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Are there yearly variations in HIOMT (HydroxyIndole-O-MethylTransferase) availability?

Are there yearly variations in HIOMT (HydroxyIndole-O-MethylTransferase) availability?


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I'm reading a booklet on melatonin published in 1996, titled "Melatonin and the Biological Clock". And see the following statement:

HIOMT (HydroxyIndole-O-MethylTransferase), one of enzymes of melatonin synthesis, rises and falls in an annual rhythm, with troughs in March and October and peaks in January and July.

Seeing how HIOMT is the last methyltransferase involved in Melatonin synthesis in humans, I'm interested in learning if there's indeed a yearly variation in this MT production in humans, and if it is regulated by genetics or photoperiod duration.

Thank you for your input!


This isn't really a complete answer but I can't fit it into a comment.

I've found that there is a large body of literature on seasonality of melatonin levels in various vertebrates, particularly livestock, because of its interaction with breeding patterns. Similar studies in humans are however, difficult to find, but the review paper cited below looks at a link between seasonal variations in melatonin levels and seasonal variations in immune system functions. It cites a few references that might be worth following up.

Srinivasan, V. et al. (2008) Immunomodulation by melatonin: Its significance for seasonally occurring diseases. Neuroimmunomodulation 15: 93-101 DOI: 10.1159/000148191

Abstract Melatonin is not only synthesized by the pineal gland but also in many other organs and tissues of the body, particularly by lymphoid organs such as the bone marrow, thymus and lymphocytes. Melatonin participates in various functions of the body, among which its immunomodulatory role has assumed considerable significance in recent years. Melatonin has been shown to be involved in the regulation of both cellular and humoral immunity. Melatonin not only stimulates the production of natural killer cells, monocytes and leukocytes, but also alters the balance of T helper (Th)-1 and Th-2 cells mainly towards Th-1 responses and increas- es the production of relevant cytokines such as interleukin (IL)-2, IL-6, IL-12 and interferon-γ. The regulatory function of melatonin on immune mechanisms is seasonally dependent. This fact may in part account for the cyclic pattern of symptom expression shown by certain infectious diseases, which become more pronounced at particular times of the year. Moreover, melatonin-induced seasonal changes in immune function have also been implicated in the pathogenesis of seasonal affective disorder and rheumatoid arthritis. The clinical significance of the seasonally changing immunomodulatory role of melatonin is discussed in this review.


Development of hydroxyindole‐O‐methyltransferase activity in the retina of the chick embryo and young chick

Select data courtesy of the U.S. National Library of Medicine. © 2021 DeepDyve, Inc. All rights reserved.

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Contents

N-Acetylserotonin O-methyltransferase is an enzyme that is coded for by genes located on the pseudoautosomal region of the X and Y chromosome, and is most abundantly found in the pineal gland and retina of humans. Β] Although the exact structure of N- Acetylserotonin O-methyltransferase has yet to be determined by X-Ray diffraction, the crystal structure of the Maf domain of human N-Acetylserotonin O-methyltransferase-like protein has been found. Γ]


Introduction

Pineal parenchymal tumors (PPTs), derived from pineocytes, are rare neoplasms and account for less than 1% of primary central nervous system (CNS) tumors ( 1). The revised World Health Organization classification of CNS tumors divides PPTs into pineocytoma (PC), pineoblastoma (PB), and PPT of intermediate differentiation (PPTID) ( 2). The 5-year survival rates of PC, PPTID, and PB are 86% to 100%, 39% to 74%, and 58%, respectively ( 2). Histologically, a high mitotic index and necrosis are associated with a poorer outcome, whereas positive immunostaining for neurofilaments is associated with a better survival ( 1). The distinction of high-grade PPTs from other embryonal tumors in CNS has relied heavily on knowledge of the primary site of the tumor and the extent of pineocytomatous differentiation, such as club-shaped argyrophilic processes, pineocytomatous rosettes, and photoreceptors ( 2). The PPTs show positive immunostaining for S100 protein, neuron-specific enolase, synaptophysin, neurofilaments, class III β-tubulin, tau protein, PGP9.5, retinal S-antigen (SAG), chromogranin A, serotonin, and α-B crystallin ( 1, 3-8). These proteins are useful for the identification of neural and neural crest cells. There is, however, no specific marker available for differentiating high-grade PPTs from other embryonal tumors ( 2).

Melatonin is a powerful antioxidant molecule involved in the protection of nuclear and mitochondrial DNA and in the regulation of circadian seasonal rhythms and immune function ( 9-13). It is produced and secreted predominantly by the pineal gland. Tryptophan, the precursor of melatonin, is metabolized into 5-hydroxytryptophan by tryptophan-hydroxylase 5-hydroxytryptophan is then metabolized by aromatic amino acid decarboxylase into N-acetylserotonin. N-acetylserotonin then undergoes modification by arylalkylamine-N-acetyltransferase. The result of this modification is metabolized into melatonin by hydroxyindole-O-methyltransferase (HIOMT) ( 14).

The expression of messenger RNAs (mRNA) for tryptophan-hydroxylase, arylalkylamine-N-acetyltransferase, and HIOMT has been previously detected in tissues or cell cultures derived from PPTs by microarray, real-time reverse transcription and polymerase chain reaction, in situ hybridization, and Northern blot analyses ( 15-17). Furthermore, HIOMT activity has been detected in PPTs ( 18-20). The evidence of high mRNA expression in PPTs for these enzymes suggests that one or more of them could serve as diagnostic markers and tools for understanding the biology of PPTs. In the present study, we focused on HIOMT and analyzed normal pineal glands, other human tissues, PPTs, and embryonal tumors in CNS by immunohistochemistry (IHC) for evidence of melatonin synthesis. We further correlated HIOMT expression with the histological differentiation of PPTs. We also compared HIOMT expression with that of retinal SAG, a major soluble photoreceptor protein that is involved in desensitization of the photoactivated transduction cascade ( 21-23), in CNS PPTs and embryonal tumors.


Materials and Methods

Animal Model

We used an established model of global maternal nutrient manipulation [ 13, 14, 42] to induce fetal growth restriction. Briefly, female Wistar rats (aged 120 days) were time mated, and after confirmation of mating, rats were housed individually in standard rat cages with free access to water. All rats were kept in the same room with a constant temperature maintained at 25°C and a 12L:12D cycle. Pregnant dams were randomized into one of four groups: 1) dams fed a control diet of 18% protein, 5% fat, and 3.4 kcal/gm digestible energy (Diet 2018 Harlan Teklad) ad libitum throughout pregnancy and lactation (Cont n = 8) 2) undernourished dams fed 50% of Cont intake throughout pregnancy and lactation (UNPL, n = 7) 3) undernourished dams fed 50% of Cont intake throughout pregnancy only (UNP, n = 6) and 4) undernourished dams fed 50% of Cont intake throughout lactation only (UNL, n = 6). After birth, the pups were sexed, weighed, and litter size was standardized to eight pups that best represented (were closest to) the mean litter weight. Each litter contained four females and four males. At weaning (Day 22), the offspring were weighed, and female offspring were weight-matched within maternal dietary groups, housed two per cage, and fed the control diet ad libitum for the remainder of the study. At 150 days of age, offspring (from different litters) were fasted overnight and killed by decapitation following pentobarbitone anesthesia (60 mg/kg, subcutaneously). All the ovarian tissue was collected between 0900 and 1200. While under anesthesia, vaginal smears were performed for determination of estrous stage [ 13- 15]. Both ovaries were collected one was fixed in Bouin solution (Sigma-Aldrich) and processed for the determination of follicular counts [ 13] or for immunohistochemistry and the other snap-frozen and stored at −80°C for molecular analyses. In all cases, all biological replicates are from different litters. All the animal experiments were approved by the Animal Ethics Committee, University of Auckland (Approval R402).

Molecular Analyses

RNA extraction and reverse transcription.

Ovarian tissues were collected, snap-frozen, and stored at −80°C in preparation for RNA extraction and reverse transcribed as previously described [ 13, 43, 44]. Total RNA was extracted using AllPrep DNA/RNA Mini kit (80204 Qiagen). Genomic DNA was removed with RNase-free DNase (Invitrogen Life Technologies). RNA quantity and purity were analyzed using a NanoDrop spectrophotometer (ND-1000 BioLab Ltd.) and NanoDrop software (version 3.1.2). RNA samples were stored at −80°C.

Five micrograms of total RNA was used for first-strand cDNA synthesis using the Moloney Murine Leukemia Virus Reverse Transcriptase enzyme (M-MLV-RT) (Promega Corp.) and a standard thermocycler (GeneAmpH PCR System 9700 Applied Biosystems). A master mix was prepared containing 5 ml M-MLV 56 buffer (M531A In Vitro Technologies), 0.5 ml M-MLV-RT (M170B In Vitro Technologies), and 1.25 ml 10 mM deoxyribonucleotides (R0181 Global Science) under the following cycling conditions: denaturation stage of 5 min at 96°C, followed by 30 cycles of 30 sec each of 96°C (denaturation), 60°C (annealing stage), and 72°C (extension stage). Complementary DNA was stored at −20°C.

Quantitative polymerase chain reaction assays.

A quantitative PCR assay was performed as previously described [ 13] using the Roche LightCycler 480 System (Roche Diagnostics) and LightCycler 480 SYBR Green I Master (04707516001 Roche Diagnostics). Primers for all genes for ER stress, autophagy, inflammation, gonadotropin receptor, and clock genes—except Period and hydroxyindole O-methyltransferase (HIOMT)—were designed using Primer BLAST software available at the National Center for Biotechnology Information Web site (blast.ncbi.nlm.nih.gov Table 1). Primers were manufactured by Invitrogen (Invitrogen Life Technologies). Ready-made primers for Period (per1, per2) and HIOMT genes were purchased from Qiagen ( Table 2).

Rat gene a . Forward primer . Reverse primer . Amplicon length (bp) . GenBank accession no. .
Beta-actinCACCAACTGGGACGATATGGA CAGCCTGGATGGCTACGTACAT 188 NM_031144
CyclophilinTTGGGTCGCGTCTGCTTCGA GCCAGGACCTGTATGCTTCA 240 NM_017101.1
BMAL1ACTGCACCTCGGGAGCGACT CGCCCGATTGCAACGAGGCA 320 NM_024352.2
CLOCKACCGCACCTGCCAGCTCATG GCGTGTCCGCTGCTCTAGCT 214 NM_021856.1
CRY1CGGAAGCTCGTGTCGGTCCG CGCGCGACGTCCTTCAGGAG 232 NM_198750.2
CRY2ACGGTCCCCGTGCAGTCGAT CTGACGAGGAGGCCGCGAAC 166 NM_113405
p21AGCCACAGGCACCATGTCCGA CGCATCGCAATCGCGGCTCA 118 U24174.1
XBP1sGAGTCCGCAGCAGGTG GCGTCAGAATCCATGGGA 165 NM_001004210
XBP1tGAGCAGCAAGTGGTGGATTT TCTCAATCACAAGCCCATGA 197 NM_001004210
P13Kca (p110) GAACGTGTGCCGTTTGTTTT ACCATGATGTGCGTCATTCA 300 NM_133399.2
P1K3r1 (p85) AGCAACCGAAACAAAGCCGA ATAGCCGGTGGCAGTCTTGT 153 NM_013005.1
Rat gene a . Forward primer . Reverse primer . Amplicon length (bp) . GenBank accession no. .
Beta-actinCACCAACTGGGACGATATGGA CAGCCTGGATGGCTACGTACAT 188 NM_031144
CyclophilinTTGGGTCGCGTCTGCTTCGA GCCAGGACCTGTATGCTTCA 240 NM_017101.1
BMAL1ACTGCACCTCGGGAGCGACT CGCCCGATTGCAACGAGGCA 320 NM_024352.2
CLOCKACCGCACCTGCCAGCTCATG GCGTGTCCGCTGCTCTAGCT 214 NM_021856.1
CRY1CGGAAGCTCGTGTCGGTCCG CGCGCGACGTCCTTCAGGAG 232 NM_198750.2
CRY2ACGGTCCCCGTGCAGTCGAT CTGACGAGGAGGCCGCGAAC 166 NM_113405
p21AGCCACAGGCACCATGTCCGA CGCATCGCAATCGCGGCTCA 118 U24174.1
XBP1sGAGTCCGCAGCAGGTG GCGTCAGAATCCATGGGA 165 NM_001004210
XBP1tGAGCAGCAAGTGGTGGATTT TCTCAATCACAAGCCCATGA 197 NM_001004210
P13Kca (p110) GAACGTGTGCCGTTTGTTTT ACCATGATGTGCGTCATTCA 300 NM_133399.2
P1K3r1 (p85) AGCAACCGAAACAAAGCCGA ATAGCCGGTGGCAGTCTTGT 153 NM_013005.1

BMAL1, brain and muscle Arnt-like protein 1 CLOCK, circadian locomotor output cycles kaput P13Kca (p110), phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha CRY1 and CRY2, cryptochrome 1 and 2, respectively P1K3r1 (p85), phosphatidylinositol 3-kinase regulatory subunit 1 (alpha) p21, cyclin-dependent kinase inhibitor 1 (also known as CDK-interacting protein 1) XBP1s and XBP1t, X-box binding protein 1 spliced and total, respectively.

Rat gene a . Forward primer . Reverse primer . Amplicon length (bp) . GenBank accession no. .
Beta-actinCACCAACTGGGACGATATGGA CAGCCTGGATGGCTACGTACAT 188 NM_031144
CyclophilinTTGGGTCGCGTCTGCTTCGA GCCAGGACCTGTATGCTTCA 240 NM_017101.1
BMAL1ACTGCACCTCGGGAGCGACT CGCCCGATTGCAACGAGGCA 320 NM_024352.2
CLOCKACCGCACCTGCCAGCTCATG GCGTGTCCGCTGCTCTAGCT 214 NM_021856.1
CRY1CGGAAGCTCGTGTCGGTCCG CGCGCGACGTCCTTCAGGAG 232 NM_198750.2
CRY2ACGGTCCCCGTGCAGTCGAT CTGACGAGGAGGCCGCGAAC 166 NM_113405
p21AGCCACAGGCACCATGTCCGA CGCATCGCAATCGCGGCTCA 118 U24174.1
XBP1sGAGTCCGCAGCAGGTG GCGTCAGAATCCATGGGA 165 NM_001004210
XBP1tGAGCAGCAAGTGGTGGATTT TCTCAATCACAAGCCCATGA 197 NM_001004210
P13Kca (p110) GAACGTGTGCCGTTTGTTTT ACCATGATGTGCGTCATTCA 300 NM_133399.2
P1K3r1 (p85) AGCAACCGAAACAAAGCCGA ATAGCCGGTGGCAGTCTTGT 153 NM_013005.1
Rat gene a . Forward primer . Reverse primer . Amplicon length (bp) . GenBank accession no. .
Beta-actinCACCAACTGGGACGATATGGA CAGCCTGGATGGCTACGTACAT 188 NM_031144
CyclophilinTTGGGTCGCGTCTGCTTCGA GCCAGGACCTGTATGCTTCA 240 NM_017101.1
BMAL1ACTGCACCTCGGGAGCGACT CGCCCGATTGCAACGAGGCA 320 NM_024352.2
CLOCKACCGCACCTGCCAGCTCATG GCGTGTCCGCTGCTCTAGCT 214 NM_021856.1
CRY1CGGAAGCTCGTGTCGGTCCG CGCGCGACGTCCTTCAGGAG 232 NM_198750.2
CRY2ACGGTCCCCGTGCAGTCGAT CTGACGAGGAGGCCGCGAAC 166 NM_113405
p21AGCCACAGGCACCATGTCCGA CGCATCGCAATCGCGGCTCA 118 U24174.1
XBP1sGAGTCCGCAGCAGGTG GCGTCAGAATCCATGGGA 165 NM_001004210
XBP1tGAGCAGCAAGTGGTGGATTT TCTCAATCACAAGCCCATGA 197 NM_001004210
P13Kca (p110) GAACGTGTGCCGTTTGTTTT ACCATGATGTGCGTCATTCA 300 NM_133399.2
P1K3r1 (p85) AGCAACCGAAACAAAGCCGA ATAGCCGGTGGCAGTCTTGT 153 NM_013005.1

BMAL1, brain and muscle Arnt-like protein 1 CLOCK, circadian locomotor output cycles kaput P13Kca (p110), phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha CRY1 and CRY2, cryptochrome 1 and 2, respectively P1K3r1 (p85), phosphatidylinositol 3-kinase regulatory subunit 1 (alpha) p21, cyclin-dependent kinase inhibitor 1 (also known as CDK-interacting protein 1) XBP1s and XBP1t, X-box binding protein 1 spliced and total, respectively.

Qiagen QuantiTect primer assays.

Rat gene a . Catalogue number . GenBank accession number .
PER1QT01615726 NM_001034125
PER2QT00184737 NM_031678
HIOMTQT02336901 NM_144759
Beclin1QT00176344 NM_001034117
NFκBQT01580012 NM_199267
MAP1LC3aQT00371546 NM_199500
IL-6QT00182896 NM_012589
IL-1βQT00181657 NM_031512
Rat gene a . Catalogue number . GenBank accession number .
PER1QT01615726 NM_001034125
PER2QT00184737 NM_031678
HIOMTQT02336901 NM_144759
Beclin1QT00176344 NM_001034117
NFκBQT01580012 NM_199267
MAP1LC3aQT00371546 NM_199500
IL-6QT00182896 NM_012589
IL-1βQT00181657 NM_031512

PER1 and PER2, Period 1 and 2 genes, respectively NFκB, nuclear factor kappa-light-chain-enhancer of activated B cells IL-6, interleukin 6 IL-1β, interleukin 1-beta MAP1LC3a, microtubule-associated protein 1 light chain 3 alpha HIOMT, hydroxyindole O-methyltransferase.

Qiagen QuantiTect primer assays.

Rat gene a . Catalogue number . GenBank accession number .
PER1QT01615726 NM_001034125
PER2QT00184737 NM_031678
HIOMTQT02336901 NM_144759
Beclin1QT00176344 NM_001034117
NFκBQT01580012 NM_199267
MAP1LC3aQT00371546 NM_199500
IL-6QT00182896 NM_012589
IL-1βQT00181657 NM_031512
Rat gene a . Catalogue number . GenBank accession number .
PER1QT01615726 NM_001034125
PER2QT00184737 NM_031678
HIOMTQT02336901 NM_144759
Beclin1QT00176344 NM_001034117
NFκBQT01580012 NM_199267
MAP1LC3aQT00371546 NM_199500
IL-6QT00182896 NM_012589
IL-1βQT00181657 NM_031512

PER1 and PER2, Period 1 and 2 genes, respectively NFκB, nuclear factor kappa-light-chain-enhancer of activated B cells IL-6, interleukin 6 IL-1β, interleukin 1-beta MAP1LC3a, microtubule-associated protein 1 light chain 3 alpha HIOMT, hydroxyindole O-methyltransferase.

Optimal primer conditions were adjusted to the following cycling conditions: length = 20 bp (range 17–23 bp), Tm = 63°C (range 60°C–65°C), and amplicon length = 100–350 bp. Dissociation analyses were performed to ensure specificity, and samples producing a single peak in dissociation curves were used. A subset of amplified products was visualized on an agarose gel using the E-GelH CloneWell 0.8% SYBR Safe gel (G6618-08 Invitrogen) run on the E-GelH iBaseTM Power System (G6400 Invitrogen).

All the quantitative PCRs were carried out with an initial denaturation at 95°C for 5 min followed by amplification of the gene product through 45 successive cycles of 95°C for 10 sec, 60°C for 10 sec, and 72°C for 10 sec. A standard curve was generated from the mean cycle threshold of eight standards (1:5 serial dilution) of a known concentration in triplicate, while amplification and dissociation curves were generated for all standards and samples (Roche Lightcycler 480 System Roche Diagnostics). Each sample was run in triplicate. All the mRNA data is expressed relative to the geometric mean of two different reference genes (cyclophilin and beta-actin), the levels of which did not differ between nutritional groups.

Immunohistochemistry and Immunofluorescence

Fixed ovaries were processed for microscopy, embedded in paraffin, and the entire ovary was serially sectioned at 8 μm as described previously [ 13]. Sections that were not used for follicle counts were then used for immunohistochemistry/immunofluorescence.

Determination of Follicular Apoptosis

Detection of apoptotic cells in follicles was performed as previously described [ 33]. A terminal deoxynucleotidytransferase-mediated deoxyuridine triphosphate nick end-labeling (TUNEL) kit (Roche Applied Science) was used according the manufacturer's protocol. Briefly, ovarian tissue sections (8 μm) were permeabilized in 0.1% Triton X-100 (Sigma), washed in PBS, and incubated for 60 min with the fluorescein isothiocyanate-conjugated TUNEL enzyme to detect DNA fragmentation. Nuclei were counterstained with propidium iodide. Apoptotic cells showing TUNEL-positive staining were counted in six fields of view per section at 250× magnification (n = 5 per nutritional group). Image analysis was performed using an Olympus BX-61 microscope and integrated morphometry software (MetaMorph). Data are expressed as apoptotic-positive follicular cells as a proportion of the total.

Determination of Ovarian Blood Vessel Density and Immunolocalization of VEGF and VEGFR2

Evaluation of blood vessel density was performed as described previously using the endothelial cell marker, CD31 [ 45]. Briefly, ovarian sections (8 μm) were immersed in 30% hydrogen peroxide to inhibit endogenous peroxidase activity for 10 min. Antigen retrieval was performed by incubating tissues in 10 mM sodium citrate buffer with Tween, pH 6.0, at 90°C for 12 min. Nonspecific binding was blocked with 5% bovine serum albumin for 10 min at room temperature (RT) and incubated overnight at 4°C with anti-CD31 primary antibody (1:100 dilution Abcam). The following day, tissue sections were incubated at RT for 2 h with anti-mouse biotinylated secondary antibody (Sigma-Aldrich Canada Ltd.) then incubated with ExtrAvidin (Sigma-Aldrich Canada Ltd.) for 1 h. CD31 was visualized with 3,3′-diaminobenzidine (DAB) (D4293 Sigma-Aldrich), and all sections were counterstained with Gills 2 hematoxylin (GHS216 Sigma-Aldrich). For blood vessel density determination, CD31-immunopositive (endothelial cells) blood vessels were measured in six fields of view per section at 250× magnification (n = 5 per nutritional group). Image analysis was performed using an Olympus BX-61 microscope and integrated morphometry software (MetaMorph). Data are expressed as vessel area as a proportion of total ovarian area analyzed.

Protein localization of vascular endothelial growth factor (VEGF), its receptor type 2 (VEGFR2), and their colocalization was performed using immunofluorescence on ovarian sections (8 μm). Sections were incubated for 1 h with rabbit polyclonal anti-human VEGF (1:600 dilution Santa Cruz Biotechnology), washed with PBS, and incubated for 1 h with an Alexa Fluor 488-conjugated anti-rabbit immunoglobulin G (IgG heavy and light chains), F(ab′)2 fragment (1:250 dilution, 8889 Cell Signaling). Sections were then washed twice for 2 min with 1× PBS and incubated with rabbit polyclonal anti-human VEGFR2 (1:500 dilution Santa Cruz Biotechnology). After a 1-h incubation, tissue sections were washed with PBS and incubated for another hour with Alexa Fluor 594-conjugated anti-rabbit IgG (heavy and light chains), F(ab') fragment. Nuclei were counterstained with propidium iodide or 4′,6-diamino-2-phenylindole, and specimens were imaged with a BX-61 fluorescent microscope (Olympus). Stained slides were stored at 4°C. Total VEGF and VEGFR2 immunostaining was quantified by determining the proportion of immunopositive cells in six fields of view per section at 250× magnification (n = 5 per nutritional group). Image analysis was performed using an Olympus BX-61 microscope and integrated morphometry software (MetaMorph). Data are expressed as VEGF/VEGFR2-positive cells as a proportion of total ovarian area analyzed. The amount of area where VEGF and VEGFR2 colocalized was also calculated and expressed as a proportion of total area analyzed. All the image analyses were performed by an investigator blind to the study groups.

Immunolocalization of the Autophagy Regulator, Beclin1

Immunolocalization of Beclin1 in ovarian tissue sections was performed as described above with the following modifications. Ovarian sections were incubated with Beclin1 antibody (1:300 dilution, ab55878 Cedarlane) overnight at 4°C. The following day, sections were incubated with biotinylated secondary antibody (1:10 dilution, Vectastain Elite ABC kit peroxidase rabbit IgG Vector Labs) for 2 h at RT then incubated with avidin-biotin peroxidase complex solution (4:10 dilution using 1% bovine serum albumin in 1× PBS) for 2 h at RT. The antibody complex was visualized using DAB, and the sections were counterstained with Gills II hematoxylin. Cover slips were mounted using Permount (SP15-500 Fisher Scientific), and immunopositive cells were imaged using the NIS-Elements AR imaging program on a Nikon 90i microscope at 200× magnification. Total Beclin1 immunostaining was quantified by determining average density of brown (DAB substrate) immunopositive cells in six fields of view per section at 200× magnification (n = 5 per nutritional group) using the NIS-Elements AR imaging program (Nikon). In all the immunohistochemical assays, negative controls were incubated in the absence of the primary antibody and were included in each assay run. All the image analyses were performed by an investigator blinded to the study groups.

Statistical Analyses

All the data were analyzed by one-way ANOVA. Data that were not normally distributed were log-transformed to achieve normality. Post-ANOVA multiple comparisons among means were performed using Bonferroni post hoc analysis where appropriate, and a P < 0.05 was considered statistically significant. All the data are presented as means ± SEM. Statistical analysis was performed using SigmaStat for Windows version 2.03 (Jandel Corp.) and GraphPad Prism version 6.00 for Mac (GraphPad Software).


<p>This section describes post-translational modifications (PTMs) and/or processing events.<p><a href='/help/ptm_processing_section' target='_top'>More. </a></p> PTM / Processing i

Molecule processing

Feature keyPosition(s)Description Actions Graphical viewLength
<p>This subsection of the 'PTM / Processing' section describes the extent of a polypeptide chain in the mature protein following processing or proteolytic cleavage.<p><a href='/help/chain' target='_top'>More. </a></p> Chain i PRO_0000083982 1 – 345 Acetylserotonin O-methyltransferase Add BLAST 345

Proteomic databases

MassIVE - Mass Spectrometry Interactive Virtual Environment

PRoteomics IDEntifications database

ProteomicsDB: a multi-organism proteome resource


Variations of melatonin bioavailability in humans

Melatonin as a food supplement is widely used in the USA and in several other countries. Its sales once exceeded vitamin C in the USA [ 115 ]. However, the pharmacokinetics of melatonin, especially its bioavailability in humans, has not drawn sufficient attention. In animal studies, particularly in laboratory rodents, the pharmacokinetic parameters of melatonin including its half-life (t1/2), clearance rate (Cl) and bioavailability are uniform and exhibit small individual variations. Compared with rodents, the bioavailability of melatonin in humans is poor. A clear study using deuterium melatonin as a reference standard revealed that the bioavailability of orally consumed melatonin was as low as 1% in some subjects with an obvious sexual difference. The bioavailability of melatonin in females is double that of males, i.e. 16.8 ± 12.7% vs. 8.6 ± 3.9%, respectively [ 116 ]. The low bioavailability of melatonin is attributed to its first pass effect through the liver. However, that a considerable amount of melatonin may be degraded by gastrointestinal CYP450 1B1, may participate in the hepato-enteric cycling or be consumed by the nonenzymatic mechanisms including an interaction with ROS/RNS could not be ruled out. High levels of melatonin in bile of rats [ 39 ] and in the biliary tract of humans [ 117 ] have been reported this suggests that a portion of orally taken melatonin may enter the hepato-enteric circulation.

In addition to its low bioavailability, substantial individual variations in melatonin bioavailability have been observed. This variation can be as high as 37-fold. The average individual variations calculated from available data in terms of melatonin's bioavailability in humans differ by about 18-fold (Table 1). The largest individual variations are probably due to the heterogenic properties of cytochrome C P450 subtype gene expression in humans.

Studies Range of bioavailability Folds of difference Mean value of bioavailability
Waldhauser et al. [ 118 ] 3–76% a 25.3 22.0% b
Di et al. [ 119 ] 10–56% 5.6 33.0%
DeMuro et al. [ 120 ] 7.3–20.3 b 3.0 14.3%
Fourtillan et al. (117) 1–37% 37 8.7% (male) 16.8% (female)
Average 17.7 18.9%

The low bioavailability (average 18.9%) and large individual variation (average 17.7-fold) may well explain the different responses in subjects who take melatonin orally. Currently, the most popular melatonin formula commercially available is a 3 mg tablet. For some subjects, this dose when taken to benefit sleep may induce drowsiness the day after for others, whose bioavailability is low, this dose may not be sufficient to treat insomnia or related disorders. To obtain the optimal effects of melatonin treatment, individualization of dose is suggested based on the serum or salivary melatonin levels after melatonin administration or adjusting the dose depending on the responses of the subjects.

Drug interactions also influence the bioavailability of melatonin. For example, co-administration of melatonin with CYP1A2 inhibitor, fluvoxamine (also a serotonin reuptake inhibitor), in healthy subjects, results in a 17-fold increase in melatonin blood levels [ 122 ]. These data also indirectly indicate a very low melatonin bioavailability in humans, probably <6% in this study. When melatonin is taken with 200 mg caffeine, equivalent to a large cup of coffee, its bioavailability increases 140% presumably because both are substrates of CYP1A2 [ 123 ]. We also observed that concomitantly when melatonin was taken with vitamin E and vitamin C in human subjects, the bioavailability of melatonin increased (Tan & Reiter, unpublished observations). Clarifying the pharmacokinetics of melatonin and its interaction with other substances will help to understand dose differences in a variety of situations and between individuals.


Pineal Gland Evolved to Improve Vision, According to Theory by NICHD Scientist

The pineal gland—which regulates the cycles of sleep and waking—appears to have evolved as an indirect way to improve vision, by keeping toxic compounds away from the eye, according to a new theory by a researcher at the National Institute of Child Health and Human Development at the National Institutes of Health.

The theory has implications for understanding macular degeneration, a condition causing vision loss in people age 60 and older.

The theory is described in the August Journal of Biological Rhythms and represents the work of David Klein, Ph.D., Chief of NICHD's Section on Neuroendocrinology. Dr. Klein studies melatonin, the pineal hormone that regulates sleep and wake cycles.

"Dr. Klein's theory extends our understanding of the pineal gland as a factor controlling the body's daily rhythms," said Duane Alexander, M.D., Director of the National Institute of Child Health and Human Development. "Klein's new theory reminds us of the common evolutionary origin of cells in the pineal gland and retina and forces us to look at one of the enzymes used to make melatonin from a new perspective-as a detoxifying system in the retina."

Briefly, the theory holds that melatonin was at first a kind of cellular garbage, a by-product created in cells of the eye when normally toxic substances were rendered harmless. Roughly 500 million years ago, however, the ancestors of today's animals became dependent on melatonin as a signal of darkness. As the need for greater quantities of melatonin grew, the pineal gland developed as a structure separate from the eyes, to keep the toxic substances needed to make melatonin away from sensitive eye tissue.

For sight to be possible, Dr. Klein explained, a form of vitamin A (also called retinaldehyde) must chemically attach itself to rhodopsin, a protein found in the light detecting cells of the retina (the photoreceptors). When struck by light, the retinaldehyde-rhodopsin combination undergoes physical changes that begin a series of chemical reactions. These reactions ultimately generate an electrical signal that travels into the brain, making vision possible.

This is a one-time event for each retinal-rhodopsin combination. In the process, light also renders the retinaldehyde inactive and frees it from rhodopsin. The free, inactive retinaldehyde is then recycled within the retina to an active form, so that it can again participate in light detection.

However, a problem arises during this recycling process: When retinaldehyde is not attached to rhodopsin, it can combine with substances known as arylalkylamines. Klein has found that one molecule of an arylalkylamine can combine with two molecules of retinaldehyde to form a substance known as a bis-retinal arylalkylamine. After this occurs, the retinaldehyde molecule can no longer be used to detect light, Dr. Klein said. Arylalkylamines are potentially dangerous because they can damage many chemicals in the cell. Some arylalkylamines are generated naturally. These include tyramine, tryptamine, phenylethylamine, and serotonin. In addition, Dr. Klein theorizes that other toxic arylalkyamines were also present in the environment early in evolution.

Roughly 500 million years ago, animals acquired the ability to make an enzyme known as arylalkylamine N-acetyltransferase (AANAT). Earlier this year, Dr. Klein and his colleagues presented evidence that animal cells may have acquired this ability by incorporating bacterial DNA into their own DNA. A release describing the earlier finding appears at http://www.nichd.nih.gov/news/releases/Pages/genes.aspx.

AANAT chemically alters arylalkylamines to prevent them from combining with retinaldehyde. AANAT alters serotonin by changing it to a compound known as N-acetylserotonin. However, N‑acetylserotonin is still toxic to the cells of the retina, although less so than is serotonin. A second enzyme, hydroxyindole-O-methyltransferase (HIOMT) further changed N-acetylserotonin, converting it into melatonin, which is relatively harmless to the eye. In the earlier paper, Dr. Klein and his coworkers also provided evidence that, like AANAT, HIOMT originated in bacteria. He believes that these enzymes—both of which are essential for melatonin synthesis—were acquired by the ancestral eye to increase sensitivity to light. The enzymes presumably were acquired before the evolution of the pineal gland.

Dr. Klein explained that, in the ancestor of today's higher animals, the conversion of serotonin to melatonin increased at night, as a way to make vision more sensitive to low light conditions. The conversion kept serotonin from combining with retinaldehyde at night, when it was needed to detect low levels of light, so that these ancestral animals could function well under dim light.

Gradually, the early organism recognized the increase in melatonin as a signal of nighttime and became dependent on it, according to Dr. Klein's theory. This signal was used to synchronize their daily cycles with the environmental night and day cycle. For this signal to be reliable, the organism needed a steady supply of serotonin in these cells. However, this requirement for higher levels of serotonin conflicted with the need for greater light detection because serotonin depleted retinaldehyde. This conflict was resolved by the evolution of a second photoreceptor cell, one that housed melatonin production. The evolution of the second photoreceptor cell allowed the original photoreceptor cell to achieve higher levels of sensitivity to light because it was not dedicated to making high levels of melatonin. Eventually, the melatonin-making photoreceptors gave rise to the pineal gland.

"To increase both sets of processes—melatonin synthesis and photodetection—evolution put them into separate cells," Dr. Klein said. "One cell moved toward detecting light, the other toward making melatonin."

In support of his theory, Dr. Klein noted that the photoreceptor cells of the retina strongly resemble the cells of the pineal gland and that the pineal cells of sub-mammals (such as fish, frogs and birds) detect light. In addition, melatonin's origin in the ancestral photoreceptor cell is indicated by the capacity of the retinas of mice, fish, frogs, and birds to make low amounts of melatonin.

Dr. Klein points out that as humans and other primates evolved, melatonin production was lost in the retina and became restricted to the pineal gland. Although melatonin is no longer manufactured in the primate retina, AANAT still is. Dr. Klein suspects that the enzyme plays a role in protecting the human retina. Arylalkylamines (tryptamine, phenylethylamine, and tyramine) are likely to be made in cells of the retina, and AANAT may function to convert them to less harmful forms.

Accordingly, AANAT may play two roles—in the retina it would have a detoxification role whereas in the pineal gland it would have a role in melatonin synthesis It's possible, Dr. Klein said, that low levels of AANAT might lead to the deterioration of the retina seen in macular degeneration and, perhaps it might be possible to prevent this disease by increasing AANAT levels.


Results

Body Weights

At birth, sex ratios were the same across groups (data not shown). Early life undernutrition significantly reduced birth weight in UNP and UNPL offspring compared to Cont this reduction in body weight persisted to weaning, and in UNPL, it persisted to adulthood [ 13] ( Table 3). We found no effect of early life undernutrition exposure on adult ovarian weight [ 13].

Offspring body and ovarian weights. *

Nutritional group . Birth weight (g) . Weaning weight (g) . Adult body weight (g) . Adult ovarian weight (g) .
Control 6.1 ± 0.09 a 59.6 ± 0.7 a 301 ± 4.9 a 0.103 ± 0.005
UNP 4.8 ± 0.06 b 54.8 ± 1.2 b 292.4 ± 7.1 a 0.096 ± 0.005
UNPL 4.8 ± 0.08 b 32.7 ± 1.3 b 263.3 ± 6.6 b 0.097 ± 0.006
UNL 6.0 ± 0.08 b 39.7 ± 1.2 b 292.6 ± 15.6 a 0.100 ± 0.006
Nutritional group . Birth weight (g) . Weaning weight (g) . Adult body weight (g) . Adult ovarian weight (g) .
Control 6.1 ± 0.09 a 59.6 ± 0.7 a 301 ± 4.9 a 0.103 ± 0.005
UNP 4.8 ± 0.06 b 54.8 ± 1.2 b 292.4 ± 7.1 a 0.096 ± 0.005
UNPL 4.8 ± 0.08 b 32.7 ± 1.3 b 263.3 ± 6.6 b 0.097 ± 0.006
UNL 6.0 ± 0.08 b 39.7 ± 1.2 b 292.6 ± 15.6 a 0.100 ± 0.006

Data are presented as mean ± SEM. Data are derived from Bernal et al. [ 13].

Values with differing letters are significantly different from one another, P < 0.001.

Offspring body and ovarian weights. *

Nutritional group . Birth weight (g) . Weaning weight (g) . Adult body weight (g) . Adult ovarian weight (g) .
Control 6.1 ± 0.09 a 59.6 ± 0.7 a 301 ± 4.9 a 0.103 ± 0.005
UNP 4.8 ± 0.06 b 54.8 ± 1.2 b 292.4 ± 7.1 a 0.096 ± 0.005
UNPL 4.8 ± 0.08 b 32.7 ± 1.3 b 263.3 ± 6.6 b 0.097 ± 0.006
UNL 6.0 ± 0.08 b 39.7 ± 1.2 b 292.6 ± 15.6 a 0.100 ± 0.006
Nutritional group . Birth weight (g) . Weaning weight (g) . Adult body weight (g) . Adult ovarian weight (g) .
Control 6.1 ± 0.09 a 59.6 ± 0.7 a 301 ± 4.9 a 0.103 ± 0.005
UNP 4.8 ± 0.06 b 54.8 ± 1.2 b 292.4 ± 7.1 a 0.096 ± 0.005
UNPL 4.8 ± 0.08 b 32.7 ± 1.3 b 263.3 ± 6.6 b 0.097 ± 0.006
UNL 6.0 ± 0.08 b 39.7 ± 1.2 b 292.6 ± 15.6 a 0.100 ± 0.006

Data are presented as mean ± SEM. Data are derived from Bernal et al. [ 13].

Values with differing letters are significantly different from one another, P < 0.001.

Early Life Undernutrition Exposure Increased Ovarian ER Stress and Follicular Apoptosis but Decreased Ovarian Autophagy in Adult Offspring

Ovarian X-box binding protein 1 spliced (XBP1s), total (XBP1t), and their ratio were determined as a marker of ER stress in offspring ovaries. Ovarian XBPT1s:XBP1t mRNA ratios were significantly increased in ovaries from offspring born to undernourished mothers (P < 0.001) ( Fig. 1A). Post hoc analysis demonstrated that although UNP and UNPL offspring both showed an increased XBP1s:XBP1t ratio compared to Cont offspring, but only UNPL reached statistical significance (UNPL P < 0.001) ( Fig. 1A). Follicular apoptosis was significantly increased in ovaries from offspring born to undernourished mothers (P < 0.001) ( Fig. 1B). Post hoc analysis demonstrated a statistically significant increase in the proportion of apoptotic follicular cells in ovaries of UNP (P < 0.05), and UNPL (P < 0.05) groups compared to Cont offspring ( Fig. 1B).

Early life exposure to undernutrition increases ovarian ER stress and follicular apoptosis but decreases ovarian autophagy in adult offspring. A) Maternal undernutrition during pregnancy and lactation (UNPL) resulted in an increase mRNA levels of ER stress-related genes expressed as a ratio of XBP1s to XBP1t (n = 6–7 per group). B) Maternal undernutrition during pregnancy and during pregnancy and lactation resulted in an increase in follicular cell apoptosis (measured as TUNEL-positive staining) as a proportion of total area analyzed. C) Maternal undernutrition decreased key components of the autophagy process, including microtubule-associated protein 1A/1B-light chain 3 (LC3a) in UNP ovaries. D) Beclin 1 in ovaries of UNP and UNPL offspring. E) Photographs represent ovarian sections stained for immunopositive Beclin1 protein using DAB substrate and counterstained with hematoxylin. Immunopositive Beclin1 protein is identified by brown staining. Bars = 100 μm. Negative controls show no positive staining (data not shown) n = 5 per group. F) Gene expression data are presented as means ± SEM. One-way ANOVA main effects: maternal diet P < 0.05 for all genes. Post hoc analyses (Bonferroni): *P < 0.05 for undernourished compared to control and UNL offspring. Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone n = 6–7 per group.

Early life exposure to undernutrition increases ovarian ER stress and follicular apoptosis but decreases ovarian autophagy in adult offspring. A) Maternal undernutrition during pregnancy and lactation (UNPL) resulted in an increase mRNA levels of ER stress-related genes expressed as a ratio of XBP1s to XBP1t (n = 6–7 per group). B) Maternal undernutrition during pregnancy and during pregnancy and lactation resulted in an increase in follicular cell apoptosis (measured as TUNEL-positive staining) as a proportion of total area analyzed. C) Maternal undernutrition decreased key components of the autophagy process, including microtubule-associated protein 1A/1B-light chain 3 (LC3a) in UNP ovaries. D) Beclin 1 in ovaries of UNP and UNPL offspring. E) Photographs represent ovarian sections stained for immunopositive Beclin1 protein using DAB substrate and counterstained with hematoxylin. Immunopositive Beclin1 protein is identified by brown staining. Bars = 100 μm. Negative controls show no positive staining (data not shown) n = 5 per group. F) Gene expression data are presented as means ± SEM. One-way ANOVA main effects: maternal diet P < 0.05 for all genes. Post hoc analyses (Bonferroni): *P < 0.05 for undernourished compared to control and UNL offspring. Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone n = 6–7 per group.

Early life undernutrition exposure resulted in a significant decrease in adult ovarian mRNA levels of Beclin1 (P < 0.001), an established component of the autophagic machinery, and of the autophagasome marker LC3 (P < 0.001 Fig. 1C). Post hoc analyses showed a statistically significant decrease in Beclin1 mRNA levels in UNP (P = 0.005) and UNPL (P < 0.001) offspring compared with Cont offspring ( Fig. 1D). Although both UNP and UNPL groups showed lower levels of LC3 mRNA, post hoc analyses showed a statistically significant decrease in LC3 mRNA levels only in UNPL offspring (P < 0.001 UNP: P = 0.06) ( Fig. 1C). Ovarian sections were immunostained for Beclin1 protein to determine follicular localization. We observed that Beclin1 protein is localized in ovarian blood vessels, oocytes, and ovarian stroma ( Fig. 1E). Consistent with mRNA levels, we observed a decrease in the mean density of immunostaining of Beclin1 protein in ovarian sections in UNP (P < 0.001), and UNPL (P < 0.05) groups compared to the Cont group ( Fig. 1, E and F). UNL offspring showed similar staining to controls ( Fig. 1, E and F). Immunopositive Beclin 1 was highly localized to oocytes and blood vessels and less so in stromal, granulosa, and thecal cells. All the negative controls in immunohistochemical staining assays showed no positive staining (data not shown).

Early Life Undernutrition Exposure Reduced Ovarian Blood Vessel Density and VEGF and VEGFR2 Immunostaining in Offspring Ovaries

Early life events have been shown to modulate vascularization of organs in offspring [ 46, 47] thus, we set out to investigate whether blood vessel density was similarly altered in the ovary. Early life undernutrition exposure significantly decreased ovarian vascularization in a manner that was dependent upon timing of the undernutrition. Blood vessel density, including perifollicular capillaries, as defined by the presence of endothelial cell marker CD31 immunostaining as a proportion of total area, was significantly decreased in UNP (P < 0.05) and UNPL (P < 0.05) offspring compared to Cont ( Fig. 2). Vascularization in UNL offspring was not different to that of the Cont group.

Early life undernutrition reduces ovarian blood vessel density. Photographs represent ovarian sections immunostained for endothelial cell marker CD31 using DAB substrate and counterstained with hematoxylin. A) CD31 immunopositive protein is identified by brown staining indicative of DAB substrate. CD31-positive endothelial cell staining within ovarian blood vessel structures are indicated by white arrows. Perifollicular capillaries, that provide vascular supply to the developing follicle and/or corpus luteum, are indicated by white arrowheads. Negative controls show no positive staining (data not shown). Original magnification ×200. B) Maternal undernutrition resulted in a significant decrease in the proportion of CD31 immunostaining (expressed as percent of vessel area of total ovarian area analyzed) in offspring ovaries. Data are presented as means ± SEM. One-way ANOVA main effects: maternal diet P < 0.05 for undernourished compared to Cont offspring. Post hoc analyses (Bonferroni): *P < 0.05 compared to Cont offspring n = 5 per group. Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone.

Early life undernutrition reduces ovarian blood vessel density. Photographs represent ovarian sections immunostained for endothelial cell marker CD31 using DAB substrate and counterstained with hematoxylin. A) CD31 immunopositive protein is identified by brown staining indicative of DAB substrate. CD31-positive endothelial cell staining within ovarian blood vessel structures are indicated by white arrows. Perifollicular capillaries, that provide vascular supply to the developing follicle and/or corpus luteum, are indicated by white arrowheads. Negative controls show no positive staining (data not shown). Original magnification ×200. B) Maternal undernutrition resulted in a significant decrease in the proportion of CD31 immunostaining (expressed as percent of vessel area of total ovarian area analyzed) in offspring ovaries. Data are presented as means ± SEM. One-way ANOVA main effects: maternal diet P < 0.05 for undernourished compared to Cont offspring. Post hoc analyses (Bonferroni): *P < 0.05 compared to Cont offspring n = 5 per group. Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone.

VEGFR2 has been found to be highly expressed in stromal, granulosa, and theca cells in the rat ovary [ 48], and critical changes in sensitivity of granulosa cells to VEGF appear to be mediated through VEGFR2 [ 49]. VEGFR2 has also been shown not only to mediate vascularization, but also to function as an antiapoptotic agent in rat granulosa cells and is necessary for dominant follicle selection. Consistent with our observed increase in apoptosis and loss of vessel density, early life nutrient restriction resulted in a significant reduction in VEGF and VEGFR2 immunopresence in adult ovaries ( Fig. 3). Immunohistochemical staining showed a significant decrease in VEGF and VEGFR2 protein in stromal and follicular cells as a proportion of total area analyzed in UNP (P < 0.05) and UNPL (P < 0.05) offspring compared to Cont offspring. Similarly, offspring born to undernourished mothers demonstrated decreased VEGF and VEGFR2 colocalization in UNP (P < 0.05) and UNPL (P < 0.05) offspring compared to Cont offspring ( Fig. 3). All negative controls showed no positive staining (data not shown).

Early life undernutrition reduces VEGF, VEGFR2, and their colocalization in offspring ovaries. A) Photographs represent immunopositive staining of VEGF (green), VEGFR2 (red), and the colocalization of VEGF/VEGFR2 (yellow). Negative controls show no positive staining (data not shown). Original magnification ×200. B) Early life undernutrition resulted in a significant decrease in the proportion of VEGF, VEGFR2, and VEGF/VEGFR2 immunostaining (expressed as percent of positive stained area of total ovarian area analyzed) in offspring ovaries. One-way ANOVA main effects: maternal diet P < 0.05. Post hoc analyses (Bonferroni): *P < 0.05 for undernourished compared to control offspring (n = 5 per group). Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone. Cell types are indicated by colored arrows: granulosa cells (purple arrow), theca cells (orange arrow), and ovarian stroma (light blue arrow).

Early life undernutrition reduces VEGF, VEGFR2, and their colocalization in offspring ovaries. A) Photographs represent immunopositive staining of VEGF (green), VEGFR2 (red), and the colocalization of VEGF/VEGFR2 (yellow). Negative controls show no positive staining (data not shown). Original magnification ×200. B) Early life undernutrition resulted in a significant decrease in the proportion of VEGF, VEGFR2, and VEGF/VEGFR2 immunostaining (expressed as percent of positive stained area of total ovarian area analyzed) in offspring ovaries. One-way ANOVA main effects: maternal diet P < 0.05. Post hoc analyses (Bonferroni): *P < 0.05 for undernourished compared to control offspring (n = 5 per group). Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone. Cell types are indicated by colored arrows: granulosa cells (purple arrow), theca cells (orange arrow), and ovarian stroma (light blue arrow).

Early Life Undernutrition Exposure Altered Proinflammatory Cytokines and Upstream Signaling Molecules in Offspring Ovaries

We have previously reported that offspring exposed to early life undernutrition demonstrate increased levels of ovarian oxidative stress [ 13], and because we now demonstrated an increased in a marker of ER stress, we therefore investigated a central signaling pathway that could contribute to these observed changes. Offspring born to undernourished mothers demonstrated elevated mRNA levels of the genes that encode both the catalytic subunit (p110α) and the regulatory subunit (p85α) of PI3K, although only p110α reached statistical significance (P < 0.001) ( Fig. 4). Post hoc analysis demonstrated that mRNA levels of PIK3CA (p110α) were significantly elevated in UNP (P = 0.023) and UNPL (P < 0.001), but not UNL offspring, compared to Cont offspring ( Fig. 4). Consistent with this, ovarian nuclear factor kappa light chain enhancer of B cells (NFκB or RelA/p65) mRNA levels were significantly increased in ovaries from offspring born to undernourished mothers (P < 0.001) ( Fig. 4). Post hoc analysis demonstrated an increase in NFκB mRNA levels in UNP (P = 0.002), UNPL (P < 0.001), and UNL (P = 0.017) compared to Cont offspring ( Fig. 4). Although offspring born to undernourished mothers tended to demonstrate increased mRNA levels of the proinflammatory cytokine IL-6, this difference was not statistically significant (P = 0.063) compared to Cont offspring ( Fig. 4). Ovarian mRNA levels of IL-1β, a proinflammatory factor shown to suppress apoptosis in the rodent ovary [ 50], was decreased in offspring born to undernourished mothers (P < 0.001). Post hoc analysis demonstrated that mRNA levels of IL-1β were significantly decreased in UNP (P < 0.001) and UNPL (P < 0.001) but not UNL offspring compared to Cont ( Fig. 4).

Early life undernutrition alters proinflammatory cytokines and upstream signaling molecules in offspring ovaries. Early life undernutrition resulted in a significant increase in the catalytic subunit of PI3 kinase PI3KCA (A), p85 (B), and NFκB (C) mRNA levels, but a decrease in p21 (E) and proinflammatory IL-1β (F). D) No effect on IL-6 was observed. Data are presented as means ± SEM. One-way ANOVA main effects: maternal diet P < 0.05 for all genes except for IL-6 undernourished compared to Cont offspring. Post hoc analyses (Bonferroni): *P < 0.05 compared to Cont offspring for PI3KCA and p21 and for IL-1β *P < 0.05 compared to Cont and as well when compared to UNL (n = 6–7 per group). Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone.

Early life undernutrition alters proinflammatory cytokines and upstream signaling molecules in offspring ovaries. Early life undernutrition resulted in a significant increase in the catalytic subunit of PI3 kinase PI3KCA (A), p85 (B), and NFκB (C) mRNA levels, but a decrease in p21 (E) and proinflammatory IL-1β (F). D) No effect on IL-6 was observed. Data are presented as means ± SEM. One-way ANOVA main effects: maternal diet P < 0.05 for all genes except for IL-6 undernourished compared to Cont offspring. Post hoc analyses (Bonferroni): *P < 0.05 compared to Cont offspring for PI3KCA and p21 and for IL-1β *P < 0.05 compared to Cont and as well when compared to UNL (n = 6–7 per group). Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone.

Maternal nutrient restriction also decreased mRNA levels of the gene encoding cyclin-dependent kinase inhibitor 1 (p21) (gene CDKN1A) (P = 0.005) ( Fig. 4). Post hoc analysis demonstrated that this is largely attributable to a significant decrease in UNP offspring (P = 0.049) and not UNPL or UNL groups compared to Cont offspring ( Fig. 4). This decrease is consistent with our previously observed loss of ovarian follicles [ 13] and p21's role in inhibiting cell proliferation.

Early Life Undernutrition Exposure Reduced Ovarian Levels of the Melatonin Synthesizing Enzyme HIOMT

Melatonin, in addition to its role in circadian rhythmicity, is also a known antioxidant in the ovary [ 39]. Because we have previously shown that early life undernutrition resulted in increased ovarian oxidative stress levels [ 13], we investigated whether this may be associated with changes in the capacity of the ovary to produce melatonin. Early life undernutrition resulted in a significant decrease in HIOMT mRNA levels (P = 0.002) ( Fig. 5). Post hoc analysis demonstrated that although UNP offspring tended to have lower HIOMT mRNA levels, differences were significant only in UNPL (P = 0.038) offspring compared to Cont and UNL offspring ( Fig. 5). We were unable to find detectable mRNA levels of the two known melatonin receptors in the ovary [ 51].

Early life undernutrition alters ovarian levels of HIOMT. Early life undernutrition resulted in a significant decrease in ovarian mRNA expression of hydroxyindole O-methyltransferase (HIOMT) in a manner that is dependent upon the timing of nutrient restriction. Data are presented as means ± SEM. One-way ANOVA main effect: maternal diet P < 0.05 for undernourished compared to Cont offspring. Post hoc analyses (Bonferroni): *P < 0.05 for UNPL (P = 0.1 UNP) compared to Cont and UNL offspring (n = 6–7 per group). Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone.

Early life undernutrition alters ovarian levels of HIOMT. Early life undernutrition resulted in a significant decrease in ovarian mRNA expression of hydroxyindole O-methyltransferase (HIOMT) in a manner that is dependent upon the timing of nutrient restriction. Data are presented as means ± SEM. One-way ANOVA main effect: maternal diet P < 0.05 for undernourished compared to Cont offspring. Post hoc analyses (Bonferroni): *P < 0.05 for UNPL (P = 0.1 UNP) compared to Cont and UNL offspring (n = 6–7 per group). Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone.

Early Life Undernutrition Exposure Altered Core Circadian Clock Genes in Offspring Ovaries

A close relationship exists between melatonin and clock genes [ 40, 52], and alterations in clock-controlled gene expression due to prenatal malnutrition have been linked to metabolic dysfunction in offspring later in life [ 53]. Clock gene knockout mice have illustrated the importance of clock genes in the regulation of reproductive function [ 54], and recently, maternal obesity has been associated with altered clock gene expression in offspring ovaries [ 41]. Thus, we investigated the effect of early life undernutrition exposure on offspring ovarian mRNA levels of core circadian clock genes. Early life undernutrition resulted in a significant increase in CLOCK mRNA levels (P = 0.015). Post hoc analysis demonstrated an increase in ovarian Clock mRNA levels in UNPL (P = 0.028) and UNL (P = 0.046), but not UNP offspring compared to Cont offspring ( Fig. 6). Although early life undernutrition tended to increase BMAL1 (also known as Arntl) mRNA levels, this difference was not statistically significant (P = 0.081). Ovarian cryptochrome 1 (CRY1) mRNA levels were significantly higher in undernourished offspring (main effect P < 0.001 Fig. 6). Post hoc analysis demonstrated that undernourished offspring showed higher ovarian CRY1 mRNA levels compared to Cont offspring, regardless of the timing of maternal undernutrition (UNP, P < 0.001 UNPL, P = 0.004 UNL, P = 0.031) ( Fig. 6). There was no effect of early life undernutrition exposure on ovarian CRY2 mRNA levels (P = 0.464). Early life undernutrition exposure resulted in a significant increase in ovarian Period 1 (PER1) mRNA levels (P = 0.033) in offspring. Post hoc analysis demonstrated that this increase was largely due to an increase in ovarian PER1 mRNA levels in UNP (P = 0.02) compared to Cont offspring ( Fig. 6) although UNPL and UNL levels tended to be higher, these differences were not statistically significant. There was a significant main effect of early life undernutrition on ovarian PER2 mRNA levels in offspring (P = 0.025), but post hoc analysis demonstrated no differences between groups. The mRNA levels of the transcriptional repressor Rev-erbα, involved in circadian rhythmicity, were not affected by early life undernutrition (P = 0.1) (data not shown).

Early life undernutrition alters core circadian clock genes in offspring ovaries. A, B, C, E) Early life undernutrition resulted in a significant increase in ovarian mRNA expression of core clock genes in the ovary in a manner that is dependent upon the timing of nutrient restriction: CLOCK (A), BMAL 1 (B), CRY1 (C), PER1 (E). Data are presented as means ± SEM. One-way ANOVA main effects: maternal diet P < 0.05 for all genes except for PER2 (F) and CRY2 (D) levels in undernourished compared to Cont offspring. Post hoc analyses (Bonferroni): *P < 0.05 compared to Cont offspring (n = 6–7 per group). Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone.

Early life undernutrition alters core circadian clock genes in offspring ovaries. A, B, C, E) Early life undernutrition resulted in a significant increase in ovarian mRNA expression of core clock genes in the ovary in a manner that is dependent upon the timing of nutrient restriction: CLOCK (A), BMAL 1 (B), CRY1 (C), PER1 (E). Data are presented as means ± SEM. One-way ANOVA main effects: maternal diet P < 0.05 for all genes except for PER2 (F) and CRY2 (D) levels in undernourished compared to Cont offspring. Post hoc analyses (Bonferroni): *P < 0.05 compared to Cont offspring (n = 6–7 per group). Cont, offspring of mothers fed a control diet UNP, offspring of mothers undernourished during pregnancy alone UNPL, offspring of mothers undernourished during pregnancy and lactation UNL, offspring of mothers undernourished during lactation alone.


Substrate Edit

MTases can be divided into three different groups on the basis of the chemical reactions they catalyze:

  • m6A - those that generate N6-methyladenineEC2.1.1.72
  • m4C - those that generate N4-methylcytosineEC2.1.1.113
  • m5C - those that generate C5-methylcytosineEC2.1.1.37

m6A and m4C methyltransferases are found primarily in prokaryotes (although recent evidence has suggested that m6A is abundant in eukaryotes [1] ). m5C methyltransfereases are found in some lower eukaryotes, in most higher plants, and in animals beginning with the echinoderms.

The m6A methyltransferases (N-6 adenine-specific DNA methylase) (A-Mtase) are enzymes that specifically methylate the amino group at the C-6 position of adenines in DNA. They are found in the three existing types of bacterial restriction-modification systems (in type I system the A-Mtase is the product of the hsdM gene, and in type III it is the product of the mod gene). These enzymes are responsible for the methylation of specific DNA sequences in order to prevent the host from digesting its own genome via its restriction enzymes. These methylases have the same sequence specificity as their corresponding restriction enzymes. These enzymes contain a conserved motif Asp/Asn-Pro-Pro-Tyr/Phe in their N-terminal section, this conserved region could be involved in substrate binding or in the catalytic activity. [2] [3] [4] [5] The structure of N6-MTase TaqI (M.TaqI) has been resolved to 2.4 A. The molecule folds into 2 domains, an N-terminal catalytic domain, which contains the catalytic and cofactor binding sites, and comprises a central 9-stranded beta-sheet, surrounded by 5 helices and a C-terminal DNA recognition domain, which is formed by 4 small beta-sheets and 8 alpha-helices. The N- and C-terminal domains form a cleft that accommodates the DNA substrate. [6] A classification of N-MTases has been proposed, based on conserved motif (CM) arrangements. [5] According to this classification, N6-MTases that have a DPPY motif (CM II) occurring after the FxGxG motif (CM I) are designated D12 class N6-adenine MTases. The type I restriction and modification system is composed of three polypeptides R, M and S. The M (hsdM) and S subunits together form a methyltransferase that methylates two adenine residues in complementary strands of a bipartite DNA recognition sequence. In the presence of the R subunit, the complex can also act as an endonuclease, binding to the same target sequence but cutting the DNA some distance from this site. Whether the DNA is cut or modified depends on the methylation state of the target sequence. When the target site is unmodified, the DNA is cut. When the target site is hemimethylated, the complex acts as a maintenance methyltransferase, modifying the DNA so that both strands become methylated. hsdM contains an alpha-helical domain at the N-terminus, the HsdM N-terminal domain. [7]

Among the m6A methyltransferases (N-6 adenine-specific DNA methylase) there is a group of orphan MTases that do not participate in the bacterial restriction/methylation system. [8] These enzymes have a regulatory role in gene expression and cell cycle regulation. EcoDam from E. coli [9] and CcrM from Caulobacter crescentus [10] are well characterized members of these family. More recently, CamA from Clostridioides difficile, was shown to play key functional roles in sporulation, biofilm formations and host-adaptation. [11]

m4C methyltransferases (N-4 cytosine-specific DNA methylases) are enzymes that specifically methylate the amino group at the C-4 position of cytosines in DNA. [5] Such enzymes are found as components of type II restriction-modification systems in prokaryotes. Such enzymes recognise a specific sequence in DNA and methylate a cytosine in that sequence. By this action they protect DNA from cleavage by type II restriction enzymes that recognise the same sequence

m5C methyltransferases (C-5 cytosine-specific DNA methylase) (C5 Mtase) are enzymes that specifically methylate the C-5 carbon of cytosines in DNA to produce C5-methylcytosine. [12] [13] [14] In mammalian cells, cytosine-specific methyltransferases methylate certain CpG sequences, which are believed to modulate gene expression and cell differentiation. In bacteria, these enzymes are a component of restriction-modification systems and serve as valuable tools for the manipulation of DNA. [13] [15] The structure of HhaI methyltransferase (M.HhaI) has been resolved to 2.5 A: the molecule folds into 2 domains - a larger catalytic domain containing catalytic and cofactor binding sites, and a smaller DNA recognition domain. [16]

Highly conserved DNA methyltransferases of the m4C, m5C, and m6A types have been reported, [17] which appear as promising targets for the development of novel epigenetic inhibitors to fight bacterial virulence, antibiotic resistance, among other biomedical applications.

De novo vs. maintenance Edit

De novo methyltransferases recognize something in the DNA that allows them to newly methylate cytosines. These are expressed mainly in early embryo development and they set up the pattern of methylation.

Maintenance methyltransferases add methylation to DNA when one strand is already methylated. These work throughout the life of the organism to maintain the methylation pattern that had been established by the de novo methyltransferases.

Three active DNA methyltransferases have been identified in mammals. They are named DNMT1, [18] DNMT3a, [19] and DNMT3b. [20] Recently, a fourth enzyme DNMT3c has been discovered specifically expressed in the male germline in the mouse. [21]

DNMT3L [22] is a protein closely related to DNMT3a and DNMT3b in structure and critical for DNA methylation, but appears to be inactive on its own.

DNMT1 Edit

DNMT1 is the most abundant DNA methyltransferase in mammalian cells, and considered to be the key maintenance methyltransferase in mammals. It predominantly methylates hemimethylated CpG di-nucleotides in the mammalian genome. Despite being able to use hemimethylated as well as unmethylated cytosine as a substrate DNMT1 is not involved in de novo methyaltion of the genome during mouse embryonic development. [23] The recognition motif for the human enzyme involves only three of the bases in the CpG dinucleotide pair: a C on one strand and CpG on the other. This relaxed substrate specificity requirement allows it to methylate unusual structures like DNA slippage intermediates at de novo rates that equal its maintenance rate. [24] Like other DNA cytosine-5 methyltransferases the human enzyme recognizes flipped out cytosines in double stranded DNA and operates by the nucleophilic attack mechanism. [25] In human cancer cells DNMT1 is responsible for both de novo and maintenance methylation of tumor suppressor genes. [26] [27] The enzyme is about 1,620 amino acids long. The first 1,100 amino acids constitute the regulatory domain of the enzyme, and the remaining residues constitute the catalytic domain. These are joined by Gly-Lys repeats. Both domains are required for the catalytic function of DNMT1.

DNMT1 has several isoforms, the somatic DNMT1, a splice variant (DNMT1b) and an oocyte-specific isoform (DNMT1o). DNMT1o is synthesized and stored in the cytoplasm of the oocyte and translocated to the cell nucleus during early embryonic development, while the somatic DNMT1 is always found in the nucleus of somatic tissue.

DNMT1 null mutant embryonic stem cells were viable and contained a small percentage of methylated DNA and methyltransferase activity. Mouse embryos homozygous for a deletion in Dnmt1 die at 10–11 days gestation. [28]

TRDMT1 Edit

Although this enzyme has strong sequence similarities with 5-methylcytosine methyltransferases of both prokaryotes and eukaryotes, in 2006, the enzyme was shown to methylate position 38 in aspartic acid transfer RNA and does not methylate DNA. [29] The name for this methyltransferase has been changed from DNMT2 to TRDMT1 (tRNA aspartic acid methyltransferase 1) to better reflect its biological function. [30] TRDMT1 is the first RNA cytosine methyltransferase to be identified in human cells.

DNMT3 Edit

DNMT3 is a family of DNA methyltransferases that could methylate hemimethylated and unmethylated CpG at the same rate. The architecture of DNMT3 enzymes is similar to that of DNMT1, with a regulatory region attached to a catalytic domain. There are four known members of the DNMT3 family: DNMT3a, 3b, 3c and 3L.

DNMT3a and DNMT3b can mediate methylation-independent gene repression. DNMT3a can co-localize with heterochromatin protein (HP1) and methyl-CpG-binding protein (MeCBP). They can also interact with DNMT1, which might be a co-operative event during DNA methylation. DNMT3a prefers CpG methylation to CpA, CpT, and CpC methylation, though there appears to be some sequence preference of methylation for DNMT3a and DNMT3b. DNMT3a methylates CpG sites at a rate much slower than DNMT1, but greater than DNMT3b.

DNMT3L contains DNA methyltransferase motifs and is required for establishing maternal genomic imprints, despite being catalytically inactive. DNMT3L is expressed during gametogenesis when genomic imprinting takes place. The loss of DNMT3L leads to bi-allelic expression of genes normally not expressed by the maternal allele. DNMT3L interacts with DNMT3a and DNMT3b and co-localized in the nucleus. Though DNMT3L appears incapable of methylation, it may participate in transcriptional repression.

DNMT inhibitors Edit

Because of the epigenetic effects of the DNMT family, some DNMT inhibitors are under investigation for treatment of some cancers: [31]


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