Transcriptome dynamics and molecular cross-talk between bovine oocyte and its companion cumulus cells

The bi-directional communication between the oocyte and its companion cumulus cells (CCs) is crucial for development and functions of both cell types. The objectives of this study were to identify transcripts that are exclusively expressed either in oocyte or CCs and those which are differentially expressed when the oocyte matures with or with out their companion CCs and vice versa and to investigate functional changes associated with transcripts that are significantly changed during CCs in vitro maturation (IVM). In experiment 1A, CCs were physically removed from oocytes at GV stage by repeated in and out pipetting and the resulting denuded oocytes (DOs) and their companion CCs were frozen. In experiment 1B, intact COCs were cultured; CCs were physically removed and the resulting denuded MII oocytes and their CCs were frozen. In experiment 2, CCs were physically removed from oocytes at GV stage and the resulting (OO-CCs) and other pools of intact oocytes (OO+CCs) were cultured and their CCs were physically removed and both oocytes were frozen. In experiment 3, the ooplasm were micro surgically removed at GV stage and the resulting oocytectomized complexes (CCs-OO) and other intact complexes (CCs+OO) were cultured. The ooplasm were removed from CCs+OO and the resulting MII CCs frozen. In experiment 4, CCs were physically removed from their enclosed oocytes both at GV and MII stages and frozen for subsequent total RNA isolation. In both cases, cells were cultured for 22 hrs and each experiment was repeated three times using pools of biological replicates (n=150). 15 μg of fragmented and biotin labelled cRNA was hybridized with Affymetrix GeneChip®Bovine Genome Array and data were analyzed using linear model for microarray. Significantly changed gene ontology (GO) terms, gene networks and canonical pathways were analyzed using GO consortium and Ingenuity pathway analysis (IPA) respectively. In experiment 1A, of 13162 detected probe sets, 1516 and 2727 are exclusively expressed in GV oocytes and CCs respectively, and 8919 are expressed in both. Similarly, in experiment 1B, of 13602 detected probe sets, 1423 and 3100 are exclusively expressed in MII oocytes and CCs respectively, and 9079 are expressed in both. In experiment 2, 265 transcripts are differentially expressed of which 217 and 48 are over expressed in OO+CCs and OO-CCs, respectively. In experiment 3, of 566 differentially expressed transcripts, 320 and 246 are over expressed in CCs+OO and CCs-OO, respectively. In experiment 4, of 12827 detected probe sets, 4689 and 834 are exclusively expressed in GV and MII CCs respectively, while 7304 are expressed in both. Oocyte specific transcripts include those involved in transcription (IRF6, POU5F1, MYF5, MED18), translation (EIF2AK1, EIF4ENIF1), biopolymer metabolic process (MOS, ACVR1, ZNF529, MAP3K3), DNA replication (MCM6, NASP, ORC6L), protein amino acid phosphorylation (MAP4K2, PRKCH, MOS) and CC specific ones include those involved in macromolecule biosynthetic process (APOA1, USPL1, APOE, NANS), carbohydrate metabolism (HYAL1, PFKL, PYGL, MPI), protein metabolic processes (IHH, APOA1, PLOD1), steroid biosynthetic process (APOA1, CYP11A1, HSD3B1, HSD3B7). While transcripts over expressed in OO+CCs are involved in carbohydrate metabolism (ACO1, 2), molecular transport (GAPDH, GFPT1) and nucleic acid metabolism (CBS, NOS2), those over expressed in CCs+OO are involved in cellular growth and proliferation (FOS, GADD45A), cell cycle (HAS2, VEGFA), cellular development (AMD1, AURKA, DPP4) and gene expression (FOSB, TGFB2). Signal transduction, cholesterol biosynthetic processes, DNA replication, cellular growth and proliferation, actin filament polymerisation and cell adhesion are among the top significantly changed biological functions associated with transcripts that are differentially expressed between GV and MII CCs. In conclusion, this study generated large scale gene expression data from different oocyte and CCs samples that would enhance our understanding of the molecular mechanisms underlying oocyte-CCs dialogue in general and oocyte maturation in particular.Transkriptomedynamik und molekulare Kommunikation zwischen Rindereizellen und deren umgebenden Kumuluszellen Die bidirektionale Kommunikation zwischen der Eizelle und den sie umgebenden Kumuluszellen (CCs) ist ausschlaggebend für die Entwicklung und Funktion beider Zelltypen. Die Ziele dieser Studie waren Transkripte zu identifizieren, die ausschließlich in den Eizellen oder den CCs exprimiert werden, sowie Transkripte, die unterschiedlich während der Maturation der Eizellen mit oder ohne der sie umgebenden Kumuluszellen exprimiert werden und umgekehrt. Zum Schluss sollten funktionelle Änderungen untersucht werden, welche mit Trankripten assoziiert sind, die sich signifikant während der in vitro Maturation (IVM) ändern. Im Experiment 1A wurden die CCs physikalisch von den Eizellen im GV Stadium durch wiederholtes Pipettieren entfernt und die freiliegenden Eizellen (DOs) sowie die CCs eingefroren. Im Versuch 1B wurden die intakten Kumulus-Eizellen-Komplexe (COCs) kultiviert, anschließend die CCs physikalisch entfernt und die freiliegenden MII Eizellen und die CCs eingefroren. Im Experiment 2 wurden die CCs wiederum physikalisch während des GV Stadiums entfernt und sowohl die daraus resultierenden Eizellen ohne CCs (OO-CCs) als auch Pools mit intakten Eizellen (OO+CCs) wurden kultiviert. Danach wurden die CCs von den intakten Eizellen entfernt und alle Eizellen eingefroren. Im Experiment 3 wurde das Ooplasma mikro-chirurgisch im GV Stadium entfernt und die Eizellenektomierten Komplexe (CCs-OO) sowie andere intakte Komplexe (CCs+OO) kultiviert. Das Ooplasma wurde im MII Stadium ebenfalls von den CCs+OO entfernt und die MII CCs eingefroren. Im vierten Experiment wurden die CCs sowohl im GV als auch im MII Stadium physikalisch von den Eizellen entfernt und für die nachfolgende totale RNA Isolation eingefroren. In beiden Fällen wurden die Zellen 22h kultiviert und jedes Experiment wurde dreimal wiederholt, indem Pools von biologischen Replikaten (n = 150) verwendet wurden. 15 μg der fragmentierten und Biotin-gelabelten cRNA wurden mit dem Affymetrix GeneChip®Bovine Genome Array hybridisiert und die Daten wurden mittels eines linearen Models für Microarray Daten analysiert. Signifikant veränderte Genontologie (GO), Gennetzwerke und kanonische Pathways wurden mit Hilfe von GO Konsortien beziehungsweise der Ingenuity Pathway Analyse (IPA) untersucht. Im Versuch 1A wurden von 13162 detektierten Proben 1516 ausschließlich in den GV Eizellen und 2727 in den GV CCs exprimiert, wohingegen 8919 Proben sowohl in den Eizellen als auch den CCs exprimiert wurden. Ähnliche Ergebnisse wurden im Experiment 1B erzielt. Hierbei wurden von 13602 detektierten Proben 1423 ausschließlich in MII Eizellen sowie 3100 in MII CCs exprimiert. 9079 Proben wurden in beiden Zelltypen exprimiert. Beim zweiten Versuch wurden 265 Transkripte unterschiedlich exprimiert, wovon 217 in OO+CCs beziehungsweise 48 in OO-CCs überexprimiert wurden. Im Versuch 3 wurden von den 566 Transkripte 320 in CCs+OO beziehungsweise 246 in CCs-OO überexprimiert. Beim vierten Experiment wurden von 12827 detektierten Proben 4689 ausschließlich in CCs des GV Stadiums sowie 834 in den CCs des MII Stadiums exprimiert, wohingegen 7304 in beiden Stadien exprimiert wurden. Eizell-spezifische Transkripte beinhalten Gene, die bei der Transkription (IRF6, POU5F1, MYF5, MED18), der Translation (EIF2AK1, EIF4ENIF1), den biopolymer-metabolischen Prozessen (MOS, ACVR1, ZNF529, MAP3K3), der DNA Replikation (MCM6, NASP, ORC6L) sowie an der Protein-Aminosäuren Phosphorylierung (MAP4K4, PRKCH, MOS) beteiligt sind. Die CCs-spezifischen Transkripte schließen Gene mit ein, die für die makromolekularen, biosynthetischen Prozesse (APOA1, USPL1, APOE; NANS), den Carbohydratmetabolismus (HYAl, PFKL, PYGL, MPI), die Protein-metabolischen Prozesse (IHH, APOA1, PLOD1) und für die Steroid-biosynthetischen Prozesse (APOA1, CYP11A1, HSD3B1, HSD3B7) verantwortlich sind. Während Transkripte, die in den OO+CCs überexprimiert wurden, am Carbohydratmetabolismus (ACO1 und 2), am molekularen Transport (GAPDH, GFPT1) und am Nukleinsäurenmetabolismus (CBS, NOS2) involviert sind, sind Transkripte, die in CCs+OO überexprimiert wurden, für das zelluläre Wachstum und die zelluläre Proliferation (FOS, GADD45A), den Zellzyklus (HAS2, VEGFA), die zelluläre Entwicklung (AMD1, AURKA, DPP4) und die Genexpression (FOSB, TGFB2) verantwortlich. Die Signalübertragung, der Cholesterol-biosynthetische Prozess, die DNA Replikation, das zelluläre Wachstum und die zelluläre Proliferation, die Aktinfilament Polymerisation und die Zelladhäsion gehören zu den, sich am signifikantesten verändernden, biologischen Funktionen, welche mit den Transkripten in Verbindung stehen, die zwischen dem GV und MII Stadium unterschiedlich exprimiert wurden. Zusammenfassend lässt sich sagen, dass diese Studie eine große Anzahl an Genexpressionsdaten von unterschiedlichen Eizellen und CCs Proben generiert hat, die unser Verständnis für die molekularen Mechanismen, welche dem Eizellen –Kumuluszellen Dialog im Allgemeinen und Maturation der Eizelle im Speziellen unterliegen, verbessern könnten

Systematic review and meta-analysis: prevalence of alcohol use among young people in eastern Africa.

OBJECTIVE: Systematic review and meta-analysis of published studies of alcohol use among young people (age 15-24 years) in eastern Africa to estimate prevalence of alcohol use and determine the extent of use of standardised screening questionnaires in alcohol studies. METHODS: Five databases (MEDLINE, EMBASE, Global Health, Africa-wide, and PsycINFO) were searched for publications until 30th June 2013. Results were summarised using the guidelines on preferred reporting items for systematic reviews and meta-analyses (PRISMA) and on quality assessment using the modified quality assessment tool for systematic reviews of observational studies (QATSO). Heterogeneity was assessed using the I(2) statistic (DerSimonian-Laird). RESULTS: We identified 2785 potentially relevant studies, of which 56 were eligible for inclusion. Only two studies (4%) used the standardised Alcohol Use Disorder Identification Test (AUDIT) questionnaire, and six studies (13%) used the Cut down, Annoyed, Guilt, Eye opener (CAGE) questionnaire. The reported median prevalence of alcohol use was ever-use 52% [interquartile range (IQR): 20-58%], use in the last month 28% (IQR: 17-37%), use in the last year 26% (IQR: 22-32%), and problem drinking as defined by CAGE or AUDIT 15% (IQR: 3-36%). We observed high heterogeneity between studies, with the highest prevalence of ever use of alcohol among university students (82%; 95%CI: 79-85%) and female sex workers (66%; 95%CI: 58-74%). Current use was most prevalent among male sex workers (69%; 95%CI: 63-75%). CONCLUSIONS: Reported alcohol use and problem drinking were common among diverse groups of young people in eastern Africa, indicating the urgent need for alcohol-focused interventions in this population. Few studies have used standardised alcohol screening questionnaires. Epidemiological research to investigate alcohol-focused interventions in young people should aim to apply such questionnaires that should be validated for use in this population

Trends in HIV/AIDS morbidity and mortality in Eastern 3 Mediterranean countries, 1990–2015: findings from the Global 4 Burden of Disease 2015 study

Objectives We used the results of the Global Burden of Disease 2015 study to estimate trends of HIV/AIDS burden in Eastern Mediterranean Region (EMR) countries between 1990 and 2015. Methods Tailored estimation methods were used to produce final estimates of mortality. Years of life lost (YLLs) were calculated by multiplying the mortality rate by population by age-specific life expectancy. Years lived with disability (YLDs) were computed as the prevalence of a sequela multiplied by its disability weight. Results In 2015, the rate of HIV/AIDS deaths in the EMR was 1.8 (1.4–2.5) per 100,000 population, a 43% increase from 1990 (0.3; 0.2–0.8). Consequently, the rate of YLLs due to HIV/AIDS increased from 15.3 (7.6–36.2) per 100,000 in 1990 to 81.9 (65.3–114.4) in 2015. The rate of YLDs increased from 1.3 (0.6–3.1) in 1990 to 4.4 (2.7–6.6) in 2015. Conclusions HIV/AIDS morbidity and mortality increased in the EMR since 1990. To reverse this trend and achieve epidemic control, EMR countries should strengthen HIV surveillance,and scale up HIV antiretroviral therapy and comprehensive prevention services

Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000–2018

Abstract: Exclusive breastfeeding (EBF)—giving infants only breast-milk for the first 6 months of life—is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization’s Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030

Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018

Anemia is a globally widespread condition in women and is associated with reduced economic productivity and increased mortality worldwide. Here we map annual 2000–2018 geospatial estimates of anemia prevalence in women of reproductive age (15–49 years) across 82 low- and middle-income countries (LMICs), stratify anemia by severity and aggregate results to policy-relevant administrative and national levels. Additionally, we provide subnational disparity analyses to provide a comprehensive overview of anemia prevalence inequalities within these countries and predict progress toward the World Health Organization’s Global Nutrition Target (WHO GNT) to reduce anemia by half by 2030. Our results demonstrate widespread moderate improvements in overall anemia prevalence but identify only three LMICs with a high probability of achieving the WHO GNT by 2030 at a national scale, and no LMIC is expected to achieve the target in all their subnational administrative units. Our maps show where large within-country disparities occur, as well as areas likely to fall short of the WHO GNT, offering precision public health tools so that adequate resource allocation and subsequent interventions can be targeted to the most vulnerable populations.Peer reviewe

Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000–2018

Exclusive breastfeeding (EBF)-giving infants only breast-milk for the first 6 months of life-is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization's Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030.This work was primarily supported by grant no. OPP1132415 from the Bill & Melinda Gates Foundation. Co-authors used by the Bill & Melinda Gates Foundation (E.G.P. and R.R.3) provided feedback on initial maps and drafts of this manuscript. L.G.A. has received support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES), Código de Financiamento 001 and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (grant nos. 404710/2018-2 and 310797/2019-5). O.O.Adetokunboh acknowledges the National Research Foundation, Department of Science and Innovation and South African Centre for Epidemiological Modelling and Analysis. M.Ausloos, A.Pana and C.H. are partially supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P4-ID-PCCF-2016-0084. P.C.B. would like to acknowledge the support of F. Alam and A. Hussain. T.W.B. was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. K.Deribe is supported by the Wellcome Trust (grant no. 201900/Z/16/Z) as part of his international intermediate fellowship. C.H. and A.Pana are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P2-2.1-SOL-2020-2-0351. B.Hwang is partially supported by China Medical University (CMU109-MF-63), Taichung, Taiwan. M.Khan acknowledges Jatiya Kabi Kazi Nazrul Islam University for their support. A.M.K. acknowledges the other collaborators and the corresponding author. Y.K. was supported by the Research Management Centre, Xiamen University Malaysia (grant no. XMUMRF/2020-C6/ITM/0004). K.Krishan is supported by a DST PURSE grant and UGC Centre of Advanced Study (CAS II) awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M.Kumar would like to acknowledge FIC/NIH K43 TW010716-03. I.L. is a member of the Sistema Nacional de Investigación (SNI), which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT), Panamá. M.L. was supported by China Medical University, Taiwan (CMU109-N-22 and CMU109-MF-118). W.M. is currently a programme analyst in Population and Development at the United Nations Population Fund (UNFPA) Country Office in Peru, which does not necessarily endorses this study. D.E.N. acknowledges Cochrane South Africa, South African Medical Research Council. G.C.P. is supported by an NHMRC research fellowship. P.Rathi acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India. Ramu Rawat acknowledges the support of the GBD Secretariat for supporting the reviewing and collaboration of this paper. B.R. acknowledges support from Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal. A.Ribeiro was supported by National Funds through FCT, under the programme of ‘Stimulus of Scientific Employment—Individual Support’ within the contract no. info:eu-repo/grantAgreement/FCT/CEEC IND 2018/CEECIND/02386/2018/CP1538/CT0001/PT. S.Sajadi acknowledges colleagues at Global Burden of Diseases and Local Burden of Disease. A.M.S. acknowledges the support from the Egyptian Fulbright Mission Program. F.S. was supported by the Shenzhen Science and Technology Program (grant no. KQTD20190929172835662). A.Sheikh is supported by Health Data Research UK. B.K.S. acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal for all the academic support. B.U. acknowledges support from Manipal Academy of Higher Education, Manipal. C.S.W. is supported by the South African Medical Research Council. Y.Z. was supported by Science and Technology Research Project of Hubei Provincial Department of Education (grant no. Q20201104) and Outstanding Young and Middle-aged Technology Innovation Team Project of Hubei Provincial Department of Education (grant no. T2020003). The funders of the study had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. All maps presented in this study are generated by the authors and no permissions are required to publish them

Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018

Anemia is a globally widespread condition in women and is associated with reduced economic productivity and increased mortality worldwide. Here we map annual 2000–2018 geospatial estimates of anemia prevalence in women of reproductive age (15–49 years) across 82 low- and middle-income countries (LMICs), stratify anemia by severity and aggregate results to policy-relevant administrative and national levels. Additionally, we provide subnational disparity analyses to provide a comprehensive overview of anemia prevalence inequalities within these countries and predict progress toward the World Health Organization’s Global Nutrition Target (WHO GNT) to reduce anemia by half by 2030. Our results demonstrate widespread moderate improvements in overall anemia prevalence but identify only three LMICs with a high probability of achieving the WHO GNT by 2030 at a national scale, and no LMIC is expected to achieve the target in all their subnational administrative units. Our maps show where large within-country disparities occur, as well as areas likely to fall short of the WHO GNT, offering precision public health tools so that adequate resource allocation and subsequent interventions can be targeted to the most vulnerable populations