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Nutrition 30 (2014) 82–89

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Nutrition

journal homepage: www.nutr i t ionjrnl .com

Basic nutritional investigation

Malnutrition suppresses cell cycle progression of hematopoietic progenitorcells in mice via cyclin D1 down-regulation

Karina Nakajima Ph.D. a,*, Amanda R. Crisma Ph.D. b, Graziela B. Silva M.S. a, Marcelo M. Rogero Ph.D. c,Ricardo A. Fock Ph.D. a, Primavera Borelli Ph.D. a

a Experimental Hematology Laboratory, Department of Clinical and Toxicological Analysis, Faculty of Pharmaceutical Sciences, University of S~ao Paulo, S~ao Paulo, BrazilbCellular Physiology Laboratory, Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of S~ao Paulo, S~ao Paulo, BrazilcDepartment of Nutrition, School of Public Health, University of S~ao Paulo, S~ao Paulo, Brazil

a r t i c l e i n f o

Article history:Received 10 December 2012Accepted 30 May 2013

Keywords:MalnutritionCell cycleHematopoietic stem cellsHematopoietic progenitor cellsCyclin D1

KN was responsible for the conception and design odata, analysis and interpretation of data; article writresponsible for conception and design of the studyarticle revising. GBdS was involved with the acquiresponsible for the nutritional consultant and article rwith article revising. PB was responsible for conceptioanalysis and interpretation of data; and article revisin* Corresponding author. Tel.: þ55 11 30913639; fax

E-mail address: knakajima@usp.br (K. Nakajima).

0899-9007/$ - see front matter � 2014 Elsevier Inc. Ahttp://dx.doi.org/10.1016/j.nut.2013.05.029

a b s t r a c t

Objective: Protein malnutrition (PM) often is associated with changes in bone marrow (BM)microenvironment leading to an impaired hematopoiesis; however, the mechanism involved ispoorly understood. The aim of this study was to compare the cell cycle progression of hemato-poietic stem cells (HSC) and hematopoietic progenitor cells (HPC) and evaluate the cell cyclesignaling in malnourished mice to assess the mechanism of cell cycle arrest.Methods: C57Bl/6J mice were randomly assigned in control and malnourished groups receivingnormoproteic and hypoproteic diets (12% and 2% protein, respectively) over a 5-wk period.Nutritional and hematologic parameters were assessed and BM immunophenotypic analysis wasperformed. Cell cycle of HPC (Lin–) and HSC (Lin–Sca-1þc-Kitþ) were evaluated after 6 h of in vivo5-bromo-2’-deoxyuridine (BrDU) incorporation. Cell cycle regulatory protein expression of HPCwas assessed by Western blot.Results: Malnourished mice showed lower levels of serum protein, albumin, glucose, insulin-likegrowth factor-1, insulin, and higher levels of serum corticosterone. PM also caused a reductionof BM myeloid compartment resulting in anemia and leukopenia. After 6 h of BrDU incorporation,malnourished mice showed G0-G1 arrest of HPC without changes of HSC proliferation kinetics.HPC of malnourished mice showed reduced expression of proteins that induce cell cycle (cyclin D1,cyclin E, pRb, PCNA, Cdc25a, Cdk2, and Cdk4) and increased expression of inhibitory proteins (p21and p27) with no significant difference in p53 expression.Conclusion: PM suppressed cell cycle progression mainly of HPC. This occurred via cyclin D1 down-regulation and p21/p27 overexpression attesting that BM microenvironment commitmentobserved in PM is affecting cell interactions compromising cell proliferation.

� 2014 Elsevier Inc. All rights reserved.

Introduction circumstances, the 2010 Food and Agriculture Organization report

As a definition, malnutrition may be taken as a subacute orchronic state of nutrition in which a combination of varying de-grees of malnutrition and inflammatory activity lead to changes inbody composition and physiological function [1]. Under these

f the study, acquisition ofing and revising. ARC was, acquisition of data, andsition of data. MMR wasevising. RAF was involvedn and design of the study,g.: þ55 11 38132197.

ll rights reserved.

[2] estimated that globally 925million peopleweremalnourished,mostly in developing countries. However, several conditions apartfrom social establishments may lead to malnutrition. Theseinclude eating disorders, individuals with chronic disease, andlong-term hospitalization [3–5], contributing to a worldwidepublic health problem. Clinically, the consequences of malnutri-tion have been associated with metabolic alterations, increasedsusceptibility to infections [6,7], and histologic and functionalchanges in several tissues, including bone marrow (BM) [8,9]. Infact, anemia and leukopenia reflect the hematopoietic tissuecommitment in response to malnutrition and are associated withmodification of the immune system that translates into increasedsusceptibility to infection [10–13], which is especially relevant tohospitalized individuals.

Table 2Nutritional and hormonal parameters

Parameters Control(n ¼ 8)

Malnourished(n ¼ 10)

P-value

Body weight variation (%) þ27.2 � 2.8 �5.6 � 0.8z <0.0001Food consumption (g/d/animal) 3.6 � 0.1 4.5 � 0.1z <0.0001Protein consumption (g/d/animal) 0.44 � 0.01 0.12 � 0.04z <0.0001Calorie intake (kcal/d) 13.95 � 0.37 16.92 � 0.48z <0.0001Total serum protein (g/dL) 5.1 � 0.4 4.2 � 0.3* 0.0451Serum albumin (g/dL) 2.0 � 0.1 1.7 � 0.1* 0.0268Serum glucose (mg/dL) 101.8 � 7.4 69.4 � 4.0y 0.0014Insulin concentration (ng/mL) 0.62 � 0.09 0.24 � 0.05y 0.0041IGF-1 concentration (ng/mL) 546 � 107 255 � 420y 0.0066Corticosterone concentration

(ng/mL)12.3 � 0.1 40.2 � 7.1* 0.0174

IGF, insulin-like growth factorData set analyzed by the Student’s t test. Values are expressed as mean � SD(*P < 0.05; y P < 0.01; z P < 0.001)

K. Nakajima et al. / Nutrition 30 (2014) 82–89 83

Hematopoietic tissues show a high turnover rate, beingextremely influenced by the availability of nutrients, becausethey are essential for cell cycle progression directly or indirectly[14]. Several studies highlight abnormalities in myelopoiesisand lymphopoiesis, followed by peripheral pancytopenia as aconsequence of protein malnutrition (PM) [13,15–18]. We havedemonstrated BM hypoplasia and structural breakdown withchanges in the extracellular matrix (ECM) and stromal cells [8,9].Cell cycle arrest of hematopoietic cells also has been observedwith a delayed BM reconstitution after 5-fluoruracil treatment inmalnourished mice [13,19].

There are two restricted populations of hematopoietic stemcells (HSC) and hematopoietic progenitor cells (HPC) in BM thathave the ability to generate all blood cell lineages in appropriateamounts to maintain system homeostasis. This is achieved dueto strict cell cycle control mediated by extrinsic factors withinBM and intrinsic factors at the cell level [20]. Therefore, cell in-teractions activate cell cycle signaling, promoting an orches-trated transition between G1-S-G2-M phases, which is regulatedby cyclins and its effectors, cyclin-dependent kinase (Cdk) andcyclin-dependent kinase inhibitor (CKI) [21–24]. Thus, extracel-lular stimuli induces cyclin D1 expression and consequent cyclinD1/cdk4,6 complex formation responsible for the initial phos-phorylation of retinoblastoma transcriptional repressors (pRb,p107, and p130), which keeps the E2F gene repressed. This initialphosphorylation promotes cyclin E synthesis and cyclin E/cdk2complex formation, which further inactivates pRb-mediated in-hibition of E2F, resulting in the G1-S transition. Meanwhile,members of the CKI family, namely inhibitors of kinase 4 (INK4:p15, p16, p19) and CDK interacting protein/kinase inhibitoryprotein (CIP/KIP: p21, p27) inhibit activation of the cyclin-cdkcomplexes, promoting a finer control of cell cycle progression[25–29].

Whereas the BM microenvironment commitment resultingfrom PM could compromise cell interactions, it is assumed thatsuch a condition may blunt cyclin D1 expression, which in turnjeopardizes cell cycle initiation. To better understand themechanisms involved in hematopoiesis impairment due to PM,we evaluated the effects of PM on HPC cell cycle signaling.

Materials and methods

Animals and diets

Two-mo-old male C57Bl/6J mice were obtained from the Animal Labora-tory of Faculty of Pharmaceutical Sciences at the University of S~ao Paulo. Themice (N ¼ 26) were housed individually in metabolic cages (temperaturecontrolled at 22 � 2�C and a relative humidity of 55 � 10% under a 12-h light/12-h dark cycle). After 2 wk of adaptation, the mice were randomly assigned tocontrol (C) and malnourished (M) groups receiving normoproteic (12% protein)and a hypoproteic (2% protein) diets, respectively, over 5-wk periods. The

Table 1Nutrient composition of the two experimental diets (g/1000 g of diet)

Ingredients Normoproteic diet Hypoproteic diet

Casein 120 20Sucrose 100 100Soybean oil 40 40Fiber 50 50Choline bitartrate 2.5 2.5L-cystine 1.8 0.3Tert-butylhydroquinone 0.008 0.008Vitamin mixture 10 10Mineral mixture 35 35Cornstarch 640.692 742.192

murine diets (Table 1) were prepared in our laboratory according to the rec-ommendations of the American Institute of Nutrition [30]. Mice were givenfree access to food and water. At the end of week 5, all mice were sacrificedunder anesthesia with 10 mg/kg of xylazin (Rompum, Bayer, SP, Brazil) and 100mg/kg of ketamine (Ketamina�, Crist�alia, SP, Brazil) between 0700 and 0900.The mice were fasted for 8 h before sacrifice. This study was approved by theEthics Committee on Animal Experimentation of the Faculty of PharmaceuticalSciences (CEEA n� 92), University of S~ao Paulo, and was conducted according tothe guidelines of the Brazilian College on Animal Experimentation.

Nutritional and hormonal evaluation

The nutritional status was assessed by body mass variation, diet consump-tion, and serum protein, albumin, and glucose determination using commercialkits (Labtest, MG, Brazil). The hormonal profile was evaluated by enzyme-linkedimmunosorbent assay (ELISA) quantification of serum insulin (Rat/Mouse InsulinELISA, LINCO, St. Charles, MO, USA), insulin-like growth factor (IGF-1, Mouse IGF-1 Quantikine ELISA, R&D System, Minneapolis, MN, USA) and corticosterone(corticosterone EIA, IDS, Boldon, UK). The colorimetric analyses were assessed ina plate reader (EL800 Universal Microplate Reader - Instrumentals Bio-Tek Inc,Winooski, VT, USA).

Hematologic evaluation

Blood samples with EDTA (Sigma-Aldrich, St Louis, MO, USA) as anticoagu-lant were used for hemogram evaluation performed on ABX Micros ABC Vet�

equipment (Horiba, Montpellier, France). Morphologic and leukocyte differenti-ation analyses were carried out on blood smears stained with standard May-Grunwald Giemsa technique. For reticulocyte identification, a supravital dyewas used and quantification was performed on smear preparations. Total BMcells were harvested from both femur and tibia cavities using Iscove’s medium(Sigma-Aldrich, St. Louis, MO, USA) and used for myelogram and immunophe-notyping analyses. For myelogram, total cell counts were carried out using aNewbauer Chamber followed by differential counts using cytocentrifuge prepa-rations stained with May-Grunwald Giemsa in which 300 cells per slide peranimal were counted.

Table 3Bone marrow cell counts

Control(n ¼ 6)

Malnourished(n ¼ 6)

P-value

Total cells (103/mm3) 40.7 � 1.4 30.3 � 1.5z <0.0001Blast cells (103/mm3) 1.0 � 0.2 0.5 � 0.1* 0.0445Granulocyte precursors (103/mm3) 2.7 � 0.3 1.7 � 0.1* 0.0304Band/segmented cells (103/mm3) 17.8 � 0.6 13.6 � 0.9* 0.0192Eosinophil (103/mm3) 0.5 � 0.1 0.2 � 0.1* 0.0149Lymphocyte (103/mm3) 8.4 � 1.2 7.5 � 0.7 0.5982Macrophage (103/mm3) 0.1 � 0.0 0.1 � 0.0 0.5200Total erythroblast (103/mm3) 9.3 � 0.5 5.8 � 0.3y 0.0052

Data set analyzed by the Student’s t test. Values expressed as mean � SD(*P < 0.05; y P < 0.01; z P < 0.001)

Fig. 1. Total bone marrow immunophenotypic analysis. Representative flow cytometer analysis of BM cell populations of control (n ¼ 4) and malnourished (n ¼ 4) animals:progenitors cells (CD45þCD34þ); granulomonocyte cells (Gr-1þCD11bþ); total erythroid cells (Ter119þ); erythroid precursors (Ter119þCD71þ); total B lymphocytes(CD19þCD5–); total T lymphocytes (CD3þ); lymphocyte T CD4þ (CD3þCD4þ); and lymphocyte T CD8þ (CD3þCD8þ).

K. Nakajima et al. / Nutrition 30 (2014) 82–8984

Immunophenotyping

Flow cytometer was used to perform immunophenotypic analysis of total BMcells. Before antibody labeling, red cells were lysed using ammonium chloridebuffer (NH4Cl 150 mM, NaHCO3 10 mM, EDTA 0,1 mM, pH 7,4) and washed twicewith PBS solution (PBS buffer containing 2 mM EDTA, 0,5% BSA, 0,01% sodiumazide, pH 7,4). Then, 1 � 106 total BM cells were incubated with following anti-bodies: CD34-FITC, CD45-APC, CD11b-FITC, Gr-1-APC, Ter119-FITC, CD71-PE,CD5-APC, CD19-PE, CD3-FITC, CD4-APC, and CD8-PE (BD Pharmingen, FranklinLakes, NJ, USA). For all antibodies, a correspondent negative control was assessed.50000 cells were acquired on FACSCanto II� flow cytometer (Becton Dickson,

Franklin Lakes, NJ, USA) using 488 nm and 633 nm excitation lasers. Data wereanalyzed with FlowJo� 7.6 software (TreeStar, Ashland, OR, USA).

Cell cycle assessment

Cell cycle evaluation was performed using APC 5-bromo-2’-deoxyuridine(BrDU) Flow kit (BD Pharmingen, Franklin Lakes, NJ, USA) following the manu-facturer’s instructions. Briefly, both C and M group animals were treated intra-peritoneally with a BrDU solution (1 mg per animal) 6 h before sacrifice. The HPC(immunophenotypically characterized as Lin– because those cells do not expressesany lineage markers) were obtained by negative depletion from BM using the

Table 4Immunophenotypical analysis of bone marrow cells

Control(n ¼ 4)

Malnourished(n ¼ 4)

P-value

HSC (Lin–Sca1þc-Kitþ) 0.06 � 0.01% 0.03 � 0.01%* 0.0246HPC (Lin–) 3.6 � 0.4% 2.5 � 0.2%y 0.0088Progenitors cells (CD45þCD34þ) 18.7 � 1.4% 10.9 � 1.9%* 0.0168Total erythroid cells (Ter119þ) 31.2 � 4.5% 11.1 � 5.5%* 0.0465

K. Nakajima et al. / Nutrition 30 (2014) 82–89 85

immunomagnetic method (Lineage cell depletion kit for mouse Milteny Biotec�,Cologne, Germany) according to the manufacturer’s instructions. Lin– cells werethen labeled with Sca-1-FITC (eBiosciences, San Diego, CA, USA) and c-Kit-PE(BD Pharmingen, Franklin Lakes, NJ, USA) for HSC (immunophenotypically char-acterized as Lin–Sca-1þcKitþ) quantification. Cell cycle evaluation was conductedon both HPC and HSC. 50000 cells were acquired on FACSCanto II� flowcytometer(Becton Dickson, Franklin Lakes, NJ, USA) using 488 nm and 633 nm excitationlasers and data were analyzed with FlowJo� 7.6 software (TreeStar, Ashland,OR, USA).

Erythroid precursors (Ter119þ

CD71þ)18.6 � 2.8% 5.6 � 2.9%* 0.0330

Granulomonocyte cells (CD11bþ

Gr-1þ)44.6 � 4.7% 28.1 � 3.9%* 0.0362

B lymphocyte (CD19þCD5–) 11.2 � 0.9% 7.9 � 2.5% 0.2218T lymphocyte (CD3þ) 7.9 � 2.6% 10.3 � 2.4% 0.5246Lymphocyte T CD4 (CD3þCD4þ) 0.9 � 0.1% 1.2 � 0.2% 0.3202Lymphocyte T CD8 (CD3þCD8þ) 1.6 � 0.4% 2.8 � 0.6% 0.1628

HPC, hematopoietic progenitor cells; HSC, hematopoietic stem cellsData set analyzed by the Student’s t test. Values are expressed as mean � SD(*P < 0.05, y P < 0.01)

Western blot analysis

1 � 106 HPC were lysed for the extraction of total proteins using RIPA�

buffer (Pierce, Rockford, IL, USA) containing protease and phosphatase in-hibitors (0.5 mM PMSF, 50 mM NaF, 10 ug/mL leupeptin, and 10 ug/mL apro-tinin, Sigma Aldrich, St. Louis, MO, USA). After total protein quantification usinga commercial kit (BCATM protein assay kit, Pierce, Rockford, IL, USA) sodiumdodecyl sulfate polyacrylamide gel electrophoresis (8%–10%) was performedusing 50 ug of protein followed by a polyvinylidene fluoride membrane (PVDF,Amersham Biosciences, Pittsburg, PA, USA) transfer. After overnight incubationwith primary antibodies (cyclin D1, cyclin E, phosphorylated pRb, Cdk-2, Cdk-4,Cdc-25a, PCNA, p21, p27, and p53; all from BD Pharmingen, Franklin Lakes, NJ,USA) at a 1:1000 dilution, membranes were washed with TBS-Tween buffer andincubated with horseradish peroxidase-labeled secondary antibody (dilution1:2000) for 1 hour. Following three washes, immunoreactive bands werevisualized using the ECL detection system (Amersham Biosciences, Pittsburg,PA, USA) and images captured using ImageQuantTM 400� version 1.0.0(Amersham Biosciences, Pittsburg, PA, USA). For standardization and quantifi-cation, the images were analyzed using ImageQuant TL� program (AmershamBiosciences, Pittsburg, PA, USA). Results were expressed in relation to the in-tensity of b-actin (Sigma-Aldrich, St. Louis, MO, USA).

Statistical analysis

After a normality test, all data sets were analyzed by the Student’s t test andthe level of significance adopted was P < 0.05. All data were expressed asmean � SD. Statistical analyzes were performed using the GraphPad Prism�

software version 5.01 (GraphPadSoftware Inc., CA, USA).

Results

PM alters hormonal and nutritional status

Mice fed a low-protein diet displayed higher food intakethan their control counterparts. Nevertheless, the low-protein intake was reflected in the loss of body mass andsignificant reduction in serum protein, albumin, and glucoselevels (Table 2). Malnourished mice showed lower serum in-sulin and IGF-1 levels, which are hormones associated withprotein anabolism, and higher serum corticosterone levels(Table 2), a catabolic hormone that could also contribute to thehigher susceptibility to infections was observed in this con-dition [31].

Table 5Peripheral blood parameters

Control(n ¼ 10)

Malnourished(n ¼ 10)

P-value

Total erythrocyte (�106/mm3) 9.3 � 0.4 7.8 � 0.3y 0.0082Hemoglobin (g/dL) 13.3 � 0.4 12.0 � 0.3y 0.0094Hematocrit (%) 38.6 � 0.9 33.6 � 1.2y 0.0030Reticulocytes (%) 4.0 � 0.2 3.2 � 0.2y 0.0045Total leukocyte (/mm3) 2532 � 251 1338 � 211y 0.0012Neutrophil (/mm3) 296.2 � 49.8 158.5 � 114.4* 0.0360Lymphocyte (/mm3) 2448.0 � 306.5 1407.1 � 341.6* 0.0381Eosinophil (/mm3) 3.1 � 9.2 0,.0 � 0.0 0.0593Monocyte (/mm3) 81.9 � 21.4 30.2 � 10.1* 0.0402

Data set analyzed by the Student’s t test. Values are expressed as mean � SD(*P < 0.05; yP < 0.01)

Hematologic impairment in response to PM

Malnourished mice showed BM hypoplasia with a strikingreduction of granulocytic and erythroid cells, with no differenceof lymphoid population as observed on both morphologic(Table 3) and immunophenotypical analysis (Fig. 1; Table 4).Malnourished mice showed a significantly lower percentage ofHPC (Lin–) and HSC (Lin–Sca-1þc-Kitþ) in BM compared withcontrol mice (Table 4), suggesting a decline in self-renewal andproliferation processes. Such changes in BM compartmentresulted in leukopenia and anemia with significant reduction inthe number of reticulocytes, indicating a non-regenerative ane-mia (Table 5).

PM inhibited cell cycle progression

After 6 h of BrDU incorporation there was no significant dif-ference of HSC proliferation kinetics between control (G0-G175.9 � 0.7%; S 22.7 � 0.6%; G2-M 1.4 � 0.1%) and malnourishedanimals (G0-G1 74.0 � 0.9%; S 24.6 � 0.9%; G2-M 1.4 � 0.2%)(Fig. 2A). However, after 6 h, the HPC of malnourished animalshad entered into a cell cycle with lower frequency because theypresented a higher percentage of HPC in G0-G1 (C 71.7 � 2.1%; M80.1 � 2.2%), with a diminished percentage of cells in S (C 24.8 �2.3%; M 15.80 � 1.5%) and G2-M phases (C 4.7 � 0.3%; M 2.5 �0.3%) (Fig. 2B). We also observed that malnourished mice dis-played an inversed pattern of proliferation rate in which HPCbecame more quiescent then HSC (Fig. 3).

Cell cycle signaling modulation in PM

By investigating the influence of PM on the intrinsic cell cyclecontrol we ascertained that HPC of malnourished animals had asignificantly lower expression of cyclin D1, cyclin E, Cdk2, cdc25a,and a non-significant difference of Cdk4 expression (Fig. 4). As aconsequence, phosphorylated pRb and PCNA expression also weresignificantly reduced, indicating a non-progression of cell cycle. Incontrast, HPC of malnourished animals exhibited a significantlyhigher expression of p21 and p27 comparedwith cells from controlanimals (Fig. 4). There was no difference of HPC p53 expression.

Discussion

Although malnourished mice presented a higher energyintake, the insufficient amount of protein compromised their

Fig. 2. Effects of PM on cell cycle analysis 6 h after BrDU incorporation. (A) flow cytometry analysis of HSC (Lin–Sca-1þcKitþ) BrDU incorporation and cell percentage in G0-G1and S phases. (B) flow cytometry analysis of HPC (Lin–) BrDU incorporation and cell percentage in G0-G1, S, and G2-M phases. Mean � SD of control (n ¼ 5) and malnourished(n ¼ 5) groups with significant difference when *P < 0.05 and yP < 0.01. Data set analyzed by the Student’s t test.

K. Nakajima et al. / Nutrition 30 (2014) 82–8986

Fig. 3. Proliferation kinetics comparison between HSC and HPC. Cell percentage comparison of HSC and HPC in G0-G1, S and G2-M phases of control and malnourishedgroups. Mean � SD with significant difference when *P < 0.05, yP < 0.01, and zP < 0.001. Data set analyzed by the Student’s t test.

K. Nakajima et al. / Nutrition 30 (2014) 82–89 87

physiology. Malnourished mice showed nutritional, hormonal,and hematologic alterations consistent with the literature [8–13,15–18,32,33]. Concerning the hormonal status, themalnourishedgroup showed lower serum insulin and IGF-1 levels than thecontrol group. IGF-1 is directly related to the protein metabolismand anabolism [34] and it has been proposed that the amount ofenergy and protein in the diet are primary determinants ofserum IGF-1 levels during growth [35]. Thus, the decrease ofserum IGF-1 and insulin levels are related to the reduction ofanabolic action favoring protein catabolism. Additionally, dietaryprotein deficiencymay provoke an increase in protein catabolismby the action of glucocorticoids, whose plasma concentration isincreased [36].

Regarding hematologic data, malnourished mice presentedperipheral cytopenia due to BM hypoplasia, which is in accor-dance with previous studies [8,15–18]. As already discussed inother studies, those alterations could, in part, contribute to theincreased susceptibility to infections observed in this condition[6,7,10–13], making it a major public health problem worldwide.In previous data [13–18], our group demonstrated a reduction ofhematopoietic progenitors in BM and spleen, especially of theerythroid precursors in response to PM. Herein, by screening allBM cell lineages, we confirmed a myeloid shrinkage with a slightreduction of the lymphoid compartment. In the present study,we also demonstrated that PM directly affects the amounts ofHPC and HSC within BM, both considered more primitive pop-ulations. These findings are highly relevant if we consider thatHSC and HPC are the key points that regulate the hematopoiesis:from their self-renewal, differentiation, and proliferation pro-cesses, blood system homeostasis is maintained under physio-logical conditions.

It has been suggested that quantitative changes may arisefrom two distinct events within BM: increased apoptotic pro-cesses and/or reduction of cell proliferation. Both processesdepend on the BMmicroenvironment integrity and are thereforesusceptible to the effects of malnutrition. Previous observation[18] excludes an increase in the apoptotic events, suggesting thatcompensatory mechanisms such as autophagy [37,38] may pre-vent programmed cell death in an attempt to bring organism

homeostasis in response to nutrient deprivation. Other studies,however, show the nutritional status influence on hematopoiesissuggesting that malnutrition compromises the process of pro-liferation and maintenance of hematopoietic tissue [15–18]. Onestudy [19] demonstrated the retention of BM cells in G0-G1 ofmalnourished animals and, after myeloablative treatment with5-fluorouracil, reconstitution of the hematopoietic tissue wasdelayed, indicating that PM impairs cell cycle progression. In thisstudy, we observed that the PM also caused G0-G1 arrest of HPCwithout affecting the proliferation kinetics of HSC after 6 h ofBrDU incorporation. Considering that we assessed a short periodof time, we are unable to predict whether PM causes cell cyclearrest of HSC for those cells predominate in a rest transient statein order to maintain their self-renewal and differentiation ability[39,40]. Regarding the diminished HSC pool of malnourishedmice, it is assumed that those cells proliferate at some point, andthe differentiation process supposedly overcame the self-renewalprocess. Nevertheless, those data indicated that malnourishedmice were unable to maintain tissue homeostasis, since evenwith reduced BM and peripheral cellularity HPC and HSC did notshorten their turnover time to thereby restore tissue integrity. Onthe contrary, HPC became more quiescent due to PM, perhaps inan attempt to protect from irreversible DNA damage. Thus, cellswith a high proliferative rate might be more susceptible to theeffects of PM leading to the BM hypoplasia.

Together with the observation of a restrained G0-G1-Stransition of HPC due to PM, cell cycle signaling analysis indi-cated a down-regulation of the major proteins that govern thisprogress; cyclin D1, cyclin E, Cdk4, Cdk2, and Cdc25a. Withoutthe cyclin D1/Cdk4 and cyclin E/Cdk2 complex formation and itsCdc25a-mediated activation, a reduced pRb phosphorylationwas expectedly observed, leading to a mild S entry, which wasconfirmed by a lower PCNA expression. In contrast, HPC ofmalnourished mice showed p21 and p27 overexpression, whichare known proteins that promote cell cycle arrest in response tonutrient limitations [41,42]. The normal levels of p53 suggest anabsence of DNA damage, because it is expected that a cell cyclearrest is p53-mediated for the HPC in this situation [43–45].Therefore, the cell cycle arrest appears to be an effective

Fig. 4. Effects of PM on cell cycle regulatory protein expression of HPC. Western blot analysis of cyclin D1, cyclin E, pRb, PCNA, Cdc25a, Cdk2, Cdk4, p21, p27, and p53 proteinexpression (in arbitrary units). Results from three independents experiments expressed in relation to the intensity of b-actin. Mean � SD with significant difference when*P < 0.05 and zP < 0.001. Data set analyzed by the Student’s t test.

K. Nakajima et al. / Nutrition 30 (2014) 82–8988

adaptation process reducing cell metabolism and minimizingcell damage.

Cell cycle progression is triggered by a myriad of extracellularsigns that activate intracellular downstream effectors thattranslate into cyclin D1 expression. Considering the structuraland biochemical BM microenvironment disarrangementobserved in PM, twomajor signaling pathways may contribute tothe down-regulation of cyclin D1 and consequently cell cyclearrest: mitogen-activated protein kinase (MAPK) and mamma-lian target of rapamycin (mTOR) [46,47]. Therefore, the bonemarrow ECM changes and stromal cells’ functional impairmentdescribed in previous studies [8,9] could jeopardize cell in-teractions, leading to an unsustained MAPK signaling. On theother hand, the lack of insulin, IGF-1, glucose, and amino acidsshown in the present study also could inhibit mTOR signaling inHPC. Hence, together with a restrained cell proliferation, mTORinactivation also could promote autophagy process, completingthe adaptation system mediated by lack of nutrients. Both hy-potheses could shed some light on the physiopathology ofmalnutrition and are now being investigated in our laboratory.

In other words, the structural changes in BM, previouslydescribed as a consequence of PM, compromise cell interactions,blunting the complex network that signalize cell cycle entry. Byaffecting HPC proliferation, PM could be critical in some medicalconditions, especially in bone marrow transplantation, in which

BM microenvironment integrity could be critical to the cellengraftment. Furthermore, by knowing how PM is compro-mising hematopoiesis, we are now able to assess whethernutritional recovery could restore blood system integrity.

Conclusion

In conclusion, we observed that PM suppresses cell cycleprogression affecting the HPC proliferation. The G0-G1 arrest ismediated by high levels of p21 and p27, and because there wasno p53 increasing, we assume that it is non-induced by DNAdamage. In parallel, a down-regulation of cyclin D1 expressionattests that BM microenvironment commitment observed in PMis affecting cell interactions compromising cell proliferation andleading to BM hypoplasia.

Acknowledgments

This work was supported by grants of the Fundac~ao deAmparo �a Pesquisa do Estado de S~ao Paulo (09/53902-6) and theCoordenac~ao de Aperfeicoamento de Pessoal de N�ıvel Superior.The authors are thankful to Renata Chaves Albuquerque for thetechnical contributions in the flow cytometry analysis.

K. Nakajima et al. / Nutrition 30 (2014) 82–89 89

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