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Finding new microbial lineages and their biogeochemical roles using emerging genomic techniques

Valerie
January 10, 2020

Finding new microbial lineages and their biogeochemical roles using emerging genomic techniques

Lamont-Doherty Earth Observatory
Geochemistry Department
Columbia University
New York
Jan 10 2020

Valerie

January 10, 2020
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  1. F i n d i n g n e w

    m i c r o b i a l l i n e a g e s a n d t h e i r b i o g e o c h e m i c a l r o l e s u s i n g e m e r g i n g g e n o m i c t e c h n i q u e s . V a l e r i e D e A n d a , P h D . @ v a l _ d e a n d a P o s t d o c t o r a l R e s e a r c h e r T h e u n i v e r s i t y o f Te x a s a t A u s t i n | M a r i n e S c i e n c e I n s t i t u t e P o r t A r a n s a s , Te x a s Lamont-Doherty Earth Observatory Geochemistry Department Columbia University New York Jan 10 2020
  2. O n e s e x t i l l

    i o n ( 1 0 2 1 ) s t a r s i n t h e o b s e r v a b l e u n i v e r s e O n e n o n i l l i o n ( 1 0 3 0 ) m i c r o b i a l a r c h a e a a n d b a c t e r i a c e l l s o n e a r t h M I C R O B E S A R E A B U N D A N T Flemming and Wuertz 2019 Nat Rev
  3. C o n s i s t i n g

    o f a n e s t i m a t e d o n e t r i l l i o n ( 1 0 1 2 ) d i f f e r e n t s p e c i e s M I C R O B E S A R E D I V E R S E M i c ro b e s a re n o t o n l y t h e m o s t a b u n d a n t a n d d i v e r s e l i f e f o r m o n o u r p l a n e t , b u t t h e i r m e t a b o l i c f u n c t i o n s a re c r i t i c a l f o r e l e m e n t a l re a c t i o n s a n d c y c l i n g i n t h e b i o s p h e re , w h i c h c o n s t i t u t e s t h e f o u n d a t i o n a n d b u i l d i n g b l o c k s o f e v e r y e c o s y s t e m o n E a r t h . Locey and Lennon PNAS 2016
  4. C o n s i s t i n g

    o f a n e s t i m a t e d o n e t r i l l i o n t r i l l i o n ( 1 0 1 2 ) d i f f e r e n t s p e c i e s M I C R O B E S A R E D I V E R S E P a r a d o x i c a l l y, s c i e n t i f i c u n d e r s t a n d i n g o f h o w t h i s “ v a s t u n i v e r s e ” o f m i c ro b e s c a t a l y z e b i o g e o c h e m i c a l re a c t i o n s i s n o t f u l l y re s o l v e d b e c a u s e 9 9 . 9 9 % o f E a r t h ’s m i c ro b i a l t a x a h a v e n o t b e e n d e s c r i b e d y e t Cavicchioli et al., 2019 Nat Rev Microbiol
  5. TREE OF LIFE Eukaryotes Archaea E u k a ryo

    te s : n i n e mi l l i o n Mi c ro o rg a n i sms : A rc h a e a a n d B a c te ria Bacteria (106) species 1012 species
  6. • • -1995 : H. influenzae becomes the first bacterium

    genome to be sequenced A T G A T G A T G A T G A T G A T G A T T A A G T G A T G A T A T G A T T G A T G A T G A T G A T G A T G A T T A A G T G A T G A T A T G A T -2000: Genome sequence of model organism fruit fly -2003: Mouse becomes first mammal with sequenced genome -2005: Human Genome Project completion announced -2005: First NGS machine allowing sequencing DNA from environmental samples -2008 Human Microbiome -2015 Ocean Microbiome -2015: MAGs -2016: Updated tree of life https://unlockinglifescode.org/timeline GENOMIC ERA BREAKTHROUGH MOMENTS Origin of metagenomics
  7. TREE OF LIFE 2016 Candidate Phyla Radiation Eukaryotes Major lineage

    lacking isolated representative Archaea Hug , Baker B et al., 2016 Nature Bacteria Eukaryotes Recently described expansion of the tree of life that represents more than 15% of all bacterial diversity and potentially contains over 70 different phyla The unseen majority
  8. ARCHAEAL TREE OF LIFE 2017 Evolution of the tree of

    life. A schematic representation of our understanding of the relationships between eukaryotes and archaea over the past 40 years. green and blue represent archaeal lineages Emme L et al., 2017 Nature Review Microbiology
  9. ARCHAEAL TREE OF LIFE 2019 Baker B, De Anda V

    et al., Accepted in Nature Review Microbiology Major lineage lacking isolated representative Archaea Bacteria Most comprehensive database up to date (>3,500 archaeal genomes )
  10. Sequencing Assembly Binning De Anda, under Review Nat Microbiogy Environmental

    sample METAGENOMICS Potential Roles in the Environment
  11. Sequencing Assembly Binning Phylogeny Physiology/ Metabolism Methanol DMA TMA MtaA

    MtaB MtaC MtbB MtbC MtbA CoM-S-S-CoB CoM-SH+HS-CoB Fdox Fdred 2H2 4H+ HdrB HdrC MvhG MvhA HdrA MvhD 1-2,5,8 1-2,5 FrhG FrhA F420 H2 F420 H2 2H+ 1-4 1-4 MttB MttA MttC HS-CoM CH3 S-CoM Biosynthesis F420 CH4 H2 MtrA MtrH CH3 -S-CoM H2 H2 H2 +HS-CoM +HS-CoM +HS-CoM 3 1-3,7 1-4,6 1-4 1-4 2-4,7 ATP ADP ATPase 1-4,6-8 1-2,6 FrhB 1-2,6 1-5,7 1-2,5,7 1-2,5-7 4 NiFe H+ H2 FdOX Fdred 2e- 8 ? ? 2e- ? PPi 2Pi H+ HppA 1-7 H+ H+ H+ Potential Role in the Environment De Anda, under Review Nat Microbiology Environmental sample METAGENOMICS
  12. OMIC DATA Gomez Cabrero et al 2014 BMC SB Reshetova

    et al 2013 BMC SB Current metagenomic studies generate More than 3 Tb of data per study Biological data interpretation (evaluate, compare and analyze complex data in a large scale) Efficiency of data processing (high performance, accuracy, high speed, data processing, reproducibility) Getting the data (45,000 USD) and Sequencing cost (3,000 per sample) T H E I C E B E R G I L L U S I O N O F O M I C S T U D I E S Genomics Transcriptomics Proteomics Metabolomics
  13. Assembly MEBS Protein coding genes (pcg) prediction Visualization Entropy-based scores

    Genomes, metagenomes MAGs MEBS computational workflow Multigenomic Entropy Based Score Metabolic potential to perform C, O, N, Fe and S cycles across the tree of life Normalized Entropy-Based Scores (NEBS) MEBS Methanogenesis Fermentative /Anaerobic Aerobic Taxa metabolic relatedness based on nutrient assimilation, biomass production or energy acquisition De Anda et al., 2017 Gigascience De Anda et al., In prep Open source algorithm which synthesizes genomic information into a single informative value Score=l>likelihood that microbial taxa/or entire communities perform specific metabolic-biogeochemical pathways
  14. Assembly MEBS Protein coding genes (pcg) prediction Visualization Entropy-based scores

    Genomes, metagenomes MAGs MEBS computational workflow Multigenomic Entropy Based Score MEBS De Anda et al., 2017 Gigascience De Anda et al., In prep Open source algorithm which synthesizes genomic information into a single informative value Score=l>likelihood that microbial taxa/or entire communities perform specific metabolic-biogeochemical pathways World-wide environmental samples with potential to perform the sulfur cycle Fluctuation dynamics of the nitrogen and sulfur cycle over 3-year period of study S N Bits 1 0 0.5 Time in years 1 2 3 Environmental perturbation De Anda et al., 2019 Frontiers in Microbiology
  15. Involves gas-phase reactions of sulfur compounds and the formation and

    subsequent involvement of sulfate aerosols as cloud-forming nuclei Atmospheric chemist SULFUR CYCLE Involves all processes influencing the transfer of sulfur compounds to and from the various Earth surface reservoir Geochemist Microbiology Relationship between the different organisms metabolizing sulfur compounds and the environment. We therefore pay attention to the organisms themselves, their diversity, ecology, and phylogeny, as well as the biogeochemical processes influencing their activity. Canfield 2005 De Anda et al., 2017 BioRxiv
  16. Sakaguchi, Arakaki and Matsunaga, 2002 Tan et al., 2019 A

    N U P D A T E D V I E W O F D E L T A P R O T E O B A C T E R I A D I V E R S I T Y Langwig M, De Anda V, et al., Under Prep <20 sequences <100 sequences >4000 Complete genomes and MAGs Marguerite Langwig Master’s thesis
  17. Pathway Langwig M, De Anda V, et al., Under Prep

    A N U P D A T E D V I E W O F D E L T A P R O T E O B A C T E R I A D I V E R S I T Y Metabolism of deltaproteobacteria Using genomic techniques to understand the relationship between a microbial community at the genomic level and its ecosystem function Marine sediments are one of the largest reservoirs of organic carbon on earth5 accounting up to ~500– 10,000 Gt (1 Gt = 1015g) of carbon in the form of methane (Bohrmann & Torres 2013)
  18. EXPANDING MICROBIAL BIODIVERSITY AND METABOLIC POTENTIAL IN DEEP- SEA SEDIMENTS

    Gong X +, De Anda V, + et al., Under Prep + equal contribution Tab. 2. Statistics of the sequence assembly and binning generated from GB sediment samples. Sample site Aceto Balsamico Megmat 19 Megamat 22 WB1 Vent1a (outside) Vent1b (intermediate) Vent1c (center) Vent2 Vent3 Background Dive4484 Depth range (cm) 0-33 0-12 0-18 mat 0-3 0-24 0-3, 9-12 0-3, 12-15 4-6 0-1, 21-24 0-1, 3-4 Number of sample 4 3 8 1 1 3 2 2 1 2 1 Number of scaffold (>2 kb) 738,968 928,695 2,019,742 107,962 145,929 261,061 158,271 216,746 9,141 61,721 12,453 Bacterial Bins 443 218 1492 34 37 106 47 94 6 14 47 Archaeal Bins 92 67 349 2 0 72 77 91 5 3 33 <20 sequences 3,7 Tb of metagenomic sequence data were generated from 16 samples, 4 sites (300-Gb per sample) + previously described in Dombrowski et al., 2019 In just 16 samples we obtained 3000 MAGs https://www.youtube.com/watch?time_continue=29&v=NRZayrzpE00 214 samples 1529 MAGs
  19. EXPANDING MICROBIAL BIODIVERSITY AND METABOLIC POTENTIAL IN DEEP- SEA SEDIMENTS

    Gong X +, De Anda V, + et al., Under Prep + equal contribution <20 sequences https://www.youtube.com/watch?time_continue=29&v=NRZayrzpE00 Potential >20 Novel Bacterial Phyla (red branches) Metabolic inference will allow us to infer potential roles in the environment Physiology is an emergent property that cannot be reliably predicted from genome data or metabolic reconstructions alone Next Generation Physiology approaches to studying microbiome function at the single cell level"
  20. EXPANDING MICROBIAL BIODIVERSITY AND METABOLIC POTENTIAL IN DEEP- SEA SEDIMENTS

    Gong X +, De Anda V, + et al., Under Prep + equal contribution <20 sequences https://www.youtube.com/watch?time_continue=29&v=NRZayrzpE00 X-Alkane? Ethane Butane, Propane Novel MCR Methanogenesis Methane as an intermediate in the global carbon cycle. Thauer et al., 2008
  21. EXPANDING MICROBIAL BIODIVERSITY AND METABOLIC POTENTIAL IN DEEP- SEA SEDIMENTS

    Gong X +, De Anda V, + et al., Under Prep + equal contribution <20 sequences https://www.youtube.com/watch?time_continue=29&v=NRZayrzpE00 Carbohydrate-active enzymes (CAZymes) encoded in GB archaeal genomes. Percentage of carbohydrate esterases (CE), glycoside hydrolases (GH) and polysaccharide lyases (PL) encoded in GB archaeal genomes. C ellulose Sucrose Selected pathways of carbon degradation encoded in individual genomes (archaea and bacteria by depth in AB sample Degradation of organic matter in detail Individual genomes Community level Geochemistry data
  22. Our understanding of the ecological roles of many groups of

    microbes has been hampered by low-resolution analytical approaches to studying the staggering diversity present in nature. The tree of life is full of branches, which remain undiscovered, and those, which have only been identified in single-gene sequencing surveys. Filling in the genomic gaps in the tree of life with state- of-the-art omic techniques will provide a rich context to understand the evolution of life on the planet and will provide us with a genetic understanding of how microbial communities drive biogeochemical cycles. Microbes are not only the most abundant and diverse life form on our planet, but are also key mediators of elemental cycles on Earth. In the Anthropocene, climate change is impacting most life on Earth. Microorganisms support the existence of all higher trophic life forms. To understand how humans and other life forms on Earth (including those we are yet to discover) can withstand anthropogenic climate change, it is vital to incorporate knowledge of the microbial ‘unseen majority’. Cavicchioli et al., 2019 Cavicchioli et al., 2019 Baker and Dick, 2013. TAKE A HOME MESSAGES
  23. MARINE SCIENCE INSTITUTE PORT ARANSAS TEXAS Baker Marine Microbial Ecology

    Lab Understanding the physiologies of uncultured marine sediment microbes using high-throughput genomic techniques https://sites.utexas.edu/baker-lab/ Brett Baker
  24. Kiley Seitz* Nina Dombrowski* Ian Rambo Xienzhe Gong Maggie Langwig

    B A K E R M A R I N E M I C R O B I A L E C O L O G Y L A B Kathryn Appler Craig Connolly M E B S T E A M I N T E R D I S C I P L I N A R Y C O L L A B O R A T O R S Roland Hatzenpichle Andreas Teske UNC Chapel Hill *Previous members Bruno Contreras Cesar Augusto Poot