Hasil untuk "Microbial ecology"

M. Dao, A. Everard, J. Aron‐Wisnewsky et al.

J. Schimel, T. Balser, M. Wallenstein

G. Olsen, D. Lane, S. Giovannoni et al.

R. Burns

N. Revsbech, B. Jørgensen

D. Kirchman

Glen D'souza, Shraddha Shitut, Daniel Preussger et al.

Literature covered: early 2000s to late 2017Bacteria frequently exchange metabolites with other micro- and macro-organisms. In these often obligate cross-feeding interactions, primary metabolites such as vitamins, amino acids, nucleotides, or growth factors are exchanged. The widespread distribution of this type of metabolic interactions, however, is at odds with evolutionary theory: why should an organism invest costly resources to benefit other individuals rather than using these metabolites to maximize its own fitness? Recent empirical work has shown that bacterial genotypes can significantly benefit from trading metabolites with other bacteria relative to cells not engaging in such interactions. Here, we will provide a comprehensive overview over the ecological factors and evolutionary mechanisms that have been identified to explain the evolution and maintenance of metabolic mutualisms among microorganisms. Furthermore, we will highlight general principles that underlie the adaptive evolution of interconnected microbial metabolic networks as well as the evolutionary consequences that result for cells living in such communities.

C. A. Francis, J. Beman, M. Kuypers

R. Lenski

Ms Jamisha Francis, Ms Mollie Gidney, Mr. Seth Reasoner et al.

Introduction: The human urobiome, comprising diverse microbial members, plays a crucial role in maintaining urinary tract health. One urobiome member identified in many studies to date – including our group - is Actinotignum schaalii. A. schaalii is a Gram-positive facultative anaerobe that has also been implicated in urinary tract infections in certain patient populations. There is a scarcity of data on the prevalence of Actinotignum in the urobiome given its fastidious growth requirements. This study focuses on the identifying the prevalence of Actinotignum species and identifying conditions necessary for its growth. Methods: In collaboration with Vanderbilt University Medical Center's clinical microbiology laboratory, we collected 350 de-identified random urine specimens. To identify and characterize the presence of Actinotignum in the urobiome we used a combination of Expanded Urine Culture (EUC), 16S rRNA amplicon sequencing, and targeted PCR that allows the propagation and identification of low abundance bacteria. Bacterial identification following EUC was performed using MALDI-TOF and standard laboratory techniques. To characterize features of A. schaalii, we used a reference strain of A. schaalii CCUG 27420 to test growth conditions and performed scanning and transmission electron microscopy. Results: From randomly collected urine samples, we detected Actinotignum species in 20% of specimens by 16S rRNA sequencing. No patient factors readily associated with the presence of Actinotignum. We were able to identify corresponding bacterial colonies by EUC. Growth of the reference strain A. schaalii CCUG 27420 was promoted by the addition of a chemically defined lipid media to BHI (brain heart infusion) broth, specifically arachidonic and myristic acid. We generated high-resolution electron microscopy images of A. schaalii to characterize its cellular morphology. Scanning electron micrographs determined the shape of A. schaalii as a coccobacillus. Transmission electron micrographs detected the presence of an s-layer, metal storage organelles, and intracellular vesicles. Discussion: We detected Actinotignum spp. in urine samples from subjects across a range of ages and medical conditions, suggesting that Actinotignum is prevalent and not limited to specific disease states. Our preliminary data indicates that A. schaalii growth is promoted by lipids. Conclusion: To date, no study has investigated the prevalence of Actinotignum in the community or its growth conditions. This study underscores the importance of leveraging high-throughput sequencing and culturing techniques for a comprehensive understanding of microbial dynamics in the urobiome. The identification of growth conditions for Actinotignum species expands our knowledge of urobiome ecology and sets the stage for mechanistic studies on the interactions of Actinotignum with the urobiome. Ultimately, elucidating the role of Actinotignum in the urobiome may pave the way for targeted therapeutic interventions and personalized approaches to urinary tract health management.

Federica Mastrolonardo, Stefano Tonini, Lena Granehäll et al.

Lentils are recognized as sustainable alternative protein sources due to their favorable nutritional and functional profiles. This study evaluated the protein quality and digestibility of raw (RRLPI) and fermented (FRLPI) red lentil protein isolates and assessed their impact on the gut microbiota using the SHIME® in vitro dynamic gut model. Fermentation significantly increased in vitro protein digestibility (IVPD), from 92.5 % in RRLPI to 94.5 % in FRLPI (p < 0.05). Amino acid profiling revealed that while sulfur-containing amino acids decreased, threonine and other key essential amino acids were better preserved or enriched in FRLPI when expressed per gram of protein. Feeding with FRLPI promoted the growth of potentially beneficial colonic genera such as Lactiplantibacillus and Furfurilactobacillus and stimulated short-chain fatty acid (SCFA) production, with a notable increase in butyrate. Moreover, FRLPI digestion yielded a greater release of low-molecular-weight peptides (<3 kDa), some of which exhibited predicted antioxidant and ACE-inhibitory activities. Together, these results highlight fermentation as a strategy to optimize lentil protein functionality, improving gut microbial ecology, nutrient bioavailability, and the release of health-relevant peptides.

J. Grilli

How the coexistence of many species is maintained is a fundamental and unresolved question in ecology. Coexistence is a puzzle because we lack a mechanistic understanding of the variation in species presence and abundance. Whether variation in ecological communities is driven by deterministic or random processes is one of the most controversial issues in ecology. Here, I study the variation of species presence and abundance in microbial communities from a macroecological standpoint. I identify three macroecological laws that quantitatively characterize the fluctuation of species abundance across communities and over time. Using these three laws, one can predict species’ presence and absence, diversity, and commonly studied macroecological patterns. I show that a mathematical model based on environmental stochasticity, the stochastic logistic model, quantitatively predicts the three macroecological laws, as well as non-stationary properties of community dynamics. Microbes interact in different ways than macro-organisms, but their interactions can still form the basis for broader macroecological patterns like the Species Abundance Distribution. Here, the author shows that thre general ecological patterns can be found in microbes, within and across biome types.

Lei Wang, Fazul Nabi, Weixue Yi et al.

Thiram, a typical fungicide pesticide, is widely used in agricultural production. The presence of thiram residues is not only due to over-utilization, but is also primarily attributed to long-term accumulation. However, there is a paucity of information regarding the impact of prolonged utilization of thiram at low doses on the gut microbiota, particularly with respect to gut fungi. Our objective is to explore the effect of thiram on broilers from the perspective of gut microbiota, which includes both bacteria and fungi. We developed a long-term low-dose thiram model to simulate thiram residue and employed 16 S rRNA and ITS gene sequencing to investigate the diversity and profile of gut microbiota between group CC (normal diet) and TC (normal diet supplemented with 5 mg/kg thiram). The results revealed that low doses of thiram had a detrimental effect on broiler’s growth performance, resulting in an approximate reduction of 669.33 g in their final body weight at day 45. Our findings indicated that low-dose thiram had a negative impact on the gut bacterial composition, leading to a notable reduction in the abundance of Merdibacter, Paenibacillus, Macrococcus, Fournierella, and Anaeroplasma (p < 0.05) compared to the CC group. Conversely, the relative level of Myroides was significantly increased (p < 0.05) in response to thiram exposure. In gut fungi, thiram significantly enhanced the diversity and richness of gut fungal populations (p < 0.05), as evidenced by the notable increase in alpha indices, i.e. ACE (CC: 346.49 ± 117.27 vs TC: 787.27 ± 379.14, p < 0.05), Chao 1 (CC: 317.63 ± 69.13 vs TC: 504.85 ± 104.50, p < 0.05), Shannon (CC: 1.28 ± 1.19 vs TC: 5.39 ± 2.66, p < 0.05), Simpson (CC: 0.21 ± 0.21 vs TC: 0.78 ± 0.34, p < 0.05). Furthermore, the abundance of Ascomycota, Kickxellomycota, and Glomeromycota were significantly increased (p < 0.05) by exposure to thiram, conversely, the level of Basidiomycota was decreased (p < 0.05) in the TC group compared to the CC group. Overall, this study demonstrated that low doses of thiram induced significant changes in the composition and abundance of gut microbiota in broilers, with more pronounced changes observed in the gut fungal community as compared to the gut bacterial community. Importantly, our findings further emphasize the potential risks associated with low dose thiram exposure and have revealed a novel discovery indicating that significant alterations in gut fungi may serve as the crucial factor contributing to the detrimental effects exerted by thiram residues.

Paul Czechowski, Michel deLange, Michael Heldsinger et al.

Abstract Effective management of biodiversity requires regular surveillance of multiple species. Analysis of environmental DNA (eDNA) by metabarcoding holds promise to achieve this relatively easily. However, taxonomy‐focused eDNA surveys need suitable molecular reference data, which are often lacking, particularly at the species level and for remote locations. To evaluate the comparability of environmental DNA surveys and traditional surveys in a real‐life case study in a marine area of high conservation value, we conducted a biodiversity survey of the fish in remote and pristine Te Wāhipounamu/Fiordland (Aotearoa/New Zealand), incorporating multiple data sources. We compared eDNA‐derived species identifications against Baited Remote Underwater Video (BRUV) data collected at the same time and locations as eDNA. We also cross‐referenced both eDNA and BRUV data against literature and the Ocean Biodiversity Information System (OBIS), with literature and OBIS data representing a summary of multiple traditional surveying approaches. In total, we found 116 fish species in our study area. Environmental DNA detected 43 species; however, only three of those species overlap with species known from the literature, OBIS, or our BRUV analyses. A total of 61 fish species were known from the region from the literature, while OBIS listed 28 species, and our BRUV analyses picked up 26 species. BRUV data coincided more strongly than eDNA data with literature and OBIS data. Twenty of the 26 species detected by BRUV were known from literature and OBIS. We argue that limitated DNA reference databases are the main cause of this discrepancy, and our results indicate that eDNA of rare and endangered species can be detected if matching reference data were available. Environmental DNA analyses can only identify species present among reference data and with relaxed taxonomic assignment parameters may converge on relatives of detected species if the actually existing species themselves are missing among reference data. However, the high number of species detected by our eDNA analyses confirms that eDNA could be a powerful tool for biodiversity surveys if suitable investments in local reference databases were made.

Alexandra K. Stiffler, Poppy J. Hesketh-Best, Natascha S. Varona et al.

Abstract Background Symbioses between primary producers and bacteria are crucial for nutrient exchange that fosters host growth and niche adaptation. Yet, how viruses that infect bacteria (phages) influence these bacteria-eukaryote interactions is still largely unknown. Here, we investigate the role of viruses on the genomic diversity and functional adaptations of bacteria associated with pelagic sargassum. This brown alga has dramatically increased its distribution range in the Atlantic in the past decade and is predicted to continue expanding, imposing severe impacts on coastal ecosystems, economies, and human health. Results We reconstructed 73 bacterial and 3963 viral metagenome-assembled genomes (bMAGs and vMAGs, respectively) from coastal Sargassum natans VIII and surrounding seawater. S. natans VIII bMAGs were enriched in prophages compared to seawater (28% and 0.02%, respectively). Rhodobacterales and Synechococcus bMAGs, abundant members of the S. natans VIII microbiome, were shared between the algae and seawater but were associated with distinct phages in each environment. Genes related to biofilm formation and quorum sensing were enriched in S. natans VIII phages, indicating their potential to influence algal association in their bacterial hosts. In-vitro assays with a bacterial community harvested from sargassum surface biofilms and depleted of free viruses demonstrated that these bacteria are protected from lytic infection by seawater viruses but contain intact and inducible prophages. These bacteria form thicker biofilms when growing on sargassum-supplemented seawater compared to seawater controls, and phage induction using mitomycin C was associated with a significant decrease in biofilm formation. The induced metagenomes were enriched in genomic sequences classified as temperate viruses compared to uninduced controls. Conclusions Our data shows that prophages contribute to the flexible genomes of S. natans VIII-associated bacteria. These prophages encode genes with symbiotic functions, and their induction decreases biofilm formation, an essential capacity for flexible symbioses between bacteria and the alga. These results indicate that prophage acquisition and induction contribute to genomic and functional diversification during sargassum-bacteria symbioses, with potential implications for algae growth. Video Abstract

Yehezkel S. Resheff, Hanna M. Bensch, Markus Zöttl et al.

Abstract The application of supervised machine learning methods to identify behavioural modes from inertial measurements of bio-loggers has become a standard tool in behavioural ecology. Several design choices can affect the accuracy of identifying the behavioural modes. One such choice is the inclusion or exclusion of segments consisting of more than a single behaviour (mixed segments) in the machine learning model training data. Currently, the common practice is to ignore such segments during model training. In this paper we tested the hypothesis that including mixed segments in model training will improve accuracy, as the model would perform better in identifying them in the test data. We test this hypothesis using a series of data simulations on four datasets of accelerometer data coupled with behaviour observations, obtained from four study species (Damaraland mole-rats, meerkats, olive baboons, polar bears). Results show that when a substantial proportion of the test data are mixed behaviour segments (above ~ 10%), including mixed segments in machine learning model training improves the accuracy of classification. These results were consistent across the four study species, and robust to changes in segment length, sample size, and degree of mixture within the mixed segments. However, we also find that in some cases (particularly in baboons) models trained with mixed segments show reduced accuracy in classifying test data containing only single behaviour (pure) segments, compared to models trained without mixed segments. Based on these results, we recommend that when the classification model is expected to deal with a substantial proportion of mixed behaviour segments (> 10%), it is beneficial to include them in model training, otherwise, it is unnecessary but also not harmful. The exception is when there is a basis to assume that the training data contains a higher rate of mixed segments than the actual (unobserved) data to be classified—such a situation may occur particularly when training data are collected in captivity and used to classify data from the wild. In this case, excess inclusion of mixed segments in training data should probably be avoided.

Manuel Stothut, Damaris Kühne, Vanessa Ströbele et al.

Abstract Environmental DNA (eDNA) metabarcoding promises to be a cost‐ and time‐efficient monitoring tool to detect interactions of arthropods with plants. However, observation‐based verification of the eDNA‐derived data is still required to confirm the reliability of those detections, i.e., to verify whether the arthropods have previously interacted with the plant. Here, we conducted a comparative analysis of the performance of eDNA metabarcoding and video camera observations to detect arthropod communities associated with sunflowers (Helianthus annuus, L.). We compared the taxonomic composition, interaction type, and diversity by testing for an effect of arthropod interaction time and occupancy on successful taxon recovery by eDNA. We also tested if prewashing of the flowers successfully removed eDNA deposition from before the video camera recording, thus enabling a reset of the community for standardized monitoring. We find that eDNA and video camera observations recovered distinct communities, with about a quarter of the arthropod families overlapping. However, the overlapping taxa comprised ~90% of the interactions observed by the video camera. Interestingly, eDNA metabarcoding recovered more unique families than the video cameras, but approximately two‐thirds of those unique observations were of rare species. The eDNA‐derived families were biased toward plant sap‐suckers, showing that such species may deposit more eDNA than, for example, transient pollinators. We also find that prewashing of the flower heads did not suffice to remove all eDNA traces, suggesting that eDNA on plants may be more temporally stable than previously thought. Our work highlights the great potential of eDNA as a tool to detect plant‐arthropod interactions, particularly for specialized and frequently interacting taxa.

O. Cordero, M. Polz

Yunfeng Yang

Functional traits are measurable characteristics that affect an organism's fitness under certain environmental conditions. The use of functional traits in microbial ecology holds great promise for improving our ability to develop biogeochemical models and predict ecosystem responses to global changes. Notably, functional traits could be decoupled from taxonomic relatedness, owing to horizontal gene transfer among microorganisms and adaptive evolution. In recent years, our knowledge about microbial functional traits has been substantially enhanced, thereby revealing the multitude of ecological processes in driving community assembly and dynamics. Here, I summarize the emerging patterns of how microbial functional traits respond to changing environments, which considerably differ from better-studied microbial taxonomy. I use niche and neutral theories to explain microbial functional traits. Finally, I highlight future challenges to analyze, elucidate, and utilize functional traits in microbial ecology.

Francisco Pascoal, R. Costa, C. Magalhães

Our ability to describe the highly diverse pool of low abundance populations present in natural microbial communities is increasing at an unprecedented pace. Yet we currently lack an integrative view of the key taxa, functions, and metabolic activity which make-up this communal pool, usually referred to as the 'rare biosphere', across the domains of life. In this context, this review examines the microbial rare biosphere in its broader sense, providing an historical perspective on representative studies which enabled to bridge the concept from macroecology to microbial ecology. It then addresses our current knowledge of the prokaryotic rare biosphere, and covers emerging insights into the ecology, taxonomy, and evolution of low abundance microeukaryotic, viral and host-associated communities. We also review recent methodological advances and provide a synthetic overview on how the rare biosphere fits into different conceptual models used to explain microbial community assembly mechanisms, composition, and function.