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328 result(s) for "Guttman, David S."
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Assembly and ecological function of the root microbiome across angiosperm plant species
Across plants and animals, host-associated microbial communities play fundamental roles in host nutrition, development, and immunity. The factors that shape host–microbiome interactions are poorly understood, yet essential for understanding the evolution and ecology of these symbioses. Plant roots assemble two distinct microbial compartments from surrounding soil: the rhizosphere (microbes surrounding roots) and the endosphere (microbes within roots). Root-associated microbes were key for the evolution of land plants and underlie fundamental ecosystem processes. However, it is largely unknown how plant evolution has shaped root microbial communities, and in turn, how these microbes affect plant ecology, such as the ability to mitigate biotic and abiotic stressors. Here we show that variation among 30 angiosperm species, which have diverged for up to 140 million years, affects root bacterial diversity and composition. Greater similarity in root microbiomes between hosts leads to negative effects on plant performance through soil feedback, with specific microbial taxa in the endosphere and rhizosphere potentially affecting competitive interactions among plant species. Drought also shifts the composition of root microbiomes, most notably by increasing the relative abundance of the Actinobacteria. However, this drought response varies across host plant species, and host-specific changes in the relative abundance of endosphere Streptomyces are associated with host drought tolerance. Our results emphasize the causes of variation in root microbiomes and their ecological importance for plant performance in response to biotic and abiotic stressors.
The pan-genome effector-triggered immunity landscape of a host-pathogen interaction
Effector-triggered immunity (ETI), induced by host immune receptors in response to microbial effectors, protects plants against virulent pathogens. However, a systematic study of ETI prevalence against species-wide pathogen diversity is lacking. We constructed the Pseudomonas syringae Type III Effector Compendium (PsyTEC) to reduce the pan-genome complexity of 5127 unique effector proteins, distributed among 70 families from 494 strains, to 529 representative alleles. We screened PsyTEC on the model plant Arabidopsis thaliana and identified 59 ETI-eliciting alleles (11.2%) from 19 families (27.1%), with orthologs distributed among 96.8% of P. syringae strains. We also identified two previously undescribed host immune receptors, including CAR1, which recognizes the conserved effectors AvrE and HopAA1, and found that 94.7% of strains harbor alleles predicted to be recognized by either CAR1 or ZAR1.
Prophages mediate defense against phage infection through diverse mechanisms
The activity of bacteriophages poses a major threat to bacterial survival. Upon infection, a temperate phage can either kill the host cell or be maintained as a prophage. In this state, the bacteria carrying the prophage is at risk of superinfection, where another phage injects its genetic material and competes for host cell resources. To avoid this, many phages have evolved mechanisms that alter the bacteria and make it resistant to phage superinfection. The mechanisms underlying these phentoypic conversions and the fitness consequences for the host are poorly understood, and systematic studies of superinfection exclusion mechanisms are lacking. In this study, we examined a wide range of Pseudomonas aeruginosa phages and found that they mediate superinfection exclusion through a variety of mechanisms, some of which affected the type IV pilus and O-antigen, and others that functioned inside the cell. The strongest resistance mechanism was a surface modification that we showed is cost-free for the bacterial host in a natural soil environment and in a Caenorhabditis. elegans infection model. This study represents the first systematic approach to address how a population of prophages influences phage resistance and bacterial behavior in P. aeruginosa .
RecPD: A Recombination-aware measure of phylogenetic diversity
A critical step in studying biological features (e.g., genetic variants, gene families, metabolic capabilities, or taxa) is assessing their diversity and distribution among a sample of individuals. Accurate assessments of these patterns are essential for linking features to traits or outcomes of interest and understanding their functional impact. Consequently, it is of crucial importance that the measures employed for quantifying feature diversity can perform robustly under any evolutionary scenario. However, the standard measures used for quantifying and comparing the distribution of features, such as prevalence, phylogenetic diversity, and related approaches, either do not take into consideration evolutionary history, or assume strictly vertical patterns of inheritance. Consequently, these approaches cannot accurately assess diversity for features that have undergone recombination or horizontal transfer. To address this issue, we have devised RecPD, a novel recombination-aware phylogenetic-diversity statistic for measuring the distribution and diversity of features under all evolutionary scenarios. RecPD utilizes ancestral-state reconstruction to map the presence / absence of features onto ancestral nodes in a species tree, and then identifies potential recombination events in the evolutionary history of the feature. We also derive several related measures from RecPD that can be used to assess and quantify evolutionary dynamics and correlation of feature evolutionary histories. We used simulation studies to show that RecPD reliably reconstructs feature evolutionary histories under diverse recombination and loss scenarios. We then applied RecPD in two diverse real-world scenarios including a preliminary study type III effector protein families secreted by the plant pathogenic bacterium Pseudomonas syringae and growth phenotypes of the Pseudomonas genus and demonstrate that prevalence is an inadequate measure that obscures the potential impact of recombination. We believe RecPD will have broad utility for revealing and quantifying complex evolutionary processes for features at any biological level.
Gut microbiota of healthy Canadian infants: profiles by mode of delivery and infant diet at 4 months
The gut microbiota is essential to human health throughout life, yet the acquisition and development of this microbial community during infancy remains poorly understood. Meanwhile, there is increasing concern over rising rates of cesarean delivery and insufficient exclusive breastfeeding of infants in developed countries. In this article, we characterize the gut microbiota of healthy Canadian infants and describe the influence of cesarean delivery and formula feeding. We included a subset of 24 term infants from the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort. Mode of delivery was obtained from medical records, and mothers were asked to report on infant diet and medication use. Fecal samples were collected at 4 months of age, and we characterized the microbiota composition using high-throughput AND sequencing. We observed high variability in the profiles of fecal microbiota among the infants. The profiles were generally dominated by Actinobacteria (mainly the genus Bifidobacterium) and Firmicutes (with diverse representation from numerous genera). Compared with breastfed infants, formula-fed infants had increased richness of species, with overrepresentation of Clostridium difficile. Escherichia–Shigella and Bacteroides species were underrepresented in infants born by cesarean delivery. Infants born by elective cesarean delivery had particularly low bacterial richness and diversity. These findings advance our understanding of the gut microbiota in healthy infants. They also provide new evidence for the effects of delivery mode and infant diet as determinants of this essential microbial community in early life.
Limiting oxidative DNA damage reduces microbe-induced colitis-associated colorectal cancer
Inflammatory bowel disease patients have a greatly increased risk of developing colitis-associated colon cancer (CAC); however, the basis for inflammation-induced genetic damage requisite for neoplasia is unclear. Using three models of CAC, we find that sustained inflammation triggers 8-oxoguanine DNA lesions. Strikingly, antioxidants or iNOS inhibitors reduce 8-oxoguanine and polyps in CAC models. Because the mismatch repair (MMR) system repairs 8-oxoguanine and is frequently defective in colorectal cancer (CRC), we test whether 8-oxoguanine mediates oncogenesis in a Lynch syndrome (MMR-deficient) model. We show that microbiota generates an accumulation of 8-oxoguanine lesions in MMR-deficient colons. Accordingly, we find that 8-oxoguanine is elevated in neoplastic tissue of Lynch syndrome patients compared to matched untransformed tissue or non-Lynch syndrome neoplastic tissue. While antioxidants reduce 8-oxoguanine, they do not reduce CRC in Lynch syndrome models. Hence, microbe-induced oxidative/nitrosative DNA damage play causative roles in inflammatory CRC models, but not in Lynch syndrome models. It is unclear how microbial-induced inflammation promotes neoplastic transformation in colitis-associated cancer (CAC). Here, the authors use models of CAC to show that inflammation induces 8-oxoguanine lesions in DNA, and that antioxidants can reduce these DNA lesions as well as CAC.
Predictive modeling of Pseudomonas syringae virulence on bean using gradient boosted decision trees
Pseudomonas syringae is a genetically diverse bacterial species complex responsible for numerous agronomically important crop diseases. Individual P . syringae isolates are assigned pathovar designations based on their host of isolation and the associated disease symptoms, and these pathovar designations are often assumed to reflect host specificity although this assumption has rarely been rigorously tested. Here we developed a rapid seed infection assay to measure the virulence of 121 diverse P . syringae isolates on common bean ( Phaseolus vulgaris ). This collection includes P . syringae phylogroup 2 (PG2) bean isolates (pathovar syringae ) that cause bacterial spot disease and P . syringae phylogroup 3 (PG3) bean isolates (pathovar phaseolicola ) that cause the more serious halo blight disease. We found that bean isolates in general were significantly more virulent on bean than non-bean isolates and observed no significant virulence difference between the PG2 and PG3 bean isolates. However, when we compared virulence within PGs we found that PG3 bean isolates were significantly more virulent than PG3 non-bean isolates, while there was no significant difference in virulence between PG2 bean and non-bean isolates. These results indicate that PG3 strains have a higher level of host specificity than PG2 strains. We then used gradient boosting machine learning to predict each strain’s virulence on bean based on whole genome k-mers, type III secreted effector k-mers, and the presence/absence of type III effectors and phytotoxins. Our model performed best using whole genome data and was able to predict virulence with high accuracy (mean absolute error = 0.05). Finally, we functionally validated the model by predicting virulence for 16 strains and found that 15 (94%) had virulence levels within the bounds of estimated predictions. This study strengthens the hypothesis that P . syringae PG2 strains have evolved a different lifestyle than other P . syringae strains as reflected in their lower level of host specificity. It also acts as a proof-of-principle to demonstrate the power of machine learning for predicting host specific adaptation.
Recombination of ecologically and evolutionarily significant loci maintains genetic cohesion in the Pseudomonas syringae species complex
Background Pseudomonas syringae is a highly diverse bacterial species complex capable of causing a wide range of serious diseases on numerous agronomically important crops. We examine the evolutionary relationships of 391 agricultural and environmental strains using whole-genome sequencing and evolutionary genomic analyses. Results We describe the phylogenetic distribution of all 77,728 orthologous gene families in the pan-genome, reconstruct the core genome phylogeny using the 2410 core genes, hierarchically cluster the accessory genome, identify the diversity and distribution of type III secretion systems and their effectors, predict ecologically and evolutionary relevant loci, and establish the molecular evolutionary processes operating on gene families. Phylogenetic and recombination analyses reveals that the species complex is subdivided into primary and secondary phylogroups, with the former primarily comprised of agricultural isolates, including all of the well-studied P. syringae strains. In contrast, the secondary phylogroups include numerous environmental isolates. These phylogroups also have levels of genetic diversity typically found among distinct species. An analysis of rates of recombination within and between phylogroups revealed a higher rate of recombination within primary phylogroups than between primary and secondary phylogroups. We also find that “ecologically significant” virulence-associated loci and “evolutionarily significant” loci under positive selection are over-represented among loci that undergo inter-phylogroup genetic exchange. Conclusions While inter-phylogroup recombination occurs relatively rarely, it is an important force maintaining the genetic cohesion of the species complex, particularly among primary phylogroup strains. This level of genetic cohesion, and the shared plant-associated niche, argues for considering the primary phylogroups as a single biological species.
An extracellular network of Arabidopsis leucine-rich repeat receptor kinases
A high-throughput assay is used to analyse 40,000 potential extracellular domain interactions of a large family of plant cell surface receptors (LRR-RKs) and provide a cell surface interaction network for these receptors. A network of cell surface interactions Cell surface receptors mediate communication between the interior of a cell and its external environment. Specifically, the extracellular domains (ECDs) of such receptors interact with external molecules. It is less clear how interactions between ECDs of different receptors help to form receptor complexes for signal transduction. Youssef Belkhadir and colleagues investigate systems-level organization of leucine-rich repeat receptor kinases (LRR-RKs)—a large family of plant cell surface receptors with roles in processes including plant defence and development. The authors use a high-throughput assay to study 40,000 potential ECD interactions. They develop a cell surface interaction network for these receptors and study its dynamics. The team demonstrate the power of this network for detecting biologically relevant interactions by predicting and validating the function of previously uncharacterized LRR-RKs in plant growth and immunity. The cells of multicellular organisms receive extracellular signals using surface receptors. The extracellular domains (ECDs) of cell surface receptors function as interaction platforms, and as regulatory modules of receptor activation 1 , 2 . Understanding how interactions between ECDs produce signal-competent receptor complexes is challenging because of their low biochemical tractability 3 , 4 . In plants, the discovery of ECD interactions is complicated by the massive expansion of receptor families, which creates tremendous potential for changeover in receptor interactions 5 . The largest of these families in Arabidopsis thaliana consists of 225 evolutionarily related leucine-rich repeat receptor kinases (LRR-RKs) 5 , which function in the sensing of microorganisms, cell expansion, stomata development and stem-cell maintenance 6 , 7 , 8 , 9 . Although the principles that govern LRR-RK signalling activation are emerging 1 , 10 , the systems-level organization of this family of proteins is unknown. Here, to address this, we investigated 40,000 potential ECD interactions using a sensitized high-throughput interaction assay 3 , and produced an LRR-based cell surface interaction network (CSI LRR ) that consists of 567 interactions. To demonstrate the power of CSI LRR for detecting biologically relevant interactions, we predicted and validated the functions of uncharacterized LRR-RKs in plant growth and immunity. In addition, we show that CSI LRR operates as a unified regulatory network in which the LRR-RKs most crucial for its overall structure are required to prevent the aberrant signalling of receptors that are several network-steps away. Thus, plants have evolved LRR-RK networks to process extracellular signals into carefully balanced responses.
Gut-associated IgA+ immune cells regulate obesity-related insulin resistance
The intestinal immune system is emerging as an important contributor to obesity-related insulin resistance, but the role of intestinal B cells in this context is unclear. Here, we show that high fat diet (HFD) feeding alters intestinal IgA + immune cells and that IgA is a critical immune regulator of glucose homeostasis. Obese mice have fewer IgA + immune cells and less secretory IgA and IgA-promoting immune mediators. HFD-fed IgA-deficient mice have dysfunctional glucose metabolism, a phenotype that can be recapitulated by adoptive transfer of intestinal-associated pan-B cells. Mechanistically, IgA is a crucial link that controls intestinal and adipose tissue inflammation, intestinal permeability, microbial encroachment and the composition of the intestinal microbiome during HFD. Current glucose-lowering therapies, including metformin, affect intestinal-related IgA + B cell populations in mice, while bariatric surgery regimen alters the level of fecal secretory IgA in humans. These findings identify intestinal IgA + immune cells as mucosal mediators of whole-body glucose regulation in diet-induced metabolic disease. The effect of diet-induced obesity on intestinal B cell populations is not well understood despite emerging evidence of a critical role for the intestinal immune system in contributing to insulin resistance. Here, the authors show important functions of IgA in regulating metabolic disease and for intestinal immunity in modulating systemic glucose metabolism.