found that plasma Fe concentrations were reduced within a very short period after initiation of Cu deficiency, plasma Cp activity was not reduced, and liver Fe was not increased until after wk 3 and 5 of the deficiency, respectively. Because anemia develops by wk 2, it is unlikely that the excess Fe from heme degradation could have been reused for Hgb synthesis to a great extent (21,42).

Low Fe in the circulation might in itself result in too little Fe being presented to the erythropoietic system. However, parenteral Fe administration to Cu-deficient animals does not cure anemia (43). On the other hand, the anemia of Hp-null mice is alleviated by parenteral administration of Fe (44). Furthermore, some mouse mutants that have inactive Cp do not become anemic (45). Together, these findings suggest the presence of a Cu-dependent factor(s) in the hemopoietic system that aids Fe utilization and cell formation.

There were numerous interactions among Cu and Fe deficiency variables in the current study related to the cells of the erythropoietic system. Previous studies suggested that anemia in humans initiates an increased release of reticulocyte from the bone marrow into the circulation (46,47). This seems to be the case for rats as well. In our study, we stained cells with a nucleic acid-specific dye and used a flow cytometer to count them. We found that deficiencies of either Cu or Fe increased the number of reticulocytes about twofold, but when the two deficiencies coexisted, the number of reticulocytes increased about fivefold. Usually, erythroid cells are released into the circulation after they have extruded their nuclei; however, in the current study, we found that a combination of Cu and Fe deficiencies caused nucleated RBC to be released to a much greater extent than in either Cu or Fe deficiency alone. Erythroblastosis usually signals a regenerative response by the bone marrow to anemia. Why the numbers of reticulocytes and nRBC are so much greater when Cu deficiency is added to Fe deficiency than with either deficiency alone is not understood at this time. However, Cu might have a more fundamental function in erythropoiesis than merely supporting iron utilization. Perhaps this occurs through reductions in free radical formation by maintaining SOD activity (48), maintenance of the cytoskeletal properties and survivability of the erythrocyte (49), control of apoptosis (50) or some other mechanism controlled specifically by Cu.

It was observed that Cu deficiency increases platelet number (24); however, in the current study, Cu deficiency had no direct effect on this variable, but interacted with Fe to elevate platelet count. Iron deficiency elevated the number of platelets/mL of blood, and their numbers were also elevated in Cu deficiency when Fe was adequate. When dietary Fe was deficient, Cu deficiency reduced the platelet counts. However, it is clear that this is an artifact of the counting method because when cells were analyzed by flow cytometry, some of the microcytic RBC were as small as platelets. On the blood analyzer, these microcytic RBC would be counted as platelets, thus elevating the apparent overall platelet count. Previous studies also have observed an apparent increase in mean platelet volume (MPV) in Cu-deficient animals (22) and humans (51); however, in the current study, we observed this anomaly only in Fe deficiency. Again, our data suggest that these apparent effects arise through analytical artifacts occurring as the result of the production of microcytic RBC in Fe-deficient animals. The overproduction of RBC small enough to be counted as large platelets results in erroneously elevated MPV. Recognizing these measurement artifacts required the greater resolving capabilities of flow cytometry. Although Johnson and Dufault (23) found that the mean volume of washed platelets, as determined by an automated blood analyzer, was 20% greater in Cu-deficient rats than controls, the difference might have been the result of incomplete removal of microcytic RBC from the platelet preparation.

The Fe/Mn/Cu connection.

Because some investigators had observed that the AIN-76A diet produced a more severe anemia than the AIN-93G diet, we hypothesized that the lower Mn content of the latter allowed more Fe to be absorbed, thus reducing the effects of Cu deficiency on Fe status. However, this did not happen in the current study. Decreasing dietary Mn from 50 to 10 mg/kg had no effect on the concentration of Fe in duodenum, serum or liver. Instead, high dietary Mn reduced the concentration of Cu in the duodenum, but had no effect on serum or liver Cu. This suggests that overall Cu status was not affected by changing the Mn concentration in the diet. In addition, low Fe intake increased Mn in the duodenum, probably as a result of DMT1 induction (8,52), whether the rats were consuming 10 or 50 mg Mn/kg diet. However, Mn concentrations in serum or liver were not affected by Fe intake. Although low dietary Cu alone had little effect on duodenal Mn, it counteracted the effects of low Fe on duodenal Mn. Because liver Mn was increased in Cu-deficient rats, the deficiency might have allowed more Mn to be transferred out of the enterocyte into the circulation, thus lowering the concentration in the duodenum. This suggests that Cu and Fe influence Mn uptake into and release from the duodenal enterocytes by different mechanisms.

The Cu/SAA connection.

Another hypothesis tested in this experiment was that changing the dietary amino acid supplement from DL-methionine to L-cystine would have an effect on Cu metabolism. Work by Kato et al. (5), Nielsen (6) and Wan et al. (7) suggested that dietary LCys fed at higher concentrations than used here enhanced the defects of Cu deficiency in rats. In the current study, there were interactions between Cu and SAA for numerous variables measured. For example, feeding LCys increased Hct and Hgb compared with feeding DLMet, but only in rats fed Cu-deficient diets; feeding LCys instead of DLMet depressed liver Cu, but only in rats fed Cu-adequate diets. Thus, although there was a slight negative effect of feeding LCys on some of the Cu status indicators, they are probably of little physiologic consequence in producing a more severe Cu deficiency.

In conclusion, feeding weanling male rats Cu-deficient diets based on the AIN-93G formulation produced severe Cu deficiency as evidenced by reductions in the activities of serum Cp (1% of control), RBC SOD1 (14% of control), liver Co1 (25% of control) and SOD3 (20% of controls). In addition, many blood variables were affected by Cu deficiency, including lowered blood Hgb, low RBC volume and low MCHC, and an elevated number of reticulocytes. Dietary Mn had little effect on most variables, except that the higher Mn intake reduced serum Cu when dietary Cu was adequate but not when it was low, and reduced RBC SOD1 activity when dietary Fe was low but not when it was adequate. Hgb concentrations were higher (P < 0.002) in Cu-deficient rats fed LCys than in those fed DLMet. SAA had no effect on Hgb in Cu-adequate rats. Hgb was higher (P < 0.004) in Fe-adequate rats fed LCys than in those fed DLMet, with no effect in Fe-deficient rats. The experiment also showed that the artifacts generated by using automated hematology cell counting techniques can be overcome to a great extent by using flow cytometry. Although the anemia of Cu deficiency produced by feeding the AIN-93G diet did not seem to be as pronounced as that reported in rats fed the AIN-76A diet containing a high sucrose content, other manifestations of the deficiency were prominent.

	ACKNOWLEDGMENTS

 
The authors appreciate the able assistance of the following individuals: Denice Schafer and staff for animal care, Jim Lindlauf and Karin Tweton for diet preparation, Kim Michelsen for enzyme analysis, Terry Shuler and staff for mineral analyses and Brenda Skinner for operating the blood analyzer.

	FOOTNOTES

 
¹ Presented in part at Experimental Biology 03, April 2003, San Diego, CA [Reeves, P.G., Ralston, N.V.C., Idso, J. P. & Lukaski, H. C. 2003 Dietary Cu-Fe-amino acid interactions: flow cytometry of rat hematology indices. FASEB J. 17: A1128 (abs.)].

³ Abbreviations used: Co1, cytochrome c oxidase; Cp, ceruloplasmin; DLMet, DL-methionine; DMT1, divalent metal ion transporter 1; Hct, hematocrit; Hgb, hemoglobin; Hp, Hephaestin; LCys, L-cystine; MCHC, mean corpuscular hemoglobin concentration; MCV, mean corpuscular volume; MVP, mean platelet volume; nRBC, nucleated erythrocyte; SAA, sulfur amino acid; SOD1, cellular superoxide dismutase; SOD3, extracellular superoxide dismutase; Tf, transferrin; TO, thiazole orange; WBC, white blood cell.

Manuscript received 6 August 2003. Initial review completed 23 September 2003. Revision accepted 21 October 2003.

	LITERATURE CITED

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 

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