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Am J Physiol Endocrinol Metab 290: E185-E191, 2006. First published August 9, 2005; doi:10.1152/ajpendo.00318.2004
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Impact of flow rate on lactate uptake and gluconeogenesis in glucagon-stimulated perfused livers

Ken D. Sumida,1 Jerry H. Urdiales,2 and Casey M. Donovan2

1Department of Biological Sciences, Chapman University, Orange, California; and 2Department of Kinesiology, University of Southern California, Los Angeles, California

Submitted 19 July 2004 ; accepted in final form 28 July 2005


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
The impact of reduced hepatic flow on lactate uptake and gluconeogenesis was examined in isolated glucagon-stimulated perfused livers from 24-h-fasted rats. After surgical isolation, livers were perfused (single pass) for 30 min with Krebs-Henseleit (KH) bicarbonate buffer, fresh bovine erythrocytes (hematocrit ~20%), and no added substrate. After this "washout" period, steady-state perfusions were initiated with a second reservoir containing the KH buffer, bovine erythrocytes, [U-14C]lactate (10,000 dpm/ml), lactate (2.5 mM), and glucagon (250 µg/ml). Perfusion flow rate was adjusted to one of five rates (i.e., 1.8, 2.7, 3.9, 7.4, and 11.0 ml·min–1·100 g body wt–1). After the perfusion, the liver was dissected out and weighed so as to establish the actual flow rate per gram of liver. The resulting flow rates ranged from 0.52 to 4.03 ml·min–1·g liver–1. As a function of flow rate, lactate uptake rose in a hyperbolic fashion to an apparent plateau of 2.34 µmol·min–1·g liver–1. Fractional extraction (FX) of lactate from the perfusate demonstrated an exponential decline with increased flow rates (r = 0.97). At flow rates above 1.0 ml·min–1·g liver–1, adjustments in FX compensated for changes in lactate delivery, resulting in steady rates of lactate uptake and gluconeogenesis. Below 1.0·min–1·g liver–1 the increased FX was unable to compensate for the decline in lactate delivery and lactate uptake declined rapidly. Gluconeogenesis demonstrated similar kinetics to lactate uptake, reflecting its dominant role among pathways for lactate removal under the current conditions.

fasted rats; U-14C-labeled lactate; 14C-labeled glucose

THE LIVER IS AN IMPORTANT SITE for lactate metabolism and could be either a contributor to systemic hyperlactatemia or a large reserve for lactate disposal to support glucose homeostasis. A reduction in hepatic blood flow is a salient feature of prolonged exercise (19, 26, 31), circulatory failure (7), hypovolemic shock (32), endotoxic shock (6, 10, 25), and starvation (24) with concomitant challenges on blood glucose homeostasis. Under such conditions, reductions in blood flow to the liver have been proposed as a potential limitation for both lactate uptake (27) and gluconeogenesis (6, 25). Attempts to quantify the impact of blood flow reductions on hepatic lactate uptake and gluconeogenesis using conscious animals have yielded inconclusive findings. Although reductions in hepatic lactate uptake and/or gluconeogenesis have been reported at decreased flow rates in anesthetized dogs by using partial portal vein occlusion (30), others have failed to substantiate these observations in conscious pigs given an endotoxin (10). The extent to which these reported differences may be attributable to the magnitude of the blood flow reduction vs. alternative compensatory mechanisms, e.g., hormonal response, precursor concentrations, and pH shifts, remains unknown. Additionally, several of the anesthetic agents employed are known to restrict portal flow and alter hepatic oxygen tension (21, 33), which may have confounded these earlier in vivo observations.

The in situ perfused liver preparation has been extensively employed to study hepatic metabolism in the absence of such confounding variables. The preparation is well suited to studies of hepatic flow but has been used only sparingly. To date, only two studies (13, 28) have specifically examined the impact of flow rate reductions on lactate metabolism using the liver perfusion technique. In both cases, livers from 48-h-fasted animals were employed and perfused in the absence of any glucoregulatory hormones. Sestoft and Marshall (28) reported a linear reduction in net lactate uptake with reductions in hepatic flow. They further observed that, at normal pH, net lactate uptake shifted to net lactate production when hepatic flow fell below 65% of "normal." These findings contrast with Iles et al. (13), who demonstrated that both net lactate uptake and gluconeogenesis were robust over a wide range of flow rates, with substantial decrements occurring only when the flow rate fell below 33% of normal. Although the differences between these observations may in part be explained by experimental conditions, they point to a need for a reexamination on the impact of hepatic flow rate reductions upon lactate metabolism.

In the current study, we sought to elucidate the impact of flow rate reductions on hepatic lactate uptake and gluconeogenesis in perfused livers of 24-h-fasted rats. A 24-h fast allowed for the depletion of >90% of endogenous glycogen stores, ensuring accurate gluconeogenic measurements while avoiding the substantial metabolic alterations characteristic of more prolonged fasting periods (8). Furthermore, most states of reduced hepatic blood flow, e.g., prolonged exercise, circulatory failure, shock, and starvation, are characterized by elevations in glucoregulatory hormone concentrations. Thus we conducted our experiments in the presence of glucagon, allowing for the metabolic disposal of lactate under conditions more closely approaching those observed in vivo. In addition, we employed the mathematical model initially proposed by Iles et al. (13) to aid in the interpretation of our results. Given the various conditions that can contribute to the reductions in hepatic blood flow, characterizing the capacity of the liver to dispose of lactate via gluconeogenesis during inadequate liver perfusion will help to differentiate when the liver contributes to systemic lactate accumulation with corresponding constraints on the maintenance of euglycemia.


   METHODS
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 METHODS
RESULTS
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Experiments. Experiments were performed on 13 female Wistar rats (240–300 g) housed individually in a temperature controlled room and maintained on a 12:12-h light-dark cycle with food and water provided ad libitum. Twenty-four hours before the experiment, food was withdrawn, whereas water continued to be provided. The 24-h fast was employed to deplete liver glycogen stores and minimize the glucose output derived from glycogenolysis.

The surgical isolation of the liver (29) and perfusion chamber apparatus has previously been described (5). All perfusions were single pass, where the perfusion medium consisted of Krebs-Henseleit buffer with 25 mM sodium bicarbonate, dialyzed bovine serum albumin (30 g/l fraction V, Sigma), and 2.5 mM calcium chloride. Fresh bovine erythrocytes were obtained and thoroughly washed before its addition to the Krebs-Henseleit bicarbonate buffer. The final hematocrit (Hct) was 22.5 ± 0.8% with a perfusate pH of 7.21 ± 0.02. The perfusate medium was then separated into two reservoirs. The first reservoir contained only the perfusate medium with no added substrate, whereas lactate (~2.5 mM), [U-14C]lactate (10,000 dpm/ml, ICN), and glucagon (250 µg/ml, Sigma) were added to the second reservoir. Both reservoirs were placed in a circulating water bath maintained at 37°C.

After the surgical isolation, the flow was adjusted to 7.4 ml·min–1·100 g body wt–1 (~2 ml·min–1·g liver–1), and a 30 min washout period was initiated using the first reservoir. At minute 30, the perfusion was switched to the second reservoir and an adjustment in flow was performed. At minute 45 (15 min after initial flow rate adjustment) perfusate sampling was initiated with samples taken from minutes 45 to 60 at 5-min intervals for the determination of steady-state rates. We (29) have previously demonstrated the attainment of steady-state values that were observed to randomly vary <0.5%/min within 15 min of altering the lactate concentration. At minute 60, the flow rate was again adjusted with sampling occurring every 5 min between minutes 75 and 90. Thus each liver received two adjustments in flow rate during the experiment with the order randomized. The flow rates employed were: 1.8, 2.7, 3.9, 7.4, or 11.0 ml·min–1·100 g body wt–1. Additional samples for perfusate pH/gas analysis (Radiometer BMS3 Mk2) and 14CO2 evolution were collected every 15 min, whereas the Hct was determined every 20 min. After all perfusions, the liver was rapidly excised, weighed, freeze-clamped with aluminum tongs precooled in liquid nitrogen, and stored at –70°C for subsequent analysis. The weight of the liver was then used to determine the actual flow rate per gram of liver.

Chemical analyses. Blood samples, initially collected in chilled test tubes containing sodium fluoride and heparin, were centrifuged and assayed for alanine aminotransferase (ALT, EC 2.6.1.2 [EC] ) activity (23). Another aliquot of the blood was deproteinized in 8% perchloric acid, neutralized with potassium hydroxide (KOH), and analyzed for glucose (22) and lactate (12). Ion exchange chromatography (29) was performed for the determination of glucose and lactate specific activity. The analyses for blood gas (PCO2 and PO2), pH, and 14CO2 evolution were determined from anaerobically drawn samples as previously described (29). Oxygen consumption (VO2) was calculated from PO2 values corrected for oxygen saturation. 14CO2 was determined utilizing the method of Chan and Dehaye (1). A portion of the liver was analyzed for glycogen content (4) and glycogen specific activity (2) after its homogenation and solubilization in KOH (9). Another portion of the liver was homogenized for the determination of protein content (18). Water content was determined on a separate portion of the liver through weight changes after drying at 80°C for 48 h. On a separate group of animals (n = 5), the hepatic glycogen content was determined immediately after the washout period.

Calculations and statistics. Each data point represents the steady-state value determined from the average of four samples observed to randomly vary by <0.5%/min. The gluconeogenic rate (GNG) was calculated as the product of portal-venous glucose difference (µmol/ml) and flow (ml/min). Similarly, lactate uptake and VO2 were calculated as the product of portal-venous difference (µmol/ml) and flow (ml/min). 14C activities (dpm/ml) were normalized to an arterial lactate specific activity of 10,000 dpm/µmol. Lactate delivery was calculated as the product of perfusate lactate concentration (µmol/ml) and flow (ml·min–1·g liver–1). Lactate fractional extraction was calculated as the portal-venous difference (µmol/ml) divided by the portal concentration (µmol/ml). We further examined our data employing the mathematical model proposed by Iles et al. (13), which assumes simple extraction based on mean transit time [represented as 1/(flow rate)]:

(1)

(2)
where U represents the lactate uptake, R is the flow rate, La and Lv are the arterial and hepatic venous lactate concentrations, and K is a constant dependent on the intrinsic capacity of the cells to take up lactate. As indicated by Iles et al., given the inability to measure K, Eq. 2 is more applicable where a linear relationship from a semilogarithmic plot of the arterial lactate concentration divided by the venous lactate concentration vs. 1/(flow rate) denotes a simple extraction model. A deviation from linearity suggests that the liver is responding to intrinsic factors (e.g., hypoxia).

Individual data were analyzed with either nonlinear or linear regressions utilizing the least squares method (SlideWrite Plus, Adv. Graphics Software), and the equations as well as the correlation coefficients were determined. When the groups were pooled (Tables 1 and 2), an ANOVA was employed, and post hoc analysis (Tukey's method) was used with the level of significance set at P < 0.05. All values are expressed as means ± SE.


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  		Table 1. Perfusate characteristics and indexes of liver integrity

 

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  		Table 2. Substrate and tracer data

 

   RESULTS
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 METHODS
 RESULTS
DISCUSSION
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Visual inspection of the liver after the perfusions revealed no swelling or discoloration. In support, the ALT efflux from the livers was 7.34 ± 0.42 U and never approached the limit indicative of a compromised preparation (23). The tissue water, 71.8 ± 0.6%, and protein content, 178 ± 10 mg/g, did not significantly vary in the glycogen-depleted livers between experimental conditions. Furthermore, perfusate characteristics as well as indexes of liver integrity (Table 1) were not significantly different between flow rates, nor were they different from our prior observation using this technique (29). The actual reservoir lactate concentration was 2.31 ± 0.07 mM and did not significantly differ between experiments. Adjusted for actual liver weight, relative flow rates were: 3.39 ± 0.16, 2.41 ± 0.10, 1.30 ± 0.05, 0.86 ± 0.03, and 0.59 ± 0.03 ml·min–1·g liver–1. Hepatic glycogen content, 0.62 ± 0.08 mg/g, after the initial washout period (performed on a separate group of animals, n = 5) was not significantly different from the final glycogen content, 0.54 ± 0.02 mg/g, following perfusions with lactate (n = 13). These data demonstrate no net glycogenolysis in this preparation and support the position that net glucose production under the current conditions was gluconeogenic in origin.

Lactate uptake as a function of flow rate was best approximated by a hyperbolic curve [y = 2.28 – (0.59/x)1.65] with a calculated x-intercept of 0.36 ml·min–1·g liver–1 and an asymptote of 2.34 ± 0.30 µmol·min–1·g liver–1 (Fig. 1A), which is consistent with the actual lactate uptake (Table 2). This reflects the relatively robust nature of hepatic lactate uptake between flow rates of 1.25–3.5 ml·min–1·g liver–1, giving way to a rapid decline as flow dropped below 1.0 ml·min–1·g liver–1. Examining the lactate uptake (Fig. 1B) using a parameter proportional to the transit time [i.e., 1/(flow rate)] generated a negative linear relationship (y = 2.56 – 0.86x). Examining the fractional extraction vs. the flow rate (Fig. 2) resulted in an exponential decay [y = 0.17 + 0.94 e(–x/1.59)]. Applying the mathematical model of Iles et al. (13) demonstrated a linear relationship (y = 0.10 + 0.97x) with a correlation coefficient of 0.96 (Fig. 3). In contrast to Iles et al. (13), there was no deviation in linearity. The GNG similarly yielded a hyperbolic pattern (y = 0.95 – [0.36/x]1.45) when plotted against the flow rate (Fig. 4A) with a calculated x-intercept of 0.37 ml·min–1·g liver–1. Again examining the GNG (Fig. 4B) with a parameter proportional to the transit time [1/(flow rate)] generated a negative linear relationship (y = 1.02 – 0.32x). The actual maximal GNG, 0.88 ± 0.02 µmol·min–1·g liver–1, and VO2, 2.97 ± 0.19 µmol·min–1·g liver–1, was not significantly different at flow rates above 1 ml·min–1·g liver–1 (Tables 1 and 2; for brevity, flow rates were grouped). At flow rates below 1 ml·min–1·g liver–1, GNG, 14CO2, and VO2 declined (Tables 1 and 2). That the GNG between flow rates was derived from gluconeogenesis is supported by the concomitant changes in [14C]glucose production (Table 2) and the minimal glycogenolysis. In addition, the amount of [14C]lactate incorporation into [14C]glycogen, expressed as a percentage of [14C]lactate uptake was 1.0 ± 0.3% and was not significantly different between flow rate conditions. Furthermore, the amount of [14C]lactate incorporation into [14C]glucose corresponded to 82.4 ± 1.1% of the [14C]lactate uptake.



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  		Fig. 1. A: effects of flow rate reductions on hepatic lactate uptake. Each point represents a steady-state value, and all data are expressed relative to actual liver weight. Nonlinear regressions were determined using the least squares method and the correlation coefficient (r) is indicated. B: effects of flow rate reductions (1/flow rate) on hepatic lactate uptake. Each point represents a steady-state value, and all data are expressed relative to actual liver weight. Linear regressions were determined using the least squares method and r is indicated.

 


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  		Fig. 2. Effects of flow rate reductions on hepatic fractional extraction (expressed as a ratio). Each point represents a steady-state value, and all data are expressed relative to actual liver weight. Nonlinear regressions were determined using the least squares method and r is indicated.

 


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  		Fig. 3. Effects of flow rate reductions (1/flow rate) using the model proposed by Iles et al. (13). Each point represents a steady-state value, and all flow rates are expressed relative to actual liver weight. Linear regressions were determined using the least squares method and r is indicated.

 


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  		Fig. 4. A: effects of flow rate reductions on hepatic gluconeogenesis (GNG). Each point represents a steady-state value, and all data are expressed relative to actual liver weight. Nonlinear regressions were determined using the least squares method and r is indicated. B: effects of flow rate reductions (1/flow rate) on hepatic gluconeogenesis (GNG). Each point represents a steady-state value and all data are expressed relative to the actual liver weight. Linear regressions were determined utilizing the least squares method and r is indicated.

 
The relationship between GNG and lactate uptake (corrected to 3 carbons; Fig. 5) indicated a strong linear correlation (y = 0.22 + 0.69x). A line of identity is depicted on the graph, illustrating that all the observations from the current study fall below this line. Any point above the line of identity suggests that glucose production was derived from carbon sources other than lactate. Finally, the venous lactate specific activity vs. 1/(flow rate) (Fig. 6) generated a negative linear relationship (y = 9,927 – 2,195x). Although the dilution of the lactate specific activity with flow rate reductions is unknown, it may be attributable to an endogenous source, i.e., amino acids.



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  		Fig. 5. Effects of lactate uptake on hepatic GNG corrected to 3 carbons. Each point represents a steady-state value, and all data are expressed relative to actual liver weight. Linear regressions were determined using the least squares method and r is indicated. Line of identity represents all carbons from lactate being converted to glucose.

 


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  		Fig. 6. Effects of flow rate reductions (1/flow rate) on venous lactate specific activity (LSA). Each point represents a steady-state value, and all flow rates are expressed relative to actual liver weight. Linear regressions were determined using the least squares method and r is indicated.

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
Under the current conditions, both hepatic lactate uptake and gluconeogenesis demonstrated responses to flow rate reductions consistent with a simple extraction model. As flow rate fell, the fractional extraction of lactate was observed to rise in an exponential fashion (Fig. 2). Assuming that the effective lactate space remains constant, reducing flow will lead to an exponential rise in the mean transit time for any given lactate molecule, increasing the probability that it will be removed. Lactate uptake demonstrated a strong correlation with the reciprocal of flow rate, a parameter proportional to the mean transit time (r = 0.84; Fig. 1B). However, with increasing transit time and fractional extraction, the average lactate concentration to which the hepatocyte is exposed will also fall. Because lactate uptake has been shown to be proportional to the lactate concentration up to ~4 mM, this additional parameter could be expected to impact further on lactate uptake. This is taken into account in the model originally proposed by Iles et al. (13), which predicts a linear relationship between the ln(LAa/LAv) and 1/(flow rate). Plotting the current data in this manner yielded and a linear correlation of 0.96 (Fig. 3). Thus the observed response for lactate uptake across the entire range of flow rates examined (Fig. 1A) can be explained by a relatively simple interaction of sinusoidal transit time and precursor delivery. The model further suggests an upper limit for the impact of flow rate on lactate uptake, i.e., as venous lactate concentration approaches arterial lactate concentration, where further increases in flow will have negligible impact upon lactate uptake. Finally, the x-intercept from Figs. 1A and 4A indicates the flow rate where the liver would switch from lactate uptake and gluconeogenesis to lactate production and glucose uptake. In both cases, the minimum flow rate was ~0.37 ml·min–1·g liver–1 (81% reduction in resting blood flow).

The similar kinetics observed for gluconeogenesis vs. flow rate (Fig. 4, A and B) reflect its dominant role for lactate removal in the current preparation, i.e., 82.4 ± 1.1% of the lactate uptake was converted to glucose (Table 2 and Fig. 5). That hepatic glucose production was derived from circulating lactate was confirmed by the minimal glycogenolysis and the incorporation of [14C]lactate into [14C]glucose. As such, the rationale put forth (above) for the interaction of flow and lactate uptake is equally applicable to the interaction of flow and gluconeogenic rates. Thus the importance of flow rate in determining rates of gluconeogenesis would be seen to vary depending on the arterial precursor concentration, i.e., lactate delivery, and absolute rate of glucose production. However, some caution is warranted in this rather simple model, as the decrease in flow rate also resulted in a decrease in oxygen delivery. As a result, there was a concomitant decline in VO2 and 14CO2 formation. These latter two observations suggest an alternative mechanism by which flow might limit gluconeogenesis, i.e., oxygen supply.

To our knowledge, the current study is only the third report that has specifically examined the impact of flow rate reductions on hepatic lactate uptake and gluconeogenesis by use of the liver perfusion technique. Sestoft and Marshall (28) examined hepatic lactate uptake under the conditions of normal to high blood glucose (5–20 mM), low lactate concentrations (~0.6 mM), and reduced flow rates (33–100%). They observed decreases in net lactate uptake that corresponded to the reductions in flow (28). At a blood glucose concentration of 20 mM and a flow rate at 65% of "normal," they observed a switch to net lactate production attributable to elevations in glycolysis (28). Although their observations of glucose-induced inhibition on lactate uptake are relevant for situations involving uncontrolled diabetes, the flow rate reductions associated with endotoxic shock, prolonged exercise, and starvation involve hypoglycemia. Only Iles et al. (13) specifically examined the impact of hepatic lactate uptake and gluconeogenesis under moderate lactate concentrations (~2 mM), reduced flow rates, and the absence of glucose in the perfusate. Before collecting their data, they proposed the mathematical model previously presented in this paper (13). The model effectively makes two assumptions regarding the relationship between flow rate and lactate uptake: 1) that fractional extraction will elevate with increasing transit time or decreased flow rate, and 2) that lactate uptake will be proportional to the mean lactate concentration. From these assumptions, a linear correlation between ln(LAa/LAv) and 1/(flow rate) can be derived from this model. At flow rates above 33% of normal, the data of Iles et al. conformed to the model, but a marked deviation from linearity below 33% led them to identify this as the flow rate where the extraction of lactate becomes limited. They proposed that intrinsic factors, e.g., energy supply, must further impact on lactate uptake at these lower flow rates (13). Interpretation of their results is somewhat complicated by the rather high flow rates employed by Iles et al. Their "normal" flow rate, 11.25 ml·min–1·100 g body wt–1 or ~3.2 ml·min–1·g liver–1, is substantially higher than the 2.0 ml·min–1·g liver–1 previously reported in rats in vivo (17) or employed with rat liver perfusions (5).

Using comparable flow rates and the model proposed by Iles et al. (13), our results did not corroborate their findings. This discrepancy may be the result of several experimental differences. The metabolic heterogeneity that characterizes the normal fed liver, i.e., gluconeogenic periportal and glycolytic perivenous cells, is diminished with fasting, such that the liver becomes more uniformly gluconeogenic (16). Thus it is possible that the more prolonged fast employed by Iles et al. led to a greater metabolic demand relative to lactate uptake. However, this seems unlikely given our use of glucagon to stimulate gluconeogenesis yielding comparable glucose production rates. A more plausible explanation is that the 48-h fast employed by Iles et al. led to metabolic alterations favoring the use of endogenous gluconeogenic precursors, e.g., hepatic amino acids. In support, at their low flow rates, Iles et al. reported lactate uptakes that would account for only one-half of the glucose output. In the absence of any other circulating precursor, the only explanation would be an endogenous precursor source. Even our data support the interaction of exogenous lactate with some endogenous carbon source, as demonstrated by the dilution in lactate specific activity with flow rate reductions (Fig. 6). However, in our study, lactate uptake was always observed to be sufficient to support hepatic gluconeogenesis on a net basis (Fig. 5). The increased use of endogenous precursors with prolonged starvation would obviously alter the relationship between circulating precursors and gluconeogenic rates. Finally, it is possible that the slight increase in the hematocrit used in the current study (i.e., ~22%) compared with the 17% Hct used by Iles et al. may have prevented us from reaching the critical threshold for oxygen delivery and the subsequent use of endogenous precursors for glucose production. This is partially supported by the higher oxygen tensions from the venous effluent that we observed (Fig. 7) compared with what was reported by Iles et al. at the point where they observed a departure from the theoretical straight line. Despite these differences, the liver (at least in rats) appears to be a remarkable source for lactate removal during substantial decrements in hepatic blood flow.



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  		Fig. 7. Effects of flow rate reductions on the hepatic venous oxygen pressure (PvO2) expressed in mmHg. Each point represents a steady-state value, and all flow rates are expressed relative to actual liver weight. Linear regressions were determined using the least squares method and r is indicated. Dotted line represents the PvO2 observed by Iles et al. (13), where their data deviated from their mathematical model.

 
Although caution must be applied in such comparisons, results of the current study are consistent with a number of in vivo studies in humans. Humans engaged in moderate exercise, a condition known to lower hepatic blood flow, demonstrated enhanced gluconeogenesis from glycerol when glycerol concentrations were elevated via exogenous infusion (31). Under similar exercise conditions, elevating the lactate concentration led to enhanced gluconeogenesis from lactate relative to the overall rate of glucose production (19). In like manner, during prolonged fasting in humans, gluconeogenesis from lactate and alanine are augmented by elevations in their respective plasma concentrations (3, 11, 15). That the provision of additional precursors did not elevate total hepatic glucose production in all these studies is indicative of the extensive regulation of glucose homeostasis involving a number of feedback mechanisms (14). This is in contrast to our preparation, where most, if not all, feedback mechanisms were eliminated. The fact that increasing the supply of a given precursor stimulates gluconeogenesis, such that the body must compensate by suppressing the utilization of other precursors or the glycogenolytic rate, denotes the importance of precursor supply. In the human studies above, the precursor supply was elevated by increasing the precursor concentration, whereas the current study adds to our understanding by elucidating the role of flow rate in sustaining precursor supply. Furthermore, it is important to note that, in both conditions (i.e., moderate exercise and prolonged fasting), hepatic blood flows have been observed to decline by less than 40% below resting values (24, 26). As such, precursor supply and uptake may not have been significantly challenged in these human observations. In a recent study, Nielsen et al. (20) evaluated the liver's contribution to blood lactate levels during intense exercise (~75% of VO2 max) in men. Using their hepatic flow rates assessed by indocyanine green and applying assumptions pertaining to human liver weight (i.e., 23 g/kg body wt), those authors observed a resting hepatic blood flow of ~0.9 ml·min–1·g liver–1, which declined to ~0.4 ml·min–1·g liver–1 during intense exercise (20). Despite the more than 55% reduction in blood flow, they observed that the liver maintained its capacity for lactate uptake and gluconeogenesis and did not contribute to the systemic lactate concentration. We offer some insights between this recent in vivo observation during intense exercise in humans and our results in perfused rat livers where hepatic blood flow is significantly reduced. The relative liver weight from rats (i.e., 35 g/kg body wt) is greater than that from humans which could support a higher relative resting blood flow (i.e., ~2 ml·min–1·g liver–1 for rats vs. ~1 ml·min–1·g liver–1 for humans). Yet the relative hepatic blood flow reduction in both humans (~56%) and rats (~75%) where lactate uptake and gluconeogenesis are maintained suggests a general response in mammals. This is also supported by the work of Tashkin et al. (30), who observed the constant uptake of lactate from the liver of anesthetized dogs despite reductions in hepatic blood flow of more than 70%. When the hepatic blood flow was severely reduced (i.e., 88%) the liver finally switched to lactate production (30). If we extrapolate our results using the x-intercept where lactate uptake would hypothetically switch to lactate production (i.e., ~0.37 ml·min–1·g liver–1) this would correspond to a blood flow reduction of 81%, which is consistent with the report of Tashkin et al., supporting the notion of a general response in mammalian livers. Based upon their observation, Tashkin et al. suggested that the liver had a large functional reserve for lactate disposal. Our results support their contention that the liver is capable of continued lactate uptake for the conversion to glucose despite significant reductions in hepatic blood flow. We note that, in all the conditions above involving severely compromised blood flow to the liver, glucoregulatory hormones may have contributed to the enhanced hepatic response. Assuming that this response also occurs in humans, the liver appears to be more robust to decrements in blood flow compared with other tissues and may be one of the last organs to contribute to hyperlactatemia.

Our reexamination and acceptance of the mathematical equations proposed by Iles et al. (13), which suggest a simple extraction model, is not without limitations. Although we chose to examine the model under glucagon-stimulated conditions, another glucoregulatory hormone or a combination of hormones might have yielded different results. Furthermore, we examined the model with the use of only lactate. Employing a precursor that enters the gluconeogenic pathway at a different site or a combination of precursors entering at various sites (where hepatic "autoregulation" could be a factor) might have similarly yielded different results. Alternatively, an examination under fed conditions might have generated results that differed from those of our fasted condition. Despite these limitations, the initial model proposed by Iles et al., our current results, and those of other investigators using animal models (28, 30) collectively aid in the characterization of flow rate reductions in the liver and its impact on lactate metabolism and gluconeogenesis.

In summary, using the mathematical model proposed by Iles et al. (13), we found that hepatic lactate uptake is a function of mean transit time. Consistent with the mathematical model, at flow rates below 1 ml·min–1·g liver–1, the lactate delivery, VO2, and GNG similarly declined. However, the liver continued to take up lactate, supporting its capacity to serve as a large functional reserve for lactate disposal even in the presence of significant reductions in flow. The mechanism for the eventual fall in GNG was beyond the scope of this study. Inherent in reduced flow rates are decreases in both oxygen and substrate delivery. As both oxygen availability and precursor delivery will at some point clearly limit gluconeogenesis, which of these factors is most likely to constrain hepatic glucose production from lactate remains unclear. The companion study (29a) specifically addresses this question.


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 ABSTRACT
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This study was supported by National Institute of Diabetes and Digestive and Kidney Diseases Grant no. DK-48000.


   FOOTNOTES
 

Address for reprint requests and other correspondence: K. D. Sumida, Dept. of Biological Sciences, Chapman University, One University Dr., Orange, CA 92866 (e-mail: sumida{at}chapman.edu)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   REFERENCES
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 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
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 REFERENCES
 

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