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\begin{document}

\title{Top-down engineering of oil field microbiomes to limit souring and
control oil composition during extraction operations}



\author[1]{Ethan Hillman}%
\author[1]{Louis Caceres Martinez}%
\author[1]{Gozdem Kilaz}%
\author[2]{Kevin Solomon}%
\affil[1]{Affiliation not available}%
\affil[2]{University of Delaware}%


\vspace{-1em}



  
  \date{May 18, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Microbial processes sour oil, corrode equipment, and degrade
hydrocarbons at an annual global cost to the oil and gas industry of
nearly \$2 billion. However, top-down control of these microbial
processes can reduce their damage and enhance oil recovery. Here, we
screened microbial communities from five oil wells in the Illinois basin
and evaluated nutrient injection strategies to control metabolism and
community composition. Molasses and molybdate supplementation stimulated
significant gas and organic acid production while completely suppressing
corrosive H2S formation in samples from two wells. These changes were
accompanied with significant shaping of the microbiome community.
Simulations of field operations via a lab-scale mini-coreflood validated
that oil well microbiomes can be engineered to also shape oil
hydrocarbon composition in situ. These pilot studies validate the
potential of economical and sustainable top-down microbiome engineering
to control microbes in oil extraction and enhance the economic viability
of oil recovery.%
\end{abstract}%



\sloppy


Top-down engineering of oil field microbiomes to limit souring and
control oil composition during extraction operations

Ethan T. Hillman\selectlanguage{ngerman}\textsuperscript{1,2¥}, Louis Edwards
Caceres-Martinez\textsuperscript{3}, Gozdem Kilaz\textsuperscript{3},
and Kevin V. Solomon\selectlanguage{english}\textsuperscript{1,2,4++}*

\textsuperscript{1} Department of Agricultural and Biological
Engineering, Purdue University, West Lafayette, IN 47907

\textsuperscript{2} Purdue University Interdisciplinary Life Sciences,
Purdue University, West Lafayette, IN 47907

\textsuperscript{3} School of Engineering Technology, Fuel Laboratory of
Renewable Energy (FLORE), Purdue University, West Lafayette, IN 47907

\textsuperscript{4} Department of Chemical \& Biomolecular Engineering,
University of Delaware, Newark, DE 19716

\textsuperscript{Y=} Present Address: Department of Internal Medicine,
University of Michigan, Ann Arbor, MI 48109, USA

\selectlanguage{english}\textsuperscript{++} Present address: Department of Chemical \&
Biomolecular Engineering, University of Delaware, Newark, DE 19716

\textbf{*} Correspondence: kvs@udel.edu



\textbf{Abstract}

Microbial processes sour oil, corrode equipment, and degrade
hydrocarbons at an annual global cost to the oil and gas industry of
nearly \$2 billion. However, top-down control of these microbial
processes can reduce their damage and enhance oil recovery. Here, we
screened microbial communities from five oil wells in the Illinois basin
and evaluated nutrient injection strategies to control metabolism and
community composition. Molasses and molybdate supplementation stimulated
significant gas and organic acid production while completely suppressing
corrosive H\textsubscript{2}S formation in samples from two wells. These
changes were accompanied with significant shaping of the microbiome
community. Simulations of field operations via a lab-scale
mini-coreflood validated that oil well microbiomes can be engineered to
also shape oil hydrocarbon composition \emph{in situ} . These pilot
studies validate the potential of economical and sustainable top-down
microbiome engineering to control microbes in oil extraction and enhance
the economic viability of oil recovery.

\emph{Topical Heading:} Biomolecular Engineering, Bioengineering,
Biochemicals, Biofuels, and Food

\emph{Keywords:} Microbial enhanced oil recovery, top-down microbiome
engineering, miniature coreflood, cultivation screening, comprehensive
two-dimensional gas chromatography

\textbf{Background:}

Fossil fuels are likely to remain a significant energy source for at
least the next 30 years as economies transition globally towards more
renewable energy sources.\textsuperscript{1--3} Extracting trapped oil
from aging wells can not only increase the overall production of
existing wells but also minimize the need to drill new wells and,
ultimately, decrease the cost of extracting oil from existing
reservoirs. Expensive polymer and/or surfactant/polymer formulations
that require large amounts of funding and research effort are used to
extract oil not recovered by primary extraction
techniques.\textsuperscript{4--6} Additionally, native and exogenous
microbes have been harnessed as a more cost-effective alternative for
secondary and tertiary oil recovery -- an approach coined microbial
enhanced oil recovery (MEOR).\textsuperscript{7,8} Microbial activity in
oil wells, however, can either be harnessed to benefit the oil recovery
process or be disruptive and hinder the process. Microbial metabolic
products can liberate trapped oil: produced gases displace immobile oil,
organic acids dissolve carbonaceous deposits and increase well
permeability, solvents dissolve and mobilize large hydrocarbons from the
pores, and biosurfactants act as emulsifiers.\textsuperscript{7,9} On
the other hand, microbes can also degrade and sour oil, and produce
metabolites that corrode the well casing, flowlines, and pipelines.
Globally, pipeline corrosion alone can result in nearly \$2 billion
dollars (USD) of damage and loss each year.\textsuperscript{7,10} This
corrosion is due primarily to oxidation of microbially-produced hydrogen
sulfide (H\textsubscript{2}S) to sulfuric
acid.\textsuperscript{10,11}Engineering the composition and metabolism
of oil well microbial communities promises to enhance the productivity
and economic viability of oil extraction operations.

Engineering microbiomes has emerged as a sustainable approach to develop
processes for a number of industries from health and nutrition to
agriculture and fuels.\textsuperscript{12--14} To engineer microbial
communities, there are two common general approaches: bottom-up and
top-down microbiome engineering.\textsuperscript{15} Generally,
bottom-up microbiome engineering pertains to constructing communities of
microbial species and strains with desired attributes and synergies to
carry out a task or set of tasks. In MEOR, bottom-up approaches often
focus on biofilm or surfactant production via communities centered
around natural and/or engineered strains of \emph{Pseudomonas}
,\emph{Bacillus} , \emph{and Enterobacter} which are able to extract up
to 26\% of the additional trapped oil\emph{.}
\textsuperscript{7,16--19}However, the ecology of engineering bottom-up
communities is very complex and developing stable communities that
colonize a natural, fluid ecosystem, like that of the oil well
microbiome, is exceedingly difficult.\textsuperscript{20} Strains may
fail to colonize because they do not fill a particular ecological niche
in the community and can change the native microbiome composition in
unpredicted and uncontrollable ways.\textsuperscript{21} Emerging
bottom-up strategies to overcome this challenge such as artificial
syntrophy where microbes exchange metabolites for mutual survival are
difficult to develop and can fail catastrophically if a single species
is lost due to unanticipated competition with native
microbes.\textsuperscript{22,23}Lastly, strains used in bottom-up
approaches are often genetically engineered, which raises both
ecological concerns and creates regulatory burden related to the
introduction of genetically modified organisms in the
environment.\textsuperscript{14,24}

In contrast, top-down microbiome engineering manipulates environmental
factors such as nutrients, pH, temperature, and ionic strength to tailor
a native community for a desired outcome or
task.\textsuperscript{15}This strategy does not require any bacterial
species to be introduced into the community or colonize a new
environment, but instead leverages the present
microbes.\textsuperscript{20,25} Tuning environmental factors, or
synthetic ecology, is typically more cost-effective and is easily
testable in controlled parallel
experiments.\textsuperscript{26}Similarly, top-down MEOR is often much
more economical than the synthetic polymers used for standard secondary
and tertiary oil recovery.\textsuperscript{27,28} However, not all
microbiomes will respond to changes in these environmental factors and
they are likely to have different responses depending on the composition
of microbes and environmental factors surrounding
them.\textsuperscript{29} Up to 89\% of MEOR trials have successfully
produced additional oil but to varying degrees.\textsuperscript{29,30}
Therefore, top-down microbiome engineering conditions must be rapidly
screened \emph{in vitro} in a high-throughput, cost-effective manner to
identify both candidate oil well communities and optimal MEOR
intervention conditions. Taken together, the facts that top-down
engineering approaches are cost-effective, can be rapidly screened, and
do not require scientific ecological barriers suggest that it is an
attractive strategy for developing MEOR formulations for field trials.

In this study, we use top-down engineering strategies to screen wells
and optimize oil extraction operations for the Illinois basin via MEOR.
Through \emph{in vitro} cultivation, we identified candidate wells that
would be responsive to MEOR intervention and characterized the response
of their microbial community as a function of specific nutrient
supplementation. We established that simple molasses injection coupled
with inorganic salt solutions could be used to stimulate microbial
activity that reduced H\textsubscript{2}S production and stimulated
desired gas and organic acid production. Simulation of field recovery
operations via a miniature coreflood experiment confirmed the ability of
these interventions to reduce oil souring and modify the specific
hydrocarbon composition of produced oil. Ultimately, this work
demonstrates that top-down microbiome engineering strategies can
significantly benefit oil recovery operations while improving economic
and environmental sustainability.

\textbf{Results and Discussion} :

Wells in the same basin have unique properties and microbial communities

Wells at mesophilic temperatures and moderate depths {[}1500-3000 ft,
457-914 m{]} are promising sites for successful MEOR
applications\textsuperscript{29--31} within the Illinois basin. We
selected five such wells from this basin that were all approximately 27
\selectlanguage{english}@C (80 @\selectlanguage{english}F) in order to hold the temperature constant between trials and
simplify cross-well comparisons (Table 1). The wells had depths of
1336-2258 ft (407-688 m) while the pH remained fairly neutral (pH 6 --
7). DNA was extracted from the produced water (effluent) of each well to
assess the native microbial community composition via 16S rRNA gene
profiling (\textbf{Supplemental Figure 1} ). We found that each well had
a distinct microbial composition with various sulfur-reducing
(H\textsubscript{2}S-producing) and
MEOR-relevant\textsuperscript{9,19,31} archaea and bacteria. Common
bacteria phyla include Proteobacteria, Bacteroidota, Firmicutes,
Synergistota, Spirochaetota, Verrucomicrobiota, Desulfobacterota and
Campilobacterota, of which the latter three are prominent
sulfur-metabolizing bacteria.\textsuperscript{32--35} These populations
were distinct from others in the literature,\textsuperscript{36,37} a
finding that is not unexpected given that each community is driven by
different environmental conditions such as temperature, salinity, pH,
nutrient availability, and oil gravity among other
factors.\textsuperscript{19} However, there is no known correlation
between native microbial community and MEOR success. Therefore, we
pursued \emph{in vitro} functional screening to evaluate candidate wells
for MEOR top-down microbiome engineering.

\textbf{Table 1} \textbf{Characteristics of candidate wells from the
Illinois basin}\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Well ID & State & Depth (ft) & Temp (@\selectlanguage{english}C) & pH\tabularnewline
\midrule
\endhead
B & IL & 1597-1626 & 27 & 7\tabularnewline
C & IL & 1585-1590 & 27 & 6.5\tabularnewline
D & IL & 1336-1343 & 27 & 7\tabularnewline
G & IL & 1620-1626 & 27 & 6\tabularnewline
S & IN & 2226-2258 & 27 & 6.5\tabularnewline
\bottomrule
\end{longtable}

In vitro screening identifies candidate wells and nutrient profiles for
MEOR

In order to evaluate which candidate wells would respond to nutrient
supplementation, \emph{in vitro} microcosms were created in an anaerobic
environment using a mixture of nine-parts oil well effluent and one-part
crude nutrient source stock {[}40\% corn syrup or molasses{]}. In
addition to culture optical density, we monitored the microbial
production of gases and organic acids that may enhance oil recovery by
tracking microcosm headspace pressure and pH, respectively, over the
course of 1 week (\textbf{Figure 1} ). While two of the wells (Wells B,
C,) did not respond to nutrient supplementation, microcosms from Well D
and G responded to both molasses and corn syrup supplementation. One
replicate from Well S demonstrated a moderate gas production on molasses
while all replicates showed a drop in pH. The responses of Wells D and G
were more reproducible, generating up to 13 PSI of pressure as well as a
2 pH-unit-drop in the culture pH. These findings are consistent with
other biostimulation\textsuperscript{36} results and further supports
the notion that not all wells respond to nutrient supplementation and
may respond in different ways (e.g., more acids than gases or vice
versa). Overall, cultures grown on molasses, a commonly used nutrient
source in MEOR,\textsuperscript{9} produced more pressure and had larger
pH drops suggesting that it had stronger microbe-activating potential
for MEOR. Therefore, molasses was chosen as the crude nutrient source
for our future screening efforts. Bacteria from the orders
Lactobacillales, Enterobacterales, Bacteroidales, and Campylobacterales
dominated the molasses microcosms from Well D and G comprising [?] 96\% of
the total reads (\textbf{Supplemental Figure 2} ). These bacteria are
collectively known to produce CO\textsubscript{2} and
H\textsubscript{2}gases as well as acetic, lactic, butyric, and
propionic acids that have roles in MEOR\textsuperscript{9,19,31}. The
increasing pressure and drop in pH imply that the production of some or
all of these was stimulated by nutrient supplementation. However,
production of H\textsubscript{2}S by Campylobacteria, such as
\emph{Sulfospirillium} and\emph{Malaciobacter,} \textsuperscript{33,38}
may have also been stimulated. While our results indicated at least two
responsive wells for MEOR intervention, successful MEOR biostimulation
requires limited production of corrosive H\textsubscript{2}S while also
increasing the gas, acid, and/or solvent production for oil recovery.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1} -- \textbf{Carbon source screening of well
candidates.} A) Accumulated pressure generated from microcosms over the
7-day span. B) Change in pH in microcosms over the 7-day experiment.
Carbon sources screens: corn syrup (solid bars) and molasses (stripped
bars). Error bars represent standard deviation, n=3.

Micronutrient supplements control metabolism and shape microbiome
composition in vitro

To investigate if micronutrients can modulate the microbiome composition
of the microcosms for top-down engineering in MEOR, our \emph{in
vitro}screening system was used to track metabolism and community
composition under various micronutrient supplements. \emph{In vitro}
screening focused on Well D because it was one of the two most
responsive wells. Moreover, Well G was heavily dominated by one genus
(\emph{Malaciobacter} , class Campylobacteria) (\textbf{Supplemental
Figure 1} ), with less microbial diversity to adapt to the micronutrient
conditions. Again, Well D was stimulated with molasses and supplemented
with a variety of micronutrients including chloride (NaCl and KCl),
phosphate (K\textsubscript{2}HPO\textsubscript{3} and
KH\textsubscript{2}PO\textsubscript{3}), nitrate (KNO\textsubscript{3}),
molybdate (Na\textsubscript{2}MoO\textsubscript{4}), and a combination
of both nitrate and molybdate. Chloride salts were used as a negative
control while phosphate salts were tested as a phosphate source, which
have been added in other MEOR studies.\textsuperscript{9,31,36} To
reduce sulfate reduction, nitrate and molybdate salts were tested.
Nitrate is a competing electron acceptor in place of sulfate in several
sulfur-reducing bacteria,\textsuperscript{11,39--41} while molybdate has
been shown to inhibit H\textsubscript{2}S generation in different
aqueous and marine contexts.\textsuperscript{40--43}

Gas and organic acid production varied strongly as a function of
micronutrient supplementation (\textbf{Figure 2A, Supplemental Figure 3}
). Nitrate- and molybdate-supplemented communities from Well D produced
significant amounts of pressure. The cumulative effects of combination
treatments were additive, resulting in the most observed pressure
generation. Similarly, nitrate dropped the pH of the culture the most
(to a pH \textasciitilde{}4) where the molybdate treatment had a
slightly smaller effect (Supplemental Figure 3B). These results suggest
that chloride and phosphorous do not alter microbial metabolism in the
microcosms and that nitrate best stimulated the production of gases and
acids for MEOR. There was some additional benefit to adding molybdate in
combination with nitrate as it generated the most gas and one of the
larger pH changes. Because only select microbes can convert nitrate into
N\textsubscript{2} and/or ammonia, or use it as a nitrogen source for
synthesis of DNA and amino acids, supplemented nitrate will confer a
competitive advantage to specific microbes in an otherwise
nitrogen-limited environment such as an oil well. In turn, we expect
that the differences in the metabolic outputs (\textbf{Figure 2A} ) are
reflective of the differences in the microbial community composition as
a result of the added compounds.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2 -- Non-essential nutrients stimulate metabolism and
manipulate the microbiome composition.} A) Pressure generated in
microcosms from Well D \& G when treated with various nutrient
supplements; T-tests performed with respect to None. B) Diversity score
(Pielou's evenness) of microcosms after treatment with micronutrients
(days 3, 4, 5 and 7). C) Unweighted Unifrac PCoA plot of Well D
microcosms after micronutrient supplementation; shapes represent days,
colors indicate treatment group: spheres = day 1, diamonds = day 3, star
= day 4, rings = day 5, cones = day 7. Error bars represent standard
deviation, n=3; * = p \textless{} 0.05, ** = p \textless{} 0.005, and
*** = p \textless{} 0.001.

While the fate of nitrate is ultimately determined by the microbial
community, we found that nitrate and molybdate supplements shifted the
microbial community composition in different ways. Nitrate, molybdate,
and the nitrate-molybdate combination treatments provide a selective
pressure that selects for or enriches specific species reducing the
alpha diversity (Shannon index) of the cultures from Well D
(\textbf{Figure 2B} ). However, the treatments do not enrich for the
same species - the beta diversity of the communities as estimated by
principal coordinate analysis (PCoA) analysis of the 16S rRNA gene
composition (\textbf{Figure 2C} ) reveal distinct groups of data points.
Moreover, the time evolution of these communities diverge over the first
three days (spheres to diamonds) as a result of their different
selective pressures. However, the combined molybdate and nitrate
treatment converges on that of molybdate alone (\textbf{Figure 3C} )
suggesting that the selection pressure applied by molybdate is stronger
than that of nitrate and, ultimately, determines microbial metabolism
and community structure. Hydrogen sulfide inhibition in the literature
is more sensitive to molybdate than nitrate\textsuperscript{42,43},
adding further support for the strong selective pressure of molybdate.

To determine which taxa were specifically selected against and enriched
in these microcosms, we evaluated the 16S rRNA gene composition of the
microbial community. Interestingly, we found that after Day 1 of
cultivation, there was little effect across the treatments with only a
slight increase in the\emph{Enterobacteriaceae} in the molybdate and
combined treatments (\textbf{Supplemental Figure 4} ). After Day 3,
however, the treatments varied noticeably from the untreated microcosms
(\textbf{Figure 3A} ). For example, nitrate microcosms saw a bloom of
\emph{Sulfospirillium} in days 3 and 4, while the molybdate and combined
treatments each saw a bloom in \emph{Enterobacteriaceae sp.} and
\emph{Lachnoclostridiumsp.,} which are MEOR-relevant bacteria.
Many\emph{Sulfospirillium} species contain both nitrate- and
sulfur-reducing pathways, so it is reasonable to expect that the nitrate
substrate allowed these species to outgrow organisms that could not use
this nutrient. Similarly, a few \emph{Enterobacteriaceae} have been
found to reduce molybdate\textsuperscript{44,45} which may have provided
a similar advantage to these microbes. At the same time, molybdate is
structurally similar to sulfate and has been shown to inhibit the growth
of H\textsubscript{2}S producers\textsuperscript{43} which may account
for the absence of \emph{Desulfovibrio} , \emph{Dethiosulfovibrio}
,\emph{Sulfospirillium} , and other sulfate reducing bacteria in the
molybdate and combined treatment microcosms. After 7 days, the cultures
primarily consisted of members of \emph{Bacteroides}
and\emph{Lachnoclostridium} regardless of treatment suggesting that the
community may have shifted to scavenge or use other nutrient sources to
survive. Similar progressions of microcosms toward primarily
Bacteroidetes and Clostridia have been seen in previous
studies\textsuperscript{36} suggesting these groups of bacteria have the
advantage over other organisms in anaerobic consortia when the initial
nutrients have been depleted at the end of the cultivation.
Additionally, no known H\textsubscript{2}S reducing bacteria were
detected with molybdate and combination treatments suggesting that the
effects of the molybdate were effective over this whole time-course of
the cultivation. In contrast, \emph{Sulfurospirillium} species were
present at several timepoints in the nitrate microcosms. In a previous
H\textsubscript{2}S inhibition study, molybdate was also found to be the
strongest inhibitor of H\textsubscript{2}S reducing
bacteria\textsuperscript{43} from marine enrichment cultures. Where
previous findings suggested that the addition of these inhibitors had no
effect on the composition of the microbial
community,\textsuperscript{42} we find that they can drastically shape
the community composition and metabolism. However, our findings that
Well D and G (\textbf{Supplemental Figure 4)} respond differently to the
nitrate and molybdate inhibitors further support previous assertations
that the efficiency of H\textsubscript{2}S inhibitors depends on the
composition of the microbiome.\textsuperscript{42,43} While changes in
microbial community composition indicate a response to our top-down
engineering, they are not definitive of metabolic output, which must be
characterized directly.

Hydrogen sulfide production reduced or suppressed by nitrate and
molybdate treatments

To assess if these supplements resulted in metabolic changes that reduce
or inhibit H\textsubscript{2}S production, we measured
H\textsubscript{2}S in the headspace of the \emph{in vitro} microcosms
from Well D. Untreated microcosms from Well D generated, on average,
approximately 220 ppm (+/- 35) of headspace H\textsubscript{2}S after 10
days of cultivation (\textbf{Figure 3B} ). Nitrate-treated microcosms
reduced the amount of H\textsubscript{2}S to \textasciitilde{}150 ppm on
average, while the molybdate and combined treatments limited the
H\textsubscript{2}S to approximately 2 ppm or less. Taken together with
the sequencing data, this suggest that the nitrate treatment here likely
allowed for competitive metabolism of nitrate over sulfate as has been
reported to decrease H\textsubscript{2}S
production.\textsuperscript{11,41,43} Biostimulation with nitrate alone,
however, was not able to completely inhibit H\textsubscript{2}S
production and enriched for specific organisms that can utilize both
nitrate and sulfate,\textsuperscript{35} like\emph{Sulfurospirillium,}
\textsuperscript{11,46}\emph{.} We hypothesize that these taxa may have
either simultaneously utilized both electron acceptors or switched to
sulfate metabolism once the nitrate was consumed, resulting in modest
decreases in H\textsubscript{2}S production. Additionally, nitrate
supplementation generally allows other species an advantage over the
sulfate-reducing bacteria like\emph{Desulfovibrio} and
\emph{Dethiosulfovibrio} species, which were present only in our
controls, but does not directly inhibit these organisms that contribute
to the production of H\textsubscript{2}S. On the other hand, molybdate
proved very effective at inhibiting H\textsubscript{2}S generation both
on its own and in combination with nitrate. Molybdate has been proposed
to inhibit H\textsubscript{2}S generation by binding to the sulfate
adenylyltransferase (Sat, ATP sulfurylase) complex and blocking the
generation of ammonium persulfate precursor to sulfide while also
depleting the ATP pools of the cell.\textsuperscript{43} We believe that
this form of selection may explain why the molybdate effectively
inhibits H\textsubscript{2}S formation while also limiting the number of
H\textsubscript{2}S generating organisms in the community, which is also
consistent with our decreased alpha diversity finding (\textbf{Figure 2}
). Based on this understanding, molybdate strongly inhibits the
sulfate-reducers, which allows other microbes to ferment the molasses to
organic acids and gases for MEOR, whereas nitrate only limits
H\textsubscript{2}S production through competition until it is all
consumed, after which the presence of microbes that can consume both
nitrate and sulfate may dominate.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Figure 3} -- Top-down nutrient treatments inhibit and enrich
specific microbes and their metabolism. A) Microbiome composition of
microcosms with and without treatment across days 3 -- 14. B)
H\textsubscript{2}S headspace measurements of microcosms after 14 days
of treatment, T-tests performed with respect to None except where
indicated. Error bars represent standard deviation, n=4 (except for
``None'', n=3); * = p \textless{} 0.05, ** = p \textless{} 0.005, and
*** = p \textless{} 0.001. \emph{Enterobacteriaceae} *
and\emph{Lachnospiraceae} * indicate unspecified genera within these two
Families.

To evaluate how persistent the impacts of these treatments are, we
passaged the communities into media that contained the same, different,
or no supplements. After three days of growth, microcosms were passaged
three separate times into fresh media with and without supplements.
Subcultures of untreated communities with either no supplement or only
nitrate produced moderate amounts of H\textsubscript{2}S although lower
than the untreated parent culture, while molybdate treatment of
untreated subcultures matched that of the initial molybdate-treated
cultures with little to no H\textsubscript{2}S formation after the
passages ([?]7 ppm H\textsubscript{2}S) (\textbf{Figure 4, Supplemental
Figure 5A} ). When cultures were passaged from nitrate treatments and
selection pressure was removed or kept the same (\textbf{Figure 4B} ; no
supplement or NO\textsubscript{3}\textsuperscript{-1} only,
respectively), the H\textsubscript{2}S production resumed and remained a
little lower than the level of the parent culture (\textasciitilde{}100
ppm). This suggests that the nitrate treatment may have enriched for
H\textsubscript{2}S-reducing bacteria or at best suppressed their
metabolism initially. However, if nitrate selection is applied to
molybdate cultures, H\textsubscript{2}S levels remained below that of
nitrate treatment of the native microbiome. Therefore, we suspect that
the reduced alpha diversity of molybdate treatment (\textbf{Figure 2} )
reflects a direct inhibition or loss of many of the sulfur-reducing
species, which are either temporarily limited or possibly enriched by
the nitrate treatment. As before, molybdate was able to limit the
H\textsubscript{2}S production of the sulfate-reducing communities to
very low levels (\textbf{Figure 4B} ), further demonstrating that it was
effective even against actively H\textsubscript{2}S-generating
communities like those from the nitrate-treated group that otherwise
produce H\textsubscript{2}S (\textbf{Figure 4C} ). Molybdate-treated
subcultures, regardless of parent culture, generated less
H\textsubscript{2}S (\textbf{Supplemental Figures 5A and D} ).
Interestingly, when molybdate microcosms were subcultured and had their
selection pressure removed (\textbf{Figure 4C} , \textbf{Supplemental
Figure 5B and C} ), H\textsubscript{2}S was produced although at low
levels (\textless{}25 ppm) with each sequential passage producing more
H\textsubscript{2}S demonstrating that continuous application of this
selection pressure is needed to permanently suppress
H\textsubscript{2}S. This suggest that H\textsubscript{2}S-generation is
inhibited by molybdate, but the associated microbes may still be present
at low levels. Lastly, subcultures of microcosms generated from
combination treatment (\textbf{Figure 4D} ) behaved like molybdate
subcultures for combined supplement and molybdate passages. However,
after three passages, H\textsubscript{2}S generation of these
communities treated with nitrate began to return to higher levels. This
suggests that the supplemented nitrate substrate in the combination
treatment may have continued enriching for nitrate consumers,
specifically some that harbor both nitrate and sulfate reducing
pathways, so that sulfate reduction resumed once the nitrate was
consumed. Throughout the subculture cultivations, the microbial
community compositions were similar to their respective nutrient
screening microcosms which were dominated by \emph{Enterobacteriaceae,
Bacteroides, and Lachnoclostridium} (\textbf{Figure 3, Supplemental
Figure 6} ). Ultimately, the combination of molybdate and nitrate best
limits H\textsubscript{2}S (\textbf{Supplemental Figure 5E} ) and
provides some redundancy of inhibitors in the case one of the selection
pressures is resisted or lost; however, molybdate is the most important
for effectively limiting H\textsubscript{2}S production from these oil
well communities (\textbf{Supplemental Figure 5D} ). From this \emph{in
vitro} screening system, we showed that oil well microbial communities
can be engineered and controlled from the top down using nitrate and
molybdate, structural analogs of sulfate, to inhibit sulfate-reducing
bacteria and H\textsubscript{2}S generation.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Figure 4}--\textbf{Continued application of H\textsubscript{2}S
inhibitors effective limits H\textsubscript{2}S production in microcosms
cultures.} Headspace H\textsubscript{2}S from microcosms 7 days after
subculture from parent cultures with A) no, B) nitrate, C) molybdate, or
D) combined supplements and subsequent treatment with no (brown),
nitrate (yellow), molybdate (aqua), or combined (teal) supplementation.
Error bars represent standard deviation, n=3. Additional comparisons and
statistical analysis are shown in Supplemental Figure 5.

Mini-coreflood experiments validate in vitro community control

To evaluate the effect of our top-down engineering approach on oil
recovery, we applied the same treatments to a miniature coreflood
system. The mini-coreflood (MCF) design (\textbf{Figure 5A-C} ) was used
to simulate microbial enhanced secondary oil recovery from
representative core material to evaluate the effects of the carbon and
micronutrient supplements in parallel. In addition to pressure generated
by the microbes in the MCF, we evaluated the composition of the
microbial community and the produced oil. After initial oil recovery
from brine flooding was completed, 9:1 mixtures of effluent and
molasses-nutrient supplements were injected into the MCFs and allowed to
sit for 10 days in an anaerobic environment to seed the core and
incubate the growing microbes. Similar to our \emph{in vitro}microcosms,
we found that molasses was able to induce microbial growth and activity,
generating up to 26 PSI. Nitrate-treated floods generated the most
pressure while the molybdate and combination treatment generated less
pressure (\textbf{Figure 5D} ). We suspect that the suppression of
H\textsubscript{2}S and the limitation of sulfate-reducing bacteria
account for the differences in pressure generation between the
molybdate-treated cultures and the untreated or nitrate-treated
cultures. Because increased pressure applies more force on the trapped
oil deposits, the amounts of oil recovered trended with the pressure
produced (\textbf{Figure 5E/F} ). We also found that the microbial
community in the MCF was distinct from our \emph{in vitro}screening,
reflecting the contribution of the high petroleum hydrocarbon
concentrations in these samples. MCF microbial communities drastically
shifted toward \emph{Bacteroides} under the molybdate and combination
treatment whereas the untreated and nitrate-treated MCFs were dominated
by \emph{Lachnoclostridium} (\textbf{Figure 5G} ). As at the end of
the\emph{in vitro} microcosms, both \emph{Bacteroides}
and\emph{Lachnoclostridium} were prominent members of the final MCF
microbiome (\textbf{Figure 4, Figure 5G} ), but these MCF trials contain
significant amounts of the oil hydrocarbons that can be used as an
additional carbon source. While the V4-V5 16S rRNA gene region amplified
here is not specific enough to identify the species of these genera,
microbes belonging to the \emph{Lachnoclostridium} group have been found
to degrade some hydrocarbons and some reduce sulfate to
H\textsubscript{2}S.\textsuperscript{47--49} Similarly, we observed
increases in the abundance of organisms belonging to the
genus\emph{Pseudomonas} which is not a prominent producer of gases and
has been linked to naphthalene,\textsuperscript{50} normal
paraffin,\textsuperscript{51} and polycyclic hydrocarbon
degradation.\textsuperscript{52,53} As shown in (\textbf{Figure 5E/G} )
the proportion of n-paraffin dropped from \textasciitilde{}35 \%w/w to
\textasciitilde{}25 \%w/w of the relative abundance
while\emph{Pseudomonas} sp. increased in abundance in the molybdate and
combination MCFs. This condition suggests that \emph{Pseudomonas
sp.}degraded around 30\% of the long chain n-paraffins (C14 -- C29) in a
period of 14 days (\textbf{Supplemental Figure 7A, Supplemental Table 1}
). Although isolates were not identified here, \emph{Pseudomonas} sp.,
such as \emph{P. proteolytica, P. xanthomarina, and P. aeruginosa} , are
expected to induce n-paraffin degradation starting from n-tetradecane
(C14) by alkane hydroxylases systems.\textsuperscript{53--55} Certainly,
biodegradation of long chain n-paraffins is recognized to have a
positive influence in oil recovery processes by means of reducing the
viscosity of the crude oil while increasing its
fluidity.\textsuperscript{56} The relative abundance of
monocyclo-paraffins increased from \textasciitilde{}30 \%w/w to
\textasciitilde{}40 \%w/w in total corresponding to the increment of the
C9 -- C17 fraction for all treatments (\textbf{Supplemental Figure 7B,
Supplemental Table 1} ), likely due to degradation of the n-paraffins.
However, no specific trend was observed for the abundance of
iso-paraffins. Aromatics such as naphthalene also decreased in abundance
with treatment and the presence of \emph{Pseudomonas} sp.
(\textbf{Figure 5F/G} ). Species such as \emph{P. mendocina, P. putida,
P. fluorescens, P. paucimobilis, P. vesicularis, P. cepacia, P.
testosteronei, P. aeruginosa,} and \emph{P. stutzeri} have been reported
to induce naphthalene biodegradation.\textsuperscript{52,57,58} In
contrast, the triaromatic fraction (C17) increased as a response of the
supplements here applied. The relative abundance of dicyclo- and
monocyclo-paraffins increased when these treatments were applied, likely
because of n-paraffin degradation, and thus, changed the overall
composition of the produced oil (\textbf{Figure 5E/G, Supplemental Table
1} ). While the results presented in Figure 5 represent one trial of
these treatments, an additional replicate treatment at a different time
(\textbf{Supplemental Figure 8A-C} ) showed n-paraffin degradation for
all treatments. However, the same trend for the aromatic polycyclic
hydrocarbon fraction is not seen in the replicate likely because the
microbiomes of the produced water used to seed these wells were
different (\textbf{Supplemental Figure 8D} ). Regardless of these
specific differences, we observed reproducible control of the oil well
microbiome as a function of nutrient supplementation to alter produced
oil paraffin profiles while limiting H\textsubscript{2}S production and
pressurizing the reserve.

Our results demonstrate a clear correlation between pressure generation
and oil recovery in MEOR processes. While the
H\textsubscript{2}S-limiting treatments did not substantially enhance
pressure generation in the presence of hydrocarbons and confined
geometry, we were able to validate the role that molybdate plays in
controlling souring and corrosion by oil well microbes. However, field
trials and economic analysis are needed to determine the viability of
our process relative to current surfactant-based oil recovery processes.
The modest improvements in oil recovery may be offset by the increased
operating costs needed for corrosion maintenance, surfactant production,
and microbial control via more expensive ammonium quaternary
disinfectants currently used.\textsuperscript{19} Moreover, we
demonstrated that the specific oil compositions were a strong function
of microbial activity, which could be controlled via top-down
engineering. Further optimization of the nutrient formulation, such as
increased amounts of molasses or other nutrients, may enhance pressure
generation or alter the microbial dynamics so that more oil can be
recovered and specific hydrocarbon compounds can be enriched or
depleted. In agreement with the \emph{in vitro} findings, these results
suggested that we can control the microbial population in small scale
oil recovery settings and can use that to concurrently modulate oil
composition.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Figure 5} -- Top-down nutrient formulations control microbial
metabolism in ways the affect both oil yield and composition. A)
Overview of mini-coreflood (MCF) experimental design where cores are
saturated with oil, accessible oil (primary recovery) is extracted with
brine and microbes are seeded with produced water, nutrients are
subsequently injected, and reactors are shut-in for ten days before they
are vented and flooded with brine to recover any of the oil liberated by
the microbial processes (i.e. secondary recovery). B) MCF experimental
setup showing the pump which injects either oil, sterile brine, well
water for seeding, or nutrient supplements with the MCF canisters
encasing the core material and C) an actual image of assembled MCF
apparatus. D) Pressure generated during 10 day mini-coreflood by various
supplements. E) Chemical composition of produced oil after microbial
mini-coreflood. F) Fraction of residual oil in place that was recovered
after 10-day microbial shut-in period. G) Composition of microbes in
effluent from the microbial mini-coreflood after 10-day shut in period.
This data represents one trial which is the most data complete, a
replicate performed at a different time from different produced water is
presented in the supplement (Supplemental Figure 8).

\textbf{Conclusions}

Microbial activity of oil wells has a significant impact on oil recovery
efficiencies, the souring of produced oil or H\textsubscript{2}S
generation, and final oil composition. Top-down engineering approaches
via direct nutrient injection and supplementation can be used to shape
community structure and control metabolism. We validated the ability of
molasses supplemented with nitrate and/or molybdate to apply different
selective pressures which were either competitive or inhibitory of
H\textsubscript{2}S production, respectively. Molybdate supplementation
in particular provided strong selective pressure whose effects persisted
over multiple generations or passages once removed, demonstrating a
strong capacity to shape community composition and function. While these
did not enhance oil recovery in our coreflood experiments under the
conditions tested, top-down engineering had demonstrable impact on the
composition of oil recovered and inhibiting microbial souring processes.
Our work highlights the power of microbiome engineering for the
improvement of oil recovery operations and develops a workflow for the
rapid screening and evaluation of candidate oil wells.

\textbf{Methods}

\emph{Cultivation}

Effluent oil well water was collected from several wells around the
Illinois oil basin and transported to the laboratory (West Lafayette,
IN, USA) the same day. For cultivation of the oil well microbiome, 9 ml
of effluent water was mixed in Hungate tubes with either 1 ml of sterile
40\% (w/v) corn syrup or 1 ml of sterile 40\% (w/v) molasses in an
anaerobic chamber (PLOS, Grand Rapids, MI, USA) with an atmosphere of
85\% N\textsubscript{2}, 10\% CO\textsubscript{2,} \& 5\%
H\textsubscript{2}. Cultures that were treated with additional
non-essential micronutrient supplements {[}final concentration of 0.5
g/L potassium nitrate, 0.5 g/L sodium molybdate, 0.25 g/L potassium
monophosphate and 0.25 g/L potassium diphosphate, or 0.25 g/L sodium
chloride and 0.25 g/L potassium chloride{]} -- solutions were sterile
filtered and equilibrated overnight in the anaerobic chamber. After
nutrient solutions were added, cultures were thoroughly mixed and
incubated at 27 @\selectlanguage{english}C. Pressure measurements were taken every 24 hours with
a pressure gauge (APG, Logan, UT, USA),\textsuperscript{59} 1 ml of
culture was removed for microbiome analysis and pH monitoring by pH test
strips (pH2-8, MilliporeSigma, St. Louis, MO, USA). After sampling, the
cultures were then vented to a gauge pressure of 0 and replaced in the
incubator; cultures were monitored and sampled for 7-10 days.

\emph{DNA extraction, PCR, Sequencing \& analysis.}

To evaluate the composition of the native oil well, \textasciitilde{}1L
of effluent water was prefiltered with Glass Fiber Filters (1.2 \selectlanguage{greek}μ\selectlanguage{english}m pore,
MilliporeSigma) and then biomass was concentrated on Express PLUS
Membrane Filters (0.22 \selectlanguage{greek}μ\selectlanguage{english}m pore, MilliporeSigma) similar to previous
work.\textsuperscript{60} DNA was then extracted from the microbial
biomass on the second filter using the DNeasy PowerFecal Kit (QIAGEN,
Germantown, MD, USA) along with the FastPrep 24 5G homogenizer (MP
Biomedicals, Santa Ana, CA, USA) as per instructed by the manufacturers.
All DNA was stored at - 20 \selectlanguage{ngerman}°C until further analysis. DNA concentration
and quality were assessed on a NanoPhotometer (Implen NP80, Los Angeles,
CA, USA). The microbial community composition of oil well microcosms was
assessed by DNA extracted from a 1-ml aliquot of the cultures as
mentioned above. The 1 ml aliquots were centrifuged at 10,000g for 7 min
to pellet the cells. After removing the supernatant, the microbial DNA
was extracted with the same DNeasy PowerFecal kit as noted above.

As in previous microcosm studies,\textsuperscript{61} the microbial
community was then assessed by amplifying and sequencing the V4-V5
region of the 16S rRNA gene from the extracted DNA (primers: 515f -
forward, 5\selectlanguage{english}' GTGYCAGCMGCCGCGGTAA 3\selectlanguage{english}'; and 926r - reverse 5\selectlanguage{english}'
CCGYCAATTYMTTTRAGTTT 3\selectlanguage{english}').\textsuperscript{62} 16S rRNA gene PCRs were
set up using Phusion Polymerase MasterMix (Thermo Fisher Scientific,
Waltham, MA, USA) as follows PCR-grade water (22 \selectlanguage{greek}μ\selectlanguage{english}l), Phusion mastermix
(25 \selectlanguage{greek}μ\selectlanguage{english}l), forward primer (10 \selectlanguage{greek}μ\selectlanguage{english}M, 1.0 \selectlanguage{greek}μ\selectlanguage{english}l), reverse primer (10 \selectlanguage{greek}μ\selectlanguage{english}M, 1.0 \selectlanguage{greek}μ\selectlanguage{english}l),
and template DNA (1.0 \selectlanguage{greek}μ\selectlanguage{english}l) in a total reaction volume of 50 \selectlanguage{greek}μ\selectlanguage{english}l; for
samples that had very low template concentration up to 5 \selectlanguage{greek}μ\selectlanguage{english}l of DNA
template was used and the water volume reduced to 17 \selectlanguage{greek}μ\selectlanguage{english}l. PCR
amplification conditions were set to 98 \selectlanguage{ngerman}°C for 0.5 min; 35 cycles of 98
°C for 15 s, 50 °C for 30 s, 72 °C for 60 s; and 72 °C for 10 min, and
then a 4 °C hold. The resulting amplicons were confirmed by gel
electrophoresis, purified using the Clean and Concentrator kit (Zymo
Research Irvine, CA, USA), and then labeled using unique 8-bp tagged i5
(i509-i516) index forward primers and 8-bp tagged i7 (i713-i724) index
reverse primers as suggested by the manufacturer (Illumina San Diego,
CA, USA). Pooled amplicons were then multiplexed and sequenced via
2\selectlanguage{english} x\selectlanguage{english} 250-bp paired reads on an Illumina MiSeq at the Purdue Genomics
facilities. Sequences were analyzed using the QIIME2
pipeline\textsuperscript{63} which quality-filtered, joined paired
reads, checked for chimeras, and denoised the data (via
DADA2\textsuperscript{64}). The operational taxonomic units (OTUs) were
assigned using the SILVA SSU database (SILVA 138)\textsuperscript{65}for
assigning taxonomy to the representative OTUs. All alpha and beta
diversity metrics were calculated using QIIME's built in analysis tools.

\emph{Micro GC H2S quantification}

An Agilent 490 Micro GC (Agilent Technologies, Palo Alto, CA, USA)
equipped with parallel Molsieve 5A and PoraPLOT U columns and a thermal
conductivity detector was used for H2S analysis with Helium carrier gas
(15PSI). The column and injector temperatures were isothermally set to
60 degC for the duration of the 120 s run. The injector was set to split
mode with an injection time of 40 ms and a backflush time of 10 s.
H\textsubscript{2}S standards were prepared as previously
described\textsuperscript{66} where, briefly, H\textsubscript{2}S was
generated by reacting Na\textsubscript{2}S (Sigma-Aldrich, Saint Louis,
MO, USA) with excess HCl (Fisher) in a 20 ml Hungate bottle with a butyl
rubber stopped in the anaerobic chamber. Six working calibration
standards at concentrations corresponding to 25, 50, 100, 250, 750, and
1,500 ppm of H\textsubscript{2}S were prepared by diluting from a 5
\selectlanguage{greek}µ\selectlanguage{english}mol/ml stock. Either a 2 ml headspace of standard or the microcosm
samples was withdrawn and injected into the instrument with a gas
syringe. Standards were run in triplicate to create a calibration curve
while the biological samples were each run once.

\emph{Mini-coreflood set up}

These studies used high-permeability (\textgreater{}400 mD), 1''
diameter by 6'' long Berea Sanstone\textsuperscript{TM} cores (Cleveland
Quarries, Vermilion, OH, USA) that were dried to completeness in an oven
at 110 \selectlanguage{ngerman}°C overnight. Once dried, the cores were saturated with a
synthetic brine comprising a salinity (9400 mg/L and a hardness of 250
mg/L) closely resembling fluids from the representative wells to
determine pore volumes (PV) by the mass of brine that was retained in
the core. Following brine saturation, mini-coreflood reactors were
assembled in the anaerobic chamber and they consisted of a PVC sleeve
(1'' inner diameter, McMaster-Carr, Cleveland, OH, USA) that surrounded
the core and a plastic canister to hold the core in place (built by
Purdue University's Chemistry Precision Machine Shop, West Lafayette,
IN, USA). The plastic canisters were then filled with DI water that was
pressurized to 80 PSI to apply pressure on the sleeve and keep it
tightly fit to the core. Once mini-coreflood reactors were assembled,
dead oil from the representative wells was processed and injected into
the core at a rate of 0.5 ml/min until the core was saturated with oil;
the amount of brine displaced represented the volume of original oil in
place (OOIP) before the primary water flood. The primary flood was
carried out by injecting of 2 PV effluent oil well water at rate of a 1
ml/min to displace the oil for primary recovery and simultaneously seed
microbes into the core. The secondary flood was carried out with 1 PV of
a mixture of nine parts well water to one part of the molasses solution
with supplements as indicated in the ``Cultivation'' methods section
above. The flow rate of the secondary flood was 1 ml/min, and no
additional oil was recovered during this nutrient injection step.
Mini-corefloods were shut-in for 10 days inside the anaerobic chamber
(27 °C) replicating ground conditions. Pressure generated over the
10-day period was measure with an in-line pressure gauge. Oil generated
by the microbial pressure was collected and then an additional 2 PV of
brine was used as a final water flood to recover oil displaced by the
microbial activity. The collected brine flood volumes were centrifuged,
and DNA was extracted from the pellet; V4-V5 16S rRNA gene regions were
amplified and sequenced as described above (see ``\emph{DNA extraction,
PCR, Sequencing \& analysis} '').

\emph{Chemical quantitation via GCxGC-FID}

The quantitative chemical characterization of the oil samples was
carried out using a comprehensive two-dimensional gas chromatography
system Agilent 7890B GC (GCxGC) coupled to a flame ionization detector
(FID). A thermal modulator cooled with liquid nitrogen (LECO
Corporation, Saint Joseph, MI), an Agilent 7683B series injector, and a
HP 7683 series autosampler were also used. A reversed phase column
configuration was selected having a primary mid-polar column DB-17ms (30
m x 0.25 mm x 0.25 \selectlanguage{greek}µ\selectlanguage{english}m) and a secondary nonpolar column DB-1ms (0.8 m x
0.25 mm x 0.25 \selectlanguage{greek}µ\selectlanguage{english}m). Both columns were provided by Agilent (Santa Clara,
CA). Ultrahigh purity helium (99.9999 \%) was used as the carrier gas at
a constant flow rate of 1.5 mL/min, and a front inlet septum purge flow
of 3 mL/min and a front inlet gas saver flow of 20 ml/min were set in
the GC x GC system. A split inlet liner with glass wool suitable for low
pressure drop provided by Agilent (Santa Clara, CA) was used to protect
the system due to the nature of the samples under study. The temperature
of the front inlet, initial oven temperature, and the target oven
temperature were set at 280 \selectlanguage{ngerman}°C, 40 °C (hold time of 0.2 min), and 260 °C
(hold time of 5 min), respectively. An oven temperature ramp rate of 3
°C/min was considered for a total GC method time of analysis of 4,712
seconds (78.5 min) per sample. Secondary oven and modulator temperature
offsets were set at 50 °C and 15 °C, respectively. A modulation period
of 2.5 s was used to avoid wraparound. Samples of 0.5 \selectlanguage{greek}µ\selectlanguage{english}L were injected
to the system using a manual dilution factor of 100 (10 \selectlanguage{greek}µ\selectlanguage{english}L of sample in
1 ml of pentane) and automatic split ratio of 20:1. The development and
refinement of the GCxGC-FID classification map (\textbf{Supplemental
Figure 9} ) was made based on the methodology described in a previous
study.\textsuperscript{67} Thus, the chemical characterization
encompassed nine hydrocarbon groups and carbon numbers as follows:
n-paraffins (C6-C32), iso-paraffins (C6-C32), monocyclo- (C6-C30),
dicyclo- (C8-C20), and tricyclo-paraffins (C10-C16), alkylbenzenes
(C6-C20), cycloaromatics (C9-C18), naphthalenes (C10-C19), and
triaromatics (C14-C19). Data were processed in ChromaTOF software
version 4.71.0.0 optimized for GC x GC -- FID (LECO Corporation, Saint
Joseph, MI) with a signal-to-noise ratio of 50. Weight percentage (wt.
\%) relative to each hydrocarbon class and carbon number was calculated
via normalizing the peak area by integration of the GC x GC
chromatograms extracting solvent and column bleed peaks using Microsoft
Excel - 365.

\emph{Statistical Methods}

T-tests were performed using GraphPad Prism's in-software analysis tools
(https://www.graphpad.com/guides/prism/latest/statistics/stat\_key\_concepts\_ttests.htm).
Relative abundance, alpha diversity, and beta diversity metrics were
calculated in QIIME2\textsuperscript{63} and the results (such as PCoA)
were visualized using QIIME2 view (https://view.qiime2.org/).

\textbf{Abbreviations:}

FID: flame ionization detector, GCxGC: comprehensive two-dimensional gas
chromatography, H\textsubscript{2}S: hydrogen sulfide, MEOR: microbial
enhanced oil recovery, MCF: mini-coreflood, OTU: operational taxonomic
unit, PCoA: principal coordinate analysis, PCR: polymerase chain
reaction

\textbf{Declarations:}

\emph{Ethics approval and consent to participate:} Not applicable

\emph{Consent for publication:} Not applicable

\emph{Availability of data and materials} : The sequencing datasets
supporting the conclusions of this article are available under the NCBI
SRA: SUB11545621. Additional Data including GCxGC data can be found in
Supplemental Materials file.

\emph{Competing interests} : The authors declare no conflict of
interest. The funders had no role in the design of the study, in the
collection, analyses, or interpretation of data; in the writing of the
manuscript, or in the decision to publish the results.

\emph{Funding:} This project was financially supported by the Pioneer
Oil Company (Vincennes, IN) and the Purdue Enhanced Oil Recovery Lab.

\emph{Author Contributions:} ETH: Conceptualization, Formal analysis,
Data curation, Investigation, Methodology, Project administration,
Supervision, Validation, Visualization; Roles/Writing - original draft.
LECM: Formal analysis, Methodology, Data curation, Investigation,
Writing - review \& editing. GK: Funding acquisition, Project
administration, Resources, Writing - review \& editing. KVS:
Conceptualization, Funding acquisition, Project administration,
Resources, Supervision, Writing - review \& editing. All authors have
read and agreed to the published version of the manuscript.

\emph{Acknowledgments:} We would like to thank the members of Purdue's
Enhance Oil Recovery Lab, specifically Dr. Nate Schultheiss, Dr. Thomas
Everett, Dr. Jeremy Holtsclaw, Dr. Katherine Wehde, and Timothy
Henderson, who made this work possible by coordinating well samplings,
provided experimental feedback, and supplying technical supported and
insight for our work. We would also like to thank Dr. Stephen Lindemann
and his lab at Purdue Food Science for providing access to their Micro
GC for H\textsubscript{2}S analyses. We are also grateful to the Purdue
University Genomics Core for their role in sequencing the 16S rRNA gene
amplicons and the Purdue Institute of Inflammation, Immunology, and
Infectious Disease for access to the Bell computing cluster which
allowed us to analyze the sequencing reads. Additionally, we are
thankful to both Bindley Bioscience Center and the Fuel Laboratory of
Renewable Energy at Purdue University for the research space and support
staff where this research was carried out.

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