Microbiome to Function-Report-final · Microbiome to Function: Next Generation Eco-Microbiology Workshop LA-UR-20-22843 1 Workshop Report INSTITUTIONAL HOSTS: J. Patrick Fitch, Associate

Microbiome to Function: Next Generation Eco-Microbiology Workshop LA-UR-20-22843

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Workshop Report

INSTITUTIONAL HOSTS: J. Patrick Fitch, Associate Laboratory Director for Chemistry, Earth, and Life Sciences, Los Alamos National Laboratory

Srinivas Iyer, Bioscience Division Leader, Los Alamos National Laboratory

TECHNICAL HOSTS: John Dunbar and Patrick Chain, Bioscience Division, Los Alamos National Laboratory

ORGANIZING COMMITTEE: David Bruce, Cheryl Kuske, Inez Valdez, Rebecca McDonald, and Srinivas Iyer, Bioscience Division, Los Alamos National Laboratory

REPORT AUTHORS: John Dunbar, Patrick Chain, Michaeline Albright, Joany Babilonia, Geoffrey House, Marie Elizabeth Kroeger, Dean Morales, Aaron Robinson, Rebecca McDonald, and Srinivas Iyer, Bioscience Division, Los Alamos National Laboratory

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EXECUTIVE SUMMARY:

The Biological and Environmental Research (BER) program champions the predictive understanding of complex biological systems to enable energy and infrastructure security. To support this challenging endeavor, BER began funding Science Focus Area (SFA) projects at the national labs a decade ago in order to foster scientific advances that are more easily achieved by sustained team research. BER has recently encouraged collaboration among SFAs as a means to accelerate innovation and scientific impact. To facilitate BER’s vision, the Bioscience Division at Los Alamos National Laboratory (LANL) proposed an annual pan-SFA workshop that would rotate among the National Labs. LANL hosted the first workshop in September 2019 to explore a common challenge—understanding how microbiomes function—and to promote collaboration opportunities among SFAs in BER’s Microbial Genomics Program. The workshop comprised overview presentations of the eight SFAs and two SFA pilots and discussions of near- and mid-term opportunities to foster collaboration. These opportunities include 1) sharing isolates, 2) sharing data and storage, 3) establishing common standards and best practices, and 4) fostering scientific exchanges. BACKGROUND AND INTRODUCTION:

The goal of the DOE Genomic Science Program (GSP) is to “achieve a predictive, systems-level understanding of plants, microbes, and biological communities to enable biobased solutions to DOE mission challenges in energy and environment.” The GSP supports research at different levels of organization to foster innovation and address problems at different scales of complexity. The organizational levels include small (single-PI) projects at universities, medium team projects that leverage national laboratory resources (SFAs), and large projects (Bioenergy Centers). This organizational strategy better covers the landscape required for science breakthroughs at multiple scales. The SFAs address priorities of the Genome Science Program. The priorities include bioenergy production, climate science, and foundational systems biology research and technology development that support the applied missions. One conceptual view of topical relationships among the SFA is illustrated in Figure 1. Despite the broad scope of research among the SFAs, there are logical overlaps that create opportunities for synergy to maximize BER investments. For instance, SFAs might be using similar tools and methods but applying them to different biological systems, or might be investigating similar model systems using different approaches. Overall, in order to gain larger ecosystems-level understanding, there should be mechanisms in place to create synergy among complementary models. To foster synergy, BER began to provide two-hour closed door sessions at the annual GSP meeting in February for the SFA teams to discuss opportunities for synergy. The two-hour sessions were a useful starting point, but far more time for extended discussion was clearly needed for meaningful progress. Towards this end, the LANL Bioscience Division Leader proposed an annual pan-SFA meeting and the first one was held in September 2019 in Santa Fe, New Mexico. Key concepts for the meeting were:

• Rotate the location annually among the national labs to promote neutrality and collaboration.

• Focus on developing synergy to accelerate innovation and impact, fulfilling the vision of national labs as a cooperative network serving the nation.

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Figure 1. One possible conceptual view of topical foci among the SFAs WORKSHOP STRUCTURE:

The Microbiome-to-Function: Next Generation Eco-Microbiology workshop was held at the Drury Plaza Hotel in Santa Fe, NM from September 15-17, 2019. The event began with a reception and dinner honoring Dr. Cheryl Kuske’s research career and included a welcome address from BSSD Division Director Todd Anderson and a keynote address from Nigel Mouncey, Joint Genome Institute Director, entitled “National Microbiome Data Collaborative: Accelerating Microbiome Discovery and Exploration”. The workshop was designed with two objectives:

1) Increase familiarity among the SFAs by allowing longer overviews of each SFA than each had achieved in the prior two-hour sessions at the annual GSP meeting.

2) Identify several specific opportunities for coordination or collaboration. To increase familiarity among the SFAs, the workshop was divided in three sessions with 30-minute overview presentations for each SFA as outline below. To identify specific opportunities

- Microbial Carbon Cycling in Terrestrial Ecosystems

- Microbes Persist: Systems Biology of the Soil Microbiome

- Phenotypic Response of the Soil Microbiome to Environmental Perturbations

Environment

- Bacterial:Fungal Interactions and Their Role in Soil Functioning

- m-CAFÉs: Microbial Community Analysis and Functional Evaluation in Soils

- ENIGMA (Ecosystems and Networks Integrated with Genes and Molecular Assemblies)

Cross-over

- A Systems Biology Approach to…Bioenergy-Relevant Microbial Communities

- Dynamic Visualization of Lignocellulose Degradation

- Plant-Microbe Interfaces

- Quantitative Plant Science Initiative

Bioenergy

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for coordination or collaboration, each session was followed by a panel discussion and/or breakout session. Participants were also encouraged to bring posters, and the posters were displayed throughout the meeting to enable on-going discussions. Session One:

• LANL SFA – “Microbial Carbon Cycling in Terrestrial Ecosystems” Presenter: John Dunbar

• PNNL SFA – “Phenotypic Response of the Soil Microbiome to Environmental Perturbations” Presenter: Janet Jansson

• LBNL SFA – “m-CAFÉs: Microbial Community Analysis and Functional Evaluation in Soils” Presenter: Trent Northen

• LLNL SFA – “A Systems Biology Approach to Interactions and Resource Allocation in Bioenergy-Relevant Microbial Communities” Presenter: Rhona Stuart

Session Two:

• ORNL SFA – “Plant Microbe Interfaces” Presenter: Mitchel Doktycz • BNL Pilot – “Integrating Genomics with Experimentation to Address Family and

Subfamily Protein Functions” Presenter: Crysten Blaby • ORNL Biofuels SFA – “How to chew up a Plant: Dynamic Visualization of

Lignocellulose Degradation by Integration of Neutron Scattering Imaging and Computer Simulation” Presenter: Jeremy Smith

Session Three:

• LANL SFA – “Investigating Bacterial-Fungal Interactions with Multi-omics” Presenter: Patrick Chain

• LLNL SFA – “Microbes Persist: Systems Biology of the Soil Microbiome” Presenter: Jennifer Pett-Ridge

• LBNL SFA – “ENIGMA: Ecosystems and Networks Integrated with Genes and Molecular Assemblies” Presenter: Lauren Lui

The abstracts for talks and posters can be found in APPENDIX III COMMON SCIENCE OBJECTIVES AND CHALLENGES

The SFAs share a common goal of achieving a predictive understanding of complex systems, and the SFAs use a shared toolset (‘omics techniques) in pursuit of this goal. However, the SFAs vary in mission (e.g., bioenergy versus environmental science), model systems (e.g. different bioenergy crops, different ecosystems), approach, and methods. The differences among SFAs simultaneously present both challenges to and opportunities for collaboration. Identifying and facilitating the opportunities for collaboration was a central focus of the Workshop. Over the past two decades, our ability to catalog the components of biological systems has improved dramatically with technological advances in the multi-omics toolset. The challenge for the next generation of eco-microbiology is to rapidly translate ‘omics measurements into predictive models of the dynamic functioning of complex systems at all needed scales. Overcoming this challenge will increasingly involve all-source data integration, which is a

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growing trend in biological science supported by increasingly powerful computation infrastructure for data storage and synthesis. Herein lies the importance of seeking synergy among the SFAs. In order to become more than the sum of the SFAs, synergy is needed within the science missions and among the disparate approaches, capabilities, and datastreams the SFAs provide. Workshop participants identified five areas that may contribute to synergy in the future: 1) sharing isolates, 2) sharing data and storage, 3) establishing common standards and best practices, and 4) fostering scientific exchanges.

1) Sharing Isolates: There is a growing interest in using defined communities (constructed with specific isolates) to validate inferences in complex natural systems and to improve understanding of mechanisms. Defined communities of 2 to 40 are of increasing interest to a) validate the major players inferred in complex systems comprised of 1000s of species, b) validate the major metabolic processes in systems of interest, c) discover additional metabolic interactions, c) investigate ecological and physiological mechanisms that influence community assembly and functional stability (reviewed in Shetty et al 2019 and Sergaki et al. 20181). Many of the SFAs have built culture collections. Sharing isolates among SFAs is an easy collaborative step that may aid individual SFAs in the construction of defined communities. ACTION: • Collect the isolate inventories from each SFA and create a composite inventory in

KBase to simplify searching. • Add metadata about isolates (e.g. source environment, link to genome sequence,

measured physiological data) when possible.

2) Sharing Data and Storage:

This topic has been discussed previously among the SFAs at the annual Genomic Science meeting. In those meetings KBase leaders suggested the intriguing idea of hosting topic-specific environments were SFAs with related interests could share data. Unresolved was the notion of types of data and metadata that might be useful—or even possible—to share. Raw omic’s data are already shared through public archives (e.g. JGI-IMG, KBase, NCBI), but the SFAs produce other types of data that may contribute to synergy. For example, analysis results such as the response of specific microbes to environmental perturbations are a type of higher-order data shared in publications but are difficult to leverage because of the unstructured format in publications. Data sharing among SFA

1 Shetty, S. A., Smidt, H., de Vos, W. M. 2019. Reconstructing functional networks in the human intestinal tract using synthetic microbiomes. Current Opinion in Biotechnology. 58: 146-154 Sergaki, C., Lagunas, B., Lidbury, I., Gifford, M. L., Schafer, P. 2018. Challenges and approaches in micribome research: from fundamental to applied. Fontiers in Plant Science. 9: 1-12

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scientists is hindered by uncertainties about the types of data that might be beneficial to other SFAs, difficulties in providing data in an accessible (structured) format, and lack of consistency in data collection and metadata annotation practices. The following types of data were identified as possibilities for sharing.

§ Isolate inventories. Minimum requirements for metadata need to be defined, and the time-drain (cost) required to supply all of the metadata that other users might need must be recognized as an ongoing challenge.

§ Isolate or OTU phenotype data, potentially organized in a “traits” database. For example:

§ growth on specific substrates (e.g. SIP results), § growth in specific (micro)environments, § response to specific environmental conditions, § linkage to specific functional states § production of specific metabolites § observed or inferred interaction types (beneficial, neutral, or antagonistic)

with specific organisms and conditions under which the interactions occur § metabolic exchanges in specific partners § measured growth rates in lab or field conditions § measured substrate diversity (e.g. Biolog profiles)

ACTION: • Draft metadata preferences by the February 2020 Gen Sci meeting, with attention to

fulfilling FAIR data principles: findable, accessible, interoperable, reuseable. • Continue a longer-term discussion about “trait” data that might be helpful to routinely

measure and share.

3) Establishing Common Standards and Best Practices Common standards and best practices for data production and quality control is an important step to promote data syntheses among SFAs. For example, just as JGI posts protocols for sequencing operations that provide a benchmark for others, SFAs could share protocols for common types of experiments or techniques. Standardization of best protocols could include everything from experimental procedures to modeling strategies and even metadata collection. Modeling emerged as a particular focus where coordination among SFAs might reduce redundant development and create synergy. The scale and purpose of modeling varies within and among SFAs, which poses a challenge. For example, some SFAs are focused more heavily on metabolic models of relatively well-defined consortia whereas other SFAs are pursuing more abstract process models applicable at the ecosystem, regional, or global scale. Nonetheless, it was noted that coordination of modeling efforts has been fruitful within the BER Climate and Environmental Science Division as a framework to enhance collaboration and is therefore worth further exploration. Questions for further discussion included how modeling (of any type or scale) may aid SFAs (this was posed as a particular uncertainty among postdocs and early career scientists), what are the potential benefits of models of different type and scale talking with one another, which

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areas of model development might gain most from coordinated development, and how might coordinated model development occur?

ACTION: Hold a mini workshop at a future (ideally the next) GSP meeting to continue this theme.

4) Fostering Scientific Exchanges One of the most efficient ways to facilitate communication and collaboration is through face-to-face interaction. To this end, the feasibility of postdoc exchanges (e.g. 1-6 weeks to learn other approaches or leverage unique equipment/capabilities such as NanoSIMS, EcoFabs, machine learning techniques, fungal highway columns, etc.) among SFAs was discussed. This would enable capability transfer among SFAs and national laboratories, and would provide relevant experience and broaden the skillset for young investigators. Exchanges would also help facilitate standardization and the sharing of resources such as reagents and equipment. However, there are complications in establishing and distributing microbial stocks between various labs and potentially utilizing non-local isolates. These are especially impacted by ease of access to various organisms (plant pathogens, viruses or BSL-2 organisms). Some possible solutions include Interlab MTA agreements, LIMS systems, and the establishment of a national lab repository. The breakout group explored several avenues to facilitate the exchanges as follows: • Each SFA could set aside a small amount of funding to support an exchange, • BER could allocate a small amount to support exchanges, • SFAs could coordinate planning of renewal proposals to jointly fund a postdoc as a

first step to building synergy.

Several labs already have a form of exchange in place. For example, PNNL has infrastructure for visiting students/postdocs where they are paid on their own lab’s funding, but given a stipend from PNNL for their stay (these stints are 3-6 months). The NNSA labs present additional administrative burdens to if a visiting postdoc is a foreign national. Coordination with the staggered SFA budget cycles is another logistic issue that must be considered.

ACTION: Document the distinctive capabilities and resources each SFA has to offer and post the information in a central location (e.g. BER BSSD website) so that new SFA postdocs (as well as SFA leaders) can quickly identify opportunities.

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CONCLUSION:

Increasing synergy among SFAs is a critical objective to foster the next generation of eco-microbiology, to maximize BER investments, and to accelerate the science missions. The innagural LANL-hosted September 2019 workshop provided an opportunity for valuable scientific discussions and for the emergence of target opportunities for further development . The workshop participants agreed on basic concepts and a collective desire to collaborate. Furthermore, the engagement of BER leadership at the workshop demonstrated the promising idea that a larger vision for SFAs and the DOE could materialize. APPENDIX I– AGENDA APPENDIX II– PARTICIPANTS APPENDIX III– ABSTRACTS APPENDIX IV– CHERYL KUSKE CONTRIBUTIONS

Appendix I – Workshop agenda


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Agenda Sunday • September 15, 2019 5:00pm

Badgepick-upandreception

6:00–8:00pm Dinner6:15pm BabsMarrone FelicitationsforCherylKuske6:45pm ToddAnderson WelcomefromBER7:00pm

NigelMouncey

KeynoteAddress:NationalMicrobiomeDataCollaborative:AcceleratingMicrobiomeDiscoveryandExploration

FoodandbeverageprovidedbytheNewMexicoConsortium



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Monday • September 16, 2019 8:00am

PatFitch

WelcomefromtheLANLAssociateLaboratoryDirectorforChemical,EarthandLifeSciences

8:10am SrinivasIyer ConferenceLogistics8:15am

JohnDunbar

TerrestrialMicrobialCarbonCycling

8:55am

JanetJansson

PhenotypicResponseoftheSoilMicrobiometoEnvironmentalPerturbations

9:35am Coffeebreak9:45am

TrentNorthen

m-CAFÉs:MicrobialCommunityAnalysisandFunctionalEvaluationinSoils

10:25am

RhonaStuart

ASystemsBiologyApproachtoInteractionsandResourceAllocationinBioenergy-RelevantMicrobialCommunities

11:05am

All

Session1questionsandpaneldiscussion

12:05pm

BuffetLunchandpostersession

2:00pm

MitchelDoktycz

PlantMicrobeInterfaces

2:40pm

CrystenBlaby

IntegratingGenomicswithExperimentationtoAddressFamilyandSubfamilyProteinFunctions

3:20pm Coffeebreak 3:30pm

JeremySmith

HowtochewupaPlant:DynamicVisualizationofLignocelluloseDegradationbyIntegrationofNeutronScatteringImagingandComputerSimulation

4:10pm All Session2questionsandpaneldiscussion5:10pm All Endofdayone-dinneronown;enjoySantaFe




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Tuesday • September 17, 2019 8:00am

PatrickChain

InvestigatingBacterial-FungalInteractionswithMulti-omics

8:40am

JenniferPett-Ridge

TheLLNLSoilMicrobiomeSFA“MicrobesPersist”:SystemsBiologyoftheSoilMicrobiome

9:20am Coffeebreak 9:30am

LaurenLui

ENIGMA(EcosystemsandNetworksIntegratedwithGenesandMolecularAssemblies)

10:10am All Session3questionsandpaneldiscussion11:10am All AdditionaldiscussionsandpostersessionNoon All Conferenceends:Lunchonown


Appendix II – Participants


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Michaeline Albright Los Alamos National Laboratory Peter Andeer Lawrence Berkeley National Laboratory Todd Anderson Dept of Energy, BER Joany Babilonia Los Alamos National Laboratory Vanessa Bailey Pacific Northwest National Laboratory Crysten Blaby Brookhaven National Laboratory Thomas Brettin Argonne National Laboratory David Bruce Los Alamos National Laboratory Patrick Chain Los Alamos National Laboratory Melissa Cregger Oak Ridge National Laboratory Karen Davenport Los Alamos National Laboratory Paramvir Dehal Lawrence Berkeley National Lab Alina Deshpande Los Alamos National Laboratory Rae DeVan Los Alamos National Laboratory Mitchel Doktycz Oak Ridge National Laboratory Daniel Drell Dept of Energy, BER, retired John Dunbar Los Alamos National Laboratory Mary Firestone University California, Berkeley Joseph (Pat) Fitch Los Alamos National Laboratory Laverne Gallegos-Graves Los Alamos National Laboratory Sarah Haag Los Alamos National Laboratory Rachel Hestrin Lawrence Livermore National Laboratory Elizabeth Hong-Geller Los Alamos National Laboratory Geoffrey House Los Alamos National Laboratory Miriam Hutchinson Los Alamos National Laboratory Srinivas Iyer Los Alamos National Laboratory Daniel Jacobson Oak Ridge National Laboratory Janet K. Jansson Pacific Northwest National Laboratory Julia Kelliher Los Alamos National Laboratory Marie Kroeger Los Alamos National Laboratory Cheryl Kuske Los Alamos National Laboratory Jessy Labbe Oak Ridge National Laboratory Lauren Lui Lawrence Berkeley National Laboratory Ramana Madupu Dept of Energy, BER Douglas Mans EMSL/Pacific Northwest National Laboratory Babetta Marrone Los Alamos National Laboratory

Appendix II – Participants


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Mary Maxon Lawrence Berkeley National Laboratory Xavier Mayali Lawrence Livermore National Laboratory Rebecca McDonald Los Alamos National Laboratory Ryszard Michalczyk Los Alamos National Laboratory Demosthenes Morales Los Alamos National Laboratory Jenny Mortimer Lawrence Berkeley National Laboratory Nigel Mouncey Joint Genome Institute Trent Northen Joint Genome Institute Erin Nuccio Lawrence Livermore National Laboratory Miriam Pasquini Brookhaven National Laboratory Dale Pelletier Oak Ridge National Laboratory Jennifer Pett-Ridge Lawrence Livermore National Laboratory Jeanne Robinson Los Alamos National Laboratory Aaron Robinson Los Alamos National Laboratory John Sarrao Los Alamos National Laboratory Nancy Sauer Los Alamos National Laboratory Sanna Sevanto Los Alamos National Laboratory Migun Shakya Los Alamos National Laboratory Jeremy Smith Oak Ridge National Laboratory Rhona Stuart Lawrence Livermore National Laboratory Charlie Strauss Los Alamos National Laboratory Scott Twary Los Alamos National Laboratory Inez Valdez Los Alamos National Laboratory Katrina Waters Pacific Northwest National Laboratory Peter Weber Lawrence Livermore National Laboratory

Appendix III – Abstracts


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LANL SFA – Terrestrial Microbial Carbon Cycling

John Dunbar Los Alamos National Laboratory

ThisScienceFocusAreaaimstoinformclimatemodelingandenablecarbonmanagementinterrestrialecosystems.Toachievetheseaims,ourprogramdevelopsandusescommunitygenomicsapproachestodiscoverwidespreadbiologicalprocessesthatcontrolcarbonstorageandreleaseintemperatebiomesoils.Weareusingourmodel-communityapproachtodiscovertraitsthatdrivecarboncyclingvariation.Theresearchprogrampursuesagradualprogressioninsystemcomplexitythatwillleadinalaterphasestoapplicationofvalidatedmicrobialprocessmodelsinfieldstudies.Weusemetagenomic,metatranscriptomic,stable-isotopeprobing,chemicalprofiling,andmachinelearningapproachestounderstandhowmodelcommunitieswithsubstantialdifferencesincarbonflowinteractwithenvironmentalfactorstocontrolecosystemcarboncyclingunderNdeposition.



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Phenotypic Response of the Soil Microbiome to Environmental Perturbations

Janet K. Jansson* and Kirsten S. Hofmockel

Pacific Northwest National Laboratory

Soilisadiverseecosystemwithmicrobialdarkmatterthatremainstobediscovered.Predictingmicrobialinteractionsinthiscomplexsystemrepresentsbothanexcitingfrontierandagrandchallengewithimplicationsfortheproductivityandfertilityofournation’ssoils.PNNL’sSoilMicrobiomeScienceFocusArea(SFA)aimstodevelopasystems-levelunderstandingofsoilmicrobiomeandphenotypicresponsestochangingmoisturethroughatractable,spatiallyexplicitexaminationofthemolecularandecologicalinteractionsoccurringwithinandbetweenmicrobialconsortiabyidentifyingsentinelbiomarkersincomplex,livesoilsystems.Wearedesigningintegratedexperimentstoconfrontboththescalingchallengesandinterkingdominteractionsthatregulatenetworksofbiochemicalreactions.Agent-basedmodelsarebeingparameterizedusinghigh-resolutionexperimentaldata,andpredictionswillbetestedinsoilsbyusingadvancedchemicalimagingandfluorescentprobesuniquetoPNNLtorevealspatiallyexplicitmicrobialinteractions.Discoveriesandoutcomesfromcontrolledexperimentswillbetestedandvalidatedinthefieldthroughmoisturegradientexperimentsatournewlocalfieldsite.Data,models,andmethodswillbecapturedandsharedwiththebroadersciencecommunity.Importantly,wewillleveragethedevelopmentsplannedundertheNationalMicrobiomeDataCollaborative(acollaborativeprogramamongfourNationalLaboratories)toensurethatourdataintegrateswiththisbroadereffort.KnowledgegainedfromthisSFAwillprovideafundamentalunderstandingofhowenzymes,metabolites,andmicrobialconsortiainteracttodecomposeorganiccarbonandwillenablepredictionofhowthesereactionnetworksandrelatedfunctionsshiftinresponsetochangingmoistureregimes.Ourcross-scaleexperimentalapproachaddressesthechallengeofdecodingmicrobiomephenotypesamidstmultiplesourcesofheterogeneity.Byworkingacrossscalesofcomplexityanditeratingbetweenenrichmentcultures,soilmicrocosms,andnaturalsystems,weaimtoidentifymeaningfulbiologicalinteractions,consistentbiochemicalsignatures,andmicrobiomephenotypesrelevanttocyclingofsoilorganiccarbon.Weareusingcomputationalmodelingtomakepredictionsandtodevelopnewhypothesestoidentify,test,andvalidatehowsoilmicrobialconsortiainteractinresponsetosoilmoisture.KnowledgegainedfromourresearchcollaborationwillallowustounderstandhowmembersofthesoilmicrobiomeinteractacrosstrophiclevelstodecomposeorganicCandpredicthowtheresultantbiochemicalreactionnetworksshiftinresponsetomoisture.



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m-CAFEs: Microbial Community Analysis & Functional Evaluation in Soils

Trent Northen

Lawrence Berkeley National Laboratory [email protected]

Rhizospheremicrobialcommunitiesarecriticaldriversofsoilnutrientcyclingandplanthealth.Thevariabilityinnaturalenvironmentsmakesdeterminingcausalmechanismschallenging.Forexample,understandingthefunctionsofexogenousmetabolitesinmediatingbeneficialmicrobialinteractions.Them-CAFEsprogramisamulti-institutionalprojectfocusedonunderstandingoftheinteractions,localization,anddynamicsofgrassrhizospherecommunitiesthatissufficient,atthemolecularlevel(genes,proteins,metabolites),topredictresponsestoperturbations.Centraltooureffortsarethedevelopmentandintegrationofadvancedfabricatedecosystems(EcoFABs)incombinationwithCRISPR-Casandphage-basedapproachesforinterrogatinggeneandmicrobialfunctionsinsitutoadvanceamechanisticunderstandingofmicrobialecology.Theseexperimentalapproachesareintegratedwithpredictivemodelsforiterativerefinementthroughintegratedsimulationsandexperimentation.Theunderstandinggainedandapproachesdevelopedbym-CAFEscanbeextendedtootherecosystemstohelpadvancemicrobiomeresearchtowardsamorepredictiveandcausativescience.Thiswilllayacriticalfoundationforharnessingbeneficialmicrobiomestosupportsustainablebioenergyandimprovingourunderstandingofnutrientcyclingintherhizosphere.



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A Systems Biology Approach to Interactions and Resource Allocation in Bioenergy-Relevant Microbial Communities

Scientific Lead: Rhona K. Stuart

Lawrence Livermore National Laboratory ParticipatingScientists:XavierMayali1,JenniferPett-Ridge1,PeterWeber1,ErinNuccio1,AliNavid1,TySamo1,JeffKimbrel1,MichaelThelen1,PatrikD'Haeseleer1,EoinBrodie2,TrentNorthen2,ToddLane3,SabeehaMerchant4,ChristineHawkes5,KellyCraven6,CullenBuie7

ParticipatingInstitutions:1LawrenceLivermoreNationalLaboratory,2LawrenceBerkeleyNationalLaboratory,3SandiaNationalLaboratory,4UniversityofCaliforniaBerkeley,5NorthCarolinaStateUniversity,6SamuelR.NobleFoundation,7MassachusettsInstituteofTechnology

https://bio-sfa.llnl.gov/

TheLLNLBioenergyScientificFocusArea(SFA)isfocusedonthecommunitysystemsbiologyofmicrobialconsortiathatarecloselyassociatedwithbioenergy-relevantplantsandalgae,withtheultimategoalofdevelopingpredictivemodelstounderstandhowthesesystemswillrespondtoexternalstimuli.PhotosyntheticalgalandplantsystemshavetheunrivaledadvantageofconvertingsolarenergyandCO2intousefulorganicmolecules.Theirgrowthandefficiencyarelargelyshapedandassistedbythemicrobialcommunitiesthatdwellinandaroundplantsandalgaeandliveofftheirprimaryproductivity.Thebiogeochemicaloutcomesoftheseinteractions—howspecifictaxonomiccombinationsaffectenergyandnutrientcyclingpathwaysandareshapedbyvariousenvironmentalstressors—arefundamentalconcernsinthefieldsofmicrobialecologyandbioenergyproduction.Ourresearchisaimedatunderstandingphototroph-symbiontinteractionsthatshapebiomassproductivity,croprobustness,thebalanceofresourcefluxes(C,nutrients,water),andthefunctionalityofthesurroundingmicrobiome.Ouroverarchinghypothesisisthatdifferentheterotrophicsymbiontsnotonlyhavedifferentialeffectsonhostproductivity,butcanchangetheentiresystem’s‘Ceconomy’—acriticalmetricforsustainablebioenergycultivation.Wefocusoninteractionsintwomodelsystems:bacteriaandalgaeinthephycosphere(thesurfaceofalgalcells)andsoilbacteria,fungi,andplantrootsintherhizosphereandendosphere.Ourresearchtargetsspecificphysically-associatedsymbiontsusingbothsimplifiedlaboratoryco-culturesandfield-scalesystems. Weareparticularlyinterestedinunderstandinghowmicroscaleinteractionsaffectlarger-scaleparameterssuchasrobustnessandsustainability.Consequently,ourapproachencompassessinglecellmeasurementsusing,forexample,quantitativeisotopetracingof

elementalexchanges,aswellassystem-scale‘omicsmeasurements.Wehavetworesearchareastosupportthisapproach:advancedcomputationalmodelingapproachestointegrateresultsanddeveloprefinedhypotheses,andnewmethodsdevelopmenttopushtheenvelopeofwhatwecanmeasureand

phycosphere

LLNL’s Bioenergy SFA model research systems



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modelatthesinglecelllevel,andhowwescalethoseresults.



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Plant-Microbe Interfaces

Mitchel Doktycz Oak Ridge National Laboratory

Understandingthephysical,molecular,andchemicalinterfacesbetweenorganismsisessentialtodeterminingtheirfunctionalrolesinbiologicalandenvironmentalsystems.OngoingeffortsinthePlant-MicrobesInterfaces(PMI)ScientificFocusArea(SFA)centeroncharacterizingandinterpretingsuchinterfacesusingsystemscomprisingplantsandmicrobes,primarilyemployingPopulusanditsmicrobialcommunityastheexperimentalplatform.OurpriorPMIeffortsdefinedthecompositionofthePopulusmicrobiome,determinedfunctionalrolesofmicrobialcomponents,andrevealedimportantmolecularsignalsthatareintegraltoestablishingsymbioses.Indoingso,theteamhasadvancedcriticalanalytical,computational,andbiologicaltoolsandresources.Significantassetsincludetheassemblyofarepresentativemicrobialcollectionthatcomprisesthousandsofbacteriaandfungi.Todate,over500bacterialand80fungalgenomeshavebeendefined,largelyincollaborationwiththeJointGenomeInstitute.Leveragingthiscollection,andoveronethousandsequencedPopulustrichocarpagenotypes,adetailedunderstandingofthefunctionalprocessesthatimpacttheperformanceofthiscriticallyimportantmemberoftheperennialforestecosystemispossible.Currently,PMIeffortarefocusedon1)definingtheprogressionofmoleculareventsthatleadstoselective,mutualisticplant-microbepartnershipsanddeterminingthegeneralapplicabilityofthesemechanismsacrossthespectrumofpotentialmicrobiomemembers.Further,wefocus2)onidentifyingandevaluatingthecomponentsofthechemicalenvironmentthatstructurethecommunityand3)onunderstandingtheresponseofthecommunitytobioticandabioticstresses.Understandingthisdynamicinterfaceandthegenomicunderpinningsofinformation,energy,andmaterialexchangeamongandbetweeninteractingorganismsarelong-termgoalsofourresearch.DefiningtheseinterfacesinthePopulus-microbiomewillsetthestagefordetailedunderstandingofothersymbioticrelationshipsandofnaturalroutestoinfluencingecosystemresponsetoglobalchange,thecyclingandsequestrationofcarboninterrestrialenvironments,andthedevelopmentandmanagementofrenewableenergysources.Anoverviewofpast,present,andfutureresearchinthePMI-SFAwillbepresented.



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Integrating Genomics with Experimentation to Address Family and Subfamily Protein Functions

Crysten E. Blaby-Haas

Brookhaven National Laboratory Sustainablebioproductioncropsthatthriveinlow-inputenvironmentsandmaintainperformanceindiverseandfluctuatingconditionsareneeded.Understandingandpredictingbiosystemproductivityindiverseenvironmentsremainsachallengeinsystemsbiologyandishinderedbyalackofinformationaboutthosesystems.Genomicandpost-genomicresourceshaveacceleratedourabilitytoachievesystems-wideinformationastohoworganismsrespondandadapttonutrientstress,butthevalueofthatdataisoftenunderminedbythelackofgeneandproteinfunctionunderstanding.TheQPSIcapabilityisdevelopingapproachesthatcombinethescalabilityoffunctionalgenomicswithproteinfunctioncharacterizationtogeneratethefoundationalknowledgeneededfortheredesignoftargetplantprocesses.Ourteamleveragescross-kingdom‘omics-derivedfunctionalextrapolationsandgene-to-phenotypeknowledgeatthesingle-cellleveltodiscovernovelniche-specificandlineage-wideprocessesastargetsforimprovingtheresilienceofbioenergytolowresourceenvironments.Emergingfromtheseanalyses,proteinfunctionpredictionsareusedtoguidefunctionalcharacterizationviagenetic,biochemicalandmolecularimagingtechniques.Wearealsodevelopingapproachesthatcombinetarget-specificexperimentationwithcomputationalplatformsfortheaccuratepropagationofexperimentallygroundedfunctionalcharacterizationacrosssequencespace.



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How to Chew Up a Plant Dynamic Visualization of Lignocellulose Degradation by Integration of

Neutron Scattering Imaging and Computer Simulation

Jeremy C. Smith Governor’s Chair, University of Tennessee and Director,

Center for Molecular Biophysics, Oak Ridge National Laboratory PlantbiomassisthemostheavilyusedformofrenewableenergyintheUSA.However,theefficientuseofplantlignocellulosiccell-wallbiomassasasourceofbiofuelsandotherhigh-valuechemicalshasbeenhinderedbyrecalcitrancetodeconstruction.TheORNLBiofuelsSFArecognizesthatrecalcitranceisaphysico-chemicalproblem,andhasresearchedwaysofovercomingitusingneutronscatteringandsupercomputing.IncollaborationwithresearchersatUCRiverside,themolecularmechanismbehindapretreatmentmethodthatworksveryefficientlyhasbeenidentified.SmithJCandPetridis,L.NatureReviewsChemistry2,382–389(2018)



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Investigating Bacterial-Fungal Interactions with Multi-omics

Patrick Chain Los Alamos National Laboratory

Fungiandbacteriaformdifferenttypesofassociationsthatarecentraltonumerousenvironmentalprocesses.Similartohumandysbiosesandmicrobiomemanipulationviaantibioticsandprobioticremediation,itmaybepossibletosteeragriculturallandecosystemfunctionbyalteringsoilenvironmentalparameterstoselectfordesiredmicrobesandtraits.Asafirststep,wewishtoinvestigateandcharacterizebacterialinteractionswithfungiatafundamentallevel,toestablishthetypesofinteractions,theirbreadthbothphylogeneticallyandfunctionally,andlater,tocharacterizetheseinteractionsatthemolecularlevel.Priorworksuggeststhatbacteriaandfungiexploiteachotherbothonthesurfacesoffungalmycelialnetworks,aswellaswithinmycelia.Webeginbyexploringthediversenatureoftheseassociationsbyscreeningbothgenomicdatabasesaswellasculturecollections.Availablefungalgenomeprojectsarescreenedforthepresenceofbacterialgenomicsignaturesthatmayhavebeeninadvertentlysequenced.Challengesinthisfieldoftaxonomyclassificationandbacterialidentificationwillbediscussed.Inaddition,wescreendiversefungalcollectionsforbacterialsignaturesusinganapproachbasedonsequencingofthe16SrRNAgenecombinedwithmicroscopicconfirmationofthepresenceofendohyphalbacteria.Forsomeisolates,weexploresomeoftheinteractionsphenotypically,bymonitoringgrowthduringconfrontationassays.Wehaveuseddevicesdubbed‘fungalhighway’columns,toisolatebacteriacapableofutilizingfungalmyceliaasadispersalmechanism,andaretestinga3Dfabricationofthistypeofdeviceforroutineexplorationofsuchinteractions.Growthphenotypesofsomeofthesebacterialandfungalisolates,aswellasknowninteractingbacterial-fungalpairs,arebeingexamined.Collectively,thesestudiesbegintoshedlightintothediversity,andrangeofinteractionsthatoccuramongthesedominantmicrobialplayers.https://github.com/LANL-Bioinformaticshttps://genomicscience.energy.gov/research/sfas/lanlbfi.shtmlThisstudywassupportedbytheU.S.DepartmentofEnergy,OfficeofScience,BiologicalandEnvironmentalResearchDivision,underawardnumbersLANLF59TandLANLF59C.



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Microbes Persist: Systems Biology of the Soil Microbiome

Jennifer Pett-Ridge*, Jill Banfield, Steve Blazewicz, Eoin Brodie, Mary Firestone, Bruce Hungate, Matt Sullivan

Lawrence Livermore National Laboratory

Soilsstoremorecarbonthantheatmosphereandbiospherecombined,yetthemechanismsthatregulatesoilCremainelusive.Whileplantrootsarethedominantsourceofcarbon(C)thatentersbelowgroundfoodwebs,microbialtransformationsofthisCdeterminewhetheritisretainedassoilorganicmatter(SOM)orreturnedtotheatmosphere(CO2,CH4).SincesoilCandassociatedorganicmoleculesaresocriticaltosoilfertility,waterholdingcapacity,andtheCbalanceofourplanet,apredictiveunderstandingofsoilCresidencetimeandturnover(i.e.‘persistence’)isessential.Ithasrecentlybecomeclearthatmicrobialcellmaterials(‘necromass’)playacriticalroleinthepersistenceofSOM.However,currentsoilCmodelscontinuetoemphasizestabilizationbyabioticmechanisms(sorption,occlusion,andrecalcitrance),largelyignoringtheimpactsofmicrobialecophysiology.Wehypothesizethatmicrobialbiochemistry,functionalpotentialandphysiologymaybeofcomparable,orgreaterimportancerelativetoabioticstabilizingeffects.Wefurthersuggestthatthebasisofmicrobialimpactsresultsfromtheirspecificecophysiological‘traits’(e.g.cellwallcomposition,hyphalgrowth,EPSproduction,sporeformation,carbonuseefficiency,extracellularenzymes,adhesiongenes,andspecificgrowthrate)thatcanbegenomicallyresolvedthroughsoilmetagenomicsandquantifiedviaisotopetracing.Wefocusonsoilmoistureasa'mastercontroller'ofmicrobialactivityandmortality,sincealteredprecipitationregimesarepredictedacrossthetemperateU.S.OurSFA’sultimategoalistodeterminehowmicrobialsoilecophysiology,populationdynamics,andmicrobe-mineral-organicmatterinteractionsregulatethepersistenceofmicrobialresiduesunderchangingmoistureregimes.Inthispresentation,IwilldiscussalistofpotentialtraitsthatmaybefruitfultargetsformetagenomicstudiesevaluatingthepersistenceandimportanceofmicrobialproductsasSOMprecursors.Withnewquantitativestableisotopeprobingapproaches,itisnowpossibletolinkthesegenome-resolvedecophysiologytraitstodirectlymeasuretaxon-specificpopulationdynamics.Iwillpresentourrecentresultswhichhighlightadvancesinstableisotopeprobing(SIP)-metagenomics,soilviromics,andthedifferentialpatternsweobserveincommunitydeathvsgrowth.Iwillalsodiscussourresultsshowingthatsoilmineraltypeinfluencesthemicrobialcommunitiesthatcolonizemineralsurfaces.Withrhizosphereisotopetracing,wefindthatplantcarbonthatflowstosoilmicrobialcellsistransformedintheprocess,andthatbothmicrobially-transformedcarbonandmicrobialcellmaterialsdirectlyassociatewithmineralsurfaces.Finally,Iwillproposeaseriesofintegratedapproachesthatusedtogethercanexaminehowgenomiccapacityandactivitiesofsoilmicrobiomesareshapedbyedaphicconditions(moisture,temperature,redoxregimes)andfundamentallyaffecttheterrestrialsoilCpool.



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ENIGMA: Ecosystems and Networks Integrated with Genes and Molecular Assemblies

Lauren Lui

Lawrence Berkeley National Laboratory [email protected]

ENIGMAisacollaborativeconsortiumof19investigatorsat13institutionslocatedacrossthecountryandisledbyprincipalsattheLawrenceBerkeleyNationalLaboratory.Establishedin2009,ENIGMAresearcherscollaboratecloselytocreateamultiscale,causalandpredictiveunderstandingofmicrobialbiologyandthereciprocalimpactofmicrobialcommunitiesontheirecosystems.Weuseasystemsbiologyapproachtounderstandtheinteractionbetweenmicrobialcommunitiesandtheecosystemsthattheyinhabit.Tolinkgenetic,ecological,andenvironmentalfactorstothestructureandfunctionofmicrobialcommunities,ENIGMAintegratesanddevelopslaboratory,field,andcomputationalmethods.EffortsarefocusedonstudyingsubsurfacemicrobiomeswithinthecontaminatedBearCreekaquiferattheOakRidgeReservation,asitewithcomplexgradientsofcontaminants,generatedbyresearchandproductionofnuclearmaterials,includingnitrate,acidity,uranium,technetiumandvolatileorganiccarbonspeciesthefateofwhichismediatedbytheactivityofsubsurfacemicrobialcommunities.Thesefollowcomplexflowpathstheaffectthedispersalofmaterialsincludingmicrobes.Here,weperformsophisticatedfieldexperimentstomeasurethenaturalandanthropogenicallyperturbeddynamicsofthesegeochemicalprocessesandmicrobialcommunityassemblyandactivity.Fromtheseweinferthechemical,physicalandmicrobialinteractionsmostpredictiveofthesedynamicsandestimatetheecologicalforces,bothstochasticanddeterministic,thatshapecommunityfunction.Todissectthecausalbasisfortheseobservationsthroughlaboratorystudies,weapplyauniquearrayofculturing,genetic,physiologicalandimagingtechnologiestomapgenefunctionandmaterialflowwithinandamongcells.IwillhighlightcurrentworkinENIGMAanddiscussalarge-scaleanalysisweperformedontwosedimentcoresandassociatedgroundwaterfromtheOakRidgeFieldResearchCenter.Thisstudyintegratesover12depth-indexdatasetsofmicrobialcommunitycomposition,activity,andenvironmentalcontrols,includingshotgunmetagenomics,16Ssequencing,metalconcentrations,activitymeasurements,carbonandnitrogenavailability,andgeneralbiogeochemicalparameterstoprovidenewinsightsintotheecologicalandenvironmentalfactorsshapingthestructureandfunctionsubsurfacemicrobialcommunities.InthelasthalfofthetalkIwilldiscussENIGMA’splansandlong-termviewforintegrationandanalysisof‘omicsdataforpredictiveandmechanisticmicrobialecology.



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Poster: Impacts of Drought Stress from Climate Change Melissa Cregger, Ph.D. Staff Scientist Biosciences, Oak Ridge National Laboratory ~Joint Assistant Professor Ecology and Evolutionary Biology, University of Tennessee Phone: (865)241-3776 • Cell: (865)621-0047 Droughtstressfromclimatechangenegativelyimpactsmicrobialactivity,butthemagnitudeofstressresponsesislikelydependentonbelowgroundinteractions.WeexposedPopulustrichocarpaindividualsandnoplantbulksoilstoextendeddrought(~0.03%GWCafter12d),re-wet,anda12-d“recovery”period(continuedirrigation)todeterminetheeffectsofplantpresenceinmediatingsoilmicrobiomestabilitytowater-stress.PlantmetabolomicsindicatedthatdroughtexposureincreasedinvestmentinCandNmetabolicpathways(aminoacids,fatty-acids,phenolicglycosides)regardlessofrecovery.Severalmetabolites(e.g.,aminoacids)positivelycorrelatedwithrootmicrobialalphadiversity,butnotsoil.BacterialcompositionshiftedwithP.trichocarpapresenceandwithdroughtrelativetoirrigatedcontrolswhereasfungalcompositiononlyshiftedwithplantpresence.Theproportionofbacterialwater-stressopportunisticOTUs(enrichedcountsinDrought)werehigh(~11%)attheendofdrying,andmaintainedafterre-wet,andrecoveryinbulksoils,butdeclinedovertimeinsoilswithplantspresent.TheproportionofsensitivebacterialOTUs(depleted)weresimilaramongbulksoilsandplantedsoilsatdrying,whereasduringrecoverytheproportionofbulksoilsensitiveOTUsincreasedandplantedsoilsdecreased.Thesedataindicatethatplantsmodulatesoilandrootassociatedmicrobialdroughtresponsesviatightplant-microbelinkagesduringextremedroughtscenarios.



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Poster: Genomic Analysis of Diverse Members of the Fungal Genus Monosporascus Reveals Novel Lineages, Unique Genome Content and the Potential to Harbor Bacterial Endosymbionts Aaron J. Robinson1,2, Donald O. Natvig2, Demosthenes Morales1, Geoffrey L. House1, Julia M. Kelliher1, Patrick S. G. Chain1 1Los Alamos National Laboratory, Los Alamos, NM, USA 2University of New Mexico, Albuquerque, NM, USA LA-UR-19-26004 ThegenusMonosporascusrepresentsanenigmaticgroupoffungiimportantinagricultureandwidelydistributedinnaturalaridecosystems.OftheeightdescribedspeciesofMonosporascus,two(M.cannonballusandM.eutypoides)areimportantpathogensontherootsofmembersoftheCucurbitaceaeinagriculturalsettings.Theremainingsixspeciesarecapableofcolonizingrootsfromadiversehostrangewithoutcausingobvioussymptomsofdisease.RecentmolecularandculturestudieshaveshownthatmembersofthegenusarenearlyubiquitousasrootendophytesinaridenvironmentsoftheSouthwesternUnitedStates.Isolateshavebeenobtainedfromapparentlyhealthyrootsofgrasses,shrubsandherbaceousplantslocatedincentralNewMexicoandotherregionsoftheSouthwest.TheseisolatesdisplayedawiderangeofmorphologicalphenotypesincultureandneitherasexualnorsexualsporeproductionhasbeenobservedintheseSouthwesternisolates.Phylogeneticandgenomicanalysesrevealsubstantialdiversityamongtheseisolates.TheNewMexicoisolatesincludecloserelativesofM.cannonballusandM.ibericus,aswellasisolatesthatrepresentpreviouslyunrecognizedlineages.Toexploreevolutionaryrelationshipswithinthegenusandgaininsightsintopotentialecologicalfunctions,wesequencedandassembledthegenomesofthreeM.cannonballusisolates,oneM.ibericusisolateandsixdiverseNewMexicoisolates.TheassembledgenomesweresignificantlylargerthanwhatistypicalfortheSordariomycetesdespitehavingpredictedgenenumberssimilartoothermembersoftheclass.VariationintheM.cannonballusgenomesindicatedsubstantialdiversityingenomesizeandgenecontentwithinthespecies.WhileregionsoftheMonosporascusgenomesexhibitsyntenywithgenomesofdiversemembersoftheXylariales,certainregionsdonot.GenomicregionslackingclearsyntenywithothermembersoftheXylarialesareingeneralAT-richandareinsomecasesenrichedforgenesinvolvedinsecondarymetabolism.Comparisonsofpredictedcarbohydrate-activeenzymesandenzymesinvolvedinpathogenicitysuggestthatendophyticMonosporascusisolatespossesshighernumbersofgenesforbothgroupsofenzymesthandopathogeniclineages.SeveralMonosporascusisolatesappeartoharborbacterialendosymbiontsfromthegenusRalstonia.



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Poster: Using Genomic Data to Identify Bacterial Associates of Fungi Geoffrey House, Aaron Robinson, Andrea Lohberger, Fabio Palmieri, La Verne Gallegos-Graves, Julia Kelliher, Demosthenes Morales, Debora Rodrigues, Hang Nguyen, Saskia Bindschedler, Jean Challacombe, Jamey Young, Pilar Junier, Patrick Chain Los Alamos National Laboratory The1000FungalGenomesProjectthroughtheJointGenomeInstitute(JGI),containsdatafromover1300diversefungalisolatesrepresentedinJGI’sMycocosmdatabase,andthereforerepresentsauniquefungalgenomicresource.Becausemanyfungihavebacteriaandvirusesassociatedwiththem,theseDNAsequencedatasetsfromfungicouldalsoprovideinformationabouttheassociatedmicrobiomeofthesefungalisolates.Tothisend,wehavedevelopedabioinformaticspipelinetoidentifysignalsofbacteriainfungalgenomesequencingdata.Wefirstremoveallidentifiablefungalsequencesfromtherawsequencingdatainordertoreducespurioussimilaritiestobacteria.Next,weassembletheremainingreadsintolongercontigs,groupthecontigsintobinsputativelyrepresentingsinglebacterialgenomes,andthenidentifybacterialcontigsusingataxonomyclassifierwithacustomreferencedatabase.Weillustratetheutilityofthisapproachusingsequencedatafrom10Monosporascusfungalisolates.Usingthisbioinformaticspipeline,wecorrectlyidentifiedtwoofthethreeisolatesexpectedtohaveassociatedRalstoniabacteriaandconfirmedtheidentificationofRalstoniapickettii,whilecorrectlynotfindingabacterialsignalinanyoftheothersevenfungalisolates.Wehavealsoevaluatedhowsensitivelythispipelineidentifiesbacterialsignalsoverarangeofbacterialabundances.Thispipelineiseffectiveinidentifyingthepresenceofstrongbacterialgenomicsignalsinfungalsequencingdatawhileproducingfewfalsepositiveresultsincontrolledtests,andinthefutureitcanbeappliedtoawidervarietyofmetagenomesamples.LA-UR-19-25107



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Poster: Investigating Chloroplast Signal within the Endo-hyphal Fungal Microbiome Julia M. Kelliher1, Geoffrey L. House1, Demosthenes P. Morales1, Aaron J. Robinson1, La Verne A. Gallegos-Graves1, Hang N. Nguyen3, Debora F. Rodrigues3, Jamey D. Young4, Jean F. Challacombe5, Saskia Bindschedler2, Pilar Junier2, and Patrick S.G. Chain1

1Bioscience Division, Los Alamos National Laboratory, Los Alamos, New Mexico; 2Insitute of Biology, University of Neuchâtel, Neuchâtel, Switzerland; 3Civil and Environmental Engineering, University of Houston, Houston, Texas; 4School of Engineering Vanderbilt University, Nashville, Tennessee; 5College of Agricultural Sciences, Colorado State University, Fort Collins, Colorado LA-UR-19-25961 Theendo-hyphalfungalmicrobiomecontainsmanyuncharacterizedinhabitantsandinteractions.Thisfungalmicrobiome,coupledwithanextensivenetworkofextracellularinteractionswithbacteriaandplantswithinthesoil,contributetothecomplexecosystemservicesfacilitatedbyfungi.Wesoughttocharacterizethemembersoftheintracellularfungalmicrobiomeasawaytobetterunderstandtherolesoffungiandtheirassociatedendosymbionts.Basedonascreeningestablishedfromsequencingofthe16SrRNAgeneoffourdistinctfungalcollectionsfromdifferentgeographiclocations,wehaveidentifiedtaxonomicsignaturesofmanybacterianotpreviouslyknowntobeassociatedwithfungi.Oneofthesesignaturesthatwasfoundacrossallculturecollections,isarecurrentsignalofsequencesthatareidenticaltovariousplantchloroplasts.Severaltechniqueswereutilizedinvalidatingthepotentialassociationsbetweenfungiandthechloroplastsrepresentedbythesesignatures,includingFISHstaining,phylogeneticanalyses,PCRamplifications,andadditionaltargetedbioinformaticscreensusingwholegenomesequencedata.Additionalanalysisofthedatafromtheseculturecollectionswillaidinourunderstandingofthefungalmicrobiomeanditscomponents.



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Poster: Addressing Multi-functional Protein Families with Comparative Genomics, Biochemistry and Genetics M. Pasquini and C.E. Blaby-Haas Department of Biology, Brookhaven National Laboratory, Upton, NY Functionalannotationveracityisoftendifficulttoassess.Thischallengeisparticularlyacuteforlargeproteinsfamilies,whichcontainmultipleparalogsandmembersfromtaxonomicallydivergentlineages,andwhereexperimentalevidenceforfunctionisscarceorabsent.Thesegenefamiliesfallvictimtounsupervised,error-pronepropagationofannotationsfromonegenometoanother,andthefrequencyofmis-annotationsisbecominganunmaneageableproblem.AttheQuantitativePlantScienceInitiative,weareleveragingphylogenomicsanddata-miningbasedfunctionpredictionscombinedwithbacterial,fungalandplantexperimentalsystemstogeneratefamily-wideandorganism-specificaspectsofgeneandproteinfunctionforuniversalfamiliesofproteins.Aclassicexampleofprolificmis-annotationisthe“CobW”family.Theseproteinsarecommonlyannotatedasfunctioningincobalaminbiosynthesis,eveninorganismsunabletosynthesizecobalamin.Usingourgenome-basedapproach,wehypothesizedthat,liketherelatedproteinsHypBandUreG,whoseGTPaseactivityaccompaniesthemetalinsertionofNiintohydrogenaseandurease,respectively,theCobW-likeproteinsareGTPaseswithmetalinsertaseactivity.UnlikeHypBandUreG,wepredictthatdifferentCobW-likesubfamiliesinteractwithnumerousmetal-dependentproteins.Usingacombinationofgenomics,geneticsandbiochemistry,wefindthatCobW-likeproteinsfrombacteriatofungitoplantsfunctioninmetaltransfertometalloproteinsduringresourcelimitation.Wefurtherhypothesizethatthisactivityestablishesahierarchyofcofactorprioritization.Inadditiontoaddressingthemis-annotationbottleneckingenefunction,thisworkprovidesanovelstrategyforadaptingorganismstolow-nutrientenvironments.



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Poster: Observing the Effect of Bacterial Presence on Fungal Spore Germination Demosthenes Morales1,2, Julia Kelliher2, Geoffrey House2, Aaron Robinson2, Laverne Gallegos-Graves2, James Werner1, Patrick Chain2

1MPA-CINT: Center for Integrated Nanotechnologies, Los Alamos National Laboratory 2B-10: Biosecurity and Public Health, Los Alamos National Laboratory Linkingbacterialandfungalco-occurrenceinsoiltofunctionalinteractionsisapresentchallengeinunderstandingcomplexmicrobialnetworks.Next-generationsequencing(NGS)offersabroadviewoftheseinteractionsbutlackstheresolutiontocataloguebehaviorsaseithermutualisticorantagonistic,forexample.Here,wearecharacterizingbacteriaandfungiatthesinglecellleveltoelucidatetheinfluenceofspatialandtemporaldependentinteractions.Inourfirstcase,weinvestigatetheinfluencebacteriahaveonthegerminationofthefungalbiocontrolagent,Trichodermaharzianum,andotherTrichodermaspecies.Usingbrightfieldmicroscopy,wedeterminetherateofgerminationforapopulationofsporesinthepresenceofbacterialpartnersrelativetoindependentspores.Thisvisualphenotypicresultwillmotivatefurthermolecularinvestigationstodeterminethecontributionbymicrobialpartnersininfluencingfungalgrowth.Wefindthatbacterialpresenceislinkedtoeitheraccelerationorretardationofsporegerminationandmayhaveimplicationsinpromotingefficientgrowthofbeneficialfungalstrainsespeciallyinstressedenvironments,whichisofinterestforbiotechnologicalapplications.LA-UR-19-26248



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Poster: Fabricated Ecosystems (EcoFABs) for Examining Plant Microbiomes in m-CAFEs Peter Andeer1, Kateryna Zhalnina1, Joelle Sasse Schlapfer2, Dawn Chiniquy1, Peter Kim3, Jens Heller1, Lauren Jabusch1, Anup K. Singh3, N. Louise Glass1, Adam M. Deutschbauer1, Trent Northen1 1Lawrence Berkeley National Laboratory, 2University of Zurich, 3Sandia National Laboratory [email protected] EcoFABs,orEcosystemFabrication,usessingleplant-scaleecosystemsfortheresearchofplantandsoilmicrobiomes(www.eco-fab.org;https://doi.org/10.3791/57170).StandardEcoFABscontainrootchambers(1.5–12ml)forimagingrootphenotypesandmicrobialcolonization,allowforsamplingofplantexudatesandhavebeentestedwithanumberofplantspeciesandgrowthmatrices.ToassessthereproducibilityofplantandmetabolitemeasurementswithinEcoFABs,aring-trialwasconductedbetweenfourlaboratoriesgrowingthemodelplantBrachypodiumdistachyonwithinEcoFABs.Form-CAFEswearedevelopingandusingstandardandspecializedEcoFABsandmicrobiomestoanalyzemicrobialinteractionsofplantandsoilmicrobiomes.SpecializedEcoFABdesignsincludethosetoinvestigate:mycorrhizal-plantinteractions(MycoFAB),chemicalandoxygengradients(μEcoFAB),andconfocalimagingoffluorescentlylabeledbacteriaonplantroots(imagingEcoFab).AdefinedcommunityofmicroorganismsforEcoFABexperimentsisbeingdevelopedform-CAFEsusinganumberofcriteria,including:taxonomicandfunctionaldiversity,abundanceandactivityintherhizosphere,co-varianceinthecommunity,activitiesassociatedwithplantgrowth,andefficientplantrootcolonization.Wewillusethiscommunityinparttoexaminehowaromaticacidsareinvolvedinthefunctionofplantmicrobiomes.Wehaveseverallinesofevidencethathypothesizethataromaticacidsarespecificrootexudatecomponentsthatareselectivelyusedbyrhizospherebacteriainsitu,enablingplantmodulationofcommunitystructureusingexudatecomposition,forexampleinresponsetonitrogenstresshowevercommunityeditingisneededtoestablishcausalmechanisms.



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Poster: Mycorrhizal Nitrogen Acquisition Enhanced by Multipartite Interactions and Gaseous Transport Rachel Hestrin, Edith Hammer, Carsten Mueller, Johannes Lehmann Lawrence Livermore National Laboratory Nitrogenavailabilityoftenrestrictsprimaryproductivityinterrestrialecosystems.Arbuscularmycorrhizalfungiareubiquitoussymbiontsofterrestrialplantsandcanimproveplantnitrogenacquisition,buthavealimitedabilitytoaccessorganicnitrogen.Althoughothersoilbiotamineralizeorganicnitrogenintobioavailableforms,theymaysimultaneouslycompetefornitrogen,withunknownconsequencesforplantnutrition.Here,weshowthatsynergiesbetweenthemycorrhizalfungusRhizophagusirregularisandsoilmicrobialcommunitieshaveahighlynon-additiveeffectonnitrogenacquisitionbythemodelgrassBrachypodiumdistachyon.Thesemultipartitemicrobialsynergiesresultinadoublingofthenitrogenthatmycorrhizalplantsacquirefromorganicmatterandatenfoldincreaseinnitrogenacquisitioncomparedtonon-mycorrhizalplantsgrownintheabsenceofsoilmicrobialcommunities.Thismultipartiterelationshipmaycontributetomorethan70Tgofannuallyassimilatedplantnitrogen,therebyplayingacriticalroleinglobalnutrientcyclingandeco-systemfunction.



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Poster: Bacterial Mutualism with Biofuel-producing Microalgae: Molecular and Single Cell Isotope Tracing Xavier Mayali Lawrence Livermore National Laboratory

AspartoftheLLNLbiofuelsScienceFocusArea,weinvestigatealgal-bacterialinteractionsandtheirimpactonnutrientcycling,microbialcommunitycomposition,andenergyandbiomassproduction.Asamodelsystem,wefocusontheinteractionsbetweenthediatomPhaeodactylumtricornutumCCMP2561andbacterialstrainsisolatedfromitsphycosphere-associatedmicrobiomeoriginallycollectedfromoutdoorraceways.Usingahigh-resolutionstableisotopeimagingapproachwithNanoSIMS,wequantifiedtheincorporationofP.tricornutumderivedorganicmatterbydifferentbacterialstrainsanditssubsequenttransferbacktothealgalcells.NanoSIMSenablescell-specificmeasurementsofincorporation,andourdatahasidentifiedwhichmicrobialmembersmediatethemajorityoftheCandNtransferinthesesimplifiedsystems.

InordertobetterunderstandP.tricornutum-bacterialinteractionsatthemolecularandgeneticlevel,andidentifyputativegenesinvolvedinbeneficialinteractions,wealsoconductedglobalproteinexpressionprofiling.WecomparedP.tricornutumaxeniccultureswithtwoP.tricornutum-bacterialco-cultures,bothduringmid-exponentialgrowth.ThetwobacterialstrainshavedistinctinteractionswithP.tricornutum:Marinobacteriscapableofattachment,andenhancesgrowthandsinglecellcarbonfixationofthealgalcells.Rhodobactersp.PT6CLA(Rhodobacter),doesnotattachtoP.tricornutumnorprovideanysignificantgrowthorcarbonfixationenhancement.Thetwobacterialstrainsalsoexhibitdistinctgrowthpatternsinco-culture,withMarinobactermaintaininglow,consistentabundancerelativetoP.tricornutum,andRhodobacterincreasingexponentiallywithP.tricornutumgrowth.Proteomicprofilingcomparingtheseco-cultureswitheachotherandtheaxenicculturerevealedanumberofputativepathwaysinvolvedinalgal-bacterialinteractions,highlightingthemultifacetednatureoftheinteraction.



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Poster: Characterizing Viruses from Soil Migun Shakya, Michaeline Albright, Patrick Chain, John Dunbar Bioscience Division Los Alamos National Laboratory, Los Alamos, NM 87545 Viruses,geneticelementsthatinfectandreplicatewithinhostorganisms,areoneofthemostabundantanddiversebiologicalentitiesonearth,yettheyremainhighlyunder-studied,particularlyinsoilecosystems.Recentstudieshavefoundthatvirusesplayasignificantroleinoceancarboncycling,buttheroleofvirusesinterrestrialcarboncyclingremainsunclear.Here,wepresentapproachesthatcombinesclassicalmicrobiologywithadvancedomicstechnologytocharacterizevirusesfromsoilecosystem.Wewilldescribeviraldiversityinsoilsusingbothpubliclyavailableandnewlysequencedgenomes,metagenomes,andmetatranscriptomes.Additionally,traditionalmicrobiologymethodswillbeusedtoidentifyvirusesthatareimportantforcarbonphenotypeofsoils.Theresultshavepotentialtoinformterrestrialecosystemmodelsandexpandtheknowndiversityofterrestrialviruses.



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Poster: Architecture Design of Microbiome Data Analysis Workflows for NMDC Bin Hu, Karen Davenport, Mark Flynn, Po-E Li, Chien-Chi Lo, Yan Xu, Migun Shakya, and Patrick Chain Biosecurity and Public Health (B-10), Los Alamos National Laboratory, Los Alamos, NM 87544 TheNationalMicrobiomeDataCollaborative(https://microbiomedata.org)isfoundedbyDOEOfficeofSciencetosupportthelong-termadvancementofmicrobiomescience.TheNMDCisbuildinganopen-source,agile,integrateddatasystem.Ourscientificmissionistoprovidecomprehensiveaccesstomultidisciplinarymicrobiomedataandaninitialsuiteofbioinformatictoolsforreproducible,cross-studyadvancedanalyses.AsoneofthefourDOEnationallaboratoriesparticipatingNMDC,theLANLbioinformaticsteamistaskedwithdevelopingsomeofthesoftwaretoolsandworkflows,includingworkflowsforshotgunmetagenomeassemblyandannotation,shotgunmetagenomeread-basedanalysis,contigbinningandMAGs(metagenome-assembledgenomes)generationpipeline,andworkflowformetatranscriptomedataanalysis.ThissetofworkflowsandsoftwarewillbehostedbyNMDCassharedcomputationalresources,whichwillcontributetothestandardizationofmicrobiomedataanalysis.Oneofthemajorchallengesofthisendeavorismanagingthecomplexityinvolvedinintegratingandpackagingalargecollectionofcarefullyselectedopensourcesoftware,writtenbydifferentgroupsinternationally,usingdifferentprogramminglanguages,andwithconflictingdependencies,intoaninteroperablesoftwaresuitethatrunsinadesignatedsupercomputingenvironmentattheBerkeleyNationalLaboratory.ToefficientlylowerthecomplexityoftheNMDCworkflowsandsoftwaredevelopment,wehaveadoptedalightweightserviceorientedsoftwarearchitecturerunningontopofsoftwarecontainers.Comparedtotraditionalmonolithicsoftwarearchitectures,thisnewdesignenablesustoshipdevelopedsoftwareincrementallyatapredictablepaceandmaximizecodereuse.



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Poster: EDGE Bioinformatics Platform for NGS Data: Empowering the Development of Genomics Expertise Chien-Chi Lo, Po-E Li, Migun Shakya, Mark Flynn, Geoffrey House, Yan Xu, Karen Davenport, Patrick Chain Applied Genomics Team, Los Alamos National Laboratory. Continuedadvancementsinsequencingtechnologieshavefueledthedevelopmentofnewsequencingapplicationsandpromisetofloodcurrentdatabaseswithrawdata.Anumberoffactorspreventtheseamlessandeasyuseofthesedata,includingthebreadthofprojectgoals,thewidearrayoftoolsthatindividuallyperformfractionsofanygivenanalysis,thelargenumberofassociatedsoftware/hardwaredependencies,andthedetailedexpertiserequiredtoperformtheseanalyses.Toaddresstheseissues,wehavedevelopedanintuitiveweb-basedenvironmentwithawideassortmentofintegratedandcutting-edgebioinformaticstoolsinpreconfiguredworkflows.Theseworkflows,coupledwiththeeaseofuseoftheenvironment,provideevennovicenext-generationsequencinguserswiththeabilitytoperformmanycomplexanalyseswithonlyafewmouseclicksand,withinthecontextofthesameenvironment,tovisualizeandfurtherinterrogatetheirresults.ThisbioinformaticsplatformisaninitialattemptatEmpoweringtheDevelopmentofGenomicsExpertise(EDGE)inawiderangeofapplicationsformicrobialresearch.EDGEisunderconstantdevelopmenttoexpanditscapabilities.Workflows:

• Pre-processing(QC&hostremoval)• Assembly&Annotation• Reference-basedAnalysis• TaxonomyClassification• PhylogeneticAnalysis• SpecialtyGenes• PrimerAnalysis• IdentificationofAMRandvirulencegenes• Comparisonofmultiplemetagenomicssamples’taxonomyresults• 16S/18S/fungalITSanalysisusingQIIME2• Integrationofsamplemetadatacollection/storage

Therecentrelease,EDGEversion2.4includesseveralnewfeatures:• Reportgeneration• Pathogenanalysisandcharacterization• Presence/absenceoftargetedampliconsd• Differentialgeneexpression(RNA-Seq)• ToolsforanalysisofNanoporeMinIondata• MetagenomeContigsBinning• SecondaryMetaboliteAnnotation

EDGEisavailableforuserstouploaddataandtryouttheplatform’stoolsandpipelinesathttps://edgebioinformatics.org/

Appendix IV – Cheryl Kuske Contributions


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For the last 26 years, Laboratory Fellow and microbiologist Cheryl Kuske worked at Los Alamos’ Bioscience Division using environmental sequencing to improve both climate and biothreat research. Her contributions to miniaturizing and automating DNA extraction from environmental samples improved research in these two arenas by allowing scientists to begin to characterize the taxonomic and ecological discovery of microorganisms in soil and to differentiate between pathogens and near-neighbors. This, combined with significant advances in sequencing technology and bioinformatics analysis, laid the groundwork for studies to better understand the roles of microorganisms in the overall ecosystem. As Kuske retired in early 2019, the Bioscience Division and Los Alamos National Laboratory sought to celebrate her retirement by hosting the workshop Microbiome-to-Function: Next Generation Eco-Microbiology. This workshop also created an opportunity to bring together more SFA scientists—from all the DOE BER Genomics Science Program projects and SFAs—to discuss the future of environmental and ecological microbiology.

Documents

Microbiome to Function-Report-final · Microbiome to Function: Next Generation Eco-Microbiology Workshop LA-UR-20-22843 1 Workshop Report INSTITUTIONAL HOSTS: J. Patrick Fitch, Associate