The Bowman Lab

Congrats to Avishek Dutta for his new paper “Detection of sulfate-reducing bacteria as an indicator for successful mitigation of sulfide production” currently available as an early view in Applied and Environmental Microbiology. This was intended to be the second of two papers on a complex experiment that we participated in with BP Biosciences, but the trials and tribulations of peer review led this to be the first. We’re pretty excited about it.

Here’s the quick background. When microbes run out of oxygen the community turns to alternate electron acceptors through anaerobic respiration. One of these is sulfate, which anaerobic respiration reduces to hydrogen sulfide. In addition to smelling bad hydrogen sulfide is pretty reactive and forms sulfuric acid when dissolved in water. For industrial processes this is a problem. Sulfide can destroy products, inhibit desired reactions, and corrode pipes and equipment. To make matters worse, sulfate reducing bacteria (SRBs: those microbes that are capable of using sulfate as an alternate electron acceptor) can form tough biofilms that are hard to dislodge.

One way of dealing with undesired SRBs is to fight biology with biology and add a more preferential electron acceptor. Oxygen would of course work really well, but it typically isn’t feasible to implement oxygen injection on a really large scale. However, nitrate also works well. If nitrate is abundant nitrate reducing bacteria (NRBs) will outcompete SRBs for resources (e.g., labile carbon). Great! Now here’s the challenge… adding massive quantities of nitrate salts is expensive and likely has it’s own ecologically and environmental consequences. So we’d like to do this judiciously, adding just enough nitrate to the system to offset sulfate reduction. But how to know when you’ve added enough? In a really big system (like an oil field) the sulfide production can be happening very far from any possible sampling site so simply measuring the concentration of hydrogen sulfide doesn’t help much. But we can learn some useful things by monitoring the microbial community in the effluent.

The figure above is a schematic of the formation and decay of the biofilm before, during, and after mitigation. In our study the biofilm was presumed to be sulfidogenic and the mitigation strategy was addition of nitrate salts, but the concept applies equally well to any biofilm and any mitigation strategy. The trick – and this is one of those things that seems painfully obvious after the fact but not before – is that you’re looking for the thing you’re mitigating to appear in the effluent. Although this might seem to suggest increased abundance in the system, it actually represents decay of the biofilm and loss from the system. To take this a step further we used paprica to predict genes in the effluent and then identified anomalies in the abundance of genes involved in sulfate reduction. This anomalies provide specific markers of successful mitigation and a means to a general strategy for monitoring the effectiveness of mitigation.

Congratulations to Srishti Dasarathy for her first first-authored publication! Srishti’s paper “Multi-year Seasonal Trends in Sea Ice, Chlorophyll Concentration, and Marine Aerosol Optical Depth in the Bellingshausen Sea” is out in advance of print in JGR Atmospheres. This paper was a really long time in coming. For this study, Srishti made use of several different satellite products including measurements of marine aerosol optical depth (MOAD) derived from the CALIPSO satellite. We are not a remote sensing lab and Srishti doesn’t come from a remote sensing or physics background, so the learning curve was pretty steep. It took a couple of years, a lot of Matlab tutorials, and an internship with the CALIPSO team at NASA’s Langley Research Center just to crack the CALIPSO data and start testing hypotheses. Srishti’s main hypothesis was that MOAD would be positively correlated with ocean color and negatively correlated with sea ice, since phytoplankton are known to be a source of volatile organic compounds that can form aerosol particles. Confounding this is that sea spray – which like phytoplankton is associated with open water periods – is also a source of aerosols.

One challenge that we faced was that CALIPSO represents data with high spatial resolution along a 2D path or “curtain”, as shown above. The orbital geometry is such that not every point on the globe gets covered; the same curtains get sampled every 16 days. Thus, while spatial resolution is high along the curtain, it is poor orthogonal to the curtain, and temporal resolution is limited to 16 days. This makes it a bit challenging to capture signals associated with relatively ephemeral events (such as phytoplankton blooms).

To work around these limitations Srishti took a basin-scale view of the CALIPSO data and looked for large scale trends that would link CMOD with chlorophyll a or ice cover. This approach isn’t idea and glosses over a lot of interesting details, but it is nonetheless sufficient to reveal some interesting relationships. Most notably that MOAD and chlorophyll a are weakly but significantly correlated in a time-lagged fashion, with a delay of approximately 1 month yielded the strongest correlation. This makes sense, as the volatile organics compounds that link phytoplankton (and ice algal) communities to MAOD are thought to be maximally produced near the end of the phytoplankton bloom as the biomass starts to decay. In the near future new satellite missions like PACE and improved land/sea observing campaigns will allows us to get into the details a bit more, including direct observations of specific blooms and the time- and space-lagged MOAD response!

Last week PhD student Natalia Erazo and I were fortunate to get back into the field after a long pandemic hiatus.  Our mission was to collect mangrove propagules (essentially a detachable bud from which the mangrove seedling sprouts) from the Indian River Lagoon in Florida for an upcoming experiment on mangrove-microbe symbiosis.  Neither of us had worked in Florida before so we teamed up with Candy Feller, an emeritus scientist with the Smithsonian Marine Station in Ft. Pierce, FL.  Candy has been working on mangroves in Florida and around the world for decades and is extremely knowledgeable about the ecology of these systems.  She and husband Ray Feller allowed us to tag along as they checked on a few long-term experiments and study sites up and down the coast.

For those not familiar with Florida’s Atlantic coast, the Indian River Lagoon is a network of estuaries and barrier islands that stretch from north of Cape Canaveral to south of Port St. Lucie.  The barrier islands form a protected waterway that provides habitat for mangroves, manatees, and a variety of other species.  The Indian River Lagoon is home to quite a few people as well, and there are some issues associated with water quality. Nutrients from septic and sewage systems are cited as a cause of high phytoplankton loads and increasingly murky water, leading to a reduction in aquatic vegetation and increased manatee mortality.  Key landscape features in the Lagoon are also the result of human habitation.  For example, much of the mangrove habitat in the Ft. Pierce region exists within engineered mosquito abatement areas.  To reduce the number of mosquitos (currently a nuisance, but previously some did carry disease) berms were created around vast tracts of mangrove habitat.  These areas were then flooded, reducing the breeding success of mosquitos because they lay eggs on wet but not flooded soil. 

Unfortunately, mosquito abatement also killed the mangrove trees which, while salt tolerant and adapted to life in saturated soils, require tidal action to oxygenate the water.  Modern mosquito abatement efforts (while still energy and labor intensive) take this into account and mangroves are thriving in areas that were formerly stagnant abatement ponds.  This is a Good Thing for anyone who likes fish, crabs, shoreline stabilization, and any of the other services that mangroves are well known for providing.

A particularly interesting feature of the Indian River Lagoon is that it is oriented north to south at nearly the northernmost known extent of mangroves on the US Atlantic Coast.  This provides an excellent opportunity to study how mangroves are responding to changing climate.  It’s known that mangroves are extending their range to the north, but climate change is anything but linear, and the rise in atmospheric and sea surface temperatures are accompanied by instabilities and severe perturbations.  The most notable may be freezing events caused by deep intrusions of the now infamous polar vortex.  Such perturbations can have a bigger impact on landscape ecology than the background climate.  Mangroves are very much a tropical species but somewhat resistant to transient freeze events (at least more so than your average Florida orange tree).  How they respond physiologically to these and other stressors that they encounter in their northward progression remains to be seen.

Congrats to Avishek Dutta for his first publication in the Bowman Lab: Understanding Microbial Community Dynamics in Up-Flow Bioreactors to Improve Mitigation Strategies for Oil Souring. Avishek did a remarkable job of resurrecting a stagnant dataset and turning it into a compelling story.

What is oil souring anyway? When oil is extracted in a production field the pressure of the field drops over time. To keep the pressure up the oil company (or more accurately, the subsidiary of the subsidiary tasked with such things) pumps in water, which is frequently seawater. When the water comes back out through wells there are two options. The most economical thing is to release it back into the environment, which has obvious negative consequences for environmental health. Alternatively, the same water can be reused by pumping it back into the ground. The downside to this is that recycled well water typically induces the production of hydrogen sulfide by sulfate reducing bacteria. The hydrogen sulfide reacts with the oil (“souring” it) and creates its own set of environmental and occupational hazards.

The oil industry has spent quite a bit of effort trying to figure out how to mitigate the process of oil souring. A leading method is to introduce nitrate salts into the system to boost the growth of nitrate reducing bacteria. The nitrate reducers out compete the sulfate reducers for reduced carbon (such as volatile fatty acids) and induce other processes that further impeded sulfate reduction.

Although the basic concept is pretty simple the details of this competition between nitrate and sulfate reducers in oil field aquifers is not well understood. In this study Avishek leveraged samples from up-flow bioreactors, analogs of the oil field aquifer system, for 16S rRNA gene analysis of the bacterial and archaeal communities. The bioreactors are vessels filled with sand, seawater, and sources of bioavailable carbon (the oil itself is a source of carbon, but requires a specialized microbial community to degrade). Some of the bioreactors also contain oil. Water flows continually through the system and nitrate salts can be added at appropriate time-points. For this experiment the nitrate amendment (the mitigation or M phase) was halted (the rebound sulfidogenesis or SG phase) and then restarted (the rebound control or RC phase).

Lots of interesting things emerged from this relatively small-scale experiment. For one thing the oil and seawater samples are not that different from one another during mitigation. However, when the nitrate addition is stopped those two treatments start to diverge, with different sulfate reducing taxa present in each. This divergence (but not necessarily the microbial community) persists after the treatment ends. But not all microbial taxa responded to the rather extreme perturbation caused by the nitrate addition. Desulfobacula toluolica, for example, which should have been out-competed during mitigation, remained a significant member of the community.

We’re currently analyzing the results of a much larger bioreactor study that we expect will shed some new light on these processes, so stay tuned!

Postdoctoral researcher Jesse Wilson has a new paper titled Using empirical dynamic modeling to assess relationships between atmospheric trace gases and eukaryotic phytoplankton populations in coastal Southern California in press in the journal Marine Chemistry. This paper is the culmination of a nearly two year effort to bring together two long-term datasets collected at the Ellen Browning Scripps Memorial Pier: the Southern California Coastal Ocean Observing System (SCCOOS) phytoplankton count and the Advanced Global Atmospheric trace Gas Experiment (AGAGE). Both of these programs encompass many more sites than the Scripps Pier, but that’s the happy point of overlap. The SCCOOS phytoplankton count (augmented by the McGowan chlorophyll time-series) is part of an effort to track potential HAB-forming phytoplankton in Southern California. Twice weekly microscope counts are made of key phytoplankton taxa, and weekly measurements are made for chlorophyll a and nutrients. AGAGE is, as the name suggests, a global effort to monitor changes in atmospheric trace gases. They do this using high frequency measurements of key gases with GC-MS and a cryo-concentration system known as Medusa.

Our study was motivated by the need to better understand the contribution of different phytoplankton taxa to atmospheric trace gases. Many phytoplankton (and macroalgae) produce volatile organic compounds (e.g., DMS and isoprene) and other trace gases (e.g., carbonyl sulfide). Some of these gases have interesting functions in the atmosphere, such as the formation of secondary aerosols. Although there are many laboratory studies looking at trace gas production by phytoplankton in culture, environmental studies on this topic are usually limited in space and time by the duration of a single cruise or field campaign.

The temporal and spatial limitation of field campaigns is what makes long-term time-series efforts so valuable. For this study we had 9 years of overlapping data between SCCOOS and AGAGE. To analyze these data Jesse designed an approach based on Empirical Dynamic Modeling (EDM) and Convergent Cross Mapping (CCM). For good measure he also aggregated the available meteorological data using a self-organizing map (SOM). EDM and CCM are emerging techniques that can identify causal relationships between variables. The basic idea behind EDM is that a time-series can be described by its own time-lagged components. Given two time-series (say a trace gas and phytoplankton taxa), if the time-lagged components of one describe the other this is evidence of a causal relationship between the two. For a more in-depth treatment of EDM and CCM see this excellent tutorial on Hao Ye’s website.

Not surprisingly our all-vs-all approach to these datasets was a bit messy. A lot of this is due to the complexity of the natural environment and the spatial and temporal disconnect between the measurements. The phytoplankton counts are hyper-local, and reflect the very patchy nature of the marine environment, while the trace gas measurements are regional at best, as the atmosphere moves and mixes over great distances in only a few hours. Nonetheless we made the assumption that ecological observations at the pier are some reflection of conditions across a wider area, and that trace gas measurements do reflect some local influence. So there should be observable links between the two even if those links are muted.

I’m particularly excited about what we can do with these data in the future, when we have several years of molecular data. As part of the Scripps Ecological Observatory initiative we’re sequencing 16S and 18S rRNA genes from the same samples as the SCCOOS microscopy counts. We have around 2.5 years of data so far. Just a few more years until we have a molecular dataset as extensive as the count data analyzed here! The key difference will be in the breadth of that data, which will allow us to identify an order of magnitude more phytoplankton taxa than are counted.