Performing Department
(N/A)
Non Technical Summary
Keystone taxa are highly connected taxa in the microbiome that, through their connectivity, can enhance microbiome resilience to environmental stress. Harnessing such taxa will create opportunities for manipulating microbiomes to enhance crop resilience to stress in a rapidly changing climate. Most studies have used network-based scores to identify keystone taxa, but the empirical validation of such taxa has remained elusive. The few attempts to perform validation used the 'add-in or exclusion' approach wherein a putative taxon is added or excluded to assess its impact. However, to assess the 'true' impact of a keystone, it must be eliminated from an already assembled community to evaluate the effect of its removal and then reintroduced to assess if it can restore its effect. The use of bacteriophage is an innovative way to address this. The proposed study aims to use salinity as a model for environmental stress and bacteriophage as a tool to validate the role of keystone taxa in microbiome resilience to saline stress. We will achieve this by 1) assessing the impact of keystone taxa on microbiome connectivity, 2) employing bacteriophage to eliminate keystone taxa and evaluate the impact of their absence, and 3) ascertaining if keystone taxa can reproduce their effects on microbiomes upon re-introduction. Overall, this study will elucidate how key microbial groups can be harnessed to improve resilience to environmental stress. The study addresses priorities outlined in the Agricultural Microbiomes Program by investigating "microbiome assembly and interactions in various environments or physiological states such as stress".
Animal Health Component
10%
Research Effort Categories
Basic
60%
Applied
10%
Developmental
30%
Goals / Objectives
Overall Goal: To validate the role of keystone taxa in microbiome resilience to environmental stress.Specific Objectives:To assess the impact of keystone taxa on the assembly of a microbiome and the evolution of network connectivity under stress (salinity).To determine how bacteriophages can be used to selectively deplete keystone taxa and evaluate the impact of their absence on network connectivity under salinity stress.To evaluate the extent to which keystone taxa can reproduce their effects after re-introduction and restore connectivity under salinity stress.Hypotheses:Keystone taxa would enhance network connectivity over time under salinity stress.Phage-mediated depletion of keystone taxa from salinity-resilient communities will lead to reduced connectivity, compromising resilience.Re-introduction of keystone taxa will restore connectivity and resilience under salinity stress.
Project Methods
Experimental Design: A microcosm study using a sand-vermiculite matrix with a sterile defined nutrient solution will be used to assess the temporal patterns of the microbiome assembly under the presence and absence of keystone taxa, along with a double-negative control. In addition to the already isolated bacterial SynCom, we will extend our high-throughput culturing effort to isolate more bacterial members from saline soils. We intend to use five putative keystone taxa, each combined with up to 50 non-keystone taxa for this experiment, selected to reflect the diversity of genera present in the communities observed in field data. Treatments will include the presence of absence of putative keystone taxa, and exposure to non-saline, low saline (3 dS) and high saline (10 dS) conditions. Samples from the microcosms for DNA extraction will be collected at five different time points post inoculation. Timepoints will be defined by performing a growth curve of the SynCom in the mesocosms (with and without salinity) and measuring population increase over a period of hours and days until growth reaches saturation. Each sample will have 10 replicates. In total, there will be 900 samples (3 salinity levels x 6 treatments x 10 replicates x 5 time-points). Samples will be stored at -80?C for DNA extraction and molecular analysis. To more accurately measure abundance of SynCom members and improve the quality of network data, we will spike the samples with known quantities of synthetic 16S DNA molecules prior to DNA extraction. From these samples we will investigate the differences in network connectivity as a measure of community resilience under stress (salinity). As mentioned in the Background section, previous studies have shown how network connectivity can be a useful metric for microbiome resilience. Also, extensive literature suggests that the removal of highly-connected (i.e., keystone) taxa can disrupt a network, which has implications for community response to stressors (Barabasi et al., 2011; Newman, 2006; Strogatz, 2001). Therefore, specific keystones that reproduce their observed effects on network connectivity in the experimentally tractable system will be identified for downstream experimentation. We will also define the optimally resilient phase of the microbiome evolution using the temporal data, which will inform downstream experiments. The optimally resilient phase will be the time-point at which the relative network connectivity of members is maximum in saline treatments relative to non-saline.Microbiome Analysis: DNA from the liquid microcosms will be extracted using a modified CTAB method. This method will involve filtering the particulates from the mesocosm using muslin cloth, and the addition of lysis and extraction buffers to the filtrate, followed by incubation at 65?C for 30 mins, which will lyse the cells. Next, we will add phenol:chloroform:isoamyl alcohol to the lysate, carefully take out the upper phase, add isopropanol, and centrifuge at 10000 rpm for 5 minutes. After discarding the supernatant and washing the pellet with 95% ethanol, we will remove the ethanol, add miliQ water and leave open overnight to dry. The next day, DNA concentrations will be determined with a Qubit fluorometer (Life Technologies, Paisley, UK). A barcoded high-throughput sequencing approach will be employed to assess the diversity and composition of bacterial communities. Bacterial communities will be examined by amplifying the V3-V4 region of the bacterial 16S rRNA gene using the primers 515FB and 806RB (Walters et al., 2016). Each primer will be tagged with a 5- nucleotide-long padding sequence and a Golay barcode. For all amplicons, Illumina 300 bp pared-end sequencing will be performed. After sequencing, demultiplexing will be performed and adapters will be removed using the Cutadapt pipieline (Martin, 2011). Sequences will be analyzed following the DADA2 pipeline (Callahan et al., 2016). ASVs will be classified according to the SILVA database (Pruesse et al. 2007). We will perform quantitative PCR to quantify the number of copies of synthetic 16S rRNA genes. The quantification data obtained from qPCR will complement the data obtained from Illumina MiSeq.Phage Work: We will use phages to selectively deplete specific target bacteria in soil-simulated mesocosms, with cocktails or specific combinations of phages showing enhanced efficacy. Our aim is to selectively deplete the keystone taxon from a resilient SynCom to validate its function. Therefore, we will first create a phage library using phages specific to the keystone taxa identified in our optimally resilient SynCom (to be identified from Objective 1). We will do this by isolating bacteriophages from saline soil samples we have collected from fields in North Dakota, followed by phage enrichment and purification as plaques to create a collection of at least five phage isolates specific to each of the five putative keystone taxa within the SynCom. Next, combinations of phages from libraries will be tested for their efficacies in maximizing keystone taxa depletion from the microcosms as we have done previously, and a phage cocktail will be created with the combination of phages that show the greatest efficacy. To develop a suitable control for keystone depletion experiments, we will also select a non-keystone member of the SynCom to target for phage isolation and depletion as described above. We will assess the specificity of phage cocktails to elimination of the targets (one keystone and control taxa) and not other members of the SynCom in two ways: First by pairwise growth curve assays in 96-well plates in a plate-reader to verify no negative effect on the growth of any other SynCom member from the established phage cocktail. Second, by introduction of the phage cocktails to the SynCom community, with and without the target (keystone or control taxa) included during outgrowth in mesocosms. Following incubation with/without phage, community members will be recovered on solid media, and the composition of the recovered communities will be profiled by amplicon sequencing to verify the depletion of targets in a community context, as well as the absence of impact of the cocktails on the communities when the targets are not present.Statistical Analysis: All statistical analyses will be conducted using R (https://www.r-project.org). We will perform network analysis using the Spearman rank correlation in the 'psych' package (Revelle, 2022). Significant coefficients (p< 0.01) will be selected, and false discovery rate correction will be performed (Benjamini, 2010). The edges and nodes tables will be imported into Gephi for visualization (Bastian et al., 2009). The network will be mapped using the undirected Fruchterman-Reingold layout. Nodes are the central units of a network while edges represent the connections or links between the nodes, and thus, degree represents the number of edges connected to a node. A combined measure of degree, betweenness centrality, closeness centrality, and transitivity will be used to identify the putative keystone taxa (Berry and Widder, 2014).