Investigating the relationship between microbial network features of giant kelp "seedbank" cultures and subsequent farm performance.

Microbial inoculants can increase the yield of cultivated crops and are successful in independent trials; however, efficacy drops in large-scale applications due to insufficient consideration of microbial community dynamics. The structure of microbiomes, in addition to the impact of individual taxa, is an important factor to consider when designing growth-promoting inoculants. Here, we investigate the microbial network and community assembly patterns of Macrocystis pyrifera gametophyte germplasm cultures (collectively referred to as a "seedbank") used to cultivate an offshore farm in Santa Barbara, California, and identify network features associated with increased biomass of mature sporophytes. We found that [1] several network features, such as clustering coefficient and edge ratios, significantly vary with biomass outcomes; [2] gametophytes that become low- or high-biomass sporophytes have different hub taxa; and [3] microbial community assembly of gametophyte germplasm cultures is niche-driven. Overall, this study describes microbial community dynamics in M. pyrifera germplasm cultures and ultimately supports the development of early life stage inoculants that can be used on seaweed cultivars to increase biomass yield.

Natural variation of Macrocystis pyrifera gametophyte germplasm culture microbiomes and applications for improving yield in offshore farms.

With national interest in seaweed-based biofuels as a sustainable alternative to fossil fuels, there is a need for tools that produce high-yield seaweed cultivars and increase the efficiency of offshore farms. Several agricultural studies have demonstrated that the application of microbial inoculants at an early life stage can improve crop yield, and there is an opportunity to use similar techniques in seaweed aquaculture. However, there is a critical knowledge gap regarding host-microbiome associations of macroalgae gametophytes in germplasm cultures. Here, we investigate the microbial community of Macrocystis pyrifera gametophyte germplasm cultures that were used to cultivate an offshore farm in Santa Barbara, California and identify key taxa correlated with increased biomass of mature sporophytes. This work provides a valuable knowledge base for the development of microbial inoculants that produce high-biomass M. pyrifera cultivars to ultimately be used as biofuel feedstocks.

Zeta diversity patterns in metabarcoded lotic algal assemblages as a tool for bioassessment.

Assessments of the ecological health of algal assemblages in streams typically focus on measures of their local diversity and classify individuals by morphotaxonomy. Such assemblages are often connected through various ecological processes, such as dispersal, and may be more accurately assessed as components of regional-, rather than local-scale assemblages. With recent declines in the costs of sequencing and computation, it has also become increasingly feasible to use metabarcoding to more accurately classify algal species and perform regional-scale bioassessments. Recently, zeta diversity has been explored as a novel method of constructing regional bioassessments for groups of streams. Here, we model the use of zeta diversity to investigate whether stream health can be determined by the landscape diversity of algal assemblages. We also compare the use of DNA metabarcoding and morphotaxonomy classifications in these zeta diversity-based bioassessments of regional stream health. From 96 stream samples in California, we used various orders of zeta diversity to construct models of biotic integrity for multiple assemblages of diatoms, as well as hybrid assemblages of diatoms in combination with soft-bodied algae, using taxonomy data generated with both DNA sequencing as well as traditional morphotaxonomic approaches. We compared our ability to evaluate the ecological health of streams with the performance of multiple algal indices of biological condition. Our zeta diversity-based models of regional biotic integrity were more strongly correlated with existing indices for algal assemblages classified using metabarcoding compared to morphotaxonomy. Metabarcoding for diatoms and hybrid algal assemblages involved rbcL and 18S V9 primers, respectively. Importantly, we also found that these algal assemblages, independent of the classification method, are more likely to be assembled under a process of niche differentiation rather than stochastically. Taken together, these results suggest the potential for zeta diversity patterns of algal assemblages classified using metabarcoding to inform stream bioassessments.

Understanding the metabolome and metagenome as extended phenotypes: The next frontier in macroalgae domestication and improvement.

"Omics" techniques (including genomics, transcriptomics, metabolomics, proteomics, and metagenomics) have been employed with huge success in the improvement of agricultural crops. As marine aquaculture of macroalgae expands globally, biologists are working to domesticate species of macroalgae by applying these techniques tested in agriculture to wild macroalgae species. Metabolomics has revealed metabolites and pathways that influence agriculturally relevant traits in crops, allowing for informed crop crossing schemes and genomic improvement strategies that would be pivotal to inform selection on macroalgae for domestication. Advances in metagenomics have improved understanding of host-symbiont interactions and the potential for microbial organisms to improve crop outcomes. There is much room in the field of macroalgal biology for further research toward improvement of macroalgae cultivars in aquaculture using metabolomic and metagenomic analyses. To this end, this review discusses the application and necessary expansion of the omics tool kit for macroalgae domestication as we move to enhance seaweed farming worldwide.

Removal of Toxic Volatile Compounds in Batch Culture Prolongs Stationary Phase and Delays Death of Escherichia coli.

The mechanisms controlling entry into and exit from the death phase in the bacterial life cycle remain unclear. Although bacterial growth studies in batch cultures traditionally focus on the first three phases during incubation, two additional phases, the death phase and the long-term stationary phase, are less understood. Although there are a number of stressors that arise during long-term batch culture, including nutrient depletion and the accumulation of metabolic toxins such as reactive oxidative species, their roles in cell death are not well-defined. By manipulating the environmental conditions of Escherichia coli incubated in long-term batch culture through chemical and mechanical means, we investigated the role of volatile metabolic toxins in modulating the onset of the death phase. Here, we demonstrate that with the introduction of substrates with high binding affinities for volatile compounds, toxic by-products of normal cell metabolism, into the headspace of batch cultures, cells display a prolonged stationary phase and delayed entry into the death phase. The addition of these substrates allows cultures to maintain a high cell density for hours to days longer than cultures incubated under standard growth conditions. A similar effect is observed when the gaseous headspace in culture flasks is continuously replaced with sterile air, mechanically preventing the accumulation of metabolic by-products in batch cultures. We establish that toxic compound(s) are produced during the exponential phase, demonstrate that buildup of toxic by-products influence entry into the death phase, and present a novel tool for improving high-density growth in batch culture that may be used in future research or industrial or biotechnology applications. IMPORTANCE Bacteria, such as Escherichia coli, are routinely used in the production of biomaterials because of their efficient and sustainable capacity for synthesis of bioproducts. Industrial applications of microbial synthesis typically utilize cells in the stationary phase, when cultures have the greatest density of viable cells. By manipulating culture conditions to delay the transition from the stationary phase to the death phase, we can prolong the stationary phase on a scale of hours to days, thereby maintaining the maximum density of cells that would otherwise quickly decline. Characterization of the mechanisms that control entry into the death phase for the model organism E. coli not only deepens our understanding of the bacterial life cycle but also presents an opportunity to enhance current protocols for batch culture growth and explore similar effects in a variety of widely used bacterial strains.

Landscape analyses using eDNA metabarcoding and Earth observation predict community biodiversity in California.

Ecosystems globally are under threat from ongoing anthropogenic environmental change. Effective conservation management requires more thorough biodiversity surveys that can reveal system-level patterns and that can be applied rapidly across space and time. Using modern ecological models and community science, we integrate environmental DNA and Earth observations to produce a time snapshot of regional biodiversity patterns and provide multi-scalar community-level characterization. We collected 278 samples in spring 2017 from coastal, shrub, and lowland forest sites in California, a complex ecosystem and biodiversity hotspot. We recovered 16,118 taxonomic entries from eDNA analyses and compiled associated traditional observations and environmental data to assess how well they predicted alpha, beta, and zeta diversity. We found that local habitat classification was diagnostic of community composition and distinct communities and organisms in different kingdoms are predicted by different environmental variables. Nonetheless, gradient forest models of 915 families recovered by eDNA analysis and using BIOCLIM variables, Sentinel-2 satellite data, human impact, and topographical features as predictors, explained 35% of the variance in community turnover. Elevation, sand percentage, and photosynthetic activities (NDVI32) were the top predictors. In addition to this signal of environmental filtering, we found a positive relationship between environmentally predicted families and their numbers of biotic interactions, suggesting environmental change could have a disproportionate effect on community networks. Together, these analyses show that coupling eDNA with environmental predictors including remote sensing data has capacity to test proposed Essential Biodiversity Variables and create new landscape biodiversity baselines that span the tree of life.

Non-additive microbial community responses to environmental complexity.

Environmental composition is a major, though poorly understood, determinant of microbiome dynamics. Here we ask whether general principles govern how microbial community growth yield and diversity scale with an increasing number of environmental molecules. By assembling hundreds of synthetic consortia in vitro, we find that growth yield can remain constant or increase in a non-additive manner with environmental complexity. Conversely, taxonomic diversity is often much lower than expected. To better understand these deviations, we formulate metrics for epistatic interactions between environments and use them to compare our results to communities simulated with experimentally-parametrized consumer resource models. We find that key metabolic and ecological factors, including species similarity, degree of specialization, and metabolic interactions, modulate the observed non-additivity and govern the response of communities to combinations of resource pools. Our results demonstrate that environmental complexity alone is not sufficient for maintaining community diversity, and provide practical guidance for designing and controlling microbial ecosystems.

Artificially selecting bacterial communities using propagule strategies.

Artificial selection is a promising approach to manipulate microbial communities. Here, we report the outcome of two artificial selection experiments at the microbial community level. Both used "propagule" selection strategies, whereby the best-performing communities are used as the inocula to form a new generation of communities. Both experiments were contrasted to a random selection control. The first experiment used a defined set of strains as the starting inoculum, and the function under selection was the amylolytic activity of the consortia. The second experiment used multiple soil communities as the starting inocula, and the function under selection was the communities' cross-feeding potential. In both experiments, the selected communities reached a higher mean function than the control. In the first experiment, this was caused by a decline in function of the control, rather than an improvement of the selected line. In the second experiment, this response was fueled by the large initial variance in function across communities, and stopped when the top-performing community "fixed" in the metacommunity. Our results are in agreement with basic expectations from breeding theory, pointing to some of the limitations of community-level selection experiments that can inform the design of future studies.

High-order interactions distort the functional landscape of microbial consortia.

Understanding the link between community composition and function is a major challenge in microbial population biology, with implications for the management of natural microbiomes and the design of synthetic consortia. Specifically, it is poorly understood whether community functions can be quantitatively predicted from traits of species in monoculture. Inspired by the study of complex genetic interactions, we have examined how the amylolytic rate of combinatorial assemblages of six starch-degrading soil bacteria depend on the separate functional contributions from each species and their interactions. Filtering our results through the theory of biochemical kinetics, we show that this simple function is additive in the absence of interactions among community members. For about half of the combinatorially assembled consortia, the amylolytic function is dominated by pairwise and higher-order interactions. For the other half, the function is additive despite the presence of strong competitive interactions. We explain the mechanistic basis of these findings and propose a quantitative framework that allows us to separate the effect of behavioral and population dynamics interactions. Our results suggest that the functional robustness of a consortium to pairwise and higher-order interactions critically affects our ability to predict and bottom-up engineer ecosystem function in complex communities.

Pre-operative hamstring length and velocity do not explain the reduced effectiveness of repeat hamstring lengthening in children with cerebral palsy and crouch gait.

BACKGROUND: Hamstring lengthening surgery (HSL) is often performed to correct crouch gait in patients with cerebral palsy (CP). However, crouch can recur over time, and repeat HSL may be ineffective. One possible reason is that the hamstrings in repeat HSL patients are neither short nor lengthening slowly and would therefore not benefit from HSL. RESEARCH QUESTION: This study aimed to determine whether the hamstrings are short and/or slow preoperatively only in patients with primary, and not repeat, HSL. METHODS: We compared pre- and postoperative dynamic semimembranosus muscle-tendon lengths for children with CP who had primary (N = 15) or repeat (N = 8) HSL to a group of control participants (N = 10). Outcome measures were compared between visits (pre- vs. postoperative) and groups (control, primary HSL, repeat HSL) using mixed model analysis. RESULTS: Preoperatively, hamstrings were shorter and slower than normal on average in both HSL groups (p < 0.001); all but 3 limbs (primary 26/28, repeat 13/14) had hamstrings that were shorter and/or slower than controls by more than two standard deviations. Postoperative improvements were observed in the primary HSL group for popliteal angle, initial contact knee flexion, minimum stance knee flexion, and dynamic hamstring length (p ≤ 0.001). The repeat HSL group improved only in dynamic hamstring length (p = 0.004) and worsened in passive knee extension (p = 0.01) and minimum hip flexion in stance (p = 0.04). Hamstrings in both surgical groups on average remained shorter and slower than controls postoperatively (p ≤ 0.001). SIGNIFICANCE: The fact that repeat HSL is less effective in improving knee motion is not due to a lack of short or slow hamstrings preoperatively. However, in recurrent crouch, short or slow hamstrings do not usually indicate hamstring dysfunction, and correction of other deformities such as rotational malalignment, fixed knee flexion contractures, patella alta, weak calf muscles, and/or loose heelcords should be considered rather than repeat HSL.

Dynamics of GreB-RNA polymerase interaction allow a proofreading accessory protein to patrol for transcription complexes needing rescue.

The secondary channel (SC) of multisubunit RNA polymerases (RNAPs) allows access to the active site and is a nexus for the regulation of transcription. Multiple regulatory proteins bind in the SC and reprogram the catalytic activity of RNAP, but the dynamics of these factors' interactions with RNAP and how they function without cross-interference are unclear. In Escherichia coli, GreB is an SC protein that promotes proofreading by transcript cleavage in elongation complexes backtracked by nucleotide misincorporation. Using multiwavelength single-molecule fluorescence microscopy, we observed the dynamics of GreB interactions with elongation complexes. GreB binds to actively elongating complexes at nearly diffusion-limited rates but remains bound for only 0.3-0.5 s, longer than the duration of the nucleotide addition cycle but far shorter than the time needed to synthesize a complete mRNA. Bound GreB inhibits transcript elongation only partially. To test whether GreB preferentially binds backtracked complexes, we reconstituted complexes stabilized in backtracked and nonbacktracked configurations. By verifying the functional state of each molecular complex studied, we could exclude models in which GreB is selectively recruited to backtracked complexes or is ejected from RNAP by catalytic turnover. Instead, GreB binds rapidly and randomly to elongation complexes, patrolling for those requiring nucleolytic rescue, and its short residence time minimizes RNAP inhibition. The results suggest a general mechanism by which SC factors may cooperate to regulate RNAP while minimizing mutual interference.

Ubiquitous promoter-localization of essential virulence regulators in Francisella tularensis.

Francisella tularensis is a Gram-negative bacterium whose ability to replicate within macrophages and cause disease is strictly dependent upon the coordinate activities of three transcription regulators called MglA, SspA, and PigR. MglA and SspA form a complex that associates with RNA polymerase (RNAP), whereas PigR is a putative DNA-binding protein that functions by contacting the MglA-SspA complex. Most transcription activators that bind the DNA are thought to occupy only those promoters whose activities they regulate. Here we show using chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-Seq) that PigR, MglA, and SspA are found at virtually all promoters in F. tularensis and not just those of regulated genes. Furthermore, we find that the ability of PigR to associate with promoters is dependent upon the presence of MglA, suggesting that interaction with the RNAP-associated MglA-SspA complex is what directs PigR to promoters in F. tularensis. Finally, we present evidence that the ability of PigR (and thus MglA and SspA) to positively control the expression of genes is dictated by a specific 7 base pair sequence element that is present in the promoters of regulated genes. The three principal regulators of virulence gene expression in F. tularensis therefore function in a non-classical manner with PigR interacting with the RNAP-associated MglA-SspA complex at the majority of promoters but only activating transcription from those that contain a specific sequence element. Our findings reveal how transcription factors can exert regulatory effects at a restricted set of promoters despite being associated with most or all. This distinction between occupancy and regulatory effect uncovered by our data may be relevant to the study of RNAP-associated transcription regulators in other pathogenic bacteria.

Operator sequence alters gene expression independently of transcription factor occupancy in bacteria.

A canonical quantitative view of transcriptional regulation holds that the only role of operator sequence is to set the probability of transcription factor binding, with operator occupancy determining the level of gene expression. In this work, we test this idea by characterizing repression in vivo and the binding of RNA polymerase in vitro in experiments where operators of various sequences were placed either upstream or downstream from the promoter in Escherichia coli. Surprisingly, we find that operators with a weaker binding affinity can yield higher repression levels than stronger operators. Repressor bound to upstream operators modulates promoter escape, and the magnitude of this modulation is not correlated with the repressor-operator binding affinity. This suggests that operator sequences may modulate transcription by altering the nature of the interaction of the bound transcription factor with the transcriptional machinery, implying a new layer of sequence dependence that must be confronted in the quantitative understanding of gene expression.

Mechanism of transcriptional repression at a bacterial promoter by analysis of single molecules.

The molecular basis for regulation of lactose metabolism in Escherichia coli is well studied. Nonetheless, the physical mechanism by which the Lac repressor protein prevents transcription of the lactose promoter remains unresolved. Using multi-wavelength single-molecule fluorescence microscopy, we visualized individual complexes of fluorescently tagged RNA polymerase holoenzyme bound to promoter DNA. Quantitative analysis of the single-molecule observations, including use of a novel statistical partitioning approach, reveals highly kinetically stable binding of polymerase to two different sites on the DNA, only one of which leads to transcription. Addition of Lac repressor directly demonstrates that bound repressor prevents the formation of transcriptionally productive open promoter complexes; discrepancies in earlier studies may be attributable to transcriptionally inactive polymerase binding. The single-molecule statistical partitioning approach is broadly applicable to elucidating mechanisms of regulatory systems including those that are kinetically rather than thermodynamically controlled.