scholarly journals The depletion mechanism can actuate bacterial aggregation by self-produced exopolysaccharides and determine species distribution and composition in bacterial aggregates

2021 ◽  
Author(s):  
Patrick R Secor ◽  
Lia A Michaels ◽  
DeAnna C Bublitz ◽  
Laura K Jennings ◽  
Pradeep K Singh
Keyword(s):  
Species Distribution ◽  
Bacterial Communities ◽  
Species Interactions ◽  
Chronic Infections ◽  
Bacterial Aggregation ◽  
Type Vi Secretion ◽  
Attached Bacteria ◽  
Secretion Inhibition ◽  
Physical Forces ◽  
Bacterial Aggregates

Bacteria causing chronic infections are often found in cell aggregates suspended in polymer secretions, and aggregation may be a factor in infection persistence. One aggregation mechanism, called depletion aggregation, is driven by physical forces between bacteria and polymers. Here we investigated whether the depletion mechanism can actuate the aggregating effects of  P. aeruginosa  exopolysaccharides for suspended (i.e. not surface attached) bacteria, and how depletion affects bacterial inter-species interactions. We found cells overexpressing the exopolysaccharides Pel and Psl, but not alginate remained aggregated after depletion-mediating conditions were reversed. In co-culture, d epletion aggregation had contrasting effects on  P. aeruginosa’s  interactions with coccus- and rod-shaped bacteria.  Depletion caused  S. aureus (cocci) and  P. aeruginosa  (rods) to segregate from each other,  S. aureus  to resist secreted  P. aeruginosa  antimicrobial factors, and the species to co-exist. In contrast ,  depletion aggregation caused  P. aeruginosa  and  Burkholderia   sp.  to intermix, enhancing  type VI secretion  inhibition of  Burkholderia  by  P. aeruginosa , leading to  P. aeruginosa  dominance . These results show that in addition to being a primary cause of aggregation in polymer-rich suspensions, physical forces inherent to the depletion mechanism can actuate the aggregating effects of self-produced exopolysaccharides and determine species distribution and composition of bacterial communities.

scholarly journals Phylogenetic and metabolic diversity have contrasting effects on the ecological functioning of bacterial communities

2021 ◽  
Vol 97 (3) ◽  
Author(s):  
Constantinos Xenophontos ◽  
Martin Taubert ◽  
W Stanley Harpole ◽  
Kirsten Küsel
Keyword(s):  
Bacterial Communities ◽  
Species Interactions ◽  
Phylogenetic Diversity ◽  
Molecular Mechanisms ◽  
Linear Models ◽  
Theory Development ◽  
Metabolic Diversity ◽  
Community Functioning ◽  
Metabolic Functions ◽  
Independent Effects

ABSTRACT Quantifying the relative contributions of microbial species to ecosystem functioning is challenging, because of the distinct mechanisms associated with microbial phylogenetic and metabolic diversity. We constructed bacterial communities with different diversity traits and employed exoenzyme activities (EEAs) and carbon acquisition potential (CAP) from substrates as proxies of bacterial functioning to test the independent effects of these two aspects of biodiversity. We expected that metabolic diversity, but not phylogenetic diversity would be associated with greater ecological function. Phylogenetically relatedness should intensify species interactions and coexistence, therefore amplifying the influence of metabolic diversity. We examined the effects of each diversity treatment using linear models, while controlling for the other, and found that phylogenetic diversity strongly influenced community functioning, positively and negatively. Metabolic diversity, however, exhibited negative or non-significant relationships with community functioning. When controlling for different substrates, EEAs increased along with phylogenetic diversity but decreased with metabolic diversity. The strength of diversity effects was related to substrate chemistry and the molecular mechanisms associated with each substrate's degradation. EEAs of phylogenetically similar groups were strongly affected by within-genus interactions. These results highlight the unique flexibility of microbial metabolic functions that must be considered in further ecological theory development.

scholarly journals Motility-Independent Formation of Antibiotic-TolerantPseudomonas aeruginosaAggregates

2019 ◽  
Vol 85 (14) ◽  
Author(s):  
Sally Demirdjian ◽  
Hector Sanchez ◽  
Daniel Hopkins ◽  
Brent Berwin
Keyword(s):  
Biofilm Formation ◽  
Bacterial Pathogen ◽  
Aggregate Formation ◽  
Flagellar Motility ◽  
Wild Type ◽  
Chronic Infections ◽  
Content Type ◽  
Temporal Adaptation ◽  
Bacterial Aggregates

ABSTRACTPseudomonas aeruginosais a bacterial pathogen that causes severe chronic infections in immunocompromised individuals. This bacterium is highly adaptable to its environments, which frequently select for traits that promote bacterial persistence. A clinically significant temporal adaptation is the formation of surface- or cell-adhered bacterial biofilms that are associated with increased resistance to immune and antibiotic clearance. Extensive research has shown that bacterial flagellar motility promotes formation of such biofilms, whereupon the bacteria subsequently become nonmotile. However, recent evidence shows that antibiotic-tolerant nonattached bacterial aggregates, distinct from surface-adhered biofilms, can form, and these have been reported in the context of lung infections, otitis media, nonhealing wounds, and soft tissue fillers. It is unclear whether the same bacterial traits are required for aggregate formation as for biofilm formation. In this report, using isogenic mutants, we demonstrate thatP. aeruginosaaggregates in liquid cultures are spontaneously formed independent of bacterial flagellar motility and independent of an exogenous scaffold. This contrasts with the role of the flagellum to initiate surface-adhered biofilms. Similarly to surface-attached biofilms, these aggregates exhibit increased antibiotic tolerance compared to planktonic cultures. These findings provide key insights into the requirements for aggregate formation that contrast with those for biofilm formation and that may have relevance for the persistence and dissemination of nonmotile bacteria found within chronic clinical infections.IMPORTANCEIn this work, we have investigated the role of bacterial motility with regard to antibiotic-tolerant bacterial aggregate formation. Previous work has convincingly demonstrated thatP. aeruginosaflagellar motility promotes the formation of surface-adhered biofilms in many systems. In contrast, aggregate formation byP. aeruginosawas observed for nonmotile but not for motile cells in the presence of an exogenous scaffold. Here, we demonstrate that both wild-typeP. aeruginosaand mutants that genetically lack motility spontaneously form antibiotic-tolerant aggregates in the absence of an exogenously added scaffold. Additionally, we also demonstrate that wild-type (WT) and nonmotileP. aeruginosabacteria can coaggregate, shedding light on potential physiological interactions and heterogeneity of aggregates.

scholarly journals YbeY controls the type III and type VI secretion systems and biofilm formation through RetS in Pseudomonas aeruginosa

2020 ◽  
Author(s):  
Yushan Xia ◽  
Congjuan Xu ◽  
Dan Wang ◽  
Yuding Weng ◽  
Yongxin Jin ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Type Iii Secretion ◽  
Biofilm Formation ◽  
Small Rnas ◽  
Type Iii Secretion System ◽  
Secretion System ◽  
Type Vi Secretion System ◽  
Chronic Infections ◽  
Type Iii ◽  
Type Vi Secretion

YbeY is a highly conserved RNase in bacteria and plays essential roles in the maturation of 16S rRNA, regulation of small RNAs (sRNAs) and bacterial responses to environmental stresses. Previously, we verified the role of YbeY in rRNA processing and ribosome maturation in Pseudomonas aeruginosa and demonstrated YbeY-mediated regulation of rpoS through a sRNA ReaL. In this study, we demonstrate that mutation of the ybeY gene results in upregulation of the type III secretion system (T3SS) genes as well as downregulation of the type VI secretion system (T6SS) genes and reduction of biofilm formation. By examining the expression of the known sRNAs in P. aeruginosa, we found that mutation of the ybeY gene leads to downregulation of the small RNAs RsmY/Z that control the T3SS, the T6SS and biofilm formation. Further studies revealed that the reduced levels of RsmY/Z are due to upregulation of retS. Taken together, our results reveal the pleiotropic functions of YbeY and provide detailed mechanisms of YbeY-mediated regulation in P. aeruginosa. IMPORTANCE Pseudomonas aeruginosa causes a variety of acute and chronic infections in humans. The type III secretion system (T3SS) plays an important role in acute infection and the type VI secretion system (T6SS) and biofilm formation are associated with chronic infections. Understanding of the mechanisms that control the virulence determinants involved in acute and chronic infections will provide clues for the development of effective treatment strategies. Our results reveal a novel RNase mediated regulation on the T3SS, T6SS and biofilm formation in P. aeruginosa.

Modeling Abiotic Niches of Crops and Wild Ancestors Using Deep Learning: A Generalized Approach

2019 ◽  
Author(s):  
W. G. Hulleman ◽  
R. A. Vos
Keyword(s):  
Deep Learning ◽  
Species Distribution ◽  
Habitat Suitability ◽  
Species Interactions ◽  
Method Development ◽  
Species Distribution Modeling ◽  
Crop Species ◽  
Data Set ◽  
Important Species ◽  
Distribution Modeling

AbstractIntroductionUnderstanding what interactions and environmental factors shape the geographic distribution of species is one of the fundamental questions in ecology and evolution. Insofar as the focus is on agriculturally important species, insight into this is also of applied importance. Species Distribution Modeling (SDM) comprises a spectrum of approaches for establishing correlative models of species (co-)occurrences and geospatial patterns of abiotic environmental variables.MethodsHere, we contribute to this field by presenting a generalized approach for SDM that utilizes deep learning, which offers some improvements over current methods, and by presenting a case study on the habitat suitability of staple crops and their wild ancestors. The approach we present is implemented in a reusable software toolkit, which we apply to an extensive data set of geo-referenced occurrence records for 52 species and 59 GIS layers. We compare the habitat suitability projections for selected, major crop species with the actual extent of their current cultivation.ResultsOur results show that the approach yields especially plausible projections for species with large numbers of occurrences (>500). For the analysis of such data sets, the toolkit provides a convenient interface for using deep neural networks in SDM, a relatively novel application of deep learning. The toolkit, the data, and the results are available as open source / open access packages.ConclusionsSpecies Distribution Modeling with deep learning is a promising avenue for method development. The niche projections that can be produced are plausible, and the general approach provides great flexibility for incorporating additional data such as species interactions.

Patterns and scale of habitat use in two temperate-zone, small mammal faunas

1984 ◽  
Vol 62 (8) ◽  
pp. 1540-1547 ◽  
Author(s):  
Douglas W. Morris
Keyword(s):  
Habitat Selection ◽  
Small Mammals ◽  
Species Distribution ◽  
Small Mammal ◽  
Habitat Preference ◽  
Species Interactions ◽  
Microhabitat Use ◽  
Microhabitat Selection ◽  
Extinction Probabilities ◽  
Mammal Faunas

Small mammals were livetrapped and habitat quantified in replicates of six macrohabitats in Alberta and in temporal replicates of four macrohabitats in Ontario, Canada. Similar patterns emerged in both locations. The relative abundances of small mammals depended upon macrohabitat; within macrohabitats, species differed significantly in microhabitat use. The patterns were dynamic and probably the result of habitat preference instead of species interactions. Macrohabitat differences may in part be outcomes of microhabitat selection, but are unlikely to be completely understood without superimposing colonization and extinction probabilities on habitat selection models. Field biologists must recognize both scales of habitat to interpret patterns of species distribution.

scholarly journals Recent advances in understanding Pseudomonas aeruginosa as a pathogen

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1261 ◽  
Author(s):  
Jens Klockgether ◽  
Burkhard Tümmler
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Population Biology ◽  
Recent Progress ◽  
Human Subjects ◽  
Opportunistic Pathogen ◽  
Mammalian Host ◽  
Secretion Systems ◽  
Chronic Infections ◽  
Type Vi Secretion

The versatile and ubiquitousPseudomonas aeruginosais an opportunistic pathogen causing acute and chronic infections in predisposed human subjects. Here we review recent progress in understandingP. aeruginosapopulation biology and virulence, its cyclic di-GMP-mediated switches of lifestyle, and its interaction with the mammalian host as well as the role of the type III and type VI secretion systems inP. aeruginosainfection.

scholarly journals Resistance and Not Plant Fruit Traits Determine Root-Associated Bacterial Community Composition along a Domestication Gradient in Tomato

Plants ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 43
Author(s):  
Lisanne Smulders ◽  
Victoria Ferrero ◽  
Eduardo de la Peña ◽  
María J. Pozo ◽  
Juan Antonio Díaz Pendón ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Plant Resistance ◽  
Bacterial Communities ◽  
Species Interactions ◽  
Plant Traits ◽  
Bacterial Community Composition ◽  
Agricultural Practices ◽  
Fruit Traits ◽  
Resistance Traits

Soil bacterial communities are involved in multiple ecosystem services, key in determining plant productivity. Crop domestication and intensive agricultural practices often disrupt species interactions with unknown consequences for rhizosphere microbiomes. This study evaluates whether variation in plant traits along a domestication gradient determines the composition of root-associated bacterial communities; and whether these changes are related to targeted plant traits (e.g., fruit traits) or are side effects of less-often-targeted traits (e.g., resistance) during crop breeding. For this purpose, 18 tomato varieties (wild and modern species) differing in fruit and resistance traits were grown in a field experiment, and their root-associated bacterial communities were characterised. Root-associated bacterial community composition was influenced by plant resistance traits and genotype relatedness. When only considering domesticated tomatoes, the effect of resistance on bacterial OTU composition increases, while the effect due to phylogenetic relatedness decreases. Furthermore, bacterial diversity positively correlated with plant resistance traits. These results suggest that resistance traits not selected during domestication are related to the capacity of tomato varieties to associate with different bacterial groups. Taken together, these results evidence the relationship between plant traits and bacterial communities, pointing out the potential of breeding to affect plant microbiomes.

scholarly journals Deep Multi-species Embedding

2017 ◽  
Author(s):  
Di Chen ◽  
Yexiang Xue ◽  
Daniel Fink ◽  
Shuo Chen ◽  
Carla P. Gomes
Keyword(s):  
Neural Network ◽  
Species Distribution ◽  
Species Interactions ◽  
Deep Neural Network ◽  
Species Distribution Models ◽  
Habitat Preferences ◽  
Bird Species ◽  
Single Species ◽  
Additional Contribution ◽  
Distribution Models

Understanding how species are distributed across landscapes over time is a fundamental question in biodiversity research. Unfortunately, most species distribution models only target a single species at a time, despite strong ecological evidence that species are not independently distributed. We propose Deep Multi-Species Embedding (DMSE), which jointly embeds vectors corresponding to multiple species as well as vectors representing environmental covariates into a common high-dimensional feature space via a deep neural network. Applied to bird observational data from the citizen science project eBird, we demonstrate how the DMSE model discovers inter-species relationships to outperform single-species distribution models (random forests and SVMs) as well as competing multi-label models. Additionally, we demonstrate the benefit of using a deep neural network to extract features within the embedding and show how they improve the predictive performance of species distribution modelling. An important domain contribution of the DMSE model is the ability to discover and describe species interactions while simultaneously learning the shared habitat preferences among species. As an additional contribution, we provide a graphical embedding of hundreds of bird species in the Northeast US.

scholarly journals Formation, Development, and Cross-Species Interactions in Biofilms

2022 ◽  
Vol 12 ◽  
Author(s):  
Aihua Luo ◽  
Fang Wang ◽  
Degang Sun ◽  
Xueyu Liu ◽  
Bingchang Xin
Keyword(s):  
Species Interactions ◽  
Bacterial Infections ◽  
Early Stage ◽  
Microbial Interactions ◽  
Bacterial Survival ◽  
Chronic Infections ◽  
Immune Attack ◽  
Biofilm Development ◽  
Natural Settings ◽  
Harmful Effects

Biofilms, which are essential vectors of bacterial survival, protect microbes from antibiotics and host immune attack and are one of the leading causes that maintain drug-resistant chronic infections. In nature, compared with monomicrobial biofilms, polymicrobial biofilms composed of multispecies bacteria predominate, which means that it is significant to explore the interactions between microorganisms from different kingdoms, species, and strains. Cross-microbial interactions exist during biofilm development, either synergistically or antagonistically. Although research into cross-species biofilms remains at an early stage, in this review, the important mechanisms that are involved in biofilm formation are delineated. Then, recent studies that investigated cross-species cooperation or synergy, competition or antagonism in biofilms, and various components that mediate those interactions will be elaborated. To determine approaches that minimize the harmful effects of biofilms, it is important to understand the interactions between microbial species. The knowledge gained from these investigations has the potential to guide studies into microbial sociality in natural settings and to help in the design of new medicines and therapies to treat bacterial infections.

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