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Arkin, Adam

Arkin, Adam

Lawrence Berkeley National Lab
SFA Technical Co-Manager
[email protected]
(510) 643-5678

 

Adam Arkin is an expert in the systems and synthetic biology of microbes. His role as the SFA Technical Co-Manager is to ensure the scientific basis of the mission goals, working with the Directors and Principal Investigators to develop coherent projects that address high value problems, especially those of scale.  As Microbial Physiology Component Director he helps Principal Investigators and Project Scientists effectively plan and execute experiments addressing relevant themes.

Adams, Mike

Adams-Mike_thumbnailUniversity of Georgia
Principal Investigator
[email protected]
(706) 540-1645

 

Michael Adams is a Principal Investigator of a Discovery Project that spans the Environmental and Microbial Physiology Components. His primary research interests are the metabolism of metals and their assimilation into metalloproteins. His laboratory conducts elemental analyses (53 metals) of environmental samples and is developing methods for high throughput characterization of metalloproteins in microbial biomass. The goal of the project is to determine how environmental metal availability determines and potentially limits microbial activity.

DuBSEQ functional characterization Nature Communications


 
ENIGMA researchers release DuBSEQ, a tool for broader use in microbial functional characterization and which allows for high throughput manipulation of specific strain libraries in Nature Communications.

A multi-disciplinary team of bench scientists and computational scientists collaborated to generate the large data set and analyses that confirm known functional genes and identify interesting genes of novel function.

Vivek K. Mutalik, Pavel S. Novichkov, Morgan N. Price, Trenton K. Owens, Sean Carim, Astrid Terry, Adam M. Deutschbauer, Adam P. Arkin

ENIGMA authors; Front row-Morgan N. Price, Pavel S. Novichkov, Vivek K. Mutalik, Astrid Terry, Sean Carim. Back row-Trenton K. Owens, Adam M. Deutschbauer, Adam P. Arkin — In Emeryville, California, 1/16/2019

Dual-barcoded shotgun expression library sequencing for high-throughput characterization of functional traits in bacteria https://doi.org/10.1038/s41467-018-08177-8

Robustness of a model microbial community emerges from population structure among single cells of a clonal population


 

Dr. Anne Thompson Portland State University https://www.pdx.edu/microbial-ecology/people

Robustness of a model microbial community emerges from population structure among single cells of a clonal population Thompson, A.W, Turkarslan S., Arens, C.E, López García de Lomana, A., Raman, A., Stahl, D.A., Baliga, N.S. Environmental Microbiology, 10.1111/1462-2920.13764

Wild type replicates begin to collapse after 3 transitions while the regulatory mutant grows across all transitions. Each line represents one of three replicate cultures. Filled circle symbols indicate the time-points and replicates that were sampled from WT and mutant for single-cell gene expression analysis.

Three cell states were defined among single cells from each condition, including state A (expression pattern present only during ST1 growth in wild type), state B (expression pattern present only during SR1 growth in wild type), and state C (expression pattern present during both SR1 and ST1 growth in wild type).

ENIGMA Researchers Uncover Factors in Microbial Community Collapse


 

DvH_MM_PopulationCurves_Turkarslan2

Regulatory mutations delay or prevent population collapse of Desulfovibrio vulgaris (Dv) co-cultures with Methanococcus maripaludis (Mm) during transitions between SR (sulfate respiration) and ST(syntrophy)

Serdar Turkarslan, a Senior Research Scientist at the Institute for Systems Biology in Seattle, Washington; along with a team of researchers has developed a framework to quantify microbial community resilience in the face of environmental changes.

This framework will be invaluable for observing the behavior of microbial communities under simulations of current and projected environmental conditions. Their work will enable ENIGMA make predictions about the future of ecosystems and identify mechanisms to protect them. Read more on the Biosciences Area website and the ISB website.

  • We demonstrated that conditional gene regulation for adapting to new environments can become detrimental and lead to population collapse when resource fluctuations are too frequent.
  • We discovered that regulation-driven dilution of essential cellular components made energetic cost of restoring the growth condition-relevant physiological state progressively more burdensome, and eventually unsustainable.
  • The collapse can be rescued by disruption of conditional regulation of essential transcripts and proteins

Just prior to collapse, the transcriptome of the wild type Dv appeared dramatically different from the state appropriate for the growth condition (SR or ST). By contrast, knockout of regulator (DVU0744) allowed Dv to reproducibly adopt the appropriate state for each growth condition.

The fraction of single cells of wild type Dv expressing transcripts essential for SR dropped significantly with repeated transitions, with very few cells expressing essential transcripts just prior to collapse. Structure of the regulatory mutant population by contrast remained unchanged.

Mechanism for microbial population collapse in a fluctuating resource environment
Turkarslan, S., A.V Raman, A.W Thompson, C.E Arens, M.A Gillespie, F von Netzer, K.L Hillesland, S Stolyar, A López García de Lomana, D.J Reiss, D Gorman‐Lewis, G.M Zane, J.A Ranish, J.D Wall, D.A Stahl, and N.S Baliga. (2017) Molecular Systems Biology 13(3) http://msb.embopress.org/content/13/3/919

 

Serdar Turkarslan, PhD

Metabolizing Data in the Cloud


 
ENIGMA researchers at Scripps Research Institute have developed tools with available data to enable microbial and environmental research.

  • ENIGMA’s XCMS Online systems biology data processing and the METLIN database represent a successful model of how community oriented cloud-computing can be implemented on a global scale. This free, cloud-based platform provides users with processing tools, data streaming, statistical analysis, and pathway-based multi-omic analysis.
  • Beyond ENIGMA’s microbial and environmental research, the success of cloud-based systems biology platforms will likely evolve and expand into other fields, such as molecular modeling, and education, to name only a few.  It was featured in Nature http://blogs.nature.com/naturejobs/2017/02/08/science-meets-netflix-with-data-streaming/
  • Cloud-based bioinformatic platforms address the fundamental demands of creating a flexible scientific environment, facilitating data processing and general accessibility. These platforms have a multitude of advantages to support both government and scientific mandates of a more open environment.

Metabolizing Data in the Cloud. Warth, B.; Levin, N.S.; Rinehart, D.; Teijaro, J.; Benton, H.P.; Siuzdak, G.

(2017) Trends in Biotechnology. http://www.cell.com/trends/biotechnology/fulltext/S0167-7799(16)30233-5. DOI: 10.1016/j.tibtech.2016.12.010

METLIN database can be found at https://metlin.scripps.edu

Rapid Detection of Microbial Cell Abundance in Aquatic Systems


 

Biosensor_RochaHazen1

(A) Overview of approach. To provide proof of principle, capacitance measurements from laboratory-sourced batch culture and environmentally-sourced samples were obtained using silicon wafer-based capacitive sensor

ENIGMA post doctoral fellow developed the application of ACEK-enhanced capacitive sensing technology as a rapid screening tool for the detection and quantification of microbial abundance in aquatic environments, such as groundwater wells at our Oak Ridge field site. As proof of principle, she applied the tool to samples from ORNL and the Great Australian Bight.

New Science & Significance

  • Results demonstrate that ACEK capacitance-based sensing can detect and determine microbial cell counts throughout cellular concentrations typically encountered in naturally occurring microbial communities (103-106 cells/mL).
  • This work provides a foundation for understanding the limits of capacitance-based sensing in natural environmental samples and supports future efforts focusing on evaluating the robustness ACEK capacitance-based within aquatic environments.

Rapid Detection of Microbial Cell Abundance in Aquatic Systems. Rocha, A.M., Q. Yuan, D. Close, K. B. O’Dell, J. L. Fortney, J. Wu, and T.C. Hazen. (2016)

Biosensors and Bioelectronics Volume 85, 15 November 2016, Pages 915–923. [doi]10.1016/j.bios.2016.05.098

Digital Droplet Multiple Displacement Amplification


 

DigitalDropletDisplacementAmplification_Singh

Fig. 1. The working principles of ddMDA. The ddMDA procedure partitions E.coli sample into millions of picoliter droplets(A) and amplification in each droplet occur independently from the other droplets(B). At ddMDA endpoint, each droplet contains a discrete hyper-branched MDA product(C). Scale bar =100µm. Fig. 2. Comparison of whole-genome coverage of assembled contigs mapped to E. coli K-12 genome for ddMDA and tube MDA. (A) From the outermost circle, ddMDA for 100 pg/µL, tube MDA for 100 pg/µL, 10 pg/µL, and 10 pg/µL and (B) ddMDA for 1 pg/µL, tube MDA for 1 pg/µL, 0.1 pg/µL, and 0.1 pg/µL, respectively. GC contents in black and genomic DNA in green as a reference.

  • The ddMDA technique enabled significantly lower bias and non-specific amplification than conventional MDA thus achieving more uniform coverage of amplification over the entire genome
  • This technique can be a powerful tool for genomic studies where DNA samples are limited such as single cells, microaggregates, and uncultured microbes from many different environments

Digital Droplet Multiple Displacement Amplification (ddMDA) for whole-genome sequencing of limited DNA samples (2016) Rhee, M., Light, Y.K., Meagher, R.J., and Singh, A.K. Plos One [doi]10.1371/journal.pone.0153699

Nitrite Reduction Assay for Whole Pseudomonas Cells


 
ENIGMA researchers at University of Georgia developed and published a rapid high-throughput assay for whole-cell nitrite reductase activity.  Such activity assays will be key for future ENIGMA endeavors to relate biological activities of individual microorganisms and their communities to the environment.

  • A rapid high-throughput assay was constructed to measure whole cell nitrite reductase activity.
  • This detailed procedure can be adapted to investigate nitrate and nitrite reduction in ENIGMA relevant strains and communities.

Standard nitrite curve from 0-100 µM nitrite A) The red-pink color develops when Griess reagent is added to the nitrite containing sample. B) A linear standard curve is shown with values ranging from 0–100 µM nitrite

Nitrite Reduction Assay for Whole Pseudomonas Cells. Thorgersen, M.P.; and M.W. Adams Bio-protocol 6(10): e1818. http://www.bio-protocol.org/e1818

Post Doc Lauren Lui profiled by Berkeley Lab for her Public Service and contribution to Women in Science


 
Lauren-Lui-portraitDuring March- Women’s History Month, Berkeley Lab recognizes and celebrates the diverse and historic accomplishments of women by honoring those who have shaped America’s history and its future through their public service and government leadership.
https://diversity.lbl.gov/2016/03/14/berkeley-lab-celebrates-women-in-science-and-public-service/

Lauren Lui, an ENIGMA postdoctoral fellow in Adam Arkin’s Lab, was one of three women profiled by the Diversity and Inclusion Office.  She works within the Environmental Genomics and Systems Biology Division of the Biosciences Area.  Lauren has served in multiple outreach areas, including SynBerc, [email protected] Santa Cruz, and now as Secretary of the Women Scientist and Engineering Council for LBL.

 

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Are free-living bacteria optimized by natural selection?


 

BacterialNaturalSelectionSimulations_Arkin_Price2016

Deleterious alleles are frequent, even though N * s >> 1 and even with recombination (To make up for the small number of individuals N, rates and fitness effects are are 10e3 faster than is realistic.)

Free-living bacteria are usually thought to have large effective population sizes, and so tiny selective differences can drive their evolution. However, because recombination is infrequent, “background selection” against slightly deleterious alleles should reduce the effective population size (Ne) by orders of magnitude. For example, for a well-mixed population with 1012 individuals and a typical level of homologous recombination (r/m = 3, i.e., nucleotide changes due to recombination [r] occur at 3 times the mutation rate [m]), we predict that Ne is <107. An argument for high Ne values for bacteria has been the high genetic diversity within many bacterial “species,” but this diversity may be due to population structure: diversity across subpopulations can be far higher than diversity within a subpopulation, which makes it difficult to estimate Ne correctly. Given an estimate of Ne, standard population genetics models imply that selection should be sufficient to drive evolution if Ne × s is >1, where s is the selection coefficient. We found that this remains approximately correct if background selection is occurring or when population structure is present. Overall, we predict that even for free-living bacteria with enormous populations, natural selection is only a significant force if s is above 10e7 or so.

Price, MN, Arkin, AP. Weakly deleterious mutations and low rates of recombination limit the impact of natural selection on bacterial genomes (2015)mBio, doi: 10.1128/mBio.01302-15

Lara Rajeev Stars in video demonstrating DNA-affinity-purified chip (DAP-chip) method to determine gene targets for bacterial two component regulatory systems


 

Lara_RajeevRajeev, L., E. G. Luning, and A. Mukhopadhyay (2014). DNA-affinity-purified chip (DAP-chip) method to determine gene targets for bacterial two-component regulatory systems. Journal of Visualized Experiments (89). Epub 2014/08/01. doi:3791/51715. PMID:25079303

http://www.jove.com/video/51715/dna-affinity-purified-chip-dap-chip-method-to-determine-gene-targets#.VR3XCenZIek.google_plusone_share

In vivo methods such as ChIP-chip are well-established techniques used to determine global gene targets for transcription factors. However, they are of limited use in exploring bacterial two-component regulatory systems with uncharacterized activation conditions. Such systems regulate transcription only when activated in the presence of unique signals. Since these signals are often unknown, the in vitro microarray-based method described in this video article can be used to determine gene targets and binding sites for response regulators. This DNA-affinity-purified-chip method may be used for any purified regulator in any organism with a sequenced genome. The protocol involves allowing the purified tagged protein to bind to sheared genomic DNA and then affinity purifying the protein-bound DNA, followed by fluorescent labeling of the DNA and hybridization to a custom tiling array. Preceding steps that may be used to optimize the assay for specific regulators are also described. The peaks generated by the array data analysis are used to predict binding site motifs, which are then experimentally validated. The motif predictions can be further used to determine gene targets of orthologous response regulators in closely related species. We demonstrate the applicability of this method by determining the gene targets and binding site motifs and thus predicting the function for a sigma54-dependent response regulator DVU3023 in the environmental bacterium Desulfovibrio vulgaris Hildenborough.