Cuyamaca Hemoglobin Function & Physiological Adaptation to Hypoxia in Mammals Discussion

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1. At which step(s) in the oxygen transport system will changes in hemoglobin have the most impact when comparing high altitude and low altitude adapted mammals?
2. What are the two subunit functional types of hemoglobin discussed in Storz (2007)?

3. What do the pie charts in Figure 7 represent?

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biology letters Biol. Lett. (2012) 8, 783-786 doi:10.1098/rsbl.2012.0331 Published online 16 May 2012 Evolutionary biology Cross Mark dick for updates More than 1000 ultraconserved elements provide evidence that turtles are the sister group of archosaurs Nicholas G. Crawford1*, Brant C. Faircloth, John E. McCormack, Robb T. Brumfield34, Kevin Winkers and Travis C. Glenn Department of Biology, Boston University, Boston, MA 02215, USA 2 Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA Museum of Natural Science, and Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA 5 University of Alaska Museum, 907 Yukon Drive, Fairbanks, AK 99775, USA Department of Environmental Health Science and Georgia Genomics Facility, University of Georgia, Athens, GA 30602, USA * Author for correspondence (ngcrawford@gmail.com). We present the first genomic-scale analysis addressing the phylogenetic position of turtles, using over 1000 loci from representatives of all major reptile lineages including tuatara. Previously, studies of morphological traits posi- tioned turtles either at the base of the reptile tree or with lizards, snakes and tuatara (lepido- saurs), whereas molecular analyses typically allied turtles with crocodiles and birds (archo- saurs). A recent analysis of shared microRNA families found that turtles are more closely related to lepidosaurs. To test this hypothesis with data from many single-copy nuclear loci dis- persed throughout the genome, we used sequence capture, high-throughput sequencing and pub- lished genomes to obtain sequences from 1145 ultraconserved elements (UCEs) and their vari- able flanking DNA. The resulting phylogeny provides overwhelming support for the hypothesis that turtles evolved from a common ancestor of birds and crocodilians, rejecting the hypothesized relationship between turtles and lepidosaurs. Keywords: turtles; ultraconserved elements; phylogenomics; evolution; archosaurs Molecular studies using mitochondrial (4,6-8,16) and nuclear DNA (5,9-14,17] typically place turtles sister to archosaurs (crocodilians and birds; figure 1). This molecular hypothesis was recently contradicted by a phylogeny reconstructed from microRNAs [15] that allied turtles with lepidosaurs. Lyson et al. [15] suggested that prior molecular evidence for a turtle- archosaur relationship may be the result of analytical artefacts. If true, the hypothetical relationship between turtles and lepidosaurs (Ankylpoda) should appear throughout the genomes of these organisms. Here, we test the Ankylopoda hypothesis and address the evolutionary origin of turtles. We reconstruct a rep- tile phylogeny using ultraconserved elements (UCES) [18] and their flanking sequence that we obtained using sequence capture of DNA from a tuatara and two species each of crocodilians, squamates and turtles (table 1). We used UCEs because they are easily aligned portions of extremely divergent genomes (19), allowing many loci to be interrogated across evolutionary time- scales, and because sequence variability within UCES increases with distance from the core of the targeted UCE (20), suggesting that phylogenetically informative content in flanking regions can inform hypotheses spanning different evolutionary timescales. To break up long branches and mitigate potential problems with long-branch attraction, we selected species representing the span of diversity within major reptilian lineages (i.e. the most divergent crocodilians, lepidosaurs and turtles). 2. MATERIAL AND METHODS We enriched DNA libraries prepared with Nextera kits (Epicentre, Inc., Madison, WI, USA) using a synthesis (Mycroarray, Inc., Ann Arbor, MI, USA or Agilent, Inc., Santa Clara, CA, USA) of RNA probes [20] targeting 2386 UCEs and their flanking sequence. We generated sequences for each enriched library using single-end, 100-base sequen- cing on an Illumina GAIIx. After quality filtering, we assembled reads into contigs using Velvet [21], and we matched contigs to the UCE loci, removing duplicate hits. We generated alignments using MUSCLE [22], and we excluded loci having missing data in any taxon. Following alignment, we estimated the appropriate finite-sites . We prepared a concatenated dataset by partitioning loci by substitution model prior to analysis using two runs of MrBayes [23] for 5 000 000 iterations (four chains per run; burn-in: 50%; thinning: 100). We also used each alignment to estimate gene trees incorporating 1000 multi-locus bootstrap replicates, which we integrated into STEAC and STAR [24] species trees. Additional details concerning UCE sequence capture methods and phylogenetic methods are available in Faircloth et al. (20). 1. INTRODUCTION The evolutionary origin of turtles has confounded the understanding of vertebrate evolution [1] (figure 1). Historically, turtles were thought to be early-diverging reptiles, called anapsids, based on their skull mor- phology and traits such as dermal armour (2]. Recent morphological studies that included soft tissue and developmental characters [3] allied turtles with lepido- saurs, a group including squamates (lizards and snakes) and tuataras. However, homoplasy stemming from the derived skeletal specializations of turtles limits the utility of phylogenetic inference based on morphological data to resolve turtle placement (4,5). 3. RESULTS We enriched genomic DNA for UCEs in corn snake (Pantherophis guttata), African helmeted turtle (Pelomedusa subrufa), painted turtle (Chrysemys picta), American alligator Alligator mississippiensis), saltwater crocodile (Crocodylus porosus) and tuatara (Sphenodon tuatara) (table 1). We sequenced a mean of 4.9 million reads from each library, and from these reads, we assembled an average of 2648 (+314 s.d.) contigs. We supplemented these taxa with UCEs extrac- ted from the chicken (Gallus gallus), zebra finch (Taeniopygia guttata), Carolina anole lizard (Anolis carolinensis) and human (Homo sapiens) genome sequences. We combined the in silico and in vitro data and generated alignments across all taxa and excluded all loci having missing data from any taxon. This Received 9 April 2012 Accepted 26 April 2012 783 This journal is © 2012 The Royal Society 784 N. G. Crawford et al. UCEs place turtles sister to archosaurs Table 1. University of California Santa Cruz (UCSC) genome build or specimen ID for each sample, the number of ~100 bp sequence reads, and the total number of UCEs assembled. common name binomial specimen ID/genome build reads assembled UCES African helmeted turtle American alligator Carolina anole corn snake human painted turtle red junglefowl saltwater crocodile tuatara zebra finch Pelomedusa subrufa Alligator mississippiensis Anolis carolinensis Pantherophis guttata Homo sapiens Chrysemys picta Gallus gallus Crocodylus porosus Sphenodon tuatara Taeniopygia guttata H20145" HCD-2620" H16061" H15909" UCSC hg19 H2662" UCSC galGal3 LM-675 UMFS-10956 UCSC taeGut 1 11 200 032 3 528 983 3 100 147 3 362 738 NA 4 467 644 NA 3 261 088 5 651 932 NA 1972 2320 21110 2168 1748 2261 23600 2218 2199 23450 "From the LSU Museum of Natural Science. "From the Darwin Crocodile Farm courtesy of L. Miles, S. Isberg and C. Moran. From the University of Michigan Museum of Zoology courtesy of R. Nussbaum and G. Schneider. "Although we identified 2386 UCES these organisms, from which lesigned capture obes, owing to slight adjustments to matching and filtering algorithms, we only recover ca 98% of these UCEs when re-screening these genomic sequences. (a) morphology snakes lizards tuatara turtles! crocodilians birds turtles2 mammals either run. Bayesian analysis of concatenated alignments and species-tree analysis of 1145 independent gene his- tories showed turtles to be the sister lineage of extant archosaurs with complete support (figure 2). Removing the snake, which had a very long branch, and re-running all analyses did not change the results. (b) mtDNA and nucDNA snakes lizards tuatara turtles crocodilians birds mammals (c) microRNAs snakes lizards turtles crocodilians birds 4. DISCUSSION Genomic-scale phylogenetic analysis of 1145 nuclear UCE loci agreed with most other molecular studies [4-14), supporting a sister relationship between turtles and archosaurs. We found no support for the turtles- lepidosaur relationship predicted by the Ankylopoda hypothesis [15] (figure 2). The combination of taxo- nomic sampling, the genome-wide scale of the sampling and the robust results obtained, regardless of analytical method, indicates that the turtle-archosaur relationship is unlikely to be caused by long-branch attraction or other analytical artefacts. Although our results corroborate earlier studies, many of these studies did not include tuatara. Because tuatara is an early-diverging lepidosaur, it is important to include this taxon in studies of turtle evolution as it breaks up the long-branch leading to squamates (figure 2b). Of the studies including tuatara, two (6,11] found results similar to this study, but both were based on a single locus. The third study [5] was unable to produce a well-resolved tree from four nuclear genes when the authors included tuatara in the dataset. Our study is the first to produce a well-resolved reptile tree that includes the tuatara and multiple loci. The discrepancy between our results showing a strong turtle-archosaur relationship and microRNA (miRNA) results, which showed a strong turtle- lepidosaur relationship, may be due to several factors. Lyson et al. (15) used the presence of four miRNA gene families, detected among turtles and lepidosaurs and undetected in the other taxa analysed, to support the turtle-lepidosaur relationship. Because complete genomes are unavailable for turtles, tuatara and crocodi- lians, and because expressed miRNA data are lacking for most reptiles, the authors collected miRNA sequences from small RNA expression libraries. miRNAs have mammals Figure 1. (a) Depicts the primary morphological hypotheses: turtles most basally branching reptilian lineage [2] or turtles related to lepidosaurs [3].' (b) Depicts the primary molecular hypothesis of a turtle-archosaur alliance (4-14]. ©) Depicts the tree derived from miRNA loci (15). resulted in 1145 individual alignments with a mean length of 406 bp (+100 bp s.d.) per alignment, total- ling 465 Kbp of sequence. Tracer showed that both Bayesian analyses converged quickly, having effective sample size (ESS) scores for log likelihood of 170 and 220. Because posterior probabilities for all nodes were 1.0, AWTY (http://ceb.csit.fsu.edu/awty) showed zero variance in the tree topology throughout Biol. Lett. (2012) UCEs place turtles sister to archosaurs N. G. Crawford et al. 785 (a) 1.0/100 snake Pantherophis guttata and relevant to resolving ancient phylogenetic enigmas throughout the tree of life [28]. This approach to high- throughput phylogenomics-based on thousands of loci—is likely to fundamentally change the way that systematists gather and analyse data. 1.0/100 lizard Anolis carolinensis tuatara Sphenodon tuatara (a) Additional information We provide all data and links to software via Dryad repo- sitory (doi:10.5061/dryad.75nv22qj) and GenBank (JQ868813-JQ885411). 1.0/100 side-necked turtle Pelomedusa subrufa painted turtle Chrysemys picta 1.0/100 1.0/100 American alligator Alligator mississippiensis saltwater crocodile Crocodylus porosus We thank R. Nilsen, K. Jones, M. Harvey, R. Nussbaum, G. Schneider, D. Ray, D. Peterson, C. Moran, L. Miles, S. Isberg, C. Mancuso, S. Herke, two anonymous reviewers and the LSU Genomic Facility. National Science Foundation grants DEB-1119734, DEB-0841729 and DEB-0956069, and an Amazon Web Services Education Grant supported this study. N.G.C., B.C.F., J.E.M. and T.C.G. designed the study; N.G.C. and B.C.F. performed phylogenetic analysis; B.C.F. created datasets; J.E.M. performed laboratory work; all authors helped write the manuscript. 1.0/100 zebra finch Taeniopygia guttata 1.0/100 chicken Gallus gallus human Homo sapiens (b) snake lizard tuatara turtles crocodilians birds human 0.03 substitutions/site Figure 2. (a) Reptilian phylogeny estimated from 1145 ultra- conserved loci using Bayesian analysis of concatenated data and species-tree methods, yielding identical topologies. Node labels indicate posterior probability/bootstrap support. (6) Phylogram of the UCE phylogeny generated with STEAC. 1 Lee, M. S. Y., Reeder, T. W., Slowinski, J. B. & Lawson, R. 2004 Resolving reptile relationships. In Assembling the tree of life (eds J. Cracraft & M. J. Donoghue), pp. 451-467. Oxford, UK: Oxford University Press. 2 Lee, M. 1997 Reptile relationships turn turtle. Nature 389, 245-246. doi:10.1038/38422) 3 Rieppel, O. 1999 Turtle origins. Science 283, 945-946. (doi:10.1126/science.283.5404.945) 4 Janke, A., Erpenbeck, D., Nilsson, M. & Aranason, U. 2001 The mitochondrial genomes of the iguana (Iguana iguana) and the caiman (Caiman crocodylus): implications for amniote phylogeny. Proc. R. Soc. Lond. B 268, 623- 631. (doi:10.1098/rspb.2000.1402) 5 Hedges, S. & Poling, L. 1999 A molecular phylogeny of reptiles. Science 283, 998-1001. (doi:10.1126/science. 283.5404.998) 6 Rest, J. S., Ast, J. C., Austin, C. C., Waddell, P. J., Tibbetts, E. A., Hay, J. M. & Mindell, D. P. 2003 Mol- ecular systematics of primary reptilian lineages and the tuatara mitochondrial genome. Mol. Phylogenet. Evol. 29, 289-297. (doi:10.1016/S1055-7903(03)00108-8) 7 Kumazawa, Y. & Nishida, M. 1999 Complete mitochon- drial DNA sequences of the green turtle and blue-tailed mole skink: statistical evidence for archosaurian affinity of turtles. Mol. Biol. Evol. 16, 784-792. (doi:10.1093/ oxfordjournals.molbev.a026163) 8 Zardoya, R. & Meyer, A. 1998 Complete mitochondrial genome suggests diapsid affinities of turtles. Proc. Natl Acad. Sci. USA 95, 14 226-14 231. doi:10.1073/pnas. 95.24.14226) 9 Katsu, Y., Braun, E. L., Guillette Jr, L. J. & Iguchi, T. 2009 From reptilian phylogenomics to reptilian genomes: analyses of c-fun and DJ-1 proto-oncogenes. Cytogenet. Genome Res. 127, 79-93. doi:10.1159/000297715) 10 Shedlock, A. M., Botka, C. W., Zhao, S., Shetty, J., Zhang, T., Liu, J. S., Deschavanne, P. J. & Edwards, S. V. 2007 Phylogenomics of nonavian reptiles and the structure of the ancestral amniote genome. Proc. Natl Acad. Sci. USA 104, 2767-2772. (doi:10.1073/pnas. 0606204104) 11 Hugall, A. F, Foster, R. & Lee, M. S. Y. 2007 Cali- bration choice, rate smoothing, and the pattern of tetrapod diversification according to the long nuclear gene RAG-1. Syst. Biol. 56, 543-563. doi:10.1080/ 10635150701477825) tissue and developmental-stage-specific expression pro- files [25,26), which could make the detection of certain miRNAs challenging. Because preparing and sequencing libraries is a biased sampling process, the detection prob- ability for specific targets is variable, and some miRNAs are likely to be more easily detected than others. Thus, failures to detect miRNA families are not equivalent to the absence of miRNA families [27]. We suggest that at least some of the four miRNA families currently thought to be unique to lizards and turtles may be present but as yet undiscovered in other reptiles. This work is the first to investigate the placement of turtles within reptiles using a genomic-scale analysis of single-copy DNA sequences and a complete sampling of the major relevant evolutionary lineages. Because UCEs are conserved across most vertebrate groups [20] and found in groups including yeast and insects [19], our framework is generalizable beyond this study Biol. Lett. (2012) Journal of Mammalogy, 88(1):24–31, 2007 HEMOGLOBIN FUNCTION AND PHYSIOLOGICAL ADAPTATION TO HYPOXIA IN HIGH-ALTITUDE MAMMALS JAY F. STORZ* School of Biological Sciences, University of Nebraska, Lincoln, NE 68588, USA Understanding the biochemical mechanisms that enable high-altitude animals to survive and function under conditions of hypoxic stress can provide important insights into the nature of physiological adaptation. Evidence from a number of high-altitude vertebrates indicates that modifications of hemoglobin function typically play a key role in mediating an adaptive response to chronic hypoxia. Because much is known about structure- function relationships of mammalian hemoglobins and their physiological role in oxygen transport, the study of hemoglobin variation in high-altitude mammals holds much promise for understanding the nature of adaptation to hypoxia from the level of blood biochemistry to the level of whole-organism physiology. In this review I 1st discuss basic biochemical principles of hemoglobin function and the nature of physiological adaptation to high- altitude hypoxia in mammals. I then discuss a case study involving a complex hemoglobin polymorphism in North American deer mice (Peromyscus maniculatus) that illustrates how integrative studies of protein function and fitness-related physiological performance can be used to obtain evolutionary insights into genetic mechanisms of adaptation. Key words: adaptation, altitude, deer mouse, ecological physiology, evolutionary physiology, hemoglobin, hypoxia, natural selection, oxygen transport, Peromyscus maniculatus Downloaded from https://academic.oup.com/jmammal/article-abstract/88/1/24/927083 by guest on 13 April 2020 High-altitude environments present a number of physiolog- ical challenges for endothermic animals, as they are character- ized by a lower partial pressure of oxygen (Po) and lower ambient temperatures compared to low-altitude environments at similar latitudes. The reduced Po, at high altitude results in reduced oxygen loading in the lungs such that the blood may not carry a sufficient supply of oxygen to the cells of respiring tissues (Bencowitz et al. 1982; Bouverot 1985; Turek et al. 1973). This reduced level of tissue oxygenation can impose severe constraints on aerobic metabolism and may therefore influence an animal's food requirements, water requirements, the capacity for sustained locomotor activity, and the capacity for internal heat production. Although the genetic basis of hypoxia tolerance has yet to be fully elucidated in any vertebrate species, evidence from a number of mammals, birds, and amphibians indicates that modifications of hemoglobin function often play a key role in mediating an adaptive response to high-altitude hypoxia (Perutz 1983). In all vertebrates other than cyclostomes, the hemoglobin protein is a heterotetramer, composed of 2 a-chain and 2 B-chain polypeptides. In mammals and birds, the different subunit polypeptides are encoded by different sets of duplicated genes that are located on different chromosomes (Hardison 2001). Because much is known about structure- function relationships of mammalian hemoglobins and their role in oxygen transport (reviewed by Perutz 1983, 2001; Poyart et al. 1992; Weber and Fago 2004), the study of hemo- globin variation in species that are native to high altitude pro- vides a unique opportunity to understand the nature of genetic adaptation to hypoxic stress from the level of blood bio- chemistry to the level of whole-organism physiology. In this review I 1st provide some background information about hemo- globin function and the nature of physiological adaptation to high-altitude hypoxia. I then discuss a case study involving a complex hemoglobin polymorphism in deer mice (Peromyscus maniculatus) that illustrates how integrative studies of protein function and fitness-related physiological performance can be used to obtain evolutionary insights into genetic mechanisms of adaptation. * Correspondent: jstorz2@unl.edu CIRCULATORY ADJUSTMENTS TO HYPOXIC STRESS When atmospheric air is drawn into the alveoli of the lungs, oxygen is under a higher partial pressure than in the pulmonary capillaries, and it therefore diffuses across the respiratory membrane into the arterial bloodstream. Once oxygen has en- tered the bloodstream, it is immediately bound to hemoglobin in the red blood cells transport the oxygen-consuming © 2007 American Society of Mammalogists www.mammalogy.org 24 February 2007 SPECIAL FEATURE-PHYSIOLOGICAL ADAPTATION TO HIGH ALTITUDE 25 blood Co, mmol-L-1 Bboz }Cao-CV, Pao, Po cells of respiring tissues. The gas exchange ends at the tissue capillaries as oxygen, released by hemoglobin, diffuses across the capillary walls through the interstitial fluid to the cells. At the same time, CO2 and other metabolic end-products enter the bloodstream and are transported to the lungs by the opposite route. At high altitude, the arterial Po, is reduced compared to what it would be in an oxygen-rich sea-level environment and it becomes critically important to minimize the corresponding reduction in tissue oxygenation. In the cascade of Po, across different compartments of the gas-exchange system, there are 2 main steps where circulatory adjustments can help minimize the inevitable reduction in tissue Po,: the gradient between alveolar gas and arterial blood, and that between capillary blood and the tissues. The Po, gradient between alveolar gas and arterial blood is normally attributable to a small amount of venous admixture and unequal matching of ventilation to per- fusion in the lungs (that is, a mismatch between the diameter of the airways and the diameter of the pulmonary blood vessels). The Po, gradient between capillary blood and the tissues results from unloading of oxygen in the tissue capillary bed. Tissue gas exchange begins at the arterial inlet to the capillary bed, and the Po, falls rapidly from the arterial side to the venous side as oxygen diffuses from the high Po, of the blood to the low Po, of the interstitial fluid. A meaningful estimate of mean capillary Po, and the gradient to the cells can be obtained from measurements of arterial and mixa mixed-venous Po, gradient can be minimized by increasing Downloaded from https://academic.oup.com/jmammal/artic blood Po,, Torr Fig. 1.—A schematic representation of the oxygen dissociation curve under physiochemical conditions prevailing in arterial blood (open circle) and mixed venous blood (solid circle). The y-axis measures the oxygen concentration in the blood (Co) and the x-axis are of oxygen in the blood (Po). Cao, and Cvo, are the oxygen concentrations in arterial and mixed venous February 2007 SPECIAL FEATURE—PHYSIOLOGICAL ADAPTATION TO HIGH ALTITUDE 25 blood Co, mmol-L BDO >Cao, CV, Pao-Poz cells of respiring tissues. The gas exchange ends at the tissue capillaries as oxygen, released by hemoglobin, diffuses across the capillary walls through the interstitial fluid to the cells. At the same time, CO2 and other metabolic end-products enter the bloodstream and are transported to the lungs by the opposite route. At high altitude, the arterial Po, is reduced compared to what it would be in an oxygen-rich sea-level environment and it becomes critically important to minimize the corresponding reduction in tissue oxygenation. In the cascade of Po, across different compartments of the gas-exchange system, there are 2 main steps where circulatory adjustments can help minimize the inevitable reduction in tissue Po,: the gradient between alveolar gas and arterial blood, and that between capillary blood and the tissues. The Po, gradient between alveolar gas and arterial blood is normally attributable to a small amount of venous admixture and unequal matching of ventilation to per- fusion in the lungs (that is, a mismatch between the diameter of the airways and the diameter of the pulmonary blood vessels). The Po, gradient between capillary blood and the tissues results from unloading of oxygen in the tissue capillary bed. Tissue gas exchange begins at the arterial inlet to the capillary bed, and the Po, falls rapidly from the arterial side to the venous side as oxygen diffuses from the high Po, of the blood to the low Po, of the interstitial fluid. A meaningful estimate of mean capillary Po, and the gradient to the cells can be obtained from measurements of arterial and mixed venous Po,. The arterial- mixed-venous Po, gradient can be minimized by increasing the circulatory conductance of oxygen in the blood. In high- altitude mammals, one of the primary mechanisms for increas- ing the circulatory conductance of oxygen involves increasing the oxygen-binding affinity of hemoglobin. blood Poz; Torr Fig. 1.—A schematic representation of the oxygen dissociation curve under physiochemical conditions prevailing in arterial blood (open circle) and mixed venous blood (solid circle). The y-axis measures the oxygen concentration in the blood (Co) and the x-axis measures the partial pressure of oxygen in the blood (Po). Cao, and Cvo, are the oxygen concentrations in arterial and mixed venous blood, respectively. Pao, and Pvo, are the partial pressures of oxygen in arterial and mixed venous blood, respectively. The slope of the line joining the arterial and mixed venous points on the curve denotes the blood oxygen capacitance coefficient (Bbo, in equations 2 and 3). Downloaded from https://academic.oup.com/jmammal/article-abstract/88/1/24/927083 by guest on 13 April 2020 ADAPTIVE MODIFICATION OF HEMOGLOBIN FUNCTION IN HYPOXIA-TOLERANT MAMMALS When the arterial Po, is reduced because of high-altitude hypoxia, the transport of oxygen by blood has to serve 2 inter- related functions: it must maintain a sufficient flux of oxygen to meet metabolic demand, and it must also maintain an adequate pressure gradient for oxygen diffusion from the lungs to the cells of respiring tissues (Bouverot 1985; Monge and León- Velarde 1991). The 1st of these 2 functions is described by the following Fick's convection equation: Vo = Qb(Cao, - Cvo), (1) This capacitance coefficient is defined as the slope of the line connecting the arterial point to the mixed venous point on the oxygen-hemoglobin dissociation curve (ODC; Fig. 1). Because of the nonlinear relationship between oxygen concentration and Po, in blood (which gives rise to the sigmoid shape of the ODC), the capacitance coefficient Bbo, is not constant. The maintenance of an adequate pressure gradient for tissue oxygenation can be understood by rearranging equation 2 as follows: Pvo, = Pao, - {1/(Bbo, (Qb/V02)]}, (4) where Pvo, is viewed as the critical pressure at the vascular supply source for oxygen diffusion into the cells of respiring tissues (Bouverot 1985). The product Bbo, (Qb/Vo) is the specific oxygen blood conductance. Under hypoxia, an increased oxygen blood conductance helps to maintain a sufficient driving force for oxygen diffusion to the tissues. One of the most important mechanisms to compensate for reduced arterial Po, at high altitude involves shifting the shape and position of the ODC (Luft 1972). The ODC describes how the reversible binding of oxygen by hemoglobin depends on Po, in the blood. At low Po, in the bloodstream, the arterial and mixed venous points on the ODC would be shifted leftward to where Vo, is the rate of oxygen consumption, Qb is the total cardiac blood flow, and Cao, and Cvo, are the oxygen con- centrations in arterial and mixed venous blood, respectively. This is equivalent to the following: Vo = b Bbo, (Pao, – Pvo), (2) where Pao, - Pvo, is the arterial-mixed-venous Po, difference, and Bbo,, called the blood oxygen capacitance coefficient Dejours et al. 1970), is defined by the ratio Bbox = (Cao, - Cvo)/(Pao - Pvo). (3)
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