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Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USARobert C. Reiner Jr., Catherine A. Welgan, Christopher E. Troeger, Mathew M. Baumann, Aniruddha Deshpande, Brigette F. Blacker, Molly K. Miller-Petrie, Lucas Earl, Daniel C. Casey, Aubrey J. Cook, Farah Daoud, Nicole Davis Weaver, Samath Dhamminda Dharmaratne, Laura Dwyer-Lindgren, Valery L. Feigin, Joseph Jon Frostad, Kimberly B. Johnson, Alice Lazzar-Atwood, Kate E. LeGrand, Stephen S. Lim, Paulina A. Lindstedt, Laurie B. Marczak, Benjamin K. Mayala, Ali H. Mokdad, Jonathan F. Mosser, Chrisopher J. L. Murray, QuynhAnh P. Nguyen, David M. Pigott, Puja C. Rao, David L. Smith, Emma Elizabeth Spurlock & Simon I. HayDepartment of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USARobert C. Reiner Jr., Samath Dhamminda Dharmaratne, Laura Dwyer-Lindgren, Stephen S. Lim, Ali H. Mokdad, Chrisopher J. L. Murray, David M. Pigott, Benn Sartorius, David L. Smith & Simon I. 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FeiginAssociated Laboratory for Green Chemistry (LAQV), University of Porto, Porto, PortugalEduarda FernandesResearch Center on Public Health, University of Milan Bicocca, Monza, ItalyPietro FerraraInstitute of Gerontological Health Services and Nursing Research, Ravensburg-Weingarten University of Applied Sciences, Weingarten, GermanyFlorian FischerInstitute of Gerontology, National Academy of Medical Sciences of Ukraine, Kyiv, UkraineNataliya A. FoigtDepartment of Child Dental Health, Obafemi Awolowo University, Ile-Ife, NigeriaMorenike Oluwatoyin FolayanDepartment of Medical Parasitology, Abadan Faculty of Medical Sciences, Abadan, IranMasoud ForoutanDepartment of Dermatology, Kobe University, Kobe, JapanTakeshi FukumotoDepartment of Community Medicine, Datta Meghe Institute of Medical Sciences, Wardha, IndiaAbhay Motiramji Gaidhane, Zahiruddin Quazi Syed & Deepak SaxenaDepartment of Pediatric Nursing, Aksum University, Aksum, EthiopiaHailemikael Gebrekidan G. K. GebrekrstosSchool of Pharmacy, Aksum University, Aksum, EthiopiaLeake GebremeskelDepartment of Pharmacy, Mekelle University, Mekelle, EthiopiaLeake GebremeskelDepartment of Reproductive Health, Mekelle University, Mekelle, EthiopiaAssefa Ayalew GebreslassieTelethon Kids Institute, Perth Children’s Hospital, Nedlands, WA, AustraliaPeter W. GethingCurtin University, Bentley, WA, AustraliaPeter W. GethingDepartment of Biostatistics, Mekelle University, Mekelle, EthiopiaKebede Embaye GezaeInfectious Disease Research Center, Kermanshah University of Medical Sciences, Kermanshah, IranKeyghobad GhadiriPediatric Department, Kermanshah University of Medical Sciences, Kermanshah, IranKeyghobad GhadiriStudent Research Committee, Iran University of Medical Sciences, Tehran, IranAhmad GhashghaeeHealth Systems and Policy Research, Indian Institute of Public Health Gandhinagar, Gandhinagar, IndiaMahaveer GolechhaDepartment of Family and Community Medicine, University Of Sulaimani, Sulaimani, IraqMohammed Ibrahim Mohialdeen GubariDepartment of Pediatrics and Child Health, Mekelle University, Mekelle, EthiopiaFikaden Berhe HadguSchool of Health and Environmental Studies, Hamdan Bin Mohammed Smart University, Dubai, United Arab EmiratesSamer HamidiDepartment of Public Health, Wachemo University, Hossana, EthiopiaDemelash Woldeyohannes HandisoDepartment of Public Health, Jigjiga University, Jijiga, EthiopiaAbdiwahab Hashi & Muktar Omer OmerCenter for International Health (CIH), University of Bergen, Bergen, NorwayShoaib HassanBergen Center for Ethics and Priority Setting (BCEPS), University of Bergen, Bergen, NorwayShoaib HassanInstitute of Pharmaceutical Sciences, University of Veterinary and Animal Sciences, Lahore, PakistanKhezar HayatDepartment of Pharmacy Administration and Clinical Pharmacy, Xian Jiaotong University, Xian, ChinaKhezar HayatSchool of Business, London South Bank University, London, UKClaudiu HerteliuDepartment of Urban Planning and Design, University of Hong Kong, Hong Kong, ChinaHung Chak HoKasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, IndiaRamesh Holla & Priya RathiInstitute of Research and Development, Duy Tan University, Da Nang, VietnamMehdi Hosseinzadeh & Yasser VasseghianDepartment of Computer Science, University of Human Development, Sulaymaniyah, IraqMehdi HosseinzadehCollege of Science and Engineering, Hamad Bin Khalifa University, Doha, QatarMowafa HousehSchool of Pharmaceutical Sciences, University of Science Malaysia, Penang, MalaysiaRabia HussainDepartment of Occupational Safety and Health, China Medical University, Taichung, TaiwanBing-Fang HwangDepartment of Health Promotion and Education, University of Ibadan, Ibadan, NigeriaSegun Emmanuel IbitoyeDepartment of Community Medicine, University of Ibadan, Ibadan, NigeriaOlayinka Stephen IlesanmiDepartment of Community Medicine, University College Hospital, Ibadan, Ibadan, NigeriaOlayinka Stephen IlesanmiFaculty of Medicine, University of Belgrade, Belgrade, SerbiaIrena M. IlicDepartment of Epidemiology, University of Kragujevac, Kragujevac, SerbiaMilena D. IlicResearch Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, IranSeyed Sina Naghibi IrvaniDepartment of Environmental Health Engineering, Guilan University of Medical Sciences, Rasht, IranJalil JaafariHealth Informatic Lab, Boston University, Boston, MA, USATahereh JavaheriDepartment of Community Medicine, Dr. Baba Saheb Ambedkar Medical College & Hospital, Delhi, IndiaRavi Prakash JhaDepartment of Community Medicine, Banaras Hindu University, Varanasi, IndiaRavi Prakash JhaDepartment of Ophthalmology, Heidelberg University, Heidelberg, GermanyJost B. JonasBeijing Institute of Ophthalmology, Beijing Tongren Hospital, Beijing, ChinaJost B. JonasDepartment of Family Medicine and Public Health, University of Opole, Opole, PolandJacek Jerzy JozwiakMinimally Invasive Surgery Research Center, Iran University of Medical Sciences, Tehran, IranAli KabirInstitute for Prevention of Non-communicable Diseases, Qazvin University of Medical Sciences, Qazvin, IranRohollah KalhorHealth Services Management Department, Qazvin University of Medical Sciences, Qazvin, IranRohollah KalhorDepartment of Forensic Medicine and Toxicology, All India Institute of Medical Sciences, Jodhpur, IndiaTanuj KanchanInstitute for Epidemiology and Social Medicine, University of Münster, Münster, GermanyAndré KarchInternational Research Center of Excellence, Institute of Human Virology Nigeria, Abuja, NigeriaGbenga A. KayodeJulius Centre for Health Sciences and Primary Care, Utrecht University, Utrecht, NetherlandsGbenga A. KayodeOpen, Distance and eLearning Campus, University of Nairobi, Nairobi, KenyaPeter Njenga KeiyoroDepartment of Public Health, Jordan University of Science and Technology, Irbid, JordanYousef Saleh KhaderDepartment of Global Health, University of Washington, Seattle, WA, USAIbrahim A. Khalil & Sonali KochharDepartment of Population Science, Jatiya Kabi Kazi Nazrul Islam University, Mymensingh, BangladeshMd Nuruzzaman KhanEpidemiology Department, Jazan University, Jazan, Saudi ArabiaMaseer KhanDepartment of Medical Microbiology & Immunology, United Arab Emirates University, Al Ain, United Arab EmiratesGulfaraz KhanFaculty of Health and Wellbeing, Sheffield Hallam University, Sheffield, UKKhaled KhatabCollege of Arts and Sciences, Ohio University, Zanesville, OH, USAKhaled KhatabDepartment of Medical Parasitology, Cairo University, Cairo, EgyptMona M. KhaterGlobal Evidence Synthesis Initiative, Datta Meghe Institute of Medical Sciences, Wardha, IndiaMahalaqua Nazli KhatibDepartment of Public Health, Kermanshah University of Medical Sciences, Kermanshah, IranNeda KianipourSchool of Traditional Chinese Medicine, Xiamen University Malaysia, Sepang, MalaysiaYun Jin KimDepartment of Nutrition, Simmons University, Boston, MA, USARuth W. KimokotiDepartment of Nursing and Health Promotion, Oslo Metropolitan University, Oslo, NorwaySezer KisaSchool of Health Sciences, Kristiania University College, Oslo, NorwayAdnan KisaGlobal Community Health and Behavioral Sciences, Tulane University, New Orleans, LA, USAAdnan KisaDepartment of Pediatrics, University of British Columbia, Vancouver, BC, CanadaNiranjan KissoonGlobal Healthcare Consulting, New Delhi, IndiaSonali KochharDepartment of Environmental Health Engineering, Arak University of Medical Sciences, Arak, IranAli KoolivandSchool of Population and Public Health, University of British Columbia, Vancouver, BC, CanadaJacek A. KopecArthritis Research Canada, Richmond, BC, CanadaJacek A. KopecCIBERSAM, San Juan de Dios Sanitary Park, Sant Boi de Llobregat, SpainAi KoyanagiCatalan Institution for Research and Advanced Studies (ICREA), Barcelona, SpainAi KoyanagiDepartment of Anthropology, Panjab University, Chandigarh, IndiaKewal KrishanInternational Institute for Population Sciences, Mumbai, IndiaPushpendra KumarFaculty of Health and Life Sciences, Coventry University, Coventry, UKOm P. KurmiDepartment of Medicine, McMaster University, Hamilton, ON, CanadaOm P. KurmiImperial College Business School, Imperial College London, London, UKDian KusumaFaculty of Public Health, University of Indonesia, Depok, IndonesiaDian KusumaPublic Health Foundation of India, Gurugram, IndiaDharmesh Kumar LalDepartment of Community and Family Medicine, University of Baghdad, Baghdad, IraqFaris Hasan LamiUnit of Genetics and Public Health, Institute of Medical Sciences, Las Tablas, PanamaIván LandiresMinistry of Health, Herrera, PanamaIván LandiresMedical Director, HelpMeSee, New York, NY, USAVan Charles LansinghGeneral Director, Mexican Institute of Ophthalmology, Queretaro, MexicoVan Charles LansinghDepartment of Otorhinolaryngology, Father Muller Medical College, Mangalore, IndiaSavita LasradoDepartment of Clinical Sciences and Community Health, University of Milan, Milan, ItalyCarlo La VecchiaSchool of Nursing, Hong Kong Polytechnic University, Hong Kong, ChinaPaul H. LeeCentre for Tropical Medicine and Global Health, University of Oxford, Oxford, UKSonia LewyckaOxford University Clinical Research Unit, Wellcome Trust Asia Programme, Hanoi, VietnamSonia LewyckaDepartment of Sociology, Shenzhen University, Shenzhen, ChinaBingyu LiDepartment of Systems, Populations, and Leadership, University of Michigan, Ann Arbor, MI, USAXuefeng LiuDepartment of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, UKJoshua LongbottomIndependent Consultant, Melbourne, VIC, AustraliaAlan D. LopezRadiology Department, Egypt Ministry of Health and Population, Mansoura, EgyptHassan Magdy Abd El RazekGrants, Innovation and Product Development Unit, South African Medical Research Council, Cape Town, South AfricaPhetole Walter MahashaEnvironmental Health, Tehran University of Medical Sciences, Tehran, IranAfshin MalekiEnvironmental Health Research Center, Kurdistan University of Medical Sciences, Sanandaj, IranAfshin Maleki & Shadieh MohammadiInstitute for Social Science Research, The University of Queensland, Indooroopilly, QLD, AustraliaAbdullah A. MamunDepartment of Epidemiology and Biostatistics, Tehran University of Medical Sciences, Tehran, IranMohammad Ali MansourniaCampus Caucaia, Federal Institute of Education, Science and Technology of Ceará, Caucaia, BrazilFrancisco Rogerlândio Martins-MeloICF International, DHS Program, Rockville, MD, USABenjamin K. MayalaDepartment of Pharmacy, Wollo University, Dessie, EthiopiaBirhanu Geta MeharieDepartment of Medical Laboratory Sciences, Bahir Dar University, Bahir Dar, EthiopiaAddisu MelesePeru Country Office, United Nations Population Fund (UNFPA), Lima, PeruWalter MendozaForensic Medicine Division, Imam Abdulrahman Bin Faisal University, Dammam, Saudi ArabiaRitesh G. MenezesDepartment of Reproductive Health and Population Studies, Bahir Dar University, Bahir Dar, EthiopiaEndalkachew Worku MengeshaCenter for Translation Research and Implementation Science, National Institutes of Health, Bethesda, MD, USAGeorge A. MensahDepartment of Medicine, University of Cape Town, Cape Town, South AfricaGeorge A. MensahBreast Surgery Unit, Helsinki University Hospital, Helsinki, FinlandTuomo J. MeretojaUniversity of Helsinki, Helsinki, FinlandTuomo J. MeretojaClinical Microbiology and Parasitology Unit, Dr. Zora Profozic Polyclinic, Zagreb, CroatiaTomislav MestrovicUniversity Centre Varazdin, University North, Varazdin, CroatiaTomislav MestrovicPacific Institute for Research & Evaluation, Calverton, MD, USATed R. MillerInternal Medicine Programme, Kyrgyz State Medical Academy, Bishkek, KyrgyzstanErkin M. MirrakhimovDepartment of Atherosclerosis and Coronary Heart Disease, National Center of Cardiology and Internal Disease, Bishkek, KyrgyzstanErkin M. MirrakhimovHeidelberg Institute of Global Health (HIGH), Heidelberg University, Heidelberg, GermanyBabak Moazen & Shafiu MohammedInstitute of Addiction Research (ISFF), Frankfurt University of Applied Sciences, Frankfurt, GermanyBabak MoazenDepartment of Biostatistics, Hamadan University of Medical Sciences, Hamadan, IranNaser Mohammad Gholi MezerjiResearch Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj City, IranShadieh MohammadiHealth Systems and Policy Research Unit, Ahmadu Bello University, Zaria, NigeriaShafiu MohammedComputer, Electrical, and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi ArabiaPaula MoragaClinical Research Development Center, Kermanshah University of Medical Sciences, Kermanshah, IranMehdi NaderiResearch and Analytics Department, Initiative for Financing Health and Human Development, Chennai, IndiaAhamarshan Jayaraman NagarajanDepartment of Research and Analytics, Bioinsilico Technologies, Chennai, IndiaAhamarshan Jayaraman NagarajanDepartment of Pediatrics, Arak University of Medical Sciences, Arak, IranJavad NazariDisease Control and Environmental Health, Makerere University, Kampala, UgandaRawlance NdejjoDepartment of General Surgery, Carol Davila University of Medicine and Pharmacy, Bucharest, RomaniaIonut NegoiDepartment of General Surgery, Emergency Hospital of Bucharest, Bucharest, RomaniaIonut NegoiDepartment of Biological Sciences, University of Embu, Embu, KenyaJosephine W. NgunjiriInstitute for Global Health Innovations, Duy Tan University, Hanoi, VietnamHuong Lan Thi Nguyen & Hai Quang PhamSouth African Medical Research Council, Cape Town, South AfricaChukwudi A. Nnaji & Charles Shey WiysongeSchool of Public Health and Family Medicine, University of Cape Town, Cape Town, South AfricaChukwudi A. Nnaji & Charles Shey WiysongeCentre for Heart Rhythm Disorders, University of Adelaide, Adelaide, SA, AustraliaJean Jacques NoubiapUnit of Microbiology and Public Health, Institute of Medical Sciences, Las Tablas, PanamaVirginia Nuñez-SamudioDepartment of Public Health, Ministry of Health, Herrera, PanamaVirginia Nuñez-SamudioDepartment of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, CanadaAndrew T. OlagunjuDepartment of Psychiatry, University of Lagos, Lagos, NigeriaAndrew T. OlagunjuCentre for Healthy Start Initiative, Lagos, NigeriaJacob Olusegun Olusanya & Bolajoko Olubukunola OlusanyaDepartment of Pharmacology and Therapeutics, University of Nigeria Nsukka, Enugu, NigeriaObinna E. OnwujekweLaboratory of Public Health Indicators Analysis and Health Digitalization, Moscow Institute of Physics and Technology, Dolgoprudny, RussiaNikita Otstavnov & Stanislav S. OtstavnovDepartment of Project Management, National Research University Higher School of Economics, Moscow, RussiaStanislav S. OtstavnovDepartment of Medicine, University of Ibadan, Ibadan, NigeriaMayowa O. OwolabiDepartment of Medicine, University College Hospital, Ibadan, Ibadan, NigeriaMayowa O. OwolabiDepartment of Respiratory Medicine, Jagadguru Sri Shivarathreeswara Academy of Health Education and Research, Mysore, IndiaMahesh P ADepartment of Forensic Medicine, Manipal Academy of Higher Education, Mangalore, IndiaJagadish Rao PadubidriDepartment of Health Metrics, Center for Health Outcomes & Evaluation, Bucharest, RomaniaAdrian PanaSchool of Global Public Health, New York University, New York, NY, USAEmmanuel K. PeprahDepartment of Parasitology and Entomology, Tarbiat Modares University, Tehran, IranMajid PirestaniUniversity Medical Center Groningen, University of Groningen, Groningen, NetherlandsMaarten J. PostmaSchool of Economics and Business, University of Groningen, Groningen, NetherlandsMaarten J. PostmaDepartment of Pharmacology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi ArabiaFaheem Hyder PottooDepartment of Nutrition and Food Sciences, Maragheh University of Medical Sciences, Maragheh, IranHadi PourjafarDietary Supplements and Probiotic Research Center, Alborz University of Medical Sciences, Karaj, IranHadi PourjafarThalassemia and Hemoglobinopathy Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, IranFakher RahimMetabolomics and Genomics Research Center, Tehran University of Medical Sciences, Tehran, IranFakher RahimSina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, IranVafa Rahimi-MovagharDepartment of Community Medicine, Maharishi Markandeshwar Medical College & Hospital, Solan, IndiaMohammad Hifz Ur RahmanDepartment of Oral Pathology, Srinivas Institute of Dental Sciences, Mangalore, IndiaSowmya J. RaoAcademic Public Health England, Public Health England, London, UKSalman RawafWHO Collaborating Centre for Public Health Education and Training, Imperial College London, London, UKDavid Laith RawafUniversity College London Hospitals, London, UKDavid Laith RawafSchool of Health, Medical and Applied Sciences, CQ University, Sydney, NSW, AustraliaLal RawalDepartment of Computer Science, Boston University, Boston, MA, USAReza RawassizadehSchool of Public Health, Haramaya University, Harar, EthiopiaLemma Demissie RegassaSchool of Social Sciences and Psychology, Western Sydney University, Penrith, NSW, AustraliaAndre M. N. RenzahoTranslational Health Research Institute, Western Sydney University, Penrith, NSW, AustraliaAndre M. N. RenzahoNetwork of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, IranNima RezaeiPediatric Infectious Diseases Research Center, Mazandaran University of Medical Sciences, Sari, IranMohammad Sadegh RezaiEpidemiology Research Unit Institute of Public Health (EPIUnit-ISPUP), University of Porto, Porto, PortugalAna Isabel RibeiroDepartment of Surgery, University of Minnesota, Minneapolis, MN, USAJennifer RickardDepartment of Surgery, University Teaching Hospital of Kigali, Kigali, RwandaJennifer RickardFaculty of Medical Sciences, Research Department, National University of Caaguazu, Cnel. Oviedo, ParaguayCarlos Miguel Rios-GonzálezDepartment of Research and Publications, National Institute of Health, Asunción, ParaguayCarlos Miguel Rios-GonzálezDepartment of Health Statistics, National Institute for Medical Research, Dar es Salaam, TanzaniaSusan Fred RumishaDepartment of Epidemiology, Shahid Beheshti University of Medical Sciences, Tehran, IranSiamak SabourDepartment of Phytochemistry, Soran University, Soran, IraqS. Mohammad SajadiDepartment of Nutrition, Cihan University-Erbil, Kurdistan Region, IraqS. Mohammad SajadiCenter for Health Policy & Center for Primary Care and Outcomes Research, Stanford University, Stanford, CA, USAJoshua A. SalomonDrug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, IranHossein Samadi KafilDepartment of Entomology, Ain Shams University, Cairo, EgyptAbdallah M. SamyDepartment of Surgery, Marshall University, Huntington, WV, USAJuan SanabriaDepartment of Nutrition and Preventive Medicine, Case Western Reserve University, Cleveland, OH, USAJuan SanabriaFaculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UKBenn SartoriusDepartment of Epidemiology, Indian Institute of Public Health, Gandhinagar, IndiaDeepak SaxenaGlobal Programs, Medical Teams International, Seattle, WA, USALauren E. SchaefferDepartment of Pediatric Newborn Medicine, Brigham and Women’s Hospital, Boston, MA, USALauren E. SchaefferEmergency Department, Manian Medical Centre, Erode, IndiaSubramanian SenthilkumaranCenter for Biomedical Information Technology, Shenzhen Institutes of Advanced Technology, Shenzhen, ChinaFeng ShaPublic Health Division, An-Najah National University, Nablus, PalestineAmira A. ShaheenIndependent Consultant, Karachi, PakistanMasood Ali ShaikhUniversity School of Management and Entrepreneurship, Delhi Technological University, Delhi, IndiaRajesh SharmaCentre for Medical Informatics, University of Edinburgh, Edinburgh, UKAziz SheikhDivision of General Internal Medicine, Harvard University, Boston, MA, USAAziz SheikhInstitute for Population Health, King’s College London, London, UKKenji ShibuyaNational Institute of Infectious Diseases, Tokyo, JapanMika ShigematsuCollege of Medicine, Yonsei University, Seoul, South KoreaJae Il ShinDepartment of Law, Economics, Management and Quantitative Methods, University of Sannio, Benevento, ItalyBiagio SimonettiWSB University in Gdańsk, Gdansk, PolandBiagio SimonettiSchool of Medicine, University of Alabama at Birmingham, Birmingham, AL, USAJasvinder A. SinghMedicine Service, US Department of Veterans Affairs (VA), Birmingham, AL, USAJasvinder A. SinghNursing Care Research Center, Semnan University of Medical Sciences, Semnan, IranAmin SoheiliDepartment of Infectious Diseases, Kharkiv National Medical University, Kharkiv, UkraineAnton SokhanDivision of Community Medicine, International Medical University, Kuala Lumpur, MalaysiaChandrashekhar T. SreeramareddyDepartment of Community Medicine, Ahmadu Bello University, Zaria, NigeriaMu’awiyyah Babale SufiyanSchool of Medicine, University of California San Francisco, San Francisco, CA, USAScott J. SwartzJoint Medical Program, University of California Berkeley, Berkeley, CA, USAScott J. SwartzDepartment of Nursing, Aksum University, Aksum, EthiopiaDegena Bahrey TadesseDepartment of Midwifery, University of Gondar, Gondar, EthiopiaAnimut Tagele TamiruDepartment of Clinical Pharmacy, University of Gondar, Gondar, EthiopiaYonas Getaye TeferaDepartment of Epidemiology and Biostatistics, University of Gondar, Gondar, EthiopiaZemenu Tadesse TessemaK.A. Timiryazev Institute of Plant Physiology, Russian Academy of Sciences, Moscow, RussiaMariya Vladimirovna TitovaLaboratory of Public Health Indicators Analysis and Health Digitalization, Moscow Institute of Physics and Technology, Moscow, RussiaMariya Vladimirovna TitovaDepartment of Health Economics, Hanoi Medical University, Hanoi, VietnamBach Xuan TranFaculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, NetherlandsPhuong N. TruongKasturba Medical College, Manipal Academy of Higher Education, Mangalore, IndiaBhaskaran UnnikrishnanAmity Institute of Biotechnology, Amity University Rajasthan, Jaipur, IndiaEra UpadhyayUKK Institute, Tampere, FinlandTommi Juhani VasankariDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, ItalyFrancesco S. ViolanteOccupational Health Unit, Sant’Orsola Malpighi Hospital, Bologna, ItalyFrancesco S. ViolanteCenter of Excellence in Behavioral Medicine, Nguyen Tat Thanh University, Ho Chi Minh City, VietnamGiang Thu VuFoundation University Medical College, Foundation University Islamabad, Islamabad, PakistanYasir WaheedCultures, Societies and Global Studies, & Integrated Initiative for Global Health, Northeastern University, Boston, MA, USARichard G. WamaiSchool of Public Health, University of Nairobi, Nairobi, KenyaRichard G. WamaiDepartment of Human Nutrition and Food Sciences, Debre Markos University, Debre Markos, EthiopiaEmebet Gashaw WassieDepartment of Midwifery, Adigrat University, Adigrat, EthiopiaFissaha Tekulu WelayDepartment of Community Medicine, Rajarata University of Sri Lanka, Anuradhapura, Sri LankaNuwan Darshana WickramasingheDepartment of Epidemiology, Johns Hopkins University, Baltimore, MD, USAKirsten E. WiensDepartment of Neurology, University of Melbourne, Melbourne, VIC, AustraliaTissa WijeratneDepartment of Medicine, University of Rajarata, Saliyapura Anuradhapuraya, Sri LankaTissa WijeratneDepartment of Public Health, Samara University, Samara, EthiopiaTemesgen Gebeyehu WondmenehDepartment of Diabetes and Metabolic Diseases, University of Tokyo, Tokyo, JapanTomohide YamadaSchool of International Development and Global Studies, University of Ottawa, Ottawa, ON, CanadaSanni YayaThe George Institute for Global Health, University of Oxford, Oxford, UKSanni YayaDepartment of Nursing, Arba Minch University, Arba Minch, EthiopiaYordanos Gizachew YeshitilaCentre for Suicide Research and Prevention, University of Hong Kong, Hong Kong, ChinaPaul YipDepartment of Social Work and Social Administration, University of Hong Kong, Hong Kong, ChinaPaul YipDepartment of Neuropsychopharmacology, National Center of Neurology and Psychiatry, Kodaira, JapanNaohiro YonemotoDepartment of Public Health, Juntendo University, Tokyo, JapanNaohiro YonemotoDepartment of Epidemiology and Biostatistics, Wuhan University, Wuhan, ChinaChuanhua YuCancer Institute, Hacettepe University, Ankara, TurkeyDeniz YuceDepartment of Health Care Management and Economics, Urmia University of Medical Science, Urmia, IranHasan YusefzadehDepartment of Medicine, University Ferhat Abbas of Setif, Sétif, AlgeriaZoubida ZaidiSocial Development and Health Promotion Research Center, Kermanshah University of Medical Sciences, Kermanshah, IranAlireza ZangenehSchool of Medicine, Wuhan University, Wuhan, ChinaZhi-Jiang ZhangSchool of Public Health, Wuhan University of Science and Technology, Wuhan, ChinaYunquan ZhangHubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan, ChinaYunquan ZhangDepartment of Health Education and Health Promotion, Kermanshah University of Medical Sciences, Kermanshah, IranArash ZiapourManaging the estimation or publication process. L.B.D. T.B.C. Writing the first draft of the manuscript. R.C.R.J. Primary responsibility for this manuscript focused on: applying analytical methods to produce estimates. L.B.D. T.B.C. Primary responsibility for this manuscript focused on: seeking, cataloguing, extracting, or cleaning data; production or coding of figures and tables. L.B.D. T.B.C. Providing data or critical feedback on data sources. L.B.D. T.B.C. and S.I.H. Development of methods or computational machinery. R.C.R.J. and L.B.D. T.B.C. Providing critical feedback on methods or results. L.B.D. T.B.C. and S.I.H. Drafting the manuscript or revising it critically for important intellectual content. R.C.R.J., L.B.D. T.B.C., and S.I.H. Management of the overall research enterprise (for example, through membership in the Scientific Council). L.B.D. T.B.C. and S.I.H. Consortia author contributions Managing the estimation or publication process. B.F.B., M.K.M.P. Writing the first draft of the manuscript. R.C.R.J. Primary responsibility for this manuscript focused on: applying analytical methods to produce estimates. C.A.W. Primary responsibility for this manuscript focused on: seeking, cataloguing, extracting, or cleaning data; production or coding of figures and tables. M.M.B. Providing data or critical feedback on data sources D.J.W., A.D., C.E.T., H.A., A.E.A., V.A., O.O.A., M.A., B.A., F.A., S.A., H.A., S.M.A., A.A.-H., N.A.-G., A.T.A., S.A., C.L.A., F.A., D.A., S.C.Y.A., J.A., O.A., M.A., F.A., Y.A.A., A.B., M.B., N.B., A.S.B., A.B., V.K.C., D.-T.C., G.D., J.D.G., A.D., S.D.D., M.D., A.E., M.El.S.Z., S.E., T.F., A.M.G., L.G., P.W.G., K.G., A.G., M.G., A.H., S.H., K.H., C.H., H.C.H., M.H., M.H., S.S.N.I., T.J., J.B.J., J.J.J., A.K., G.A.K., Y.S.K., I.A.K., M.N.K., M.K., K.K., M.N.K., Y.J.K., S.K., A.K., N.K., K.K., P.K., D.K., D.K.L., F.H.L., V.C.L., S.L., A.L.-A., K.E.L., S.S.L., P.A.L., X.L., H.M.A.E.R., M.A.M., B.K.M., W.M., R.G.M., E.M.M., B.M., N.M.G.M., S.M., S.M., A.H.M., M.M., A.J.N., J.N., I.N., J.W.N., Q.P.N., H.L.T.N., C.A.N., J.J.N., A.T.O., J.O.O., B.O.O., O.E.O., N.O., S.S.O., M.O.O., M.P.A., J.R.P., A.P., E.K.P., H.Q.P., M.P., M.J.P., H.P., Z.Q.S., F.R., V.R.-M., S.J.R., P.R., S.R., D.L.R., L.R., R.R., A.M.N.R., N.R., J.R., C.M.R.-G., S.S., S.M.S., A.M.S., B.S., D.S., A.A.S., M.A.S., J.I.S., J.A.S., A.S., E.S., C.T.S., S.J.S., D.B.T., A.T.T., B.X.T., P.N.T., B.U., E.U., T.J.V., Y.V., G.T.V., Y.W., R.G.W., T.W., C.S.W., T.G.W., S.Y., Y.G.Y., N.Y., C.Y., H.Y., Z.Z., A.Z., and S.I.H. Development of methods or computational machinery R.C.R.J., C.A.W., M.M.B., A.D., L.E., S.B., C.E.T., H.A., D.A., Y.A.A., A.S.B., D.C.C., V.K.C., F.D. A.D., M.D., M.E.S.Z., N.F., J.J.F., P.W.G., M.H., K.B.J., S.K., A., A.D.L., S.M., A.H.M., J.W.N., Q.P.N., S.F.R., A.M.S., E.E.S., S.J.S., E.U., Y.V., K.E.W., Y.G.Y., and N.Y. Providing critical feedback on methods or results C.A.W., A.D., C.E.T., H.A., A.E.A., E.A.-G., V.A., O.O.A., M.A., B.A., F.A., Z.A.-A., R.K.A., S.A., H.A., A.A.-H., H.M.A.M., K.A.A., N.A.-Gu., A.T.A., S.A., D.A.A., C.L.A., F.A., D.A., S.C.Y.A., J.A., O.A., M.M.W.A., M.A., F.A., Y.A.A., Z.N.A., A.B., M.B., A.S.B., D.B., N.B., P.B., K.B., O.J.B., Z.A.B., A.B., Z.W.B., A.B., Z.A.B., V.C., M.A.K.C., D.-T.C., C.H.C., G.D., J.D.G., A.H.D., A.D., J.K.D., K.D., A.D., S.D.D., M.D., D.D., S.D., F.D., B.D., L.D.-L., A.E., V.L.F., F.F., N.A.F., M.O.F., M.F., T.F., A.M.G., H.G.G.K.G., L.G., A.A.G., K.E.G., A.G., M.G., F.B.H., S.H., A.H., S.H., C.H., H.C.H., R.H., M.H., M.H., R.H., B.-F.H., S.E.I., O.S.I., I.M.I., M.D.I., S.S.N.I., T.J., R.P.J., J.B.J., J.J.J., A.K., R.K., T.K., A.K., G.A.K., P.N.K., Y.S.K., I.A.K., M.N.K., M.K., K.K., M.M.K., M.N.K., Y.J.K., R.W.K., S.K., A.K., N.K., S.K., A.K., J.A.K., A.K., K.K., P.K., O.P.K., D.K., D.K.L., S.L., K.E.L., S.L., B.L., X.L., A.D.L., H.M.A.E.R., P.W.M., A.A.M., M.A.M., L.B.M., F.R.M.-M., B.K.M., W.M., R.G.M., E.W.M., T.J.M., T.R.M., E.M.M., B.M., N.M.G.M., S.M., S.M., A.H.M., R.M., J.F.M., M.N., A.J.N., J.N., R.N., I.N., J.W.N., H.L.T.N., C.A.N., J.J.N., A.T.O., J.O.O., B.O.O., M.O.O., O.E.O., N.O., S.S.O., M.O.O., M.P.A., J.R.P., A.P., E.K.P., H.Q.P., M.J.P., F.H.P., H.P., Z.Q.S., F.R., V.R.-M., S.J.R., P.R., S.R., D.L.R., L.R., R.R., L.D.R., A.M.N.R., N.R., M.S.R., A.I.R., J.R., C.M.R.-G., S.S., S.M.S., J.A.S., H.S.K., A.M.S., J.S., B.S., D.S., L.E.S., S.S., F.S., A.A.S., M.A.S., A.S., K.S., M.S., J.I.S., B.S., J.A.S., D.L.S., A.S., E.E.S., C.T.S., M.B.S., D.B.T., A.T.T., Y.G.T., M.-H.T., Z.T.T., M.V.T., B.X.T., P.N.T., B.U., E.U., Y.V., F.S.V., G.T.V., Y.W., R.G.W., E.G.W., F.T.W., N.D.W., K.E.W., T.W., C.S.W., T.G.W., T.Y., S.Y., Y.G.Y., P.Y., N.Y., C.Y., D.Y., Z.Z., M.Z., Z.-J.Z., Y.Z., and S.I.H. Drafting the manuscript or revising it critically for important intellectual content R.C.R.J., C.A.W., M.K.M.-P., L.E., H.A., E.A.-G., V.A., O.O.A., M.A., B.A, F.A., R.K.A., H.A., A.A.-H., N.A.-G., A.T.A., S.A., D.A.A., R.A., C.L.A., J.A., O.A., M.M.W.A., M.A., F.A., M.A.A., Z.N.A., A.B., A.A.B., M.B., N.B. A.S.B., D.B., K.B., T.T.M.B., O.J.B., J.C., F.C., V.K.C., G.D., A.D., N.D.W., K.D., S.D.D., D.D., E.D., A.E., M.E.S.Z., M.E.T., S.E., V.L.F., E.F., P.F., F.F., N.A.F., M.O.F., M.F., T.F., A.M.G., L.G., A.G., M.I.M.G., D.W.H., A.H., S.H., C.H., H.C.H., R.H., M.H., S.E.I., O.S.I., I.M.I., M.D.I., S.S.N.I., J.J., R.P.J., J.B.J., J.J.J., A.K., A.K., G.A.K., M.N.K., M.K., G.K., K.K., M.M.K., M.N.K., A.K., N.K., A.K., A.K., K.K., P.K., O.P.K., D.K., I.L., S.L., C.L.V., P.H.L., K.E.L., J.L., A.D.L., H.M.A.E.R., P.W.M., A.M., A.A.M., M.A.M., L.B.M., F.R.M.-M., B.G.M., W.M., R.G.M., E.W.M., G.A.M., T.J.M., T.M., T.R.M., B.M., S.M., S.M., A.H.M., R.M., P.M., J.F.M., A.J.N., J.N., I.N., J.W.N., H.L.T.N., V.N.-S., A.T.O., J.O.O., B.O.O., M.O.O., O.E.O., N.O., S.S.O., M.O.O., M.P.A., J.R.P., A.P., H.Q.P., M.J.P., Z.Q.S., F.R., V.R.-M., M.H.U.R., S.J.R., S.R., D.L.R., L.R., N.R., A.I.R., J.R., C.M.R.-G., S.F.R., S.S., J.A.S., H.S.K., A.M.S., J.S., D.S., R.S., M.S., J.A.S., A.S., C.T.S., M.B.S., D.B.T., A.T.T., M.V.T., B.X.T., B.U., E.U., T.J.V., Y.V., F.S.V., G.T.V., R.G.W., N.D.W., K.E.W., T.W., .C.S.W., S.Y., Y.G.Y., Z.Z., M.Z., Z.-J.Z., and S.I.H. Management of the overall research enterprise (for example, through membership in the Scientific Council) B.F.B., A.J.C., P.W.G., J.A.K., A.H.M., C.J.L.M., P.C.R., J.A.S., B.S., and S.I.H. More

Parties to the Convention on Biological Diversity will meet this month to finalize the post-2020 Global Biodiversity Framework and the text for the stand-alone target on gender equality (Target 22). This target aims to reshape conservation policy and practice to make them more inclusive, equitable and effective.
Competing Interests
The authors declare no competing interests. More

Identification, phylogeny, and distribution of five phylaTo advance our understanding of marine sediment microbial diversity, we obtained over 30 billion paired DNA sequences from 42 marine sediment samples (coastal and deep sea) (Supplementary Data 1). From this, we reconstructed over 8000 ( >50% complete, 95%) to genes from coastal waters (Venezuela), a hypersaline pond in Carpinteria (US), sediments in Garolim Bay (Korea), and others (Supplementary Data 6 and 7). The worldwide distribution of these five phyla suggests that they have potentially overlooked ecological roles across many environments.Detection of novel protein familiesTo explore novel metabolic capabilities of these bacteria, we employed a recently described approach to identify and characterize unknown genes exclusive to uncultivated taxa17. Using this computational method, we identified 1,934 novel protein families (NPFs) and 6,893 novel singletons (NSs) in the 55 MAGs. The former can be define as families that do not show any homology in broadly used databases (including eggNOG, pfamA, pfamB, and RefSeq, see “Methods”) while the latter (NSs) are NPFs that are detected only once in each given genome or group of genomes. To determine if this novelty was specific to the five phyla or distributed across other uncultivated prokaryotic taxa, we mapped these NPFs and NSs against a comprehensive dataset of 169,642 bacterial and archaeal genomes covered in Rodriguez del Río et al.17. Using an in-house pipeline (Supplementary Fig. 4), we found that 44.6% of these NPFs and NSs are present in other uncultured taxa, highlighting the novel and undescribed metabolic repertoire that these five phyla share with other uncultured prokaryotic lineages17. Specifically, we found that these proteins are also present in Marinisomatota, Bacteroidota, and WOR-3 from publicly available genomes obtained from both marine and terrestrial environments17. When comparing the total number of NPFs per genome in the novel bacterial phyla against the genomic dataset (approximately 170,000 genomes), we found that the novel taxa described in this study have a higher than average percentage of novel proteins per genome (5.68 ± 4.89%) (p  0.7) and widespread (coverage > 0.7) within each phylum are shown in dark purple bars. The number of novel protein families with conserved neighboring genes are shown in light gray bars. c, d, Selected examples of phylogenetic trees and novel protein family genomic context marked in gray with a black outline) in Blakebacterota and Arandabacterota. The protein families are similar between these two phyla and have conserved neighboring genes, including translation initiation factor IF-3 gene (infC), large subunit ribosomal protein L20 gene (rplT), phenylalanyl-tRNA synthetase genes (pheST), cell division protein gene (zapA), phosphodiesterase gene (ymdB), methenyltetrahydrofolate cyclohydrolase gene (folD), and exodeoxyribonuclease genes (xseAB). e Phylogenetic tree and genomic context of a novel protein family uniquely distributed in Joyebacterota. The novel protein family has conserved genomic neighbors related to energy conservation (Rnf complex genes, rnfABCDEG). The phylogeny was generated using FastTree2 and numbers on the top and bottom of the branch represent the bootstrap and branch length, respectively. Source data are provided as a Source Data file.Full size imageMetabolic pathways are often encoded by ‘genome neighborhoods’ (gene clusters and/or operons)18. Therefore, we calculated the genomic context conservation of the NPFs containing three or more sequences (3773 NPFs in total) and examined the annotation of genes found in genomic proximity of the NPFs to determine their potential function. Of the inspected families, 513 (14%) had a conservation score ≥ 0.9 (see “Methods”) indicating a high degree of conserved neighboring proteins. Manual annotation of these neighboring proteins indicated they are potentially involved in sulfur reduction, energy conservation, as well as the degradation of organics such as starch, fatty acids, and amino acids (highlighted in red in Supplementary Fig. 5). For example, a NPF predominantly found in Blakebacterota is neighbored by putative menaquinone reductases (QrcABCD), a conserved complex related to energy conservation in sulfate reducing bacteria19,20,21,22. However, metabolic annotations of Blakebacterota genomes that encode QrcABCD indicate that they largely lack the key enzymes for sulfate reduction, dissimilatory sulfite reductases (DsrABC), suggesting this QrcABCD complex may be involved in other bioenergetic contexts such as linking periplasmic hydrogen and formate oxidation to the menaquinone pool22.In some instances, we found NPFs coded near genes predicted to produce key proteins in nitrogen cycling. Two of the Joyebacterota MAGs code NPF neighboring proteins with homology to hydroxylamine dehydrogenases (HAO). HAO is a key enzyme in marine nitrogen cycling that has traditionally been thought to catalyze the oxidation of hydroxylamine (NH2OH) to nitrite (NO2−) in ammonia oxidizing bacteria. Recently, it has been suggested that HAO may also convert hydroxylamine to nitric oxide (NO) as an intermediate, which is then further oxidized to nitrite by an unknown mechanism. Hydroxylamine is also known to be an intermediate in the nitrogen cycle. It is a potential precursor of nitrous oxide (N2O), a potent greenhouse gas that is a byproduct of denitrification, nitrification23,24, and anaerobic ammonium oxidation25. The presence of HAO within the genomic context of these NPFs suggests they may be involved in mediating hydroxylamine metabolism, and thus may play an important role in nitrogen cycling.A number of NPFs are colocalized with genes predicted to be involved in the utilization of organic carbon. For example, one NPF found in Blakebacterota genomes is adjacent to a peptidase (PepQ; K01271) for dipeptide degradation. Another NPF, only detected in Blakebacterota, is neighbored by long-chain acyl-CoA synthetase (FadD; K01897), a key enzyme in fatty acid degradation (Supplementary Fig. 6). In Joyebacterota, as well as in publicly available Bacteroidetes and Latescibacteria we identified an NPF that is colocalized with amylo-alpha-1,6-glucosidase (Glycoside Hydrolase Family 57), suggesting a potential role in starch degradation.We also identified NPFs that are specific and very conserved in AABM5, Blakebacterota, Orphanbacterota, Arandabacterota, and Joyebacterota (2, 39, 3, 16, and 26 respectively). These NPFs were found in at least 70% of the MAGs belonging to each phylum, and rarely present in other genomes across the tree of life. Due to their unique nature, the 86 unique NPFs could be used as marker genes for future characterizations of the novel bacteria described in this study. When examining the genomic context of the phyla-specific NPFs, we found that more than half of the NPFs (49 of 86) shared the same gene order and are next to genes predicted to be involved in various catabolic and anabolic processes. For example, an NPF in Joyebacterota MAGs is adjacent to an Rnf complex26, which is important for energy conservation in numerous organisms21 (Fig. 2e). Also, two different NPFs in Blakebacterota and Arandabacterota MAGs were located next to tRNA synthesis genes (Fig. 2c, d). Additional phyla-specific NPFs were colocalized with genes predicted to be involved in other important processes, including peptidoglycan biosynthesis (Supplementary Fig. 6a), F-type ATPase (Supplementary Fig. 6b), acyl-CoA dehydrogenase, elements for transportation, sulfur assimilation (Supplementary Fig. 6c), and others (Supplementary Fig. 6d).Metabolic potential of the novel bacterial phylaIn addition to NPF-based analyses, we compared the predicted proteins in the novel lineages to a variety of databases and gene phylogenies to understand their metabolism (see “Methods”). The distribution of key metabolic proteins based on presence/absence of protein families (using MEBS: see methods) in the 61 MAGs is largely consistent with their phylogeny (Fig. 1a). Below, we detail the predicted metabolism of each novel bacterial phyla based on these analyses (Supplementary Fig. 5 and Supplementary Data 8 and 9, see details in Supplementary Information).JoyebacterotaJoyebacterota is composed of 20 MAGs predominantly reconstructed from hydrothermal vent sediments (blue, lower right side in the phylogeny shown in Fig. 1a). Metabolic inference suggests that these bacteria are obligate anaerobes encoding extracellular carbohydrate-active enzymes (CAZymes) with the potential to degrade pectate or pectin, photosynthetically fixed carbon in marine diatoms, macrophytes27, and terrestrial plants28. Furthermore, Joyebacterota seems to be involved in the sulfur cycle. Seven Joyebacterota MAGs encode sulfide:quinone oxidoreductases (SQR). Phylogenetic analysis indicate these SQR belong to the membrane-bound type I and III29. Interestingly, these SQR type I sequences are closely related to those sequences mostly found in terrestrial environments, e.g., freshwater, soil, and hot spring, while SQR-III  have been previously suggested to play a key role maintaining the sulfide homeostasis or bioenergetics in deep-sea sediments30. The presence of these pathways highlight the potential adaptation of Joyebacterota to several environments, contributing to recycling of carbon and sulfur.BlakebacterotaThe Blakebacterota phylum is composed of 11 MAGs predominantly reconstructed from the surface layer of GB sediments (0–6 cm). In this environment, temperatures range from 25 to 29 °C, CH4 measures 0.4–0.8 mM, CO2 reaches up to 10 mM, and SO42− concentrations are high (up to 28 mM)30. Metabolic inference using MEBS31 suggests Blakebacterota play an important role in N and S cycles. These findings were supported by the presence of key enzymes in these cycles. For example, we identified a nitrous oxide reductase in Blakebacterota, the only known enzyme to catalyze the reduction of nitrous oxide to nitrogen gas. This reaction acts as a sink for nitrous oxide, and thus is an important removal mechanism for this potent greenhouse gas. In addition to nitrogen cycling, we identified key genes involved in sulfur cycling in Blakebacterota. Six of the MAGs possess genes that code for SQR with sulfate or nitrous oxide as the final electron accepter. In addition, seven of the MAGs contain genes for thiosulfate dehydrogenase (doxD), which may convert thiosulfate to tetrathionate. Finally, one MAG is predicted to produce dimethyl sulfide (DMS) under oxic conditions via methanethiol S-methyltransferase (MddA) from methylate L-methionine or methanethiol (MeSH). Thus, these bacteria may play important roles in a variety of intermediate steps in nitrogen and sulfur cycling.ArandabacterotaLike Joyebacterota, Arandabacterota were largely recovered from shallow (2–14 cm) GB and deep (26–38 cm) BS sediments. This phylum contains 11 MAGs that are predicted to be anaerobic polysulfide and elemental sulfur reducers. They may mediate sulfur reduction via sulfhydrogenases (HydGB), which results in the production of sulfide32,33. Thus, Arandabacterota may contribute to sulfur cycling in marine sediments. Arandabacterota also code distinct hydrogenases, [NiFe] 3c and 4g types, (Fig. 3) for H2 oxidation. In addition, Arandabacterota may reduce nitrite via periplasmic dissimilatory nitrite reductases (NrfAH) present in Meg22_24_Bin_129, BHB10-38_Bin_9, and SY70-4-3_Bin_59. This mechanism for energy conservation is more efficient than polysulfide and elemental sulfur reduction. Therefore, they are likely to use sulfur species as electron donors in the absence of nitrite.Fig. 3: Maximum likelihood phylogenetic tree of NiFe hydrogenases from the novel phyla.The majority of NiFe hydrogenases identified from the five phyla in this study are highlighted in the gray background. Most hydrogenases are types 4g and 3c. Starred branches denote the minor NiFe hydrogenases identified in this study. Bootstrap values ≥ 80 are shown in circles. Source data are provided as a Source Data file.Full size imageOrphanbacterotaOrphanbacterota is composed of seven MAGs that were mostly obtained from the BS, and appear to be metabolically versatile, facultative aerobes. The BS has an average water depth of 18 m and is strongly influenced by anthropogenic activities in China, mainly the terrestrial input of nutrients and organic matter34. Orphanbacterota code a diversity of CAZymes for the degradation of complex carbohydrates. We identified genes coding for extracellular glycoside hydrolase family 16 (GH16), which may be involved in the degradation of laminarin, releasing glucose and oligosaccharides35. Six Orphanbacterota genomes also contain genes predicted to produce extracellular peptidases belonging to family M28 and S8, which are nonspecific peptidases (Supplementary Fig. 7 and Supplementary Data 10–14). The released amino acids could be taken up via ABC transporters coded by these bacteria.Consistent with their recovery from shallow sediment habitats (Supplementary Data 1), Orphanbacterota have a diverse repertoire of terminal cytochrome oxidase genes (Supplementary Data 9) suggesting they are capable of surviving in a range of oxygen concentrations. Based on the presence of isocitrate lyase and malate synthase, they may use the glyoxylate cycle for carbohydrate synthesis when sugar is not available, or use simple two-carbon compounds for energy conservation36,37. They also appear capable of reducing nitrate to nitrite via periplasmic nitrate reductases (NapAB)38. Moreover, they could reduce nitrate via the membrane-bound nitrate reductase for energy conservation and reducing nitrous oxide.One Orphanbacterota genome (M3-44_Bin_119) has genes predicted to mediate sulfate/sulfite reduction, including DsrABC, QmoABC, and membrane bound Rnf complexes (Supplementary Fig. 8a, b and Supplementary Data 8 and 9). Another Orphanbacterota (LQ108M_Bin_12) is predicted to contain diverse metabolic pathways, including MmdA for DMS production, SQR for sulfide oxidation, the Rnf complex for energy conservation21 or detoxification (Supplementary Fig. 8c), and sulfhydrogenases (HydABDG) for H2 oxidation. In addition to energy conservation and detoxification, sulfide oxidation is important for preventing the loss of sulfur through H2S volatilization. This is predicted to be an important process in sulfur-rich sediments, where large quantities of the self-produced H2S are produced during heterotrophic growth29.AABM5AABM5 (12 genomes, 7 obtained in this study) is an understudied bacterial group that has largely been recovered from shallow (4–12 cm) sediments in GB and deep (44–62 cm) sediments in BS. Despite the distinct environments where they have been found, genomes within this phylum have several shared metabolic abilities. In contrast to the strict anaerobic lifestyle that was previously reported in a subgroup within AABM5 (candidate division LCP–89)12, we predict they are facultative anaerobes. In support of this, we identified cytochrome c oxidase (CtaDCEF) and cytochrome bd ubiquinol oxidase (CydAB) for aerobic respiration39. In addition, we identified DsrABC in nine genomes (Supplementary Fig. 8 and Supplementary Data 15), indicating these organisms can potentially reduce sulfate/sulfite for energy conservation. Several AABM5 genomes are predicted to use H2 as an electron donor due to the presence of type 3c [NiFe] hydrogenase (MvhADG) (Fig. 3, Supplementary Fig. 9, and Supplementary Data 8 and 9). The metabolic versatility in this phylum better explains their global distribution.Ecological significance of the new phylaThese previously overlooked bacterial phyla appear to be involved in key biogeochemical processes in marine sediments, namely sulfur and nitrogen cycling, and the degradation of organic carbon. However, we did not find any evidence for complete autotrophic metabolisms (Wood-Ljungdahl pathway, Calvin–Benson–Bassham, reductive tricarboxylic acid, 3-hydroxypropionate bicycle, 3-hydroxypropionate-4-hydroxybutyrate, and dicarboxylate-4-hydroxybutyrate cycles) in any of these bacteria. Instead, they have a variety of pathways for the utilization of organic compounds as detailed above. These novel bacteria phyla (all except Blakebacterota) have the potential to degrade the algal glycan laminarin, one of the most important complex carbon compounds in the ocean40. These novel phyla encode extracellular laminarinases that specifically cleave the laminarin into more readily degradable sugars, e.g., glucose and oligosaccharide (Supplementary Fig. 7 and Supplementary Data 10–12). Laminarin glycan is produced in the surface ocean by microalgae that sequester CO2 as an important carbon sink in the oceans41. This is a key process of the global carbon cycle, and most studies have focused on understanding aerobic laminarin-degrading bacteria in the surface oceans41,42. Recently, it has been shown that laminarin plays a prominent role in oceanic carbon export and energy flow to higher trophic levels and the deep ocean40, yet the organisms responsible for laminarin degradation under anoxic conditions are unknown. The discovery of  these novel bacterial phyla opens new doors for future studies exploring laminarin degradation in the deep sea. In addition, most of them contain genes predicted to code for sulfatases. Blakebacterota, Orphanbacterota, Arandabacterota, and Joyebacterota code for arylsulfatase, mainly arylsulfatase A, for desulfation of galactosyl moiety of sulfatide. They also code choline sulfatase, iduronate 2-sulfatase and some uncharacterized sulfatases for different types of substrates43. This suggests they are capable of cleaving organic sulfate ester bonds as a source of sulfur and organic carbon on the ocean floor.Many metabolic processes identified here, including pathways for polysaccharide degradation, sulfur, and nitrogen metabolism are often incomplete (Fig. 4). This may be due to the incompleteness of these genomes, or it suggests that these processes occur via metabolic handoffs within the community. Some of the phyla are capable of mediating a variety of sulfur and nitrogen redox reactions (Fig. 4a, b). For example, four phyla code DsrABC, suggesting they play an overlooked role in inorganic matter degradation in marine sediments through sulfate reduction. The resultant sulfide may be reoxidized to sulfur intermediates and organic sulfur compounds by these newly described bacteria. Four phyla (Blakebacterota, Orphanbacterota, Arandabacterota, and Joyebacterota) code an SQR for producing elemental sulfur from sulfide. Methanethiol S-methyltransferase (MddA) is predicted to be produced by individual MAGs Blakebacterota (M3-38_Bin_215) and Orphanbacterota (LQ108M_Bin_12) for the production of DMS from methionine44. DMS is important in climate regulation and sulfur cycling in marine environments45,46, though little is known about the fate or production of DMS in anoxic environments like marine sediments. As detailed above, Blakebacterota contains genes for the conversion of thiosulfate to tetrathionate. Four phyla (AABM5, Orphanbacterota, Arandabacterota, and Joyebacterota) are predicted to disproportionate thiosulfate to sulfite via thiosulfate/3-mercaptopyruvate sulfurtransferase. Thus, we suspect these bacteria may be capable of mediating intermediate sulfur species in anoxic environments. These results provide a predictive framework for future physiological studiesto confirm our genomic-based predictions.Fig. 4: Genomic-based predictions of the potential metabolic role of the novel bacterial phyla.Key steps in the (a) sulfur and (b) nitrogen cycles predicted in the five bacterial phyla. Compounds (in gray triangle frames) were arranged according to the standard Gibbs free energy of formation of each sulfur or nitrogen compound (values next to the compound taken from Caspi et al.93). Star, square, triangle, pentagon, and diamond shapes correspond to AABM5, Blakebacterota, Orphanbacterota, Arandabacterota and Joyebacterota, respectively. Colored shapes represent the presence of genes in a given pathway. Fully colored shapes indicate the presence of genes in over 50% of the phyla. Half colored shapes signify that less than 50% of the phyla code for those genes. Uncolored shapes indicate presence of genes in only one MAG. Note that only pathways encoded in at least one MAG are shown. The red dotted line indicates the assimilatory process. The blue soild line indicates the confirmed pathway with phylogeny of key genes. c Phylogenetic tree and genomic context of a novel protein family (NPF) next to putative menaquinone reductase complex genes (qrcABCD) found in Blakebacterota and Orphanbacterota. d Phylogenetic tree and genomic context of a NPF next to hydroxylamine oxidoreductase genes (hao) in Joyebacterota.Full size imageIn addition to potential roles in sulfur cycling, the phyla described here may play key roles in nitrogen processes, for example several MAGs contain genes that code predicted hydroxylamine dehydrogenase proteins (HAO, confirmed by different databases)47,48. HAO is a precursor of nitrous oxide (N2O), a potent greenhouse gas and ozone destructing agent in the atmosphere. Marine N2O stems from nitrification and denitrification processes which depend on organic matter cycling and dissolved oxygen. Since hydroxylamine is a precursor of N2O, deciphering the organisms that can mediate the formation of N2O has important implications for Earth’s climate49. In addition, three phyla (AABM5, Blakebacterota, and Orphanbacterota) code for periplasmic and/or transmembrane nitrate reductase, and two phyla (AABM5 and Arandabacterota) are predicted to reduce nitrite via dissimilatory nitrite reductase.In recent years, there have been large advances in the exploration of novel microbial diversity. Genomic data has provided crucial insights into the ecological roles and biology of these new microbes. The recovery of bacterial genomes belonging to five overlooked, globally distributed phyla with considerably novel protein composition reminds us there is much to be learned about the microbial world. The identification of NPFs provides targets for future studies to elucidate the ecophysiology of these organisms. The presence of genes for organic carbon degradation and sulfur and nitrogen cycling in these new bacteria suggests they contribute to a variety of key processes in marine sediments. Thus, the addition of these bacterial genomes to ecosystem models will likely transform our understanding of how microbial communities drive carbon degradation and nutrient cycling in the oceans. More

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The rise of animals (metazoans) is a seminal event in the history of life. The Cambrian Radiation ~540 Ma marks the appearance of abundant and diverse metazoans and increasing ecosystem complexity in the fossil record1. A causal relationship between the redox and fossil records is proposed, where oxygen provision reached a threshold, or series of thresholds, which allowed for the diversification of metazoans with increasing metabolic demands2. Global geochemical data, however, suggest that oxygenation was not a simple, linear process, but rather occurred episodically via a series of short-lived pulses (1–3 Myr), or ‘oceanic oxygenation events’ (OOEs)3,4. Early and even later Cambrian seas likely had shallower, and more dynamic, oxygen minimum zones (OMZs) than modern oceans5,6. Such pulses of increased oxygenation (and related changes in productivity) are hypothesised to have increased the extent of shallow-ocean oxygenation and hence to have promoted diversification7. But what remains unquantified is the community-wide response of metazoans to such redox cycles, an insight into the evolutionary processes involved, and hence whether these pulses were indeed a driving force for the Cambrian Radiation.In order to test the hypothesis that oxic pulses led to diversification and potentially ecological development, a correlation between increased oxygenation, rates of origination, and metrics of metazoan ecosystem complexity needs to be demonstrated. Early Cambrian marine environments were heterogeneous with respect to oxygen provision and nutrient load at a regional scale, so in order to investigate potential correlations, we require the integration of global and local redox proxies, and biotic records in the same stratigraphically well-constrained geological successions.During the early Cambrian, the Siberian Platform was a vast isolated, tropical continent almost entirely covered by an epicontinental sea (Fig. 1a)8,9. The platform supported a single metacommunity, i.e. a species pool with many local, interacting communities e.g.10, representing a third of total early Cambrian metazoan benthic diversity with widespread metazoan (archaeocyath sponge) reefs that formed bioherms (Fig. 1b)7,11. Dynamic and synchronous changes of body size in archaeocyath sponges, hyoliths, and helcionelloid molluscs through the early Cambrian on the Siberian Platform have been quantified, which coincide with elevated biodiversity and rates of origination: these have been proposed to follow OOEs12. Here we consider temporal changes in both the position of archaeocyath sponge reefs as a function of relative water depth, and in individual reef size (diameter), as well as the ecological complexity of the reef-building and dwelling communities by quantification of changing reef community membership of sessile archaeocyath sponge, coralomorph, and cribricyath species, on the Siberian Platform.Fig. 1: Palaeogeographic and stratigraphic position of the early Cambrian archaeocyath reefs of the Lena-Aldan area on the Siberian Platform.a Early Cambrian palaeofacies zonation map of the Siberian Platform. b Cross section to show relative positions of sampled transects along the Lena River11,40,66,67,68. c Lithostratigraphy, biostratigraphy, carbon isotope (δ13C)29,31,32 and carbonate-associated sulfate sulfur isotope (δ34SCAS)7 data for sections from the middle Lena River (Isit’, Zhurinsky Mys, Achchagy-Kyyry-Taas, and Achchagy-Tuoydakh). S.E.—Sinsk Event; Tolb.—Tolba Formation; ATD., BOT., N.-D., TOM.—Atdabanian, Botoman, Nemakit-Daldynian, and Tommotian local stages, respectively.Full size imageTo quantify ecological complexity, we used metacommunity analyses, which compare the structure between communities in terms of taxa (generally species) compositions spatially and temporally10 (see Methods). The ‘Elements of Metacommunity Structure’ framework used here is a hierarchical analysis that identifies properties in site-by-species presence/absence matrices that are related to the underlying processes, such as species interactions, dispersal, and environmental filtering that shape species distributions10. Application to various marine and terrestrial palaeocommunities has demonstrated the robustness of these methods to fossil data and sample size variations13,14. There are fourteen different types of metacommunity structure which are determined by the calculation of three metacommunity metrics: Coherence, Turnover, and Boundary Clumping, which reveal different controlling processes of underlying metacommunity structure10,15,16,17,18.The most ecologically complex metacommunities are classified as Clementsian, and have positive coherence, turnover and boundary clumping16. Clementsian metacommunities contain groups of taxa with similar range boundaries that respond to the environment synchronously as taxa have physiological or evolutionary trade-offs within the communities associated with environmental thresholds19. By contrast, when taxa respond individualistically to the underlying environment, without accounting for other taxa within the community, the structure is Gleasonian, and is defined by positive coherence and turnover but no significant boundary clumping16. When coherence is positive, but turnover is not significantly different from random, then the resultant metacommunity structures are known as quasi-structures (e.g. quasi-Clementsian), which reflect weaker underlying structuring processes.We determined the metacommunity structure for archaeocyath sponge species on the Siberian Platform throughout their early Cambrian record using an entire previously published data set11 then on a sub-set of metacommunities which had a sufficient number of reef sites to be suitable for analyses, i.e. with a sufficient number of sites to be statistically significant. Further, to investigate the effects of water depth on metacommunity structure, we used Spearman rank correlations to test whether the metacommunity ranking (as determined by reciprocal averaging, a type of correspondence analysis which ordinates the sites based on their species composition17), is significantly correlated to water depth. Finally, to quantify how pairwise associations between taxa change between the three temporally different metacommunities, we determined which pairwise taxa co-occurrences are significantly non-random using a combinatorics approach, and whether any non-random co-occurrences are positive or negative20.Species richness estimates are highly sensitive to differences in sampling. When comparing species richness of assemblages from several time intervals, it is advisable to standardise sampling across those assemblages to ensure that changes in species richness are not attributable to sampling differences. One approach is to subsample each time interval down to a standardised number of individuals (size-based rarefaction), but this approach can underestimate changes in richness because it tends to sample low-richness assemblages more completely than high-richness ones21. Coverage-based rarefaction, where each sample is down-sampled to a standardised level of taxonomic completeness, avoids this potential issue. The coverage of a sample is the proportion of species in the assemblage which are represented in that sample, and it can be estimated by subtracting the proportion of singletons in a sample from 1 (e.g.22; see also21 for details). We used the estimateD function from R package iNEXT23 to produce coverage-standardised species richness estimates with 95% confidence intervals, by repeatedly down-sampling the sampled assemblage from each time interval to match the coverage of the lowest-coverage interval. We did this by setting datatype = “abundance”, base = “coverage” and leaving all other arguments as default.In sum, we test the biotic response to OOEs by compiling metrics of archaeocyath reef size, location, and metacommunity complexity, integrated with existing data on archaeocyath individual size, species richness and origination and extinction rates12 and high-resolution geochemistry4,7 recalculated to the same stratigraphic scale, on the Siberian Platform over 11 Myr through Cambrian stages 2–3 (mid-Tommotian to early Botoman on the Siberian stratigraphic scale; 525–514 Ma). These results are used to quantify the community-wide response of metazoans to extrinsic redox cycles, and hence gain insight into the evolutionary processes involved.Geological setting and evolution of redoxDuring the early Cambrian shallow marine carbonates associated with evaporites and siliciclastics dominated the inner Siberian Platform, passing to shallow marginal carbonates of transitional facies known as the transitional zone (or the Anabar-Sinsk), thence to deep ramp and slope settings that accumulated organic-rich limestone and shale (Fig. 1a)24,25,26. Archaeocyathan reefs or bioherms were almost entirely restricted to the transitional facies. Such reefs appeared and proliferated during Cambrian stages 2 and 3 (Tommotian, Atdabanian and earliest Botoman), disappeared at the beginning of Stage 4 (middle Botoman) and re-appeared briefly at the end of this stage (Toyonian).We integrate palaeontological (archaeocyath species number and individual size), palaeoecological (reef size and palaeodepth location) and chemostratigraphic information (carbon isotope cycles 5p, 6p, and II–VII) for sections of the Aldan, Selinde and Lena rivers with sub-metre-scale lithostratigraphic subdivisions27,28,29,30,31,32,33 (Figs. 1c, 2a–c, 3a). This results in negligible uncertainty associated with sample heights, which are fixed relative to a consistent datum within each section.Fig. 2: Lithostratigraphy, biostratigraphy and carbon isotope (δ13C) data for sections of the Aldan and Selinde rivers bearing the earlierst archaeocyath reef communities of the Siberian Platform.a Dvortsy27,28,30 b Ulakhan-Sulugur33,34, and c Selinde69,70.Full size imageFig. 3: Summary of geochemical and biotic changes through the early Cambrian, Siberian Platform, and uranium isotope data representing a global record.a International and Siberian timescale, within age model C of 57. ND—Nemakit-Daldynian regional stage; U’-Y—Ust’-Yudoma Formation. b Summary of carbon and sulphur isotopes (from the Lena River, Siberia7). c Uranium isotopes from Siberia (grey; Sukharikha and Bol’shaya Kuonamka rivers), South China (blue), and Morocco (orange) (all data points are larger than 2SE)4. d Archaeocyath sponge species diversity and maximum diameter12. Plotted richness values are the species richness estimator21 with accompanying 95% confidence interval, calculated using the estimated function from R package iNEXT62. e Rates of archaeocyath sponge species origination and extinction12. f Reef location as a function of relative water depth (Supplementary Table 1). FWWB—Fair weather wave base. SWB—Storm weather wave base. g Reef/bioherm diameter, coloured by relative water depth (see column f, and Supplementary Table 2). h Number of reef community types (Supplementary Table 3). i Archaeocyath reef ecosystem complexity, with percentage of species co-occurrence as changing proportions of total non-random and positive and negative. G = Gleasonian, QG = Quasi-Gleasonian, C = Clementsian.Full size imageThroughout Cambrian stages 2 and 3, high-amplitude positive δ13C carbon isotope excursions show a strong positive covariation with the sulphur isotope composition of carbonate-associated sulphate (δ34SCAS) in sections from the Lena River (Fig. 3b)7. The rising limbs of these excursions are interpreted as intervals of progressive burial of reductants under anoxic bottom water conditions, and a progressive increase in atmospheric oxygen7. Coincident δ13C and δ34SCAS peaks (numbered II–VII) correspond with a pulse of atmospheric oxygen into the shallow marine environment (creating an OOE), followed by a corresponding decrease in reductant burial under more widespread marine oxia (falling limbs of δ13C and δ34SCAS), and leading to gradual de-oxygenation over Myr7. In addition, phosphorous retention might have occurred under oxic shallow marine conditions, acting to reduce primary productivity and further oxygenate the shallow marine environment in the short-term ( More

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Effect of phosphorus starved cultures of Dunaliella tertiolecta on growth represented as optical density under stress of nickel ionsIn the case of normal culture, phosphorus starved control culture (without nickel stress), and phosphorus-starved treated cultures, data presented in Table 1 and graphed in figure (S1, Supplementary Data) clearly showed a progressive increase in optical density with increasing culturing period in case of normal culture, phosphorus-starved control culture, and phosphorus-starved treated cultures. Our findings are consistent with those of18 who found that in phosphorus starved cultures of three algae species, Microcystic aeruginosa, Chlorella pyrenoidesa, and Cyclotella sp., the biomass, specific growth rate, and Chl-a all declined significantly.The optical density achieved during the four periods of culturing was lower in phosphorus-depleted control cultures than in normal cultures (i.e., cultures contained phosphorus). When compared to a normal control (without nickel addition), the optical density was reduced by 9.1% after 4 days of culturing under phosphorus deprivation and by 10.0 percent after 8 days of culturing. In the case of 5 mg/L dissolved nickel, however, the obtained optical density values in phosphorus starved treatment cultures rose with the increase in culturing period during all culturing periods as compared to phosphorus-starved control (without nickel addition) cultures.At 10 mg/L dissolved nickel and after 4 days of culturing, the optical density although less than those in case of concentration 5 mg/L, yet it was higher than control (− P) but by increasing the culturing period more than 4 days, the optical density was less than control (− P). Our results are similar to those of19 who observed that the decrease in cell division rate signaled the onset of P-deficiency. The cultures that showed no significant increase in cell number for at least three consecutive days under the experimental conditions were considered P-depleted. In addition20, observed that the growth rate of Dunaliella prava was found to be dramatically lowered when phosphorus was limited. The content of chlorophyll fractions, total soluble carbohydrates, and proteins all fell considerably as a result of phosphorus restriction.The results concerning the effect of dissolved nickel on the growth of Dunaliella tertiolecta under conditions of phosphorus limitation show that phosphorus starved Dunaliella had lower growth as compared to the control (phosphorus-containing culture medium). These results are in agreement with those obtained by7 who reported that the optical density of Chlorella kessleri cell suspension decreased with phosphorus deficiency compared to control. Also21, found that Chlorella vulgaris cells grew 30–40% slower in phosphorus-starved cultures than in control cultures. Furthermore22, showed that diatoms were unable to thrive when phosphorus levels were insufficient. Diatom dominances were reduced to 45 and 55% in enclosures where phosphate was not provided23 observed that, under salt stress, Chlorella’s metabolic rate was substantially lower than Dunaliella’s.It can be concluded that when microorganisms are deprived of phosphorus, dissolved nickel uptake decreases, resulting in an increase in algal metabolism24. Also25, examined the effects of phosphorus and nitrogen starvation on the life cycle of Emiliania huxleyi (Haptophyta) and proved that various biochemical pathways’ metabolic load increased under P-starvation while it decreased under N-starvation.Effect of phosphorus starved cultures of Dunaliella tertiolecta on chlorophylls content under stress of nickel ionsTable 2 and figure (S2, Supplementary Data) show the sequences of change in the amount of chlorophylls a and b in phosphorus-depleted cultures of Dunaliella tertiolecta in response to various dissolved nickel concentrations. The results show that total chlorophyll content rose steadily until the end of the experiment under normal conditions (a control containing phosphorus). These results are in harmony with those obtained by24. The ratio between chlorophylls “a” and “b” remained nearly constant till the end of the 12th day. At the 16th day of culturing, the ratio decreased from 2.9:1 to 2.4:1. On the contrary, the total chlorophylls under control (in the absence of nickel element) in case of phosphorus-starved cultures showed a progressive increase up to the 12th day. At the 12th day the total chlorophylls in case of phosphorus-starved cultures decreased by 10.7% compared to the normal control. At the 16th day, the total chlorophylls in case of untreated phosphorus starved culture decreased by 20.8% compared to those obtained at normal control26. Reported that the chlorophyll content of Chlorella sorokiniana was significantly reduced due to a lack of nitrogen and phosphorus in the medium.Table 2 Effect of different concentrations of dissolved nickel (mg/L) on chlorophylls content (µg/ml) of Dunaliella tertiolecta under the stress of phosphorus starvation.Full size tableThe total chlorophyll content of Dunaliella tertiolecta in the phosphorus-starved cultures treated with 5 mg/L of dissolved nickel increased gradually until the 12th day, when the content of the total chlorophylls reached 2.11 µg/ml, i.e., higher than the phosphorus-starved control (− P) by 15.3%. At the 16th day, the total chlorophylls, although lower than those obtained at the 12th day, were still higher than the control (− P). At a concentration of 10 mg/L of dissolved nickel, slight increase in the content of total chlorophylls was recorded from the beginning to the end of the culturing period, i.e., from the 4th to the 16th day. At the other concentrations of dissolved nickel (15, 20, and 25 mg/L), a pronounced decrease in the total chlorophylls could be observed from the 4th to the 16th day of culturing compared to control (− P). Our results are going with an agreement with those obtained by27 who found that chlorophylls were inhibited maximum at higher dissolved nickel concentrations but activated at lower values. The normal ratio between chlorophylls “a” and “b” (3:1) was upset after the 8th day of culturing under concentrations 5, 10, and 15 mg/L of dissolved nickel. At 20 and 25 mg/L of dissolved nickel, this ratio was unstable from the beginning to the end of the experiment. The fact that dissolved nickel is extremely mobile and hence only absorbed to a minimal level may explain the sensitivity of the tested alga to nickel in response to phosphorus deficiency, and an increase in phosphorus concentration favors its absorption by microorganisms28. It can be concluded that when microorganisms are deprived of phosphorus, dissolved nickel uptake decreases, resulting in an increase in algal metabolism.Effect of different concentrations of dissolved nickel on photosynthesis (O2-evolution) of phosphorus starved cells of Dunaliella tertiolecta
Data represented in Table 3 and graphed in figure (S3, Supplementary Data S3) showed that the effect of phosphorus limitation on the photosynthetic activity of Dunaliella tertiolecta in response to five different concentrations of dissolved nickel revealed that, under phosphorus limiting conditions, the amount of O2-evolution was lower than in untreated cultures (the control). The evolution of O2 after 4 days of culturing in case of phosphorus starved control decreased by 8.7% compared to normal control, while after 12 days it decreased by 30.4%. The rate of O2-evolution at different concentrations of dissolved nickel over 5 mg/L caused successive reductions in the O2-evolution of phosphorus starved cells. Application of 5 mg/L of dissolved nickel, the results cleared that the rate of O2-evolution increased under the effect of all tested concentrations till the end of the experiment. It is clear from our data that the rate of O2-evolution depended mainly on the concentration of the nickel element and the length of culturing period. The lower the rate of O2-evolution, the higher the element’s concentration, and the longer the culturing period. This coincided with the findings of7 who found that low phosphorus treatment causes Chlorella kessleri to lose its photosynthetic activity. In this regard, it was discovered that phosphorus deficiency resulted in a decrease in photosynthetic electron transport activity29 found that the O2-evolution of Chlamydomon reinhardtii declined by 75%. This decrease reflects damage of PSII and the generation of PSII QB-non reducing centers.Table 3 Effect of different concentrations of dissolved nickel (mg/L) on photosynthetic activity (O2-evolution calculated as µ mol O2 mg chl-1 h-1) on phosphorus supplemented and starved cells of Dunaliella tertiolecta.Full size tableAlso30 found that P- deficiency has been correlated with lower photosynthetic rates. In the case of the treated phosphorus-starved cultures with lower concentrations (5 mg/L) of dissolved nickel, the rate of photosynthesis increased when compared to the phosphorus-starved control, but was less than that of the normal control (without nickel treatment). On the contrary, it was found that, in the treated phosphorus-starved cultures at concentrations of 10, 15, 20 and 25 mg/L of the tested element, the rate of photosynthesis decreased from the beginning to the end of the experiment. With increasing concentration, duration of the culturing period, and kind of element, the condition of decrease in O2-evolution became more pronounced; the same results were also recorded by24. The stimulation of growth and photosynthesis in the presence of some concentrations of dissolved nickel under phosphorus-limiting conditions is observed by31 they report that in Cu2+ sensitive Scenedesmus acutus, intracellular polyphosphate plays a key role in shielding photosynthesis from Cu2+ toxicity but not in copper resistant species.Effect of different concentrations of dissolved nickel on respiration (O2-uptake) of phosphorus starved cells of Dunaliella tertiolectaData obtained in Table 4 and graphed in figure (S4, Supplementary Data S4) concerning the rate of respiration of Dunaliella tertiolecta under phosphorus-limiting conditions was higher than that of untreated phosphorus-starved (control) for a short period of time only, i.e., after 4 days, at concentrations 5, 10 and 15 mg/L of dissolved nickel, After 8 days of culturing, the rate of O2- uptake increased only at 5 mg/L of dissolved nickel, while at the other concentrations it decreased gradually with increasing the concentration of the element. This finding is consistent with the findings of23, who discovered that Dunaliella cells increased their O2 absorption and evolution rates in the presence of 2 M salt NaCl in the media. In terms of oxygen uptake rate, Dunaliella cells demonstrated an increase in salt concentrations. In 1.5 M NaCl, it increased significantly by 60–80%.Table 4 Effect of different concentrations of dissolved nickel (mg/L) on respiration activity (O2-uptake calculated as µ mol O2 h-1) on phosphorus supplemented and starved cells of Dunaliella tertiolecta.Full size tableConcerning the increase in respiration in P-depleted green alga species cultures5 suggested that Scenedesmus, for example, can utilize the energy stored in starch and lipids for active phosphorus uptake from lake sediments. This process is aided by an increase in phosphatase production32 and these cells’ ability to operate anaerobically33. When unicellular green algae or higher plants are exposed to P deficiency, the majority of newly fixed carbon appears to be allocated to the synthesis of non-phosphorylated storage polyglucans (i.e., starch) or sucrose, with less photosynthetic activity directed to respiratory metabolism and other biosynthesis pathways34. It can be concluded from the obtained results that, when the alga was cultivated under phosphorus deficiency and treated with varied amounts of dissolved nickel, the growth was the most sensitive characteristic, followed by photosynthesis, and then dark respiration. In the few comparative studies with several species of green algae, growth was more sensitive than the other physiological processes examined. Out of them35, reported that growth was more susceptible to phosphorus deficiency in Chlorella pyrenoidosa and Asterionella gracilis than photosynthesis and respiration (the least sensitive processes). Growth was also more sensitive than photosynthesis in Nitzschia closterium 36 . Another important fact reported by37 is that under low phosphorus conditions, Dunaliella parva accumulates lipids rather than carbohydrates. These findings imply that phosphorus stress may prevent starch and/or protein production, leading to an increase in carbon flux to lipids. More