Microbiome Composition and Function in Aquatic Vertebrates: Small Organisms Making Big Impacts on Aquatic Animal Health

Aquatic ecosystems are under increasing stress from global anthropogenic and natural changes, including climate change, eutrophication, ocean acidification, and pollution. In this critical review, we synthesize research on the microbiota of aquatic vertebrates and discuss the impact of emerging stressors on aquatic microbial communities using two case studies, that of toxic cyanobacteria and microplastics. Most studies to date are focused on host-associated microbiomes of individual organisms, however, few studies take an integrative approach to examine aquatic vertebrate microbiomes by considering both host-associated and free-living microbiota within an ecosystem. We highlight what is known about microbiota in aquatic ecosystems, with a focus on the interface between water, fish, and marine mammals. Though microbiomes in water vary with geography, temperature, depth, and other factors, core microbial functions such as primary production, nitrogen cycling, and nutrient metabolism are often conserved across aquatic environments. We outline knowledge on the composition and function of tissue-specific microbiomes in fish and marine mammals and discuss the environmental factors influencing their structure. The microbiota of aquatic mammals and fish are highly unique to species and a delicate balance between respiratory, skin, and gastrointestinal microbiota exists within the host. In aquatic vertebrates, water conditions and ecological niche are driving factors behind microbial composition and function. We also generate a comprehensive catalog of marine mammal and fish microbial genera, revealing commonalities in composition and function among aquatic species, and discuss the potential use of microbiomes as indicators of health and ecological status of aquatic ecosystems. We also discuss the importance of a focus on the functional relevance of microbial communities in relation to organism physiology and their ability to overcome stressors related to global change. Understanding the dynamic relationship between aquatic microbiota and the animals they colonize is critical for monitoring water quality and population health.

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Longitudinal sampling of external mucosae in farmed European seabass reveals the impact of water temperature on bacterial dynamics

ISME Communications ◽

10.1038/s43705-021-00019-x ◽

2021 ◽

Vol 1 (1) ◽

Author(s):

Daniela Rosado ◽

Raquel Xavier ◽

Jo Cable ◽

Ricardo Severino ◽

Pedro Tarroso ◽

...

Keyword(s):

Environmental Factors ◽

Microbial Diversity ◽

Water Temperature ◽

Abiotic Factors ◽

Seasonal Effect ◽

Microbial Composition ◽

Surrounding Water ◽

European Seabass ◽

And Function ◽

The Impact

AbstractFish microbiota are intrinsically linked to health and fitness, but they are highly variable and influenced by both biotic and abiotic factors. Water temperature particularly limits bacterial adhesion and growth, impacting microbial diversity and bacterial infections on the skin and gills. Aquaculture is heavily affected by infectious diseases, especially in warmer months, and industry practices often promote stress and microbial dysbiosis, leading to an increased abundance of potentially pathogenic bacteria. In this regard, fish mucosa health is extremely important because it provides a primary barrier against pathogens. We used 16 rRNA V4 metataxonomics to characterize the skin and gill microbiota of the European seabass, Dicentrarchus labrax, and the surrounding water over 12 months, assessing the impact of water temperature on microbial diversity and function. We show that the microbiota of external mucosae are highly dynamic with consistent longitudinal trends in taxon diversity. Several potentially pathogenic genera (Aliivibrio, Photobacterium, Pseudomonas, and Vibrio) were highly abundant, showing complex interactions with other bacterial genera, some of which with recognized probiotic activity, and were also significantly impacted by changes in temperature. The surrounding water temperature influenced fish microbial composition, structure and function over time (days and months). Additionally, dysbiosis was more frequent in warmer months and during transitions between cold/warm months. We also detected a strong seasonal effect in the fish microbiota, which is likely to result from the compound action of several unmeasured environmental factors (e.g., pH, nutrient availability) beyond temperature. Our results highlight the importance of performing longitudinal studies to assess the impact of environmental factors on fish microbiotas.

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Profiling soil microbial communities with next-generation sequencing: the influence of DNA kit selection and technician technical expertise

10.7287/peerj.preprints.3073 ◽

2017 ◽

Author(s):

Taha Soliman ◽

Sung-Yin Yang ◽

Tomoko Yamazaki ◽

Holger Jenke-Kodama

Keyword(s):

Next Generation Sequencing ◽

Microbial Communities ◽

Dna Extraction ◽

Dna Isolation ◽

Soil Microbial Communities ◽

Next Generation ◽

Microbial Composition ◽

Okinawa Island ◽

The Impact ◽

Generation Sequencing

Structure and diversity of microbial communities are an important research topic in biology, since microbes play essential roles in the ecology of various environments. Different DNA isolation protocols can lead to data bias and can affect results of next-generation sequencing. To evaluate the impact of protocols for DNA isolation from soil samples and also the influence of individual handling of samples, we compared results obtained by two researchers (R and T) using two different DNA extraction kits: (1) MO BIO PowerSoil® DNA Isolation kit (MO_R and MO_T) and (2) NucleoSpin® Soil kit (MN_R and MN_T). Samples were collected from six different sites on Okinawa Island, Japan. For all sites, differences in the results of microbial composition analyses (bacteria, archaea, fungi, and other eukaryotes), obtained by the two researchers using the two kits, were analyzed. For both researchers, the MN kit gave significantly higher yields of genomic DNA at all sites compared to the MO kit (ANOVA; P <0.006). In addition, operational taxonomic units for some phyla and classes were missed in some cases: Micrarchaea were detected only in the MN_T and MO_R analyses; the bacterial phylum Armatimonadetes was detected only in MO_R and MO_T; and WIM5 of the phylum Amoebozoa of eukaryotes was found only in the MO_T analysis. Our results suggest the possibility of handling bias; therefore, it is crucial that replicated DNA extraction be performed by at least two technicians for thorough microbial analyses and to obtain accurate estimates of microbial diversity.

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Profiling soil microbial communities with next-generation sequencing: the influence of DNA kit selection and technician technical expertise

10.7287/peerj.preprints.3073v1 ◽

2017 ◽

Author(s):

Taha Soliman ◽

Sung-Yin Yang ◽

Tomoko Yamazaki ◽

Holger Jenke-Kodama

Keyword(s):

Next Generation Sequencing ◽

Microbial Communities ◽

Dna Extraction ◽

Dna Isolation ◽

Soil Microbial Communities ◽

Next Generation ◽

Microbial Composition ◽

Okinawa Island ◽

The Impact ◽

Generation Sequencing

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Profiling soil microbial communities with next-generation sequencing: the influence of DNA kit selection and technician technical expertise

PeerJ ◽

10.7717/peerj.4178 ◽

2017 ◽

Vol 5 ◽

pp. e4178 ◽

Cited By ~ 17

Author(s):

Taha Soliman ◽

Sung-Yin Yang ◽

Tomoko Yamazaki ◽

Holger Jenke-Kodama

Keyword(s):

Next Generation Sequencing ◽

Microbial Communities ◽

Dna Extraction ◽

Dna Isolation ◽

Soil Microbial Communities ◽

Next Generation ◽

Microbial Composition ◽

Okinawa Island ◽

The Impact ◽

Generation Sequencing

Structure and diversity of microbial communities are an important research topic in biology, since microbes play essential roles in the ecology of various environments. Different DNA isolation protocols can lead to data bias and can affect results of next-generation sequencing. To evaluate the impact of protocols for DNA isolation from soil samples and also the influence of individual handling of samples, we compared results obtained by two researchers (R and T) using two different DNA extraction kits: (1) MO BIO PowerSoil®DNA Isolation kit (MO_R and MO_T) and (2) NucleoSpin®Soil kit (MN_R and MN_T). Samples were collected from six different sites on Okinawa Island, Japan. For all sites, differences in the results of microbial composition analyses (bacteria, archaea, fungi, and other eukaryotes), obtained by the two researchers using the two kits, were analyzed. For both researchers, the MN kit gave significantly higher yields of genomic DNA at all sites compared to the MO kit (ANOVA;P < 0.006). In addition, operational taxonomic units for some phyla and classes were missed in some cases: Micrarchaea were detected only in the MN_T and MO_R analyses; the bacterial phylum Armatimonadetes was detected only in MO_R and MO_T; and WIM5 of the phylum Amoebozoa of eukaryotes was found only in the MO_T analysis. Our results suggest the possibility of handling bias; therefore, it is crucial that replicated DNA extraction be performed by at least two technicians for thorough microbial analyses and to obtain accurate estimates of microbial diversity.

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Structure and function of the bacterial and fungal gut flora of Neotropical butterflies

10.1101/128884 ◽

2017 ◽

Cited By ~ 3

Author(s):

Alison Ravenscraft ◽

Michelle Berry ◽

Tobin Hammer ◽

Kabir Peay ◽

Carol Boggs

Keyword(s):

Amino Acids ◽

Microbial Communities ◽

Bacterial Species ◽

Microbial Community Composition ◽

Structure And Function ◽

Feeding Guilds ◽

Gut Flora ◽

Microbial Composition ◽

Host Diet ◽

And Function

AbstractThe relationship between animals and their gut flora is simultaneously one of the most common and most complex symbioses on Earth. Despite its ubiquity, our understanding of this invisible but often critical relationship is still in its infancy. We employed adult Neotropical butterflies as a study system to ask three questions: First, how does gut microbial community composition vary across host individuals, species and dietary guilds? Second, how do gut flora compare to food microbial communities? Finally, are gut flora functionally adapted to the chemical makeup of host foods? To answer these questions we captured nearly 300 Costa Rican butterflies representing over 50 species, six families and two feeding guilds: frugivores and nectivores. We characterized the bacteria and fungi in guts, wild fruits and wild nectars via amplicon sequencing and assessed the catabolic abilities of the gut flora via culture-based assays.Gut communities were distinct from food communities, suggesting that the gut environment acts as a strong filter on potential colonists. Nevertheless, gut flora varied widely among individuals and species. On average, a pair of butterflies shared 21% of their bacterial species and 6% of their fungi. Host species explained 25-30% of total variation in microbial communities while host diet explained 4%. However, diet was still relevant at the individual microbe level—half of the most abundant microbial species differed in abundance between frugivores and nectivores. Diet was also related to the functional profile of gut flora: compared to frugivores, nectivores’ gut flora exhibited increased catabolism of sugars and sugar alcohols and decreased catabolism of amino acids, carboxylic acids and dicarboxylic acids. Since fermented juice contains more amino acids and less sugar than nectar, it appears that host diet filters the gut flora by favoring microbes that digest compounds abundant in foods.By quantifying the degree to which gut communities vary among host individuals, species and dietary guilds and evaluating how gut microbial composition and catabolic potential are related to host diet, this study deepens our understanding of the structure and function of one of the most complex and ubiquitous symbioses in the animal kingdom.

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Long term exposure of human gut microbiota with high and low emulsifier sensitivity to soy lecithin in M-SHIME model.

10.1101/2021.12.16.472798 ◽

2021 ◽

Author(s):

Lisa Miclotte ◽

Ellen De Paepe ◽

Qiqiong Li ◽

Andreja Rajkovic ◽

John Van Camp ◽

...

Keyword(s):

Gut Microbiota ◽

Day Treatment ◽

Treatment Phase ◽

Microbial Composition ◽

Soy Lecithin ◽

Potential Health ◽

And Function ◽

The Impact

In the context of the potential health hazards related to food processing, dietary emulsifiers have been shown to alter the structure and function of the gut microbial community, both in vivo and in vitro. In mouse models, these emulsifier exposed gut microbiota were shown to contribute to gut inflammation. Several knowledge gaps remain to be addressed though. As such, the impact from a longer timeframe of exposure on the gut microbiota is not known and interindividual variability in microbiome response needs to be measured. To answer these research questions, in this study the faecal microbiota from two individuals, previously selected for high and low emulsifier sensitivity, were exposed to two concentrations of soy lecithin during a 7 day treatment phase in the dynamic mucosal simulator of the human intestinal microbial ecosystem (M-SHIME). The results showed mild effects from soy lecithin on the composition and functionality of these microbial communities, which depended on the original microbial composition. The effects also mostly levelled off after 3 days of exposure. The emulsifier sensitivity for which the microbiota were selected, was preserved. Some potentially concerning effects were also registered: butyrate levels, positively correlating with Faecalibacterium abundance, were lowered by soy lecithin. Also the abundance of the beneficial Bifidobacterium genus was lowered, while the abundance of the notorious unclassified Enterobacteriaceae was increased. Within the family of the unclassified Lachnospiraceae, several genera were either suppressed or stimulated. The effects that these microbial alterations would have on a living host is not yet certain, especially given the fact that large fractions of soy lecithins constituents can be absorbed. Nevertheless, choline and phosphatidylcholine, both primary and absorbable constituents of soy lecithin, have recently been linked to cardiovascular disease via the generation of TMA by the gut microbiota. Further studies that validate our findings and link them to potential health outcomes are thus justified.

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Dynamic simulations of microbial communities under perturbations: opportunities for microbiome engineering

10.21203/rs.2.24431/v1 ◽

2020 ◽

Author(s):

Beatriz García-Jiménez ◽

Jorge Carrasco ◽

Joaquín Medina ◽

Mark D Wilkinson

Keyword(s):

Microbial Communities ◽

Biological Knowledge ◽

Sample Collection ◽

Biomedical Knowledge ◽

Microbial Composition ◽

Dynamic Simulations ◽

Soil Microbial ◽

Types Of Information ◽

The Impact

Abstract Background : There are few large longitudinal microbiome studies, and fewer that include controlled, well-annotated perturbations between sampling-points. Thus, there are few opportunities to employ data-driven computational analyses of perturbed microbial communities over time. Results : Our novel computational system simulates the dynamics of microbial communities under perturbations using genome-scale metabolic models (GEMs). Perturbations include modifications to a) the nutrients available in the medium, allowing modelling of prebiotics; and/or b) the microorganisms present in the community to model, for example, probiotics or pathogen infection. These simulations generate the quantity and types of information required by MDPbiome, an AI system which builds predictive models suggesting the perturbation(s) required to engineer microbial communities to a desired state. We call this novel combination of technologies "MDPbiomeGEM"'. We demonstrate, in a Crohn’s disease microbiome, that MDPbiomeGEM correctly models the influence of both prebiotic fiber and a probiotic, resulting in a recommendation to consume inulin to recover from dysbiosis, consistent with prior biomedical knowledge. When used to model the soil microbiome's ability to degrade the herbicide Atrazine, differing recommendations arise depending on the highly variable state of the initial soil microbial composition, highlighting the relevance of both phosphate and microbes (i.e. Halobacillus sp. and H.stevensii ) in a directed microbiome engineering strategy, consistent with previously published observations. Conclusions : MDPbiomeGEM generates large volumes of longitudinal data of complex microbial communities experiencing perturbations. Machine learning on these data reveal patterns consistent with existing biological knowledge, supporting the validity of the approach. MDPbiomeGEM could save research resources by optimizing sample collection in metagenomics studies through identification of "informative" scenarios/time-points, or by predicting optimal in-vitro culture formulations for generating performant synthetic microbial communities. Finally, MDPbiomeGEM outputs include detailed information about the metabolic state of the community, which can be used to further interpret the impact of perturbations, and potentially could be used to predict novel metabolic biomarkers of a microbiome's state.

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Identifying biases and their potential solutions in human microbiome studies

Microbiome ◽

10.1186/s40168-021-01059-0 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Jacob T. Nearing ◽

André M. Comeau ◽

Morgan G. I. Langille

Keyword(s):

Microbial Communities ◽

Human Body ◽

Human Microbiome ◽

Sample Collection ◽

Sequencing Technology ◽

Microbial Composition ◽

Significant Bias ◽

Typical Sequence ◽

Entire Experiment ◽

The Impact

AbstractAdvances in DNA sequencing technology have vastly improved the ability of researchers to explore the microbial inhabitants of the human body. Unfortunately, while these studies have uncovered the importance of these microbial communities to our health, they often do not result in similar findings. One possible reason for the disagreement in these results is due to the multitude of systemic biases that are introduced during sequence-based microbiome studies. These biases begin with sample collection and continue to be introduced throughout the entire experiment leading to an observed community that is significantly altered from the true underlying microbial composition. In this review, we will highlight the various steps in typical sequence-based human microbiome studies where significant bias can be introduced, and we will review the current efforts within the field that aim to reduce the impact of these biases.

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The Upper Airway Microbiota, Environmental Exposures, Inflammation, and Disease

Medicina ◽

10.3390/medicina57080823 ◽

2021 ◽

Vol 57 (8) ◽

pp. 823

Author(s):

Ziyad Elgamal ◽

Pratyush Singh ◽

Patrick Geraghty

Keyword(s):

Upper Airway ◽

Environmental Exposures ◽

Microbial Composition ◽

Upper Airways ◽

Airborne Pollutants ◽

Host Interactions ◽

Microbial Profile ◽

And Function ◽

Community Segregation ◽

The Impact

Along with playing vital roles in pathogen exclusion and immune system priming, the upper airways (UAs) and their microbiota are essential for myriad physiological functions such as conditioning and transferring inhaled air. Dysbiosis, a microbial imbalance, is linked with various diseases and significantly impedes the quality of one’s life. Daily inhaled exposures and/or underlying conditions contribute to adverse changes to the UA microbiota. Such variations in the microbial community exacerbate UA and pulmonary disorders via modulating inflammatory and immune pathways. Hence, exploring the UA microbiota’s role in maintaining homeostasis is imperative. The microbial composition and subsequent relationship with airborne exposures, inflammation, and disease are crucial for strategizing innovating UA diagnostics and therapeutics. The development of a healthy UA microbiota early in life contributes to normal respiratory development and function in the succeeding years. Although different UA cavities present a unique microbial profile, geriatrics have similar microbes across their UAs. This lost community segregation may contribute to inflammation and disease, as it stimulates disadvantageous microbial–microbial and microbial–host interactions. Varying inflammatory profiles are associated with specific microbial compositions, while the same is true for many disease conditions and environmental exposures. A shift in the microbial composition is also detected upon the administration of numerous therapeutics, highlighting other beneficial and adverse side effects. This review examines the role of the UA microbiota in achieving homeostasis, and the impact on the UAs of environmental airborne pollutants, inflammation, and disease.

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Mass-immigration determines the assembly of activated sludge microbial communities

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2021589118 ◽

2021 ◽

Vol 118 (27) ◽

pp. e2021589118

Author(s):

Giulia Dottorini ◽

Thomas Yssing Michaelsen ◽

Sergey Kucheryavskiy ◽

Kasper Skytte Andersen ◽

Jannie Munk Kristensen ◽

...

Keyword(s):

Activated Sludge ◽

Microbial Communities ◽

Abundant Species ◽

Partial Least Square ◽

Least Square ◽

Partial Least Square Regression ◽

Similar Process ◽

Microbial Composition ◽

Species Abundances ◽

The Impact

The assembly of bacterial communities in wastewater treatment plants (WWTPs) is affected by immigration via wastewater streams, but the impact and extent of bacterial immigrants are still unknown. Here, we quantify the effect of immigration at the species level in 11 Danish full-scale activated sludge (AS) plants. All plants have different source communities but have very similar process design, defining the same overall environmental growth conditions. The AS community composition in each plant was strongly reflected by the corresponding influent wastewater (IWW) microbial composition. Most species in AS across the plants were detected and quantified in the corresponding IWW, allowing us to identify their fate in the AS: growing, disappearing, or surviving. Most of the abundant species in IWW disappeared in AS, so their presence in the AS biomass was only due to continuous mass-immigration. In AS, most of the abundant growing species were present in the IWW at very low abundances. We predicted the AS species abundances from their abundance in IWW by using a partial least square regression model. Some species in AS were predicted by their own abundance in IWW, while others by multiple species abundances. Detailed analyses of functional guilds revealed different prediction patterns for different species. We show, in contrast to the present understanding, that the AS microbial communities were strongly controlled by the IWW source community and could be quantitatively predicted by taking into account immigration. This highlights a need to revise the way we understand, design, and manage the microbial communities in WWTPs.

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