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bacteria

Airborne Bacteria: A Hidden Regulator of Ocean Blooms

May 4, 2025 by Ella Scott

Context

Marine phytoplankton are microscopic algae integral to oceanic ecosystems and global biogeochemical cycles. They contribute significantly to the process of carbon displacement into the deep ocean and primary production, forming the foundation of the marine food web. However, these phytoplankton populations are vulnerable to various environmental and biological stressors, including temperature changes, nutrient availability, and pathogen infections. When a phytoplankton bloom collapses, bacteria consume their organic matter, a process that requires oxygen. The decay of the bloom and oxygen levels can deplete oxygen and lead to “dead zones” that can suffocate marine life (US EPA, 2013). Researching the components of bloom dynamics enables us to better understand their interactions as a foundation of the food web and regulator of oxygen levels.

 

Fig 1. Demise of a phytoplankton bloom over the course of a handful of days (Demise of a Phytoplankton Bloom, 2014)

One of the most abundant bloom-forming phytoplankton is Gephyrocapsa Huxley, a species of coccolithophore, a type of phytoplankton covered in calcium carbonate plates known for its widespread blooms in the ocean. While viral infections have long been recognized as a primary cause of phytoplankton bloom collapse, researchers have questioned whether bacteria could be another potential source of pathogenicity. Recent research regarding G. huxleyi phytoplankton suggests so.

 

Fig 2. Calcium carbonate plating on a coccolithophore phytoplankton (Briggs, 2021)

 

This groundbreaking study by Lang-Yona et al. investigated whether airborne bacteria could infect G. huxleyi blooms and be an explanation for bloom collapses. This research aimed to analyze atmospheric bacteria as an ecological regulator of phytoplankton populations, an often disregarded consideration in the dynamics of oceanic microbial interactions and climate models. Understanding these interactions is critical for predicting changes in marine ecosystems and their impact on global carbon cycles.

Methods of the Study

To explore whether airborne bacteria play a role in controlling phytoplankton populations, researchers collected air and water samples above a bloom of G. huxleyi in the North Atlantic. They conducted this work aboard the research vessel R/V Tara, using specialized instruments to capture airborne bacteria at different heights. These included high-volume air samplers and devices called cascade impactors, which were set up at different points on the ship, including the deck and mast. This setup allowed them to collect bacteria from various altitudes and better understand how microbes travel through the air (Lang-Yona et al., 2024)

Back in the lab, the team introduced the airborne bacteria into cultures of G. huxleyi to see what would happen. They carefully watched for signs of infection, such as a drop in the algae’s natural fluorescence (a sign they were losing their ability to photosynthesize), increased debris in the water (indicating cell death), and visible damage to the algal cells. When signs of infection appeared, they filtered out the bacteria from the cultures and grew them on a nutrient-rich surface called Marine Agar 2216. This step helped them isolate specific bacterial strains. To confirm that these bacteria were truly responsible for the infection, they then reintroduced them to fresh G. huxleyi cultures and checked whether the same effects occurred.

To track how the bacteria and algae interacted over time, researchers used a technique called flow cytometry. This method shines a laser through tiny droplets of water containing cells, measuring their size, shape, and natural glow. It allows scientists to quickly count how many algae and bacteria are present and determine how the infection is progressing.

Finally, they identified the bacteria using genetic sequencing and measured their presence in air and water samples with a technique called quantitative PCR (qPCR). This method detects and counts bacterial DNA, helping researchers understand how common these airborne microbes are in different environments.

Results of the Study and Implications

The study identified the airborne bacterium Roseovarius nubinhibens as a key bacteria capable of infecting and contributing to the collapse of G. huxleyi blooms. This bacterium was found to remain viable after atmospheric transport and effectively infects phytoplankton upon reaching ocean waters. The ability of R. nubinhibens to survive and remain pathogenic after airborne dispersal suggests a more dynamic role for bacteria in ocean-atmosphere interactions than previously recognized.

The ability of bacteria to be transported via wind patterns indicates a geologically vast and major mechanism that has previously been overlooked. The findings suggest that in addition to viral infections, bacterial pathogens may serve as natural regulators of phytoplankton populations, influencing bloom duration and oceanic carbon cycling. This discovery is particularly significant because phytoplankton blooms play a critical role in the global carbon cycle by taking carbon from the atmosphere, and upon death, sinking to the deep ocean where the carbon is stored. If bacterial infections contribute to bloom collapse and can be dispersed so vastly,  they may influence carbon fluxes in ways that need to be accounted for in climate models.

Previously, viral infections were considered the primary biological driver of bloom decline, but this study introduces airborne bacteria as an additional player in phytoplankton mortality. This raises important questions about how environmental factors such as wind patterns and ocean currents influence bacterial dispersal. Additionally, climate change may impact the spread of airborne pathogens, potentially altering bloom dynamics in unforeseen ways. A warming climate and shifting atmospheric circulation patterns could enhance or suppress the spread of algicidal bacteria, with cascading effects on marine ecosystems.

Furthermore, this research highlights the complexity of microbial interactions in the ocean. Many bacterial species exhibit “Jekyll-and-Hyde” dynamics, shifting between mutualism and pathogenicity depending on environmental conditions and the physiological state of their algal hosts. In the case of R. nubinhibens, it is possible that under certain conditions, it exists in a neutral or even beneficial relationship with G. huxleyi, but when environmental factors such as nutrient depletion or increased bacterial density trigger a shift, it becomes pathogenic. The study’s infection experiments demonstrated that R. nubinhibens could rapidly induce algal demise, suggesting a transition from a benign to an algicidal state. This aligns with previous findings that some marine bacteria can switch between cooperative and harmful interactions based on chemical signaling. Understanding these complex interactions is essential for developing a more accurate picture of microbial regulation in marine environments, as such shifts can significantly alter bloom dynamics and oceanic food webs.

This study provides new insight into the role of airborne bacteria in regulating marine phytoplankton populations, demonstrating that Roseovarius nubinhibens can contribute to G. huxleyi bloom collapse. These findings expand our understanding of ocean-atmosphere microbial interactions and introduce airborne bacteria as an important but previously overlooked factor in bloom dynamics. Incorporating airborne bacterial processes into ecological and climate models will be crucial for accurately predicting future oceanic changes. Further research is necessary to determine whether other phytoplankton species are similarly affected and how environmental shifts may influence the prevalence and impact of airborne bacterial infections on marine ecosystems. Understanding these dynamics is essential for assessing ocean health and resilience in a rapidly changing climate.

 

References:

Briggs, G. M. (2021). Coccolithophores, photosynthetic unicellular algae. https://milnepublishing.geneseo.edu/botany/chapter/emiliana-huxleyi/

Demise of a Phytoplankton Bloom. (2014, November 26). [Text.Article]. NASA Earth Observatory. https://earthobservatory.nasa.gov/images/84797/demise-of-a-phytoplankton-bloom

Lang-Yona, N., Flores, J. M., Nir-Zadock, T. S., Nussbaum, I., Koren, I., & Vardi, A. (2024). Impact of airborne algicidal bacteria on marine phytoplankton blooms. The ISME Journal, 18(1), wrae016. https://doi.org/10.1093/ismejo/wrae016

US EPA, O. (2013, March 12). The Effects: Dead Zones and Harmful Algal Blooms [Overviews and Factsheets]. https://www.epa.gov/nutrientpollution/effects-dead-zones-and-harmful-algal-blooms

 

Filed Under: Biology, Environmental Science and EOS Tagged With: bacteria, phytoplankton

The Battle of the Medications: The Connection Between Antidepressants and Antibiotic Resistance in Bacteria

April 2, 2023 by Sam Koegler

         The consumption of antidepressant medications has skyrocketed in recent decades, reaching more than 337 million prescriptions written in 2016 in the United States alone (Wang et. al. 2019). For many individuals, these drugs are critical to maintaining everyday health as they treat many life-threatening psychiatric disorders. While their exact mechanisms differ, these medications travel in the bloodstream to the brain where they are able to influence the release of chemicals known as neurotransmitters that generate emotional states. However, while their intended target is the brain, these drugs continue to circulate throughout the body, thereby interacting with other organs and structures (Wang et. al. 2019).

         In their 2019 study, researchers led by Iva Lukic used data indicating the presence of antidepressants in the digestive tract to investigate the effect of these medications on the gut microbiome. After treating mice with different types of antidepressants, the team noticed a change in the types of bacteria present within the gut when compared to controls (Lukic et. al. 2019). This discovery that antidepressants could impact the types of bacteria present within the body ultimately led researcher Jianhua Guo to question the additional effects that these medications could have on bacteria. As antibiotics have also been shown to affect the composition of the gut microbiome, Guo began by investigating if the antidepressant fluoxetine could help Escherichia coli cells survive in the presence of various antibiotics. After finding that exposure to this medication did increase E. coli’s resistance to antibiotic treatments, Guo decided to expand his hypothesis to examine the overall connection of antidepressant usage with antibiotic resistance in bacteria.

        Collaborating with researchers Zue Wang and Zhigang Yue, Guo’s lab began by choosing five major types of antidepressant medications: sertraline, escitalopram, bupropion, duloxetine, and agomelatine. These medications differ in the ways that they prevent the reuptake of serotonin and norepinephrine in the brain, thereby allowing the researchers to examine the effects of various types of antidepressants that may be prescribed to patients. Then, E. coli bacteria were added to media containing varying concentrations of these five antidepressants. Once these cells were treated with antidepressants, the researchers began to test the cells’ resistance against antibiotics. In order to accurately reflect antibiotic use in the real world, the tested antibiotics covered the six main categories of antibiotic medications available on the market. The antidepressant-treated bacteria were then swabbed onto plates containing one of the tested antibiotics to observe cell growth. Based on the growth present on these plates, the researchers were able to estimate the incidence rate of bacterial resistance of E. coli bacteria treated with different antidepressants.

         Through this experiment, the lab observed that E. coli cells grown in sertraline and duloxetine, two antidepressants that inhibit the reuptake of serotonin, exhibited the greatest number of resistant cells across all the tested antibiotics (fig. 1). They also noted that E. coli cells exhibiting resistance to one antibiotic often demonstrate some level of resistance to other antibiotics as well. After detecting a correlation between antibiotic-resistance development and exposure to antidepressants, the lab tested the concentration dependence of this effect. While lowering the concentration of antidepressants seemed to decrease the amount of resistant E. coli cells, resistant cells continued to appear on the plates over time, suggesting that lowering antidepressant dosages only prolongs the process of developing antibiotic resistance.

Figure 1: These graphs showcase the change in the number of antibiotic-resistant E. coli cells after exposure to antidepressants over sixty days. The title of each graph indicates the tested antibiotic while the colored trend lines on the graph represent one of the five, tested antidepressants. On the y-axis of each graph, the fold change measurement is used to describe the change in the number of resistant cells that develop over time. As demonstrated by the purple and yellow trend lines, duloxetine and sertraline are associated with the greatest development of resistant cells to each of the four represented antibiotics. (Adapted from Wang et. al. 2019)

         After analyzing this data, the researchers were confronted with a question: what about anti-depressants led to the development of antibiotic resistance in bacteria? To examine this question, the lab used flow cytometry to examine what was happening within the bacterial cells. This lab technique uses a fluorescent dye that binds to specific intercellular target molecules, thereby allowing these components to be visualized. After applying this dye to resistant cells grown on the antibiotic agar plates, the researchers noticed the presence of specific oxygen compounds known as reactive oxygen species (ROS). Unstable ROS bind to other molecules within a cell, disrupting normal functioning and causing stress. Elevated cellular stress levels have been shown to induce the transcription of specific genes in bacteria that produce proteins to help return the cell to normal functioning (Wang et. al. 2019).

         ROS molecules have been shown to induce the production of efflux pumps in bacteria, leading the lab to investigate if these structures were involved in the antibiotic resistance of E. coli cells. Efflux pumps are structures in the cell membrane of a protein that pump harmful substances out of the cell. The lab mapped the genome to look for activated genes associated with the production of this protein. According to the computer model, more DNA regions in resistance bacteria coding for efflux pumps were active than in the Wild Type. The researchers then concluded that efflux pumps were being produced in response to antidepressant exposure. These additional efflux pumps removed antibiotic molecules in resistant E. coli, thereby allowing them to survive in the presence of lethal drugs.

         The antibiotic resistance uncovered in this study was significant and persistent. Even one day of exposure to antidepressants like sertraline and duloxetine led to the presence of resistant cells. Furthermore, the team demonstrated that these antibiotic-resistant capabilities often do not disappear over time; rather, they are inherited between generations of bacteria, leading to the proliferation of dangerous cells unsusceptible to available treatments. The next logical step towards validating the connection between antidepressants and antibiotic resistance would include studying the gut microbiomes of patients taking anti-depressants to look for antibiotic-resistant bacteria.

         This study reveals a novel issue that must be attended to.  In 2019, 1.27 million deaths worldwide could be directly attributed to antibiotic-resistant microbes, a number expected to grow to 10 million by the year 2050 (O’Neill 2023). These “superbugs” present a dangerously growing reality. If the correlation between antidepressant use and antibiotic resistance is left uninvestigated, superbugs will likely continue to develop even as antibiotic use is regulated and monitored to battle them. Only by taking this connection seriously will researchers be able to fully grapple with and battle the growing antibiotic resistance trends, thereby preventing common infections from becoming death sentences. 

 Sources:

CDC. (2022, July 15). The biggest antibiotic-resistant threats in the U.S. Centers for Disease Control and Prevention. https://www.cdc.gov/drugresistance/biggest-threats.html

Drew, L. (2023). How antidepressants help bacteria resist antibiotics. Nature. https://doi.org/10.1038/d41586-023-00186-y

Jin, M., Lu, J., Chen, Z., Nguyen, S. H., Mao, L., Li, J., Yuan, Z., & Guo, J. (2018). Antidepressant fluoxetine induces multiple antibiotics resistance in Escherichia coli via ROS-mediated mutagenesis. Environment International, 120, 421–430. https://doi.org/10.1016/j.envint.2018.07.046 

Lukić, I., Getselter, D., Ziv, O., Oron, O., Reuveni, E., Koren, O., & Elliott, E. (2019). Antidepressants affect gut microbiota and Ruminococcus flavefaciens is able to abolish their effects on depressive-like behavior. Translational Psychiatry, 9(1), 1–16. https://doi.org/10.1038/s41398-019-0466-x

O’Neill, J. (Ed.). (2016). Tackling Drug-Resistant Infections Globally: Final Report and Recommendations. The Review on Antimicrobial Resistance. https://amr-review.org/sites/default/files/160518_Final%20paper_with%20cover.pdf

Thompson, T. (2022). The staggering death toll of drug-resistant bacteria. Nature. https://doi.org/10.1038/d41586-022-00228-x

Wang, Y., Yu, Z., Ding, P., Lu, J., Mao, L., Ngiam, L., Yuan, Z., Engelstädter, J., Schembri, M. A., & Guo, J. (2023). Antidepressants can induce mutation and enhance persistence toward multiple antibiotics. Proceedings of the National Academy of Sciences, 120(5), e2208344120. https://doi.org/10.1073/pnas.2208344120

Filed Under: Biology, Chemistry and Biochemistry, Science Tagged With: antibiotics, antidepressants, bacteria

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