Erika M. Zink

Bio: Erika M. Zink is an academic researcher from Pacific Northwest National Laboratory. The author has contributed to research in topics: Microbiome & Lipid metabolism. The author has an hindex of 23, co-authored 49 publications receiving 1600 citations. Previous affiliations of Erika M. Zink include Environmental Molecular Sciences Laboratory.

Drought delays development of the sorghum root microbiome and enriches for monoderm bacteria

Abstract: Drought stress is a major obstacle to crop productivity, and the severity and frequency of drought are expected to increase in the coming century. Certain root-associated bacteria have been shown to mitigate the negative effects of drought stress on plant growth, and manipulation of the crop microbiome is an emerging strategy for overcoming drought stress in agricultural systems, yet the effect of drought on the development of the root microbiome is poorly understood. Through 16S rRNA amplicon and metatranscriptome sequencing, as well as root metabolomics, we demonstrate that drought delays the development of the early sorghum root microbiome and causes increased abundance and activity of monoderm bacteria, which lack an outer cell membrane and contain thick cell walls. Our data suggest that altered plant metabolism and increased activity of bacterial ATP-binding cassette (ABC) transporter genes are correlated with these shifts in community composition. Finally, inoculation experiments with monoderm isolates indicate that increased colonization of the root during drought can positively impact plant growth. Collectively, these results demonstrate the role that drought plays in restructuring the root microbiome and highlight the importance of temporal sampling when studying plant-associated microbiomes.

Signature-discovery approach for sample matching of a nerve-agent precursor using liquid chromatography-mass spectrometry, XCMS, and chemometrics.

Abstract: This report demonstrates the use of bioinformatic and chemometric tools on liquid chromatography-mass spectrometry (LC-MS) data for the discovery of trace forensic signatures for sample matching of ten stocks of the nerve-agent precursor known as methylphosphonic dichloride (dichlor). XCMS, a software tool primarily used in bioinformatics, was used to comprehensively search and find candidate LC-MS peaks in a known set of dichlor samples. These candidate peaks were down selected to a group of 34 impurity peaks. Hierarchal cluster analysis and factor analysis demonstrated the potential of these 34 impurities peaks for matching samples based on their stock source. Only one pair of dichlor stocks was not differentiated from one another. An acceptable chemometric approach for sample matching was determined to be variance scaling and signal averaging of normalized duplicate impurity profiles prior to classification by K-nearest neighbors. Using this approach, a test set of seven dichlor samples were all correctly matched to their source stock. The sample preparation and LC-MS method permitted the detection of dichlor impurities quantitatively estimated to be in the parts-per-trillion (w/w). The detection of a common impurity in all dichlor stocks that were synthesized over a 14-year period and by different manufacturers was an unexpected discovery. Our described signature-discovery approach should be useful in the development of a forensic capability to assist investigations following chemical attacks.

Influence of early life exposure, host genetics and diet on the mouse gut microbiome and metabolome.

Abstract: Although the gut microbiome plays important roles in host physiology, health and disease1, we lack understanding of the complex interplay between host genetics and early life environment on the microbial and metabolic composition of the gut. We used the genetically diverse Collaborative Cross mouse system2 to discover that early life history impacts the microbiome composition, whereas dietary changes have only a moderate effect. By contrast, the gut metabolome was shaped mostly by diet, with specific non-dietary metabolites explained by microbial metabolism. Quantitative trait analysis identified mouse genetic trait loci (QTL) that impact the abundances of specific microbes. Human orthologues of genes in the mouse QTL are implicated in gastrointestinal cancer. Additionally, genes located in mouse QTL for Lactobacillales abundance are implicated in arthritis, rheumatic disease and diabetes. Furthermore, Lactobacillales abundance was predictive of higher host T-helper cell counts, suggesting an important link between Lactobacillales and host adaptive immunity.

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

Chemicals from lignin: an interplay of lignocellulose fractionation, depolymerisation, and upgrading

Abstract: In pursuit of more sustainable and competitive biorefineries, the effective valorisation of lignin is key. An alluring opportunity is the exploitation of lignin as a resource for chemicals. Three technological biorefinery aspects will determine the realisation of a successful lignin-to-chemicals valorisation chain, namely (i) lignocellulose fractionation, (ii) lignin depolymerisation, and (iii) upgrading towards targeted chemicals. This review provides a summary and perspective of the extensive research that has been devoted to each of these three interconnected biorefinery aspects, ranging from industrially well-established techniques to the latest cutting edge innovations. To navigate the reader through the overwhelming collection of literature on each topic, distinct strategies/topics were delineated and summarised in comprehensive overview figures. Upon closer inspection, conceptual principles arise that rationalise the success of certain methodologies, and more importantly, can guide future research to further expand the portfolio of promising technologies. When targeting chemicals, a key objective during the fractionation and depolymerisation stage is to minimise lignin condensation (i.e. formation of resistive carbon–carbon linkages). During fractionation, this can be achieved by either (i) preserving the (native) lignin structure or (ii) by tolerating depolymerisation of the lignin polymer but preventing condensation through chemical quenching or physical removal of reactive intermediates. The latter strategy is also commonly applied in the lignin depolymerisation stage, while an alternative approach is to augment the relative rate of depolymerisation vs. condensation by enhancing the reactivity of the lignin structure towards depolymerisation. Finally, because depolymerised lignins often consist of a complex mixture of various compounds, upgrading of the raw product mixture through convergent transformations embodies a promising approach to decrease the complexity. This particular upgrading approach is termed funneling, and includes both chemocatalytic and biological strategies.

Current understanding of the human microbiome.

Abstract: Our understanding of the link between the human microbiome and disease, including obesity, inflammatory bowel disease, arthritis and autism, is rapidly expanding. Improvements in the throughput and accuracy of DNA sequencing of the genomes of microbial communities that are associated with human samples, complemented by analysis of transcriptomes, proteomes, metabolomes and immunomes and by mechanistic experiments in model systems, have vastly improved our ability to understand the structure and function of the microbiome in both diseased and healthy states. However, many challenges remain. In this review, we focus on studies in humans to describe these challenges and propose strategies that leverage existing knowledge to move rapidly from correlation to causation and ultimately to translation into therapies.

Plant–microbiome interactions: from community assembly to plant health

Abstract: Healthy plants host diverse but taxonomically structured communities of microorganisms, the plant microbiota, that colonize every accessible plant tissue. Plant-associated microbiomes confer fitness advantages to the plant host, including growth promotion, nutrient uptake, stress tolerance and resistance to pathogens. In this Review, we explore how plant microbiome research has unravelled the complex network of genetic, biochemical, physical and metabolic interactions among the plant, the associated microbial communities and the environment. We also discuss how those interactions shape the assembly of plant-associated microbiomes and modulate their beneficial traits, such as nutrient acquisition and plant health, in addition to highlighting knowledge gaps and future directions. In this Review, Trivedi and colleagues explore the interactions between plants, their associated microbial communities and the environment, and also discuss how those interactions shape the assembly of plant-associated microbiomes and modulate their beneficial traits.