N-arachidonoyl-ethanolamine as endogenous ligand of cannabinoid type-1 and type-2 receptors as well as the development of different–omics technologies have the merit to have led to the discovery of a huge number of naturally occurring N-acyl-amines. Among those mediators, N-acyl amino acids, chemically related to the endocannabinoids and belonging to the complex lipid signaling system now known as endocannabinoidome, have been rapidly growing for their therapeutic potential. Here, we review the current knowledge of the mechanisms for the biosynthesis and inactivation of the N-acyl amino acids, as well as the various molecular targets for some of the N-acyl amino acids described so far.The lipid signal is becoming increasingly crowded as increasingly fatty acid amide derivatives are being identified and considered relevant therapeutic targets. The identification of  N-acyl amino acids (NAAAs) are an important family of endogenous signaling molecules in which an amide bond covalently links an amino acid to the acyl moiety of a long-chain fatty acid. Although lipid containing amino acids, some of them produced in response to certain stress conditions, were identified in different bacterial membranes, little is known about their specific molecular functions [unctions ,2. In adunctions ,4,5.N-arachidonoyl-ethanolamine (AEA) as one of the endogenous ligand able to bind with different affinity cannabinoid type-1 (CB1) and type-2 (CB2) receptors, with which NAAAs share chemical structure and same biologic activities, let to a renewed scientific interest toward these compounds. Indeed, some NAAAs were initially synthesized for structure-activity relationship studies to optimize the CB1 binding and later, identified as naturally occurring in bovine and rat brain [N-acyl taurines, NATs) [N-acyl alanines (Ala) exhibited antiproliferative effect in vitro [N-oleoyl phenylalanine (Phe) regulated energy homeostasis [N-linoleoyl Tyr, by activating CB2 receptor, protected against transient cerebral ischemia [The discovery of at brain ,7. Subseat brain . These cs, NATs) . Later, s, NATs) ,10,11. Ein vitro  as well eostasis . Moreoveeostasis  and N-liischemia .N-acyl glycines (NAGlys) and NASers, to underscore that the understanding of biochemical and molecular mechanisms, underlying their pharmacological actions, may serve to find way to properly exploit their therapeutic potential.The purpose of this article is to overview NAAAs to provide information as complete and as updated as possible regarding their biosynthetic pathways, physiological role, and biological activity. Therefore, in this review we summarize literature data on the most widely studied member of NAAA family, i.e., N-arachidonoyl glycine (NAraGly) from glycine and Ara-CoA in presence or not of hydrogen peroxide was reported [N-oleoyl glycine (NOleGly) formation [N-arachidonoyl γ-aminobutyric acid (NAraGABA) from Ara-CoA and the respective amino acids were described [N-acyltransferase-like 2 (GLYATL2) and 3 (GLYATL3) described in human [N-palmitoyl glycine  and NOleGly were detected in siRNA knockdown of GLYATL3-N18TG2 cells [N-arachidonoyl-ethanolamine via the sequential enzymatic reaction of alcohol dehydrogenase (ADH) and aldehyde dehydrogenase [N-arachidonoyl glycinal as intermediate [Any amino acid, theoretically, might be able to form an amide with any fatty acid, thereby generating hundreds of novel bioactive lipids, via metabolic pathways that are still not completely understood . Little reported ,17. Thisormation  as well in human  and in min human  respectiin human  and, redG2 cells . A seconrogenase ,22. Thisrmediate . It seemrmediate . Indeed,rmediate .N-acyl-amides including NATs and NAAAs. Several NAAAs were synthesized and their potencies as FAAH inhibitors were evaluated [N-stearoyl, and NOle derivatives of Ala, Gly and Ser were also detected in all brain regions analyzed [Regarding NAAAs inactivation, since these compounds have chemical features in common with AEA, it was expected that they might share some of its catabolic fate . Indeed,valuated . The relvaluated . Moreovevaluated . Curiousvaluated . In addianalyzed .Growing evidence indicates that, just like AEA, some NAraAAs because of the presence of arachidonic acid, are also substrates to most of the oxidative metabolic pathways that lead to eicosanoid biosynthesis. Indeed, NAraGly, NAraAla, and NAraGABA are hydroxylated to the corresponding 12- and 15-hydroxyeicosatetraenoic (HETE) derivatives by both 12- and 15-lipoxygenases (LOX) at rates comparable to arachidonic acid . Cycloox1 [2 [N-terminus of the human GPR55 cDNA (HAGPR55/CHO), reported that NAraGly behaved as GPR55 agonist [A receptor [Ca) [Ca channels [Drosophila melanogaster [1, and inhibits GLYT2 and paraoxonase [1 antagonist, AM251, but not the PPARα antagonist, MK886, prevented NOleGly effect suggesting a CB1 receptor-mediating action. Altogether, these data point out NOleGly as a potential player in combating the high tobacco smoking rate and in protecting against the negative effects of drugs of abuse. Finally, NOleGly was reported to be active in reducing cell proliferation in vitro assay using the RAW 267.4 mouse macrophage cells [NAGlys are widely distributed throughout the central nervous system and other mammalian tissues, where they play preeminent roles in cell physiology and exhibit interesting pharmacological properties. Although an accurate quantification of their tissue levels is still missing, the endogenous concentration of these molecules ranges from high nM to low μM values. Based on its chemical similarity with AEA, NAraGly might be considered the most representative of this family and is certainly the most studied one. Analgesic and anti-inflammatory activities as well as vasorelaxation and inhibition of T-type calcium channels are some of the features of NAraGly recently summarized in a comprehensive review . Differe1  or CB2 [1 [2 . Althoug1 [2 , control1 [2  and migr1 [2 , anti-in1 [2 , neuropa1 [2 , diurnal1 [2  and micr1 [2 . It was 1 [2 . In addi1 [2 . Moreove1 [2 . However1 [2  as well 1 [2 . Recentl agonist . Indeed, agonist . Finally agonist . NAraGly agonist  and, by  agonist . NAraGlyreceptor  and behareceptor . Moreovereceptor . In addireceptor . On thisreceptor  by likelreceptor . Again, receptor . It shoureceptor ,49 and stor [Ca) . Finallychannels . NOleGlynogaster ,20,50, aaoxonase ,52,53. Aaoxonase ,55. NOleaoxonase . The antaoxonase . Moreoveaoxonase . NOleGlyge cells , althougDrosophila melanogaster that also expressed acyl derivatives of Val, Leu, Ala, Tryr, Phe, Ser and GABA [NPalGly was identified in murine cells and tissues  and humaand GABA ,69. The and GABA  as well and GABA . It has and GABA ,71. Indeand GABA ,71. Of nRecently, a urinary metabonomic study showed a significant increase of NPalGly in primary dysmenorrhea women suggesting that this elmiric acid, together with other metabolites, could be a potential biomarker in clinical diagnosis and treatment of this gynecological disorder . In addiLittle is known regarding the subfamily of NASers and they might still be considered endogenous orphan lipid mediators.1, CB2 or TRPV1 [1/CB2 activation [1, CB2 and TRPV1 activation [1, CB2 and TRPV1 receptors [NAraSer was isolated ten years ago from bovine brain  and, excor TRPV1 , althougor TRPV1 . In parttivation . Similartivation . Later, tivation . NAraSertivation . Of notetivation . Severaltivation ,63,64. Weceptors ,63,64. Feceptors .In the last few years, published data suggested NOleSer as new potential therapeutic against bone diseases. Indeed NOleSer, which naturally occurs in bone, increased osteoblast proliferation and reduced osteoclast survival by modulating Erk1/2 phosphorylation in vitro as well as affected bone volume density in vivo . HoweverDifferent technologies, such as proteomics, lipidomics, bioinformatics as well as systems biology approaches let to the identification of many NAAAs in the mammalian body. In this article, we have attempted to provide an extensive and comprehensive summary of 1) biosynthesis, mechanism of action and inactivation of NAAAs and 2) the role of NAGlys and NASers in biological processes. For the experimental data described here, it is evident that considerable progress has been made in this research field, although we are still far from fully appreciating the physiological importance of NAAAs and, more importantly, their involvement in pathological conditions. It is crucial to be established, for example, how and following which stimuli they might be produced or whether their endogenous levels might be modulated by age, environmental factors, epigenetic changes as well as nutrition. Indeed, since both fatty acids and amino acids are essential diet elements, it is realistic to hypothesize that NAAA tissue levels might be modulated by food. Again, NAAAs, which share with endocannabinoids both inactivating enzymes and molecular targets, have been considered “endocannabinoidome” mediators , but fur


On page 277, the sixth sentence of the first paragraph should have read “Among patients with ARI who were tested, EV-D68 was detected in two patients (0.08%) patients in 2017 and 358 (13.9%) in 2018.”On page 278, in the second section of the summary box, the first sentence should have read “Based on active, prospective surveillance of ARI through the New Vaccine Surveillance Network, EV-D68 was detected in two (0.08% of patients tested in 2017 and 13.9% in 2018.”On page 280, the first sentence of the last paragraph should have read “Through recently established active, prospective, ARI surveillance in NVSN, EV-D68 was detected in


Azoarcus sp. strain DN11, a denitrifying bacterium capable of anaerobic benzene degradation.Here, we present the complete genome sequence of  Azoarcus sp. strain DN11, a denitrifying bacterium capable of anaerobic benzene degradation. The DN11 genome is 4,956,835 bp long with a G+C content of 66.3%. Genome analysis suggested the possibility that DN11 utilizes three proposed pathways for anaerobic benzene degradation, namely, methylation, hydroxylation, and carboxylation pathways.Here, we present the complete genome sequence of  Azoarcus sp. strain DN11 (NBRC 108892) is a denitrifying, facultative anaerobic bacterium isolated from gasoline-contaminated groundwater in Kumamoto, Japan  was done manually with AceFileViewer 1.5 and GenoFinisher 2.1 (default settings) (DN11 was grown in diluted casitone glycerol yeast autolysate (dCGY) medium , and itsaffolds 6 in totalettings)  and Micrettings) , and annettings)  to manuabssABCD gene clusters involved in the anaerobic conversion of toluene to benzylsuccinate, with amino acid identities ranging from 49% to 71% compared with another anaerobic benzene-degrading bacterium, Geobacter metallireducens , with a G+C content of 66.3%. Also, 4,593 coding DNA sequences (CDSs), 4 copies of the rRNA operon, and 57 tRNA genes were identified. A BLAST search of the DN11 genome revealed two reducens . The preAzoarcus sp. strain DN11 has been deposited at DDBJ/ENA/GenBank under the accession number CP021731 . Raw sequencing data have been deposited in the SRA under the accession number PRJNA388763.The complete genome sequence of


To investigate the effects of low-dose trace mineral proteinates on reproductive performance, mineral status, milk immunoglobulin contents and fecal mineral excretion of sows.Eighty crossbred sows (Landrace×Large White) were randomly allocated to two groups in a 135-day trail, from breeding through 21 d postpartum. The two treatments were inorganic trace minerals (ITM): a basal diet+inorganic iron (Fe), copper (Cu), manganese (Mn), and zinc (Zn) at 90, 15, 25 and 90 mg/kg, respectively and organic trace minerals (OTM): a basal diet+proteinates of Fe, Cu, Mn, and Zn at 72, 12, 20, and 72 mg/kg, respectively.Compared with ITM, OTM significantly increased (p<0.05) the number of piglets with birthweight >1 kg, the litter weaning weight, and milk Fe, Cu contents. No significant differences (p>0.05) were observed on sow hair mineral contents or immunoglobulin M (IgM), IgG, and IgA contents in colostrum and milk. In comparsion to ITM, OTM decreased fecal Fe, Cu, Mn, and Zn contents of gestating sows (p<0.01) and Fe, Mn, and Zn in lactating sows (p<0.01).These results indicate that low-dose mineral proteinates can increase the number of piglets with birthweight >1 kg, the litter weaning weight and certain milk mineral concentrations while reducing fecal mineral excretion. Under this condition, only a small amount of dietary iron (Fe), zinc (Zn), copper (Cu), and manganese (Mn) will be utilized with 70% to 95% excreted into the environment through manure, which may lead to bioaccumulation in the soil and potentially threaten water sources due to runoff [Fetal growth and development rely entirely on the maternal supply of nutrients, including trace mineral elements . Mineralo runoff ,7. Organo runoff ,9.Dietary supplementation with organic microminerals has been reported to enhance sow reproductive performance , improveThe experimental use of animals and procedures for their management and collection of tissues was performed in accordance with the Chinese Guidelines for Animal Welfare and approved by the Institutional Animal Care and Use Committee of Zhejiang University .4·7H2O, Cu2(OH)2Cl, MnSO4·H2O, ZnSO4·7H2O .A total of 80 crossbred sows (Landrace×Large White) with similar body weight, parity and breeding date were randomly allocated to 2 treatments with 40 replicates each. Experimental diets were fed for 135 d, from breeding through 21 d postpartum. The two treatments were as follows: inorganic trace minerals (ITM): a basal diet+inorganic Fe, Cu, Mn, and Zn at levels of 90, 15, 25, and 90 mg/kg, respectively in gestation and lactation periods and organic trace minerals (OTM): a basal diet+organic Fe, Cu, Mn, and Zn at levels of 72, 12, 20, and 72 mg/kg , respectively in gestation and lactation periods. The organic Fe, Cu, Mn, and Zn were metal proteinates, sequestered with enzymatically hydrolyzed soybean protein , the analyzed values of which were 16.7%, 10.2%, 15.8%, and 16.2%, respectively. The inorganic forms of these minerals were provided as FeSODiets of sows were formulated to meet or exceed NRC  nutrient2) in an enclosed facility with temperatures averaging 21°C±4°C and fed 3.0 kg feed daily. At approximately 107 d post-coitum sows were placed in individual farrowing crates  and fed with the lactation treatment diet until weaning at 21 d postpartum. Sows were not fed on the day of farrowing, then the feed amount was raised by 1.0 kg daily until ad libitum feeding was reached. Piglets and sows had free access to water via a stainless-steel nipple waterer. Within 3 d postpartum, all piglets were processed , injected with 200 mg of Fe (iron dextran), and the litter size was equalized between sows within treatments.During pregnancy sows were housed in individual gestation crates  and pre-weaning livability of piglets. On farrowing and weaning day, the backfat thickness of sows at 6 cm perpendicular to the dorsal midline of the last rib was measured using Lean meter . Feed intake of sows during lactation was recorded daily.Diets, feces and hair were analyzed for Fe, Cu, Mn, and Zn concentrations via an inductively coupled plasma optical emission spectrometer (ICP-OES)  after wet ashing with 3 mL nitric acid and 1 mL hydrogen peroxide in a microwave digester . A specThe concentrations of immunoglobulin G (IgG), IgA, and IgM were determined using enzyme-linked immunosorbent assay kits .Statistics analysis was performed with SPSS 22.0 Software . The data were analyzed by T-test and the results are presented as mean and standard error of mean. Significance was declared at p<0.05, and p<0.10 was considered to represent tendencies between treatments.OTM increaed milk Fe and Cu contents (p<0.01) and tended to increase colostrum Zn content (p = 0.09) compared with ITM .As shown in During the gestation and lactation periods, sows have an increased demand for trace elements such as Fe, Cu, Mn, and Zn to support their growth and production needs. Fetal growth and development rely entirely on the maternal nutrient supply, including trace minerals, deficiency of which will result in poor growth and health of the conceptus ,2. It haSerum and tissues are commonly used to reflect body mineral status ,20. HoweNewborn piglets with immature immune systems rely entirely on colostrum immunoglobulins, mainly IgG to provide passive immunity. As reported by Kielland et al , increasMinerals in excrement are mainly derived from unabsorbed trace minerals in the diet and those excessively absorbed and excreted by the bile under the action of homeostatic balance regulation . Thus, tIn summary, total replacement of inorganic trace element compounds  by mineral proteinates at approximately 80% increased the number of piglets with birthweight >1 kg, litter weaning weight, and milk mineral levels and reduced trace mineral excretion of commercial gestating and lactating sows, while having no significant influences on immunoglobulins IgG, IgA, and IgM levels in colostrum and milk of the sows.


Vibrio, were determined in moderate density/semi-intensive (40 post-larvae m-3) and high density/intensive shrimp ponds (90 post-larvae m-3), over the shrimp cultivation time. Free-living and particle-attached bacterial communities were characterized by amplicon sequencing of the 16S rRNA gene. Suspended particulate matter (SPM), salinity, chlorophyll a, pH, and dissolved oxygen differed significantly between semi-intensive and intensive systems. These variations contrasted with the equal abundance of cultivable heterotrophic bacteria and inorganic nutrient concentrations. Bacterial communities were dominated by Gammaproteobacteria, Alphaproteobacteria, Flavobacteriia, Bacilli, and Actinobacteria. Halomonas and Psychrobacter were the most dominant genera in the particle-attached fractions, while Salegentibacter, Sulfitobacter, and Halomonas were found in the free-living fractions of both systems. Redundancy analysis indicated that among the observed environmental parameters, salinity was best suited to explain patterns in the composition of both free-living and particle-attached bacterial communities , although a large fraction remained unexplained. Based on 16S rRNA gene sequences, aggregated particles from intensive ponds loaded a higher proportion of Vibrio than particles from semi-intensive ponds. In individual ponds, sequence proportions of Vibrio and Halomonas displayed an inverse relationship that coincided with changes in pH. Our observations suggest that high pH-values may suppress Vibrio populations and eventually pathogenic Vibrio. Our study showed that high-density shrimp ponds had a higher prevalence of Vibrio, increased amounts of SPM, and higher phytoplankton abundances. To avoid rearing failure, these parameters have to be managed carefully, for example by providing adequate feed, maintaining pH level, and removing organic matter deposits regularly.In shrimp aquaculture, farming systems are carefully managed to avoid rearing failure due to stress, disease, or mass mortality, and to achieve optimum shrimp production. However, little is known about how shrimp farming systems affect biogeochemical parameters and bacterial communities in rearing water, whether high stocking densities (intensive system) will increase the abundance of pathogenic bacteria. In this study, we characterized bacterial communities in shrimp ponds with different population densities. Water quality, such as physical parameters, inorganic nutrient concentrations, and cultivable heterotrophic bacterial abundances, including potential pathogenic  Litopenaeus vannamei  and particle-associated (PA) bacterial communities from the same water sample can be distinct . As orgaAlthough the causative agents for bacterial diseases in shrimps have been identified , preventV. parahaemolyticus in the FL and the PA/aggregates fraction. We hypothesize that (i) different shrimp farming systems affect pond water quality, including suspended particulate matter (SPM) loading, bacterial abundance and community composition, and (ii) SPM loads more bacterial cells, including pathogenic bacteria.The current study aims to comprehend the effect of shrimp farming systems of different intensity on water quality parameters and BCC, to elucidate factors affecting bacterial communities, and to evaluate the presence of pathogenic bacteria, including pathogenic 2, water depth 1.3–1.5 m) of semi-intensive  and intensive  systems, during a cycle of shrimp rearing at day 10, 20, 30, 40, 50, 60, and 70 (September to November 2016). Shrimp ponds were located in Rembang Regency, Central Java, Indonesia . Two liters of water were taken from 5 points of each pond at 1 m depth, and then mixed. Two liters of the mixed water were prepared for bacterial abundance and community analysis; 3 liters for SPM and inorganic nutrient analysis. Samples were stored in a cold and dark container, and transported to the laboratory at Diponegoro University, Semarang, Indonesia, for immediate analysis. Remaining water was used for physical parameter measurement. Total harvest of each pond was recorded at the end of shrimp rearing.Water samples were collected between 9–10 a.m. from no water-exchange and plastic lining ponds .Salinity, temperature, pH, chlorophyll a, DO, and turbidity were measured -1 HgCl2 solution for inorganic nutrient analysis . The samples were stored at -20°C until analysis. Inorganic nutrient measurements were done in triplicates at the Laboratory of Chemistry, Research Center for Oceanography (LIPI), Jakarta, Indonesia, according to the colorimetry method by Of each water sample, 0.3 L were filtered through a 0.45 μm syringe filter and the filtrate was poisoned with 1.2 mL of a 0.35 g LSuspended particulate matter was measured as dry mass on pre-combusted GF/F filters  in triplicates after filtration of a known volume of water sample (0.1–0.5 L). Weight of the filters was determined using a precision balance  after drying the filters for 24 h at 40°C.-2–10-5) were plated onto Marine Agar 2216  and incubated at 28°C (room temperature) for 48 h. While potentially pathogenic Vibrio were isolated by inoculating 100 μL of undiluted to 10-4 diluted water sample onto selective Thiosulfate Citrate Bile Salts Sucrose(TCBS) medium , followed by incubation at 35°C for 24 h.To obtain cultivable heterotrophic bacterial number, 100 μL of water samples  to determine bacterial cells in the particle-attached (PA) and the free-living (FL) fractions, respectively. For the FL fractions at day 30, 40, and 70, only 5 ml filtrates were filtered. Filters were air dried and stored at -20°C for further staining. A 4′,6-diamidino-2-phenylindole (DAPI) staining was performed according to -1 of DAPI solution for 5 min, then washed in 80% ethanol and rinsed with sterile distillated water. Stained filters were air dried in the dark for 30 min, and then mounted with 10 μL of mounting solution consisting of 3:1 Citifluor AF mounting medium  and Vectashield . Bacterial cells, as well as size and number of aggregates were observed under a fluorescence microscope Axio Imager.D2  at 1000× magnification. Bacterial cell abundance in FL filters was calculated from 30 photos per filter, using the free software ImageJ. Bacterial cells in PA filters were manually counted from 10 aggregates per filter of similar size. Sizes of aggregates were determined using a net micrometer grid . The cell average per filter was then divided by volume of filtered samples multiplied by dilution and factor of effective filter area  and number of aggregates , for the FL and the PA fraction, respectively.Samples for total bacterial cell counts were prepared by fixing 50 mL water with 4% v/v paraformaldehyde and stored at 4°C for 24 h. The dilution factors for the samples were as follows: undiluted for day 10 samples, 5 × 10Vibrio) and bacterial disease evidence (white feces disease), which occurred at previous rearing cycles between 50 and 65 days of rearing .Five hundred milliliters of water samples were filtered subsequently through 3.0 and 0.2 μm polycarbonate filters  for PA and FL bacterial fractions, respectively. Genomic DNA was extracted according to trimmomatic v.033 (swarm v2.1.1 (DNA sequences of the V3–V4 hypervariable region of the 16S rRNA gene were obtained from amplicon sequencing with the primer set S-D-Bact-0314-b-S-17 (5′-CCTACGGGNGGCWGCAG-3′)/S-D-Bact-0785-a-A-21  with the project accession number a GFBio, , while btoxR), thermolabile haemolysin (tlh), thermostable direct haemolysin (tdh), Photorhabdus insect-related (pirA and pirB) was performed in a Mastercycler®  using the set of primers described in Supplementary Table 2. As these genes are common genes in several representative of the genus Vibrio , we designed specific primer pairs which only amplify DNA sequences belonging to V. parahaemolyticus as this bacterium causes most of bacterial diseases in shrimp . The PCR conditions were as follows: a reaction mixture consisted of 2 μL (20 ng μL-1) of template, 2 μL of 10× PCR buffer B containing 15 mM MgCl2, 0.5 μL of 25 mM MgCl2, 0.5 μL of 0.2 mM dNTPs, 1 μL of 0.1 mM forward and reverse primer, 0.1 μL of 5U μL-1 Taq polymerase  and 12.9 μL sterile distillated water. The amplification conditions were as follows: pre-denaturation at 95°C for 3 min, followed by 40 amplification cycles consisting of denaturation at 95°C for 30 s, annealing at 60°C for 15 s, and extension at 72°C for 30 s, and a final elongation at 72°C for 5 min. Vibrio parahaemolyticus DSM 11058  was used as positive control for those toxin genes, while Vibrio vulnificus DSM 10143  served as negative control.Detection of toxin genes, i.e., transcriptional regulator (n shrimp . Ten samTukey’s post hoc tests were applied in cases where there were significant differences among sampling days and/or an interaction between sampling day and shrimp farming system. Forward model selection based on the Akaike information criterion (AIC), considering collinearity of the variables and variance inflation values, was used to determine environmental parameters, which best explained observed counts of cultivable heterotrophic bacteria and potential pathogenic Vibrio. Total shrimp harvest was tested with one-way ANOVA and total bacterial cell numbers from DAPI counting of FL and PA bacterial communities were analyzed using MANOVA. As first-level post hoc test, the effect of significant predictor variable (here: sampling day) in MANOVA of FL and PA bacterial numbers was then tested with individual GLMMs per fraction. Furthermore, pairwise comparisons between sampling days were conducted as second-level post hoc test. Repeated measures correlation between FL and PA bacterial cell numbers was estimated using rmcorr R package , and among days, as well as the interaction between culturing system and sampling day, general linear mixed models (GLMM) were performed with shrimp pond as random factor. Data were log-transformed to achieve normal distribution prior to statistical testing.  package .metaMDS of the vegan R package  was conducted to examine the relationship among environmental parameters, as well as cultivable bacterial abundances, and to characterize shrimp ponds of the different farming systems over time. Bray–Curtis dissimilarity coefficients were calculated to investigate variation of OTU compositions in FL and PA communities among ponds, as well as within and between the systems. Patterns of BCC in both fractions was visualized by non-metric multidimensional scaling (NMDS) based on Bray-Curtis dissimilarities using the function  package . Analysialdex.clr  was performed to explore relationships between bacterial communities and environmental variables in FL and PA fractions, for OTUs occurring in at least 10 samples, and with a sequence proportion of at least 1% in one sample. Data sets were separated by size fractions, and then centered log-ratio-transformed using ldex.clr  before bSalegentibacter, Psychrobacter, Halomonas, and Vibrio, using the fraction of read abundance times cells method (FRAxC) proposed by Vibrio abundance and selected environmental parameters .Population turnover, which occurred in the FL and PA fractions, was estimated for certain interesting OTUs of the genera All statistical analyses, as well as figure visualizations were performed in R . The intensive system showed a twofold higher production than semi-intensive system, which were 3,950 ± 284 kg and 1,990 ± 151 kg, for intensive and semi-intensive final harvest . There was a high variability among the ponds within each system for turbidity, chlorophyll a, pH, salinity, DO, and inorganic nutrients during rearing time, which increased over time (Table 1). Physical parameters such as salinity, pH, DO, chlorophyll a, and SPM were significantly different between the two systems . Among sampling days, we detected differences in temperature, salinity, pH, turbidity, chlorophyll a, SPM, cultivable heterotrophic bacteria and potential pathogenic Vibrio . The interaction between day and farming system was also significant for temperature, salinity, and turbidity. However, there were no significant differences between semi-intensive and intensive systems for dissolved inorganic nutrients, temperature, and turbidity .Total shrimp harvest differed significantly between semi-intensive and intensive systems .In both systems, pH decreased rapidly after day 40, but when limestones were added into the ponds, it increased from 7.92 ± 0.13 to 8.38 ± 0.53 and 7.63 ± 0.46 to 8.11 ± 0.13, in semi-intensive and in intensive system, respectively. Salinity decreased from 35.37 ± 0.15 to 32.44 ± 3.26 PSU and 38.43 ± 0.78 to 33.57 ± 0.45 PSU, in semi-intensive and in intensive system, respectively, due to freshwater input. Overall, the intensive system showed significantly higher salinities, SPM, and chlorophyll a concentration than the semi-intensive system, as well as higher variability of inorganic nutrients (Vibrio (TPPV) in semi-intensive and intensive systems increased with rearing time, and peaked at day 60, at concentrations of 3.4 × 107 CFU mL-1 of THB and 1.4 × 104 CFU mL-1 of TPPV, and 2.6 × 107 CFU mL-1 of THB and 2.65 × 105 CFU mL-1 of TPPV, respectively (Table 1). Forward model selection showed that SPM, salinity, turbidity, temperature, and phosphate were major determinants for THB, while the determinants for TPPV were SPM, salinity, turbidity, pH, temperature, nitrite, and silicate.The abundances of cultivable heterotrophic bacteria (THB) and potential pathogenic Figure 1). According to water parameters and cultivable bacterial abundances, there was a clear separation by shrimp farming systems based on rearing time. At the beginning of rearing (days 10 and 20), ponds of intensive and semi-intensive systems were clustered with high values of the first principal component, which was driven mainly by high salinity. Afterward, they were separated by the second principal component with ponds of the intensive system characterized by high concentrations of chlorophyll a. The abundances of THB and TPPV highly correlated to SPM .Principal component analysis for environmental parameters and cultivable bacterial abundances was able to retrieve 42.61% of the variation among ponds on the first two principal components  and at day 40 (494 ± 27 aggregates mL-1), containing 86 ± 3 and 72 ± 6 bacterial cells per individual aggregate for semi-intensive and intensive pond waters, respectively . Free-living (FL) bacterial cells of both systems increased and peaked at day 60 in concentration 3.8 × 107 cells mL-1 and 5.0 × 107 cells mL-1, for semi-intensive and intensive systems, respectively. Total particle-attached (PA) bacterial cell numbers were steady after day 40, with 6.8 × 105 cells mL-1 and 6.4 × 105 cells mL-1, for semi-intensive and intensive systems, respectively (Table 2). The FL cell numbers were positively correlated to the PA cell numbers  and differed only among days (Supplementary Tables 6).Aggregates containing bacterial cells were found in different sizes. At day 10, small aggregates appeared which were formed by bacterial cells and their exudates. After 40 days, aggregates were composed of plankton, bacterial cells and bacterial exudates, causing the increase of aggregate sizes in both systems, as well as bacterial cell numbers. Aggregates of sizes between 937.5 and 1,406.5 μmSupplementary Figure 2).After removal of low-quality reads, 8,994–78,615 sequences, with on average 34,471 sequences per sample, were obtained from 59 samples. One sample was removed due to low sequence counts (<500 sequences). A total of 77,433 OTUs was obtained, ranging from 426 to 2465 OTUs, with an average of 1,312 OTUs per sample . Among them, the genera Alteromonas, Erythrobacteraceae, Exiguobacterium, Halomonas, Vibrio, Pseudoalteromonas, Psychrobacter, Salegentibacter, and Sulfitobacter were present in every sample. Cyanobacteria, such as Synechococcus and Cobetia, were frequently present in the semi-intensive system. The highest sequence proportion in the FL fraction of both systems belonged to Salegentibacter, Sulfitobacter, and Halomonas, while in the PA fraction Psychrobacter, Vibrio, and Halomonas were dominant, where the latter comprised up to 80% of the sequences in samples from the semi-intensive system after 40 and 50 days . In the SILVA reference database (SILVA 128 version), Halomonas OTU1 has a sequence similarity of 98 and 100% to H. aquamarina and H. meridiana, respectively.Most abundant bacterial OTUs in both systems belonged to the classes Acidimicrobiia, Actinobacteria, Alphaproteobacteria, Bacilli, Cyanobacteria, Flavobacteriia, and Gammaproteobacteria (Table 3). In addition, there was high variability in BCC within the same fraction among replicate ponds, which lead to a wide range in Bray-Curtis dissimilarity coefficients  between intensive and semi-intensive systems (Table 4).Free-living and particle-associated bacterial communities from the same water sample were very different from each other as indicated by Bray–Curtis dissimilarity coefficients . Analysis of similarity (ANOSIM) confirmed that there was no detectable pattern in FL or PA the BCC between system and day (Supplementary Table 7).NMDS showed a highly heterogeneous composition of the bacterial communities in the FL and the PA fraction for both systems . Among the observed environmental parameters, salinity was best suited to explain patterns in the composition of both FL and PA bacterial communities (R2 > 10%). Furthermore, chlorophyll a and nitrate had a minor effect on BCC in the FL fractions (Table 5).Redundancy analysis revealed that environmental variables explained 20.53 and 36.77% of the BCC in the FL and the PA fractions, respectively  of the dominant Vibrio OTU differed strikingly from that of the other dominant OTUs, such as Halomonas, Psychrobacter, and Salegentibacter, suggesting an inverse relationship. When FRAxCs of Vibrio were overly high, the proportions of the other genera were low. In the PA fraction, FRAxCs of Vibrio were negatively correlated to FRAxCs Halomonas .All tested samples were negative for Vibrio in both fractions were positively correlated to SPM, temperature, ammonium, NP ratio, and TPPV, but they were negatively correlated to pH and salinity. In addition, Vibrio was negatively correlated to inorganic nitrite and phosphate in the FL fraction, although in the PA fraction the opposite trend was observed. In general, all correlation coefficients did not suggest strong correlation with values between -0.36 and 0.38 (Supplementary Table 8).FRAxCs of No water discharge shrimp aquaculture resulted in an accumulation of organic matter, through feed pellets, shrimp feces and other organic materials. Previous studies reported that degradation of organic matter, leaching of feed pellets, and release of ammonium from feces increase inorganic nutrients in the water column . These nIn this study, shrimp pond water parameters and respective BCC in intensive and semi-intensive systems were compared. Contrary to our expectations, higher shrimp density in intensive farming systems did not significantly increase inorganic nutrients in the water column. We suggest that excessive nutrients were rapidly taken up by bacteria and phytoplankton as their abundance increased more strongly in the intensive system. This was also reflected in high SPM values in the intensive system due to the aggregation of phytoplankton cells. Phytoplankton can take up total ammonia nitrogen (TAN), while heterotrophic bacteria perform nitrification and nitrogen assimilation . In pondWe observed fluctuation of particle (aggregate or flocs) number over rearing time. We supposed that lower pellet input, sinking or consumption of flocs might cause the fluctuation of particle numbers. Water movement and exudate secreted either by bacteria or plankton lead to particle agglomeration , generat43-, C/N ratio (2S) or sulfite which may explain the continually presence of Sulfitobacter in FL fraction.Environmental factors shape the structure and function of microbial communities . Previou/N ratio , total p/N ratio , and fee/N ratio . Of the /N ratio . We obseAlteromonas, Erythrobacter, Halomonas, Pseudoalteromonas, Salegentibacter, Sulfitobacter, and Psychrobacter. Halomonas and Psychrobacter, the salt-tolerant heterotrophic nitrifying bacteria , which contained Bacillus sp., Pseudomonas sp, Nitrosomonas sp., Aerobacter sp., Nitrobacter sp., and Nitrosococcus sp. did not affect BCC in the FL and PA fractions of both systems, indicating that nitrification processes were generated by other microbes. We propose that in our study the dominance of particular heterotrophic halophilic bacteria may result in higher uptake of inorganic nutrient such as ammonium and nitrite . We propose that pH was a disturbing factor for heterotrophic halophilic bacteria in our shrimp systems and lead to the change of BCC only in the intensive system. This is supported by Bacterial communities in intensive and semi-intensive systems were dominated by heterotrophic halophilic bacterial genera bacteria , can oxibacteria . Sulfitoc matter . Other b molting . In our bacteria . We assubacteria . This is nitrite . Therefo nitrite , in whicVibrio, a potential opportunistic pathogen for L. vannamei  of V. parahaemolyticus , as indicated by the lower proportion of Sulfitobacter. We suggest that giving adequate feed, discarding sludge, maintaining pH, and salinity, might avoid abrupt water quality change, eliminate large anaerobic areas at the pond bottom, and may minimize proliferation of potential pathogens, especially Vibrio. Some aspects of shrimp pond management related studies are given in vannamei , has beevannamei . Our hypes occur . Nevertholyticus , as wellor AHPND  were notor AHPND , as propvannamei . Howevers Vibrio . ConsideIn view of BCC in FL and PA fraction over rearing period and the absence of virulence genes, we propose to apply “bioflocs” in shrimp aquaculture. This can be generated by adding carbohydrates such as molasses, rice bran or tapioca. Bioflocs might become an alternative food source for shrimps and be able to maintain ammonia and nitrite concentration in shrimp pond . MoreoveVibrio growth. Despite a wide variability of BCCs in intensive and semi-intensive systems, the abundance of Vibrio was higher in the intensive system, which may therefore be more vulnerable to disease outbreaks. Monitoring BCC, especially the PA fraction’s, and larger particulates such as aggregates in shrimp pond waters may potentially prevent disease outbreaks such as Vibriosis, white feces disease, white-tale disease, and AHPND.Different stocking densities influenced water quality parameters, especially SPM, DO, chlorophyll a, and pH. High salinity shaped the BCC in the PA and FL fraction, favoring heterotrophic halophilic bacteria which facilitate an optimum uptake of inorganic nutrients and prevent increase of This study did not sacrifice any organism, nor introduce viable pathogenic bacteria to the environment. All sampling procedures were already informed to and have been agreed upon by shrimp pond owners.in situ measurement with the logistic support of AT and AK. YA and CH completed the statistical analysis. YA prepared the manuscript with input from all co-authors.YA, JH, and AG designed the project. YA collected the samples and conducted the The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Moreover, p53 induces metabolic change by directly regulating several metabolic enzymes. The collective data indicate the importance of oncogenic metabolism in the regulation of EMT, cell invasion and metastasis, and adoption of the CSC phenotype, which all contribute to malignant transformation and tumor development. In this review, we highlight the oncogenic metabolism as a key regulator of EMT and CSC, which is related with tumor progression involving metastasis and chemoresistance. Targeting oncometabolism might be a promising strategy for the development of effective anticancer therapy.Metastasis is a major obstacle to the efficient and successful treatment of cancer. Initiation of metastasis requires epithelial-mesenchymal transition (EMT) that is regulated by several transcription factors, including Snail and ZEB1/2. EMT is closely linked to the acquisition of cancer stem cell (CSC) properties and chemoresistance, which contribute to tumor malignancy. Tumor suppressor p53 inhibits EMT and metastasis by negatively regulating several EMT-inducing transcription factors and regulatory molecules; thus, its inhibition is crucial in EMT, invasion, metastasis, and stemness. Metabolic alterations are another hallmark of cancer. Most cancer cells are more dependent on glycolysis than on mitochondrial oxidative phosphorylation for their energy production, even in the presence of oxygen. Cancer cells enhance other oncogenic metabolic pathways, such as glutamine metabolism, pentose phosphate pathway, and the synthesis of fatty acids and cholesterol. Metabolic reprogramming in cancer is regulated by the activation of oncogenes or loss of tumor suppressors that contribute to tumor progression. Oncogenic metabolism has been recently linked closely with the induction of EMT or CSC phenotypes by the induction of several metabolic enzyme genes. In addition, several transcription factors and molecules involved in EMT or CSCs, including Snail, Dlx-2, HIF-1 Cancer cells can acquire multiple biological capabilities to overcome their multistage resistance during carcinogenesis. Hanahan and Weinberg defined ten hallmarks of cancer that alter cell physiology to enhance malignant transformation: 1) sustained proliferation, 2) evasion of growth suppression, (3) cell death resistance, (4) replicative immortality, (5) evasion of immune destruction, (6) tumor-promoting inflammation, (7) activation of invasion and metastasis, (8) induction of angiogenesis, (9) genome instability, and (10) alteration of metabolism [ sustaine evasion One of the most important differences between benign and malignant tumors is metastatic potential –3. A malMetastasis is regulated by intrinsic and extrinsic cancer cell mechanisms. Extrinsic mechanisms, such as the metabolic, stromal, and immunological microenvironments, can control metastasis –8. Accorα), and distal-less homeobox 2 (Dlx-2), and several regulatory molecules contribute to EMT, invasion, and metastasis. Epithelial cells undergoing EMT exhibit phenotypic changes, including the loss of epithelial cell polarity and the gain of mesenchymal proteins [A typical intrinsic mechanism of cancer cells is the epithelial-mesenchymal transition (EMT). The EMT plays an essential role in the initial step of metastasis. Many transcription factors, including Snail, Slug, zinc finger E-box-binding homeobox (ZEB)1/2, Twist-related protein (Twist) 1/2, E12/E47, hypoxia-inducible factor-1-alpha , and fibroblast-specific protein 1. The foregoing molecules are usually used as EMT markers [EMT involves the loss of epithelial homeostasis with the acquisition of migratory mesenchymal capabilities. The characteristics of EMT include the downregulation of epithelial markers, such as E-cadherin, desmoplakin, mucin-1, cytokeratin-18, occludins, claudins, and zonula occludens-1 (ZO-1), and the acquisition of mesenchymal markers, such as N-cadherin, vimentin, fibronectin, vitronectin,  markers , 16–23.Both EMT and the reverse process, mesenchymal-epithelial transition (MET), occur in the development of embryonic cells and cancerous cells. MET involves profound phenotypic changes, including the loss of migratory freedom with the expression of junction complexes. MET is essential for clonal outgrowth at metastatic sites. EMT and MET both are crucial in the invasive and metastatic properties of cancer cells , 20–22. Transcription factors capable of inducing EMT play a crucial role in cancer progression, including tumor growth and drug resistance in cancer cells, as well as in promoting invasion and metastasis , 22, 23.δEF1, ZEB2/SIP1, Twist1/2, and E12/E47, which regulate the expression of proteins involved in cell polarity, cell-cell contacts, cytoskeletal structural maintenance, and extracellular matrix (ECM) degradation. A hallmark of EMT is a loss of E-cadherin in various cancers. These EMT-inducing transcription factors repress E-cadherin transcription by binding to the E-box elements of the E-cadherin gene promoter. Especially, Snail is involved in the initial cell-migratory phenotype and is regarded as an early marker of EMT [β-catenin, which plays a significant role in adherens junctions. The E-cadherin/β-catenin complex contributes to the maintenance of epithelial integrity. Loss of E-cadherin promotes β-catenin release and subsequent activation. When β-catenin translocates to the nucleus, it can directly transcriptionally activate EMT-associated target genes, including Slug, thereby facilitating EMT [EMT-inducing transcription factors include Snail/Slug, ZEB1/r of EMT , 24–27. ting EMT .ZEB1 and 2 repress the expression of several cellular junction proteins, such as claudins and ZO-1, thereby promoting invasion and metastasis. Twist directly and indirectly affects other EMT-linked factors and then induces EMT. For example, Twist1 binds to the E-cadherin promoter to repress its expression but also induces Snail to inhibit E-cadherin –27, 29.The expressions of Snail and ZEB1/ZEB2/Twist are mutually dependent, although they can occur in different directions depending on the cell system. In many cases, Snail increases the levels of ZEB1 and ZEB2 proteins through both transcriptional and posttranscriptional mechanisms. In addition, Snail can regulate Twist1 protein and mRNA. Snail may be required for the initiation of EMT with subsequent consolidation by Twist and ZEB factors –32.α and Dlx-2, contribute to EMT. HIF-1α is a transcription factor that responds to low oxygen concentrations (hypoxia). HIF-1α has been strongly correlated with cell survival, proliferation, motility, EMT, metastasis, metabolism, pH regulation, ECM function, inflammatory cell recruitment, angiogenesis, chemotherapeutic resistance, and poor prognosis by regulating the expression of its target genes in several types of tumors [α suppresses E-cadherin expression by activating Snail, which promotes EMT [α also binds to β-catenin by competing with transcription factor 4 (TCF4), thereby inducing EMT in colorectal cancer [α promotes EMT and cancer metastasis by binding to the promoter of ZEB1 in colorectal cancer [Several other transcription factors, including HIF-1f tumors –36. HIF-otes EMT . HIF-1α l cancer . In addiβ-) and Wnt-induced EMT by Snail activation [β tumor suppressive activity in early stages to tumor promoting activity in later stages [Dlx-2 is a homeobox transcription factor that is crucial for embryonic development, morphogenesis, and tissue homeostasis , 38. Rectivation , 39, 40,tivation , 39–52. tivation , 50, 52.r stages . Dlx1/2 r stages . In addir stages , 41, 48.r stages .Recently, it was also reported that Dlx-2 negatively regulates the growth, migration, and invasion of cells. Dlx-2 is regulated by p53-R273H, which exhibits a gain of function that promotes cell mobility and tumor metastasis. p53-R273H induces the downregulation of Dlx-2 and the upregulation of neuropilin 2 (NRP2) , which aβ, Wnt, epidermal growth factor (EGF), Notch, and Hedgehog and their associated signaling proteins, which include nuclear-factor kappa B (NF-κB), extracellular signal-regulated kinase (ERK), and phosphatidylinositol 3-kinase (PI3K)/Akt. These signaling pathways are linked to tumorigenesis and tumor progression in response to stresses that include hypoxia, oncogenic or metabolic stress, inflammation, and physical constraints. These signals activate EMT-inducing transcription factors, including Snail, Slug, ZEB1/2, and Twist1/2 [EMT is controlled by a network of growth factors that include TGF-Twist1/2 , 57–60.β signaling activates Smad2 and 3, which form a complex with Smad4 and translocate to the nucleus. The complex induces target genes by the transcription of EMT-inducing transcription factors [β signaling also induces the activation of GTPases, PI3K, and mitogen-activated protein kinase (MAPK) pathways in the Smad-independent pathway, thereby inducing EMT [TGF- factors , 58, 60.cing EMT .β-catenin and Notch signaling pathways are important in the induction of EMT. These signaling pathways have been implicated in the activation of EMT-inducing transcription factors [Wnt/ factors , 57–59.  factors –66. ThusEMT programs are aberrantly activated in triple-negative breast cancer (TNBC) –70. BreaThe tumor suppressor p53 is activated by various cellular stresses, including DNA damage, ribosomal stress, hypoxia, nutrient deprivation, and oncogene activation. Activated p53 exerts the tumor suppressive function through transcriptional regulation of target genes that regulate numerous cellular processes, such as cell cycle arrest, DNA repair, senescence, apoptosis, autophagy, antioxidant defense, mRNA translation, and feedback mechanisms –78.p53 is one of the most potential regulators of metastasis. p53 binds to the promoters of a variety of genes associated with cell motility, adhesion, and invasion, thereby regulating the transcription of genes involved in metastasis –87. p53 The functions of p53 are negatively regulated by Twist. Twist inhibits alternative reading frame tumor suppressor protein and then induces Mdm2-mediated p53 ubiquitination and degradation. Thus, Twist indirectly antagonizes p53 function to promote EMT , 88.p53 acts as an antagonist of HIFs, which contribute to resistance to therapy and metastasis and are associated with poor survival rates in cancer patients. The activation of HIF-1-dependent signaling is suppressed by p53. The interplay between the p53 family and HIFs is important in cancer progression via the regulation of angiogenesis, the tumor microenvironment, dormancy, metastasis, and recurrence .β-catenin, to inhibit EMT, invasion, and metastasis [β-catenin [In addition, p53 regulates other molecules, including p21, Bcl-2 family proteins, KAI, and tastasis –87. p53 tastasis . Furthertastasis . Cytoplatastasis . p53 acttastasis . p53 alsα, and Snail expression. Under hypoxic conditions, TP53INP1 suppresses EMT and vasculogenic mimicry, which is the formation of a new tumor vascular supply system, by regulating the ROS/GSK-3β/Snail pathway in breast cancer, which is crucial role in cancer progression and metastasis [In addition, tumor protein p53-inducible nuclear protein 1 (TP53INP1), also termed stress-induced protein, inhibits malignant tumor metastasis. In response to oxidative stress, TP53INP1 is a key regulator of p53. High expression of TP53INP1 negatively correlates with VE-cadherin, HIF-1tastasis .The foregoing findings indicate that loss of p53 function is important in the progression of carcinogenesis. Indeed, p53 is the most frequently lost or mutated molecule in human cancer. More than half of human cancers display loss of p53 function through DNA mutations and different mechanisms. In human cancer, the majority of p53 mutations are missense mutations and mutant p53 protein accumulates to very high levels. p53 mutants are also associated with poor prognosis in many human tumors , 90–92. p53 mediates tumorigenesis by regulating the expression of ncRNAs, such as miRNAs and long ncRNAs (lncRNAs). The wt p53 regulates the transcriptional expression and the biogenesis of specific miRNAs involved in cell cycle arrest, senescence, and apoptosis, as well as in the inhibition of metastasis, angiogenesis, and glycolysis , 93–95.However, many mutant p53 have gain-of-function activities that are involved in regulation of the expression and the biogenesis of different miRNAs independent of wt p53, thereby promoting tumorigenesis , 94, 95.A number of miRNAs target EMT-inducing transcription factors or EMT-activating pathways that control epithelial cell plasticity. For example, Snail and Slug are repressed by p53-dependent miR-34a/b/c. ZEB1 and ZEB2 are suppressed by the miR-200 family, including miR-200a/b/c, miR-141, and miR-429, thereby inhibiting EMT. Twist1 is negatively regulated by miR-186, which inhibits EMT , 29, 96.Some miRNAs and EMT-inducing transcription factors form the most relevant networks that contribute to maintenance of the epithelial or mesenchymal state. Recent studies demonstrated that p53 regulates EMT-inducing transcription factors and miRNA loops, and the epigenetic regulation of miRNAs, to maintain the epithelial phenotype , 96.p53 regulates the transcriptional expression of miR-34a, a key regulator of tumor suppression. p53-dependent regulation of miR-34a expression has been implicated in context-dependent feedback loops , 97–99. p53 regulates the transcriptional level of long intergenic ncRNA- (lincRNA-) p21. lincRNA-p21 represses the expression of p53 target genes . In addi2-terminal kinase group of MAPKs and inhibits EMT of TNBC cells [Several miRNAs, including miR-125b and miR-655, inhibit EMT in TNBC , 107. miBC cells . miR-655EMT has been closely linked to CSCs , 108–120CSCs comprise a small subpopulation of cancer cells. These cells have stem cell-like properties; they are able to self-renew, generate differentiated daughter cells, and give rise to heterogeneous tumor tissue. CSCs have been found in several solid tumors, including breast, brain, colon, ovary, pancreas, prostate, and melanoma –127. CSCCSCs are detected in solid and hematological tumors using markers that are specific for normal stem cells. The markers include CD133 , CD44, CD24, epithelial cell adhesion molecule , THY1, ATP-binding cassette B5, and CD200 . Given tβ1 induces stemness properties by increasing EMT markers  and CSC markers  in breast and lung cancer cells [β-catenin signaling pathways also promote the stemness characteristics of liver CSCs. Expression of transcription factors involving EMT (such as Snail) and stemness (such as Sox2 and Nanog) can be decreased by blocking the function of the Wnt/β-catenin and/or Notch [TGF-er cells , 118. Thor Notch . This inIn addition, EMT-inducing transcription factors are able to mitigate p53-dependent tumor-suppressive functions and gain of stemness-related properties, creating a protumorigenic environment , 25. A pp53 regulates several cell surface markers, including CD44 and CD133, which are associated with CSCs. Furthermore, p53 negatively regulates CD44 expression to regulate stemness. CD44 is involved in anchorage-independent growth and metastasis. p53 may contribute to growth inhibition and tumor suppression functions by directly repressing CD44 expression. Constitutive CD44 expression inhibits p53-dependent apoptosis and enhances genotoxic doxorubicin-resistant cell populations , 146. Inp53, focal adhesion kinase (FAK), and Nanog, a key embryonic stem cell (ESC) transcription factor, are interconnected in the regulation of CSCs. Nanog and FAK survival signaling pathways contribute to maintenance of CSCs. p53 upregulation blocks the Nanog and FAK survival signaling pathways, and p53 suppresses FAK and Nanog. FAK induces p53 degradation by binding Mdm2. Nanog maintains the CSC pool and blocks differentiation, cell cycle arrest, apoptosis, and cell growth by suppressing p53, thereby enhancing tumor growth. Nanog also leads to the upregulation of FAK, which in turn leads to the phosphorylation of Nanog. This cross-linked signaling plays an important role in cell motility and invasion of CSCs and contributes to tumor metastasis , 149.In response to DNA damage, activated p53 also induces ESC differentiation by suppressing Nanog , 144. InEMT is also involved in the generation of circulating tumor cells (CTCs). CTCs are cells left from the primary tumor. They are present in the bloodstream and can spread from the original tumor to distant locations. EMT and CSC phenotypes have been demonstrated in CTCs of some cancer patients. CTC subpopulations exhibit several phenotypes, such as epithelial, mesenchymal, and stem-like cell traits. Among these subpopulatons, CTCs with a mesenchymal phenotype presumably underwent EMT. In addition, CTCs with stem cell-like characteristics may be important drivers in tumor progression . CTCs wiβ-catenin/Snail signaling pathway [In addition, EMT and CSC phenotypes contribute to chemoresistance in cancer cells. Chemoresistance increases the likelihood of cancer recurrence and metastasis. Intriguingly, chemotherapy can induce the EMT and CSC phenotypes. For example, cisplatin-resistant lung cancer cells exhibit enhanced EMT and CSC properties by the Akt/ pathway , 151. A  pathway . Thus, tCancer cells exhibit phenotypic plasticity, in which the cells switch back and forth among multiple phenotypes, including epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M) phenotype(s), in response to signals. Phenotypic plasticity is associated with metabolism, immune evasion, invasion, and metastasis, thereby accelerating tumor progression –154.E/M plasticity is a canonical example of phenotypic plasticity, which contributes to metastasis and drug resistance. Interestingly, cancer cells rarely display all or none of these transitions. Rather, partial EMT, or full EMT, and its reverse, MET, are evident. A hybrid E/M phenotype can often be observed in cancer cells. This phenotype combines various epithelial and mesenchymal morphological and/or molecular features. These hydrid cells can be markedly more tumorigenic and drug-resistant as compared to cells in a strongly full epithelial or mesenchymal state –156. E/MHighly metastatic TNBC tumors often contain cells with E/M plasticity, which lead to the reversible expression of epithelial or mesenchymal protein. E/M plasticity can induce mesenchymal CSCs that are very prone to migrate. The primary tumors in TNBC patients are effectively removed by standard care chemotherapy to eliminate the more proliferative epithelial cells, which are regarded as epithelial/non-CSCs. Epithelial/non-CSCs often lack the aggressive CSC properties. On the other hand, mesenchymal CSCs can grow slowly. Thus, chemotherapy can fail for mesenchymal CSCs , 158–160Cancer cells that undergo extensive proliferation can senesce through the loss of telomeres. Cellular senescence irreversibly arrests cell proliferation and is also induced by diverse stimuli, including oxidative stress, DNA-damaging agents, and activation of oncogenes, independent of telomere length –170. TheγH2AX by recruiting the protein kinase ATM. γH2AX binds to mediator of DNA damage checkpoint 1 (MDC1) and p53 binding protein 1 (53BP1), inducing the activation of Chk2. In case of SSB, the 9-1-1 complex and TOPBP1 induce the activation of the protein kinase ATR, leading to the activation of Chk1. Subsequently, p53 is activated by ATM-Chk2 and ATR-Chk1 pathways [DNA damage activates the DNA damage response (DDR) signaling. The key components of DDR are p53, ATM, ATR, and Chk1/2. DNA damage can occur in several different forms, including large chromosomal lesions, such as double-strand breaks (DSBs), and small, local lesions such as single-strand breaks (SSBs) , 174. DSpathways , 174.Activated p53 regulates the transcription of several target genes. p53 transactivates many proapoptotic proteins including the BCL2 family  to induce apoptosis , 176. InCells that undergo transient cell cycle arrest accurately repair DNA damage before cell cycle progression , 174 Fi. HoweverIf DNA damage is not severe enough to induce genomic instability, it induces senescence as well as transient cell cycle arrest. Senescence has been shown to be a tumor suppressor pathway. In fact, senescence acts as a tumorigenesis barrier in preneoplastic lesions , 174. ReInterestingly, Snail, ZEB, and Twist confer resistance to senescence and prevent oncogene-induced senescence and replicative senescence in cancers. Snail inhibits oncogene-induced senescence by decreasing p16INK4a expression, thereby helping premalignant cells to escape the oncogene-induced senescence, which acts as a tumorigenesis barrier , 193.κB, c/EBPβ, and GATA4. The expression of cell surface–bound IL-1α is an early response of senescence. IL-1α acts in a juxtacrine manner and binds to the IL-1 receptor, thereby initiating the signal cascade that activates the transcription factors NF-κB and C/EBPβ. The transcription factors subsequently stimulate the expression of many SASP proteins, including IL-1α and the inflammatory cytokines IL-6 and IL-8 [Recently, senescence has been implicated in the promotion of tumor progression; thus, senescence exerts a dual function in tumorigenesis. Cellular senescence leads to the secretion of diverse growth factors, cytokines, chemokines, and ECM-remodeling proteases, as a form of the senescent-associated secretory phenotype (SASP) , 194–198and IL-8 , 200.Many factors that compose SASP have numerous biological activities, all highly dependent upon physiological contexts, including the nature of the senescence stimulus, cellular context, and duration and composition of the SASP response. These regulate cell proliferation and induce EMT, angiogenesis, and chronic inflammation, stem cell renewal, and/or differentiation. This suggests that SASP has a dual role  in tumorigenesis. It can act as tumor suppressor in normal cells or low-grade premalignant cells by inducing aging and otherwise promote tumor progression in high-grade premalignant and malignant cells , 199 Fi.κB and C/EBPβ stimulate the expression of various cytokines including IL-1α and IL-6 and IL-8, thus activating immune response [κB and IFN-regulatory factor (IRF) response, thus activating immune response [Senescence triggers an immune response. The transcription factors NF-response , 200. Inresponse , 168. Furesponse , 168. Imresponse , 168.Senescent cells also exhibit distinctive metabolic phenotypes, such as increased glycolysis over mitochondrial oxidative phosphorylation. Subsequent studies showed that these metabolic changes are a key characteristic of senescent cells , 201–203SASP factors positively modulate tumor development in senescent tumor cells, as well as in high-grade premalignant and malignant cells by regulating all steps of tumor progression, such as facilitating tumor proliferation, inducing EMT, invasion, and metastasis, and indirectly promoting angiogenesis –198, 201Most cancer cells rely on a high rate of glycolysis instead of mitochondrial oxidative phosphorylation to produce their energy even under aerobic conditions. This phenomenon is known as the Warburg effect, aerobic glycolysis, or the glycolytic switch –214. TheCancer cells also exhibit elevations of other oncogenic metabolic pathways, including glutamine metabolism, pentose phosphate pathway, and synthesis of fatty acids and cholesterol. Alterations of cellular metabolism in cancer cells produce intermediate biosynthetic precursors for nucleic acids, lipids, and proteins , 222–224Tumor cells in hypoxic regions of the tumor consume glucose and release lactate in glycolytic metabolism. Oxygenated cancer cells consume the lactate released by hypoxic cancer cells to produce ATP through oxidative energy production. Thus, glycolytic and oxidative tumor cells mutually regulate their activities concerning energy metabolites in a process of metabolic symbiosis –228. AltCSCs share general features of metabolic processes with non-stem cancer cells , 230. MeCSCs exhibit higher glucose uptake, lactate production, glycolytic enzyme expression, and ATP content than do non-stem cancer cells. The stemness marker CD44 also contributes to the regulation of glycolytic metabolism . CSCs ofRecently, it was reported that the quiescent or slow-cycling tumor-initiating CSCs are highly dependent on OXPHOS when compared with the differentiated cancer progeny cells in many other tumor types. It implies that CSCs preferentially use mitochondrial oxidative metabolism for glycolysis , 233–236α, which is a master regulator of mitochondrial biogenesis [Furthermore, CSCs display increased mitochondrial mass and membrane potential and increased oxygen consumption rates. Invasive cancer cells induce very elevated mitochondrial metabolism by increasing the expression of the transcription factor peroxisome proliferator-activated receptor gamma coactivator (PGC)1ogenesis , 238.CSCs may exhibit increased glycolysis or increased OXPHOS depending on the cancer type. The metabolic phenotype of the CSCs is fine-tuned between glycolysis and OXPHOS by the environment and cellular signaling pathway. The CSC metabolic phenotype can switch to glycolysis during the inhibition of OXPHOS , 240.Since the metabolic pathways are connected with each other in complicated manners, glycolysis and OXPHOS alone cannot be considered as the basis of CSC metabolism. CSCs rely on the metabolism of glucose and glutamine. CSCs utilize glutamine metabolism for the biosynthesis of amino acids, nucleotides, and lipids because glutamine provides carbon and amino-nitrogen . Thus, gHowever, mitochondrial function does play an important role in either case and contributes to CSC functions, including stemness, migration, and drug resistance . NANOG iα [In CSCs, the capacity for chemoresistance is involved in the increased OXPHOS phenotype and expression of PGC1α –247. Celα [β-catenin, PI3K/Akt, phosphatase and tensin homolog (PTEN), NF-κB, KRAS, HIF, TP53, and many oncogenic pathways. The metabolic phenotype of CSCs is also affected by these signals [In addition, it has very recently been reported that the metabolic phenotype plasticity of pancreatic CSCs is determined by the balance between MYC and PGC-1α . The micα . In normα . However signals . TargetiThe tumor microenvironment is also associated with neoplastic mitochondria. The metabolism of tumor stroma cells, such as cancer-associated fibroblasts (CAF), is reprogrammed. CAF, which is the key component of tumor stroma that surrounds the tumor, represent aerobic glycolysis, like tumor cells. CAF secrete energy metabolites, such as lactate and pyruvate, generated by anabolic glycolysis. Cancer cells assimilate lactate from CAF and utilize mitochondrial OXPHOS for efficient energy production, resulting in a higher proliferative capacity. It is the reverse Warburg effect. Emerging evidence supports the idea that cancer cells exhibit a hybrid glycolysis/OXPHOS phenotype, which plays an important role in energy production and biomass synthesis by cancer cells. The hybrid glycolysis/OXPHOS phenotype leads to enhanced metabolic plasticity of cancer cells for better survival in response to external stimuli and contributes to metastasis and therapeutic resistance. In addition, CAF secrete various cytokines and a distinctive ECM, which promotes tumor growth, invasion, and tumor progression , 248–251α, STAT3, TGF-β, Wnt, and Akt. The induction of EMT contributes to the acquisition of CSC properties and also leads to the repression of mitochondrial metabolism and induction of the glycolytic switch [EMT can regulate the metabolic reprogramming of cancer cells by regulating the many regulatory molecules involved in EMT, including Snail, Dlx-2, HIF-1c switch , 252–259Snail has recently been shown to promote metabolic alterations , 260. Snβ/Wnt-induced glycolytic switch and mitochondrial repression by increasing Snail expression [β/Wnt inhibits mitochondrial complex IV  to prevent mitochondrial respiration [β/Wnt-induced, Snail-dependent EMT, and glycolytic switch [Dlx-2 plays a critical role in EMT and the glycolytic switch , 39, 40.piration –258. DlxHIF-1 acts as a major regulator of glycolytic enzymes, including GLUT, hexokinase, lactate dehydrogenase (LDH), and MCT, thereby contributing to the glycolytic switch , 262. Fuα enhances the translation of PKM2, which is an isoform of pyruvate kinase, a rate-limiting enzyme of glycolysis. On the other hand, cytokines, growth factors, or oncogene-induced STAT3 activation leads to HIF-1α transcription and STAT3 activation, which also induces a PKM2/HIF-1α-positive feedback loop [In addition, the positive feedback loop between HIF-1, STAT3, and pyruvate kinase M2 (PKM2) contributes to the induction of proteins involved in glycolysis –266. Oxyack loop –266.STAT3 also contributes to the EMT-induced metabolic changes. Mammosphere culture produces stable EMT cells in epithelial breast cancer cells. STAT3 is activated in these EMT-derived cancer cells, which induces aerobic glycolysis and the upregulation of certain enzymes and transporters related to glycolysis (such as MCT2). Inhibition of STAT3 prevents EMT-associated changes with the overexpression of MCT2 and ZEB1 in EMT-derived cancer cell lines. This suggests that STAT3 is required for the EMT-induced metabolic changes .Akt has important roles in the glycolytic switch and invasiveness in cancer cells. Overexpression of Akt promotes glycolytic metabolism and mitochondrial dysfunction. It also switches from a radial growth  melanoma to vertical growth  melanoma .Several metabolic enzymes, including pyruvate kinase M2 (PKM2), LDH, pyruvate carboxylase (PC), fatty acid synthase (FASN), aldolase, glutaminase (GLS), citrate synthase (CS), and fructose-1,6-bisphosphate (FBP), have been associated with EMT, metastasis, and CSCs , 267–285β-induced factor homeobox 2 (TGIF2), a transcriptional repressor of TGF-β signaling, and suppresses E-cadherin transcription by recruiting histone deacetylase 3 to promote EMT [Glucose metabolism has been linked with EMT and CSCs , 279. PKmote EMT , 267. PKmote EMT .High levels of LDH A trigger the expression of EMT and CSC markers in invasive bladder cell lines and in muscle-invasive bladder cancer specimens. Thus, LDH A likely has a critical role in the activation of EMT and CSCs , 270.Silencing of the glycolytic enzyme aldolase A suppresses cell proliferation, invasion, and the EMT phenotype in colon cancer. The mRNA and protein levels of aldolase A are upregulated during the progression of human colon cancer and high aldolase A protein expression promotes EMT and migration of colon cancer cells. In addition, aldolase A interacts with HIF-1 and other EMT-related signaling pathways and affects the development of colon cancer. Thus, aldolase A contributes to tumor progression by inducing EMT and is correlated with poor prognoses in colon cancer , 279.In addition, loss of FBP, the gluconeogenesis regulatory enzyme, is important in the EMT-driven CSC phenotype. The expression of FBP1 is suppressed by Snail. Snail also enhances glycolysis, suppresses oxygen consumption and ROS production, and promotes EMT and CSC phenotypes by inducing epigenetic silencing of FBP1 , 240.β levels and TGF-β also leads to the induction of FASN expression. A FASN-TGF-β1-FASN regulatory loop is involved in high EMT/metastatic potential in cisplatin-resistant cancer cells [The dysregulation of lipid metabolism and glutaminolysis has also been associated with EMT , 277. FAer cells .β-, Wnt-, and Snail-induced EMT and the glycolytic switch are prevented through the inhibition of glutamine metabolism by short hairpin GLS1, Gln deprivation, and Gln metabolism inhibitors. These results indicate that the Dlx-2/GLS1/glutamine metabolic axis is a crucial regulator of TGF-β/Wnt-induced, Snail-dependent EMT, metastasis, and the glycolytic switch [Glutaminase 1 (GLS1) is the first enzyme in glutamine anaplerosis. GLS1 promotes tumor growth and metastasis , 40. Thec switch , 40.In addition, TCA cycle enzymes contribute to EMT and cell migration and invasion , 272. PCLoss of the TCA cycle enzyme CS is involved in EMT and the glycolytic switch. Knockdown of the enzyme increases the upregulation of Snail and Twist and downregulates p53 and its target genes (TIGAR and SCO2), resulting in EMT, mitochondrial repression, and the glycolytic switch. p53 prevents glycolysis by increasing the expression of TIGAR and enhances mitochondrial respiration by the activation of SCO2 , 272. ThThe Warburg effect leads to the destruction of the ECM and induces metastasis by the induction of an acidic environment , 286. A Metabolic reprogramming toward aerobic glycolysis unavoidably induces the accumulation of potent toxic metabolites, such as reactive carbonyl species. Methylglyoxal, a reactive dicarbonyl intermediate, is formed as a side product during glycolysis in cancer cells. Methylglyoxal accumulation correlates with tumor growth and metastasis , 290. MeHigh levels of methylglyoxal maintain the nuclear localization and activity of Yes-associated protein (YAP) in breast cancer cells. YAP is a key transcriptional coactivator that is involved in the induction of tumor growth and invasion and contributes to cancer progression by transcriptional activation of c-myc and CTGF . RecentlBesides metabolic enzymes and metabolites, proteins involved in cell survival, including heat shock protein (Hsp)90 and Hsp27, are associated with metabolic alterations and EMT. The Hsp90 molecular chaperone is important in cell proliferation, cell cycle progression, and apoptosis. Hsp90 also functions as an oncogenic protein to regulate metabolic alterations, EMT, invasion, metastasis, and drug resistance –303.β-dependent manner. The phosphorylation stabilizes PKM2 and contributes to biological functions that include regulation of glycolysis, mitochondria respiration, cell apoptosis, proliferation, and cofactor function. Furthermore, the expression of HSP90 positively regulates PKM2 expression in HCC tissues and overexpression of HSP90 and PKM2 are associated with poor prognosis of HCC patients [α and NF-κB [Hsp90 also contributes to induction of proliferation, glycolysis, and inhibition of apoptosis by phosphorylation of PKM2 at the Thr-328 residue . Hsp90 ipatients . Inhibitnd NF-κB .Hsp90 is secreted by tumor cells. Extracellular Hsp90 interacts in an autocrine or paracrine manner with the surfaces of adjacent cells to enhance the growth and metastasis . ExtraceHsp90 is associated with methylglyoxal-mediated metastasis. Methylglyoxal also induces the downregulation of Hsp90 expression levels in human retinal pigment epithelial cells . Hsp90 rβ1-induced EMT. Thus, Hsp27 induces EMT by inducing Snail stabilization [κB activity in breast cancer [Hsp27 is another small molecular chaperone. It contributes to the malignant properties of cancer cells, including EMT and drug resistance. It is avidly expressed in aggressive cancers. Hsp27 knockdown induces proteasomal degradation of Snail, thereby suppressing TGF-lization , 309. Hs2+ levels, synthesis of macromolecules, generation of metabolites for epigenetic regulation, and the innate immune response [+, ATP, α-ketoglutarate, and acetyl CoA, which are required for many transcriptional and epigenetic processes, including chromatin remodeling, histone modifications, and nucleosome positioning [Mitochondria have important roles in cellular functions that include energy production, apoptosis, control of cytosolic Caresponse –316. Mititioning , 318.Contrary to the conventional wisdom that mitochondria are not functional in cancer cells, functional mitochondria are in fact essential for cancer cells. Although mutations in mitochondrial genes are common in cancer cells, they do not inactivate mitochondrial energy metabolism, but rather alter the mitochondrial bioenergetic and biosynthetic state. The mitochondrial dysfunction is implicated in the metabolic reprogramming of cancer cells. The dysregulation of mitochondrial respiration may enhance glycolysis in cancer cells , 319–321Mitochondrial DNA alterations are commonly caused by point mutations and copy number changes in cancer cells, which contributes to cancer progression by increasing the chemoresistance or invasive phenotype. For example, mitochondrial DNA mutations induce the complex I defect, which is accompanied by the overproduction of ROS and upregulation of nuclear genes essential for cell survival and angiogenesis, which promotes the metastatic potential of tumor cells . In addiMitochondrial oxidative stress can enhance tumor progression and the metastatic potential of cancer cells . MitochoIn response to ROS, epigenetic alterations may contribute to the regulation of mitochondrial metabolism by inducing the altered expressions of genes. In addition, alterations of epigenetic patterns, including global DNA methylation and histone modifications, are induced by endogenous metabolite levels, metals, and other environmental pollutants in vitro and in vivo , 325.Mitochondria have important roles in the alteration of metabolic processes in tumors . AlteratSDH and FH act as tumor suppressors. However, mutations of SDH and FH induce the accumulation of succinate or fumarate, respectively, in tumors and leads to EMT, metastasis, and tumorigenesis –333. Genβ/Snail-mediated process in colorectal cancer and ovarian cancer [β/β-catenin axis to induce metastasis in vivo [SDH is a heterotetrameric and highly conserved protein. SDH consists of catalytic subunits (SDHA and SDHB) and binding sites for ubiquinones (SDHC and SDHD) . SDHB mun cancer , 339. Lo in vivo , 340. SD in vivo .FH deficiency is associated with a highly aggressive phenotype that is prone to metastasize and has been correlated with a very poor clinical outcome in renal cancer. In addition, fumarate accumulation caused by the loss of FH can be critical in transformation. Loss of FH and increased fumarate accumulation are closely associated with the induction of EMT in mouse and human cells. Fumarate accumulation elicits EMT by epigenetic suppression of the miR-200 antimetastatic miRNA and suppresses several transcription factors, including Slug and ZEB1/2. Loss of FH and fumarate accumulation may play a critical role in aggressive features of cancer cells , 342.α-ketoglutarate. The gain-of-function IDH1/2 mutations convert α-ketoglutarate to 2-hydroxyglutarate, which may contribute to the inhibition of DNA demethylases and aberrant regulation of gene expression patterns. IDH1/2 mutation leads to formation of 2-hydroxyglutarate in acute myeloid leukemia and glioblastoma. High levels of 2-hydroxyglutarate have frequently been observed in tumors harboring IDH mutations. These metabolites dysregulate the competitive inhibition of α-ketoglutarate–dependent processes, including demethylation of histones [IDH is another mitochondrial enzyme involved in EMT. IDH catalyzes the oxidative decarboxylation of isocitrate to histones , 344. IDhistones . The highistones .α by accumulation of succinate and fumarate which prevent HIF-α prolyl hydroxylation [α prolyl hydroxylase, thereby inducing the stabilization of HIF-1α [α stabilization by accumulation of fumarate in FH mutant cells and then a shift in metabolism from oxidative phosphorylation to glycolysis [SDH or FH mutation induces the stabilization of HIF-1xylation –350. Sucf HIF-1α , 351. Reycolysis , 348–350α stabilization by inhibition of prolyl hydroxylase, which hydroxylates HIF-1α and uses α-ketoglutarate as a substrate allowing for the proteasomal degradation of HIF-1α [α-ketoglutarate-binding site on prolyl hydroxylase [In addition, IDH1 mutation also leads to HIF-1f HIF-1α , 352. Muroxylase , 352. Thα is a master integrator of cellular signals and mediates mitochondrial biogenesis and OXPHOS. It is involved in metastatic dissemination in breast cancer [PGC-1t cancer . In addit cancer .Mitochondrial dysfunction is caused by defects in mitophagy. Accumulation results in excessive ROS production , 354–356Altered oncogenes/tumor suppressors including HIF-1 and p53 modulate the expression of their target genes to regulate mitochondrial respiration and cellular metabolism. Therefore, mitochondrial dysfunction is crucial for cancer progression. A better understanding of the molecular mechanisms of mitochondrial alterations and mitochondrial retrograde signaling is required to improve the efficacy of selective anticancer therapy .Metabolic reprogramming contributes to cell survival and sustains the increased demands of cell proliferation. The activation of oncogenes or the loss of tumor suppressors affects metabolic reprogramming . The tump53 mediates mitochondrial respiration by inducing the expression of SCO2 and GLS2. SCO2 is a crucial regulator of the assembly of complex IV, and it is important in OXPHOS. Mitochondrial respiration is stipulated by p53 via the transactivation of SCO2. The glutamine metabolic enzyme GLS2 is important in the TCA cycle and mitochondrial oxidative phosphorylation. The induction of GLS2 by p53 leads to decreased ROS levels due to the increased glutathione (GSH) levels, which protects cells from DNA damage or oxidative stress , 363.κB-dependent upregulation of GLUT3 [p53 also reduces glucose uptake and glycolysis by repressing the expression of glucose transporter (GLUT) 1 and 4 . Loss ofof GLUT3 . p53 inhof GLUT3 .β1 and PTEN negatively regulate the Akt/PI3K/mTOR signaling pathways, which mediates cell growth, protein translation, autophagy, metabolism, and cell survival. As well, p53 inhibits the Warburg effect by repressing glycolysis and reducing cell growth by acting on AMPK and PTEN [Furthermore, p53 inhibits cancer metabolism by activating the AMPK and PTEN energy-sensing mechanisms during nutrient stresses. AMPKand PTEN .In another function, p53 regulates cell metabolism and proliferation by suppressing the expression of malic enzymes 1 and 2. These enzymes influence NAPDH production, glutamine metabolism, and lipogenesis . p53 alsIn still another function, p53 has an important role in anoikis, which contributes to the suppression of metastasis , 373. AnSalt-inducible kinase 1 is a member of the AMPK-related kinase family. The kinase induces the p53-dependent suppression of tumor metastasis by mediating liver kinase B, which is a tumor suppressor that acts as an upstream regulator to activate AMPK. Salt-inducible kinase 1 acts as an upstream regulator of p53-mediated anoikis and leads to p53-dependent anoikis and suppression of metastasis by regulating liver kinase B1 , 373.Inadequate/inappropriate matrix attachment also leads to the production of ROS, which is associated with anoikis. The Warburg effect allows cancer cells to avoid excessive ROS produced by mitochondrial respiration, which contributes to the acquisition of anoikis resistance. This is a survival advantage for metastasis. Consistent with this, p53 tumor suppressor enhances mitochondrial oxidation, whereas HIF and Snail pro-metastatic transcription factors lead to decreased oxidative metabolism .The oncogenic metabolism is important in the induction of EMT . In thisAccumulating evidence suggests that oncogenic metabolism may negatively regulate p53 , 376. Thp53 stability is regulated by a variety of deubiquitinating enzymes that directly or indirectly affect the ubiquitination of p53. These enzymes can regulate various cellular processes associated with p53 and affect diseases, such as cancer . Therefoβ-catenin pathways, and then regulate most physiological and pathological processes, including metastatic tumor progression, EMT, and CSC phenotype [In addition, ncRNAs have been suggested to play important roles in p53 dysregulation and tumorigenesis . Recent henotype . miRNAs henotype .Specific miRNAs directly target p53 3′-untranslated region mRNA or indirectly inhibit p53-modulator proteins, such as Mdm2 and Mdm4, thereby determining the cell fate of damaged/transformed cells , 95. TheThe genetic inactivation of p53 is induced by increasing ROS and ROS-mediated oxidative DNA damage through the impairment of the electron transport chain. p53, which regulates mitochondrial metabolism and cellular redox, is genetically inactivated in high-grade glioma , 384–386β/Wnt/Dlx-2/Snail-induced EMT and glycolytic switch. GLS1 knockdown also leads to inhibition of tumor growth and metastasis in vivo [Glutamine metabolism negatively regulates p53, which inhibits Snail stability by upregulating miRNA, thereby promoting EMT . Glutami in vivo . Glutami in vivo . These o in vivo .As well as GLS, other enzymes active in oncogenic metabolism may also contribute to Snail-induced EMT by regulating the p53-dependent modulation of Snail-targeting miRNAs. In addition, abnormal TCA cycle enzymes, such as IDH, prevent p53 activities . These rOncogenic metabolism can cause changes in the levels of ROS and NADPH, which may contribute to cancer metastasis and progression. Mutations in metabolic enzymes increase ROS production . Indeed,β treatments. NADPH oxidase generates superoxide by transporting electrons from NADPH to oxygen. Conversely, TGF-β-induced EMT is inhibited by antioxidant treatment. In addition, the NADPH oxidase 2 complex and ROS production are activated by overexpression of neutrophil cytosolic factor 4. The latter encodes the p40phox polypeptide, which is the last NADPH oxidase subunit. In response to the expression of neutrophil cytosolic factor 4, expressions of several matrix metalloproteinases are increased. Snail, Slug, and vimentin are also increased and E-cadherin is decreased in response to neutrophil cytosolic factor 4 expression. Thus, ROS signaling is required for increased EMT [ROS play an important role in EMT. ROS and NADPH oxidase 2 are dramatically induced by TGF-ased EMT .Under conditions of metabolic stress, NADPH homeostasis is important in the survival of cancer cells. NADPH is mainly generated from the cytosolic oxidative pentose phosphate pathway and one-carbon metabolism. NADPH is necessary to scavenge ROS, which is generated with ATP during OXPHOS. Under oxidative and metabolic stress, Snail regulates glucose flux through the pentose phosphate pathway for cancer cell survival .IDH mutation inhibits the production of NADPH and increases the consumption of NADPH , 391–393Therefore, oncogenic metabolism may contribute to cancer metastasis and progression by the changes in the levels of ROS and NADPH.Most (90%) of cancer deaths results from cancer that metastasized. Metastasis is the movement of cancer cells from the primary tumor to surrounding tissues and sometimes more distant organs , 16–23. α, and Dlx-2) and signaling factors  [EMT is regulated by various transcription factors  , 57–60. I3K/Akt) –82. p53 I3K/Akt) –78. It iI3K/Akt) –87. IndeI3K/Akt) . In addiI3K/Akt) , 103–105Numerous EMT-inducing transcription factors and EMT-related signaling pathways contribute to metastasis as well as the CSC phenotype , 108–114α, STAT3, TGF-β, Wnt, and Akt, have been implicated in the metabolic reprogramming of cancer cells. The induction of EMT leads to repression of mitochondrial metabolism and induction of the glycolytic switch [Many regulatory molecules that are involved in EMT, including Snail, Dlx-2, HIF-1c switch , 252–259c switch .The Warburg effect induces an acidic environment, leading to ECM destruction and induction of metastasis , 286. A p53 directly regulates several metabolic enzymes that regulate the metabolic network. Under nutrient stress conditions, p53 inhibits anabolic metabolism to conserve cellular energy . p53 is The collective findings presented in this review indicate that oncogenic metabolism can regulate metastasis and CSCs. Oncogenic metabolism may also be closely related with metastasis. Thus, oncogenic metabolism might be the major target for the prevention of metastasis. Understanding the molecular mechanisms between oncogenic metabolism and metastasis will reveal the role of the metabolism in tumor development and will be crucial for the development of therapeutic strategies.