Functional Gene and Metabolic Changes of Marine Microbial Populations Involved in Hydrocarbon Degradation Under Different Enrichment Conditions


 In this study, seawater from the area of an oil extraction platform in Bohai Bay was subjected to experimental treatments with oil as the only carbon source to understand the transcriptional responses of seawater microbial populations to oil degradation treatments. Twelve enrichment conditions were used, and fluorescent in situ hybridization (FISH) along with metatranscriptomic analyses were used to understand functional changes within each treatment. RNA from the petroleum-degrading bacterial enrichments was extracted after cultivation and FISH was used to evaluate overall activity, while changes in gene expression among different culture conditions were analyzed based on eight hydrocarbon-specific gene probes and flow cytometry. Concomitantly, 1,066 metabolic pathways were identified as being expressed in the populations through RNA sequencing, metatranscriptomic analysis, and metabolic pathway enrichment analysis. The addition of oil led to the inhibition of carbohydrate metabolism and inositol phosphate metabolism, while also reducing extracellular signaling pathway transcription levels. When low- and high-nutrient conditions were compared, low-nutrient conditions inhibited taurine and hypotaurine metabolism in addition to inositol phosphate metabolism. Among oxygen-treated, carbon dioxide-treated, and air-treated conditions, oxygen-treated conditions inhibited taurine and hypotaurine metabolism but promoted galactose metabolism, while carbon dioxide-treated conditions promoted inositol phosphate metabolism. Overall, metabolic pathway expression and functional gene changes indicated that high-nutrient, oil-free, and aerobic culture conditions best promoted the growth and reproduction of marine microbial communities.


Introduction
Marine pollution caused by offshore oil exploitation is one of the most important challenges for modern environments. However, microbial oil degradation offers unique advantages for the prevention and treatment of offshore oil pollution due to the low cost of application, high e ciency of degradation activity, and minimal pollution risk [1,2]. Dehydrogenation, hydroxylation, and hydroperoxidation activities by microorganisms lead to the breakdown of alkanes and aromatic hydrocarbons in petroleum that are then used in the tricarboxylic acid cycle, transforming the carbon to CO 2 and water while simultaneously promoting energy conservation within microbial populations [3,4]. Environmental variation can signi cantly impact the ability of microorganisms to degrade petroleum hydrocarbons, and these degradation e ciencies can greatly vary across environments. If environmental parameters inhibit the growth of petroleum hydrocarbon-degrading bacteria, petroleum hydrocarbon can inde nitely persist in environments [5]. Consequently, understanding the interactions of gene activities in petroleum degradation in an inter-speci c, networked, and comprehensive framework is key for understanding the microbial degradation of petroleum.
Metatranscriptomics allows the investigation of gene transcription within natural samples, in addition to the transcription and regulation of genes under speci c conditions and in the life cycles of a speci c population, thereby providing a more comprehensive understanding of the degradation of petroleum hydrocarbons by microbial metabolic activities. For example, Kothari compared the cultivation of Acinetobacter venetianus RAG-1 on dodecane, dodecanol, and sodium acetate, observing that three genes were transcribed that were involved in alkane oxidation-alkMa, alkMb, and almA. Among these, alkMb exhibited the highest differential expression and may be involved in dodecane oxidation. Further comparison of the strain grown on sodium acetate medium led to the identi cation of 1,074 differentially expressed genes, of which 622 up-regulated genes were involved in alkane catabolism and stress response to alkanes [6]. Moreover, Hong observed that Achromobacter.sp. HZ01 can degrade anthracene, phenanthrene, pyrene, and n-alkanes, using polycyclic aromatic hydrocarbons as the sole carbon source after petroleum treatment of strain HZ01 for 16 h. In addition, a total of 742 differentially expressed genes were identi ed from strain HZ01 by transcriptomic analysis, with most down-regulated genes being related to cell motility, sugar metabolism, and ribosomal proteins, while genes involved in fatty acid metabolic pathways, some monooxygenases, and dehydrogenases were up-regulated, and TCA cycle genes were inactive [7]. Johanne Aubé compared a contaminated mat exposed to chronic petroleum contamination and a reference mat by using metagenomic and metatranscriptomic approaches. ABC transporters, two-component systems, and type IV secretion system-related genes were overabundant in the contaminated mats. Xenobiotic degradation metabolism was lesser in the metagenomes of both mats, and only the expression of genes involved in polycyclic aromatic hydrocarbon degradation was higher in the contaminated mat [8]. Thus, most previous studies have primarily focused on types of oil-degrading bacteria and their associated genes, while investigations have been lacking regarding the comprehensive regulation of marine oil hydrocarbon-degrading bacteria under speci c environmental conditions (e.g., those associated with offshore drilling platforms). Consequently, this study evaluated the metabolic pathways and gene regulation of natural marine bacterial communities involved in the degradation of petroleum hydrocarbons. In particular, we systematically evaluated community structures, degradation pathways, and metabolic gene networks involved in petroleum hydrocarbon metabolism in near offshore drilling platform waters. The overall goal of the study was to provide a theoretical foundation for the microbial treatment of oil-spill accidents in offshore drilling platforms.

Experimental Materials and Sampling
Seawater samples were collected near an oil drilling platform located at 38°26'31.7" N, 118°24'45.2" W. Samples were divided into 13 equal portions, each of which comprised 50 L. For 12 of them, different culture conditions comprising high-and low-nutrient conditions, different aeration conditions, and conditions with or without oil were used to evaluate differences in gene transcription among treatments; the rest one was set as control (named as ORI group; the condition was kept as same as of the sampled seawater around oil drilling platform). Different ventilation conditions: Every day in the morning and evening, the 50 L seawater of barrel of each different aeration group was ventilated for half an hour with a steel cylinder lled with CO 2 , O 2 , or air.
All ow rates are controlled at 5 mg L − 1 . Detailed cultivation parameters are described in Table 1.
On the 1st, 5th, 15th, and 20th day of such culture, the bacteria in the seawater were ltered with a glass sand lter device to a 0.45µm and then a 0.22µm lter membrane, respectively. Each lter membrane was enriched with bacteria from 1000ml of seawater. The lter membrane, after bacterial enrichment, was divided into different 50ml centrifuge tubes according to different samples, marked, and stored in a refrigerator at -80℃.
Gene transcription was evaluated by extracting RNA samples of treatment cultures on the 20th day of cultivation.

Experimental Methods
Fluorescence in Situ Hybridization (Fish) of Petroleum-Degrading Bacteria Phosphorus absorption in Alcanivorax borkumensis is regulated by the high-a nity ABC transporter system that is composed of phoU-pstBACS and phoBR gene expression products through the Pit transport system in nutrient-rich environments (> 20 mM Pi). The znuA gene of Alcanivorax borkumensis is a periplasmic Zn 2+ binding protein that is related to the high-a nity ATP-binding ZnuABC transport protein from E. coli [9]. In addition, phoB encodes positive regulators of the E. coli phosphor-regulator (including phoA, phoS, phoE, and ugpAB) [10]. Based on these previous studies, the following gene probes were used to evaluate gene transcription in the culture communities: znuA, phoB, nqrf, rubb, znub, moda, gltx, and ecta. The DNA of petroleum-degrading bacteria and performed primer veri cation were extracted. FISH was given on petroleumdegrading bacteria, and then used the American BD C6 ow cytometer (American BD Co., Tianjin Municipality, China) for detection.

Metatranscriptomic Analyses
RNA libraries were subjected to fragment screening prior to establishing the nal RNA library. A qualitycontrolled library was then sequenced on the Illumina Hiseq high-throughput sequencing platform, and the raw data obtained from sequencing was used for subsequent transcriptomic analysis. Raw data was quality ltered to obtain clean data for evaluating taxonomic and functional differences between samples. The assembled sequencing data is available in the IMG/JGI (Integrated Microbial Genomes & Microbiomes, DOE's Joint Genome Institute, USA) database (GOLD Analysis Project IDs are, ORI: Ga0439915, OOL: Ga0439914, OOH: Ga0439913, ONL: Ga0439912, ONH: Ga0439911, COL: Ga0439910, COH: Ga0439909, CNL: Ga0439908, CNH: Ga0439504, AOL: Ga0439503, AOH: Ga0439502, ANL: Ga0439501, ANH: Ga0439470). The abbreviations mean speci c transcriptomes from certain conditions: ORI, marine bacteria, directly from seawater, origin; OOL, marine bacteria, cultured with oxygen, oil(petroleum), and low nutrient content; OOH, oxygen, oil(petroleum), and high nutrient content; ONL, oxygen, no oil(petroleum), and low nutrient content; ONH, oxygen, no oil(petroleum), and high nutrient content; COL, carbon dioxide, oil(petroleum), and low nutrient content; COH, carbon dioxide, oil(petroleum), and high nutrient content; CNL, carbon dioxide, no oil(petroleum), and low nutrient content; CNH, carbon dioxide, no oil(petroleum), and high nutrient content; AOL, air, oil(petroleum), and low nutrient content; AOH, air, oil(petroleum), and high nutrient content; ANL, air, no oil(petroleum), and low nutrient content; ANH, air, no oil(petroleum), and high nutrient content.
BLAST (The Basic Local Alignment Search Tool) alignment (e value threshold of ≤ 1e-5 for positive hits) of the quality ltered data against the NCBI non-redundant (NR) protein database was conducted. The lowest common ancestor (LCA) classi cation algorithm implemented in MEGAN (Metagenome Analyser) [11] was used to assign taxonomic classi cations based on alignments, since each sequence might have multiple alignment results. Speci cally, the taxonomic classi cation based on the rst branch served as the species annotation for the sequence in question. Relative abundances of the ten most abundant classes are shown in the results, with the largest relative abundances in each sample shown and the remaining taxa being grouped as "Others".
Functional annotation of the quality ltered data was conducted using BLAST alignment of protein sequences against the assembled transcriptomic and protein annotation databases. Since multiple results could arise from each sequence alignment, the alignment results of each sequence were screened by calculating the alignment coverage ratio of each gene based on the reference and query lengths (i.e., the BLAST coverage ratio; BCR) to ensure that the BCR of the reference and query in each alignment exceeded 40%. The corresponding functional annotation information was then compiled from the databases.

Analysis of Metabolic Pathways
Digital gene expression (DGE) pro ling was used to compare the expression differences between the transcriptomic responses of this study's communities against that of transcriptome directly from marine environment. Metabolic pathway enrichment analysis based on KEGG pathways was then conducted in Pathview (a package in R) to investigate differences in metabolic pathway representation of differentially expressed genes under different conditions, in addition to identifying potential regulatory mechanisms of functional genes.

Changes in Fluorescence Intensity of Petroleum-Degrading Bacteria under Different Culture Conditions
The uorescence intensities of cultures under high-and low-nutrient conditions with and without oil amendment are shown in Figs. 1 and 2, respectively. In the presence of oil and oxygen, the genes 3 (znuA), 7 (gltX), and 8 (ectA) exhibited higher uorescence intensity on the 10th day of culture under high-nutrient conditions than under low-nutrient conditions. In conditions with oil and carbon dioxide supplementation, the uorescence intensity of gene 3 (znuA) was higher under high-nutrient conditions than under low-nutrient conditions on the 15th day of culture. When supplemented with oil and oxygen, the uorescence intensity of gene 6 (modA) was higher under high-nutrient conditions than under low-nutrient conditions on the 20th day of culture. In non-oil amended, air-treated conditions, the uorescence intensity of gene 2 (phoB) was higher under high-nutrient conditions than under low-nutrient conditions on the 15th day of culture. The non-oil amended and oxygen-treated condition cultures exhibited a higher uorescence intensity of gene 2 (phoB) under high-nutrient conditions than under low-nutrient conditions on the 10th day of culture. In addition, the non-oil amended and oxygen-treated condition cultures exhibited a higher uorescence intensity of gene 6 (modA) on the 20th day of culture under high-nutrient conditions than under low-nutrient conditions.

Variation in Functional Gene Composition Within Metabolic Pathways under Different Culture Conditions
The logarithmic ratios of the 20 most up-regulated (Table 2) and 20 most down-regulated (Table 3) differentially expressed genes within metabolic pathways under all conditions were speci cally evaluated.
The three most up-regulated protein encoding genes among all culture conditionsencoded 1) heat shock 70 kda proteins under COL vs ORI conditions, 2) heat shock 70 kda proteins under COL vs AOL conditions, and 3) superoxide dismutases within the Fe-Mn family under CNL vs ANL conditions. The three most down-regulated functional genes among all culture conditions were genes encoding 1) glutathione peroxidases under OOL vs AOL conditions, 2) elongation factor 1α-like proteins under CNL vs ANL conditions, and 3) GMP synthetases (glutamine hydrolysis) under CNH vs ANH conditions.

The Number of Metabolic Pathways under Different Culture Conditions
A total of 1,066 metabolic pathway maps were obtained under when comparing culture conditions ( Table 4).

Analysis of Functional
The gene transcription pro le comparisons between oxygen-treated and air-treated cultures under non-oil amended and high-nutrient conditions (ONH vs ANH) are shown in Figs. 7 and 8, respectively. Genes encoding glucose 4-epimerase (K01784), glutathione phosphate (K01835), and maltose amylase (K12047) were upregulated in the galactose metabolic pathway (Fig. 7). In addition, genes encoding glutamate decarboxylase (K01580) and γ-glutamyl transpeptidase (K00681) were down-regulated in the taurine and hypotaurine metabolic pathways (Fig. 8). In contrast, genes encoding proteins like cysteine dioxygenase (K00456) and glutamate dehydrogenase (K00260) were up-regulated in the taurine and hypotaurine metabolic pathway.
Comparisons between carbon dioxide-treated and oxygen-treated conditions under oil amended and highnutrient conditions (COH vs OOH) are shown in Fig. 9. Genes encoding inositol-1-phosphate synthase (K01858) and phosphatidylinositol 4-kinase A (K00888) were up-regulated in the inositol phosphate metabolic pathway, while genes encoding malonate-semialdehyde dehydrogenase (K00140) and triose phosphate isomerase (K01803) were down-regulated in the inositol phosphate metabolic pathway.

Analysis of Optimal Culture Conditions
The optimal or sub-optimal nature of culture conditions can signi cantly effect gene expression and subsequent hybridization patterns [12]. Consequently, we compared changes in the uorescence intensities of petroleum-degrading bacteria based on the hybridization with various probes under 12 culture conditions. The uorescence intensities of cells under oxygen-treated conditions were the highest, indicating that oxygentreatment conditions provided the most favorable culture environment for aerobic bacteria and therefore greater gene transcription hybridization. In addition, high-nutrient conditions provide adequate nutrient levels for cell growth, leading to greater levels of genes being expressed under high-nutrient conditions than in lownutrient conditions.

Analysis of Pathways Differentially Expressed under ANL vs ANH Conditions
The metabolism of taurine and hypotaurine is primarily involved in the synthesis of taurine, hypotaurine, and their derivatives. Taurine and hypotaurine are antioxidants that protect cells from toxic oxidants [13]. Glutamate decarboxylase (K01580) catalyzes the transformation of 3-sul nyl-L-alanine to hypotaurine, but also catalyzes the transformation of L-cysteine to taurine (Fig. 4) [14]. Thus, decreased nutrient concentrations will inhibit the activity of glutamate decarboxylase, resulting in less hypotaurine and taurine production. γ-glutamyl transpeptidase (K00681) catalyzes the transfer of γ-glutamyl to other amino acids and peptides, while also catalyzing the formation of 5-glutamyl-taurine from taurine within this metabolic pathway [15]. Decreased nutrient concentrations inhibited the activity of γ-glutamyl transpeptidase, likely leading to decreased end products. Glutamate dehydrogenase (K00260) catalyzes the reversible conversion of 2oxoglutarate and L-glutamate [16] and decreased nutrient concentrations inhibited the activity of glutamate dehydrogenase when treated with air.
Metabolism of inositol phosphate is used to synthesize inositol phosphate (Fig. 5) that can be used as a second messenger for a variety of extracellular signals [17]. Inositol-1-phosphate synthase (K01858) catalyzes the conversion of D-glucose-6-phosphate to 1L-inositol-1-phosphate, with an intermediate product of 1D-inositol-3-phosphate [18]. When nutrient concentrations were lowered, the activity of inositol-1phosphate synthase was inhibited, thereby reducing 1D-inositol-3-phosphate concentrations.
Malonate-semialdehyde dehydrogenase (K00140) catalyzes the oxidation of malonate semialdehyde (MSA) to acetyl-CoA [21]. The lower nutrient concentration treatment led to the inhibition of malonate-semialdehyde dehydrogenase activity. Triose phosphate isomerase (K01803) regulates the rapid balancing of dihydroxyacetone phosphate and glyceraldehyde-3-phosphate produced by aldolase during glycolysis [22], and decreased nutrient concentrations led to inhibition of its activity.
In summary, decreased nutrient concentrations inhibited the metabolic pathways of taurine and hypotaurine, thereby likely reducing the production of taurine and hypotaurine, and potentially enhancing the impact of harmful oxidants on cells. At the same time, these decrease also inhibit the metabolism of inositol phosphate and reduce the synthesis of inositol phosphate, potentially leading to losses of extracellular signaling and inhibiting cell growth and metabolism. Consequently, these results indicate that bacteria require su cient nutrient levels to secure their own growth and reproduction requirements.

Analysis Of Metabolic Pathways Differentially Expressed under CNH vs ANH Conditions
Galactose metabolism involves the conversion of polysaccharides into monosaccharides like galactose and glucose. Galactose also exhibits a strong inhibitory effect on cell growth [23]. Galactokinase (K00849) catalyzes the conversion of α-D-galactose into galactose 1-phosphate (Fig. 6) [24]. The carbon dioxide-treated condition in the CNH and ANH treatments led to the enhancement of galactokinase activity, leading to increased levels of galactose 1-phosphate. UTP-glucose-1-phosphate uridylyltransferase (K00963) catalyzes the synthesis of UDP-glucose from glucose-1-phosphate and UTP [25]. However, in the carbon dioxide vs air treatment with high nutrients, the carbon dioxide-treatment conditions reduced the activity of the transferase.  [29]. When comparing the CNH and ANH conditions, the carbon dioxide-treated conditions inhibited the activity of maltogenic amylase, thereby likely leading to reduced levels of glucose production. 6phosphofructokinase 1 (K00850) catalyzes the conversion of 6-phosphate fructose to 1,6-diphosphate [30].
Carbon dioxide treatment also enhanced the activity of 6-phosphofructokinase 1 in the CNH vs ANH comparisons, likely leading to increased conversion e ciency of the above product.
Overall, changes of enzyme activity in the CNH vs ANH conditions led to increased galactose content, thereby inhibiting cell growth, with bacteria likely growing better in air-treated conditions.

Analysis of Metabolic Pathways Differentially Expressed under ONH vs ANH Conditions
Galactose metabolism converts polysaccharides into monosaccharides like galactose and glucose (Fig. 7).

Glucose 4-epimerase (K01784) catalyzes the mutual conversion of UDP-galactose and UDP-glucose [26].
Oxygen treatment enhanced the isomerase activity compared to the air-treated conditions and thus, likely the overall conversion e ciency of this reaction. Glutathione phosphate (K01835) is an enzyme necessary for the mutual conversion of glucose 1-phosphate and glucose 6-phosphate [27]. The oxygen-treatment in the ONH vs ANH treatment apparently enhanced the activity of glutathione phosphate, which would lead to increased transformation e ciency of the above reaction. Maltose amylase (K12047) converts glucan derived from starch decomposition into glucose [29], and oxygen treatment enhances the activity of maltogenic amylase and thus, the likely production of glucose when comparing the ONH and ANH conditions. Cysteine dioxygenase (K00456) sulfonates and oxidizes cysteine to cysteine sul nic acid (Fig. 8) [31] and catalyzes the transformation of cysteine to 3-sul nyl-L-alanine in this metabolic pathway. Oxygen addition increased the expression of cysteine dioxygenase compared with the air-ventilated condition. Glutamate decarboxylase (K01580) catalyzes the transformation of 3-sul nyl-L-alanine to hypotaurine, but also catalyzes the transformation of L-cysteine to taurine [14]. Oxygen inhibited the activity of glutamate decarboxylase in the ONH vs ANH comparison, which would result in a decrease in the products hypotaurine and taurine. γ-glutamyl transpeptidase (K00681) can catalyze the transfer of γ-glutamyl to other amino acids and peptides, while catalyzing the formation of 5-glutamyl-taurine from taurine via this metabolic pathway [15]. Oxygen also inhibited the activity of γ-glutamyl transpeptidase, which would result in decreased reaction products. Glutamate dehydrogenase (K00260) can catalyze the reversible conversion of 2-oxoglutarate and Lglutamate [16] and its activity was up-regulated by oxygen treatment compared with the air-ventilated condition.
In conclusion, oxygen-treatment conditions compared to air-treatment conditions promote the metabolism of galactose, accelerate polysaccharide degradation e ciency and provide additional nutrients for bacterial growth. Thus, bacteria would exhibit better survival under oxygen treatment conditions. At the same time, oxygen will reduce the production of taurine and hypotaurine compared with air-treatment conditions. Thus, taurine and hypotaurine content will increase under air-treated conditions, potentially due to the presence of harmful oxidants present in air relative to exposure to only oxygen. Increasing taurine and hypotaurine content will inhibit the effect of harmful oxidants on cells.

Analysis of Metabolic Pathways Differentially Expressed under COH vs OOH Conditions
Inositol-1-phosphate synthase (K01858) catalyzes the conversion of D-glucose-6-phosphate into 1L-inositol-1phosphate, forming the intermediate product of 1D-inositol-3-phosphate ( Fig. 9) [18]. Compared with oxygentreated condition, carbon dioxide treatment enhances the activity of inositol-1-phosphate synthase, which in turn increases 1D-inositol-3-phosphate levels. Phosphatidylinositol 4-kinase A (K00888) catalyzes the conversion of PtdIns to 4-phosphate PtdIns [19]. The COH treatment enhanced the activity of phosphatidylinositol 4-kinase A compared to the OOH condition and would lead to increased product levels. Malonate-semialdehyde dehydrogenase (K00140) catalyzes the oxidation of malonate semialdehyde (MSA) to acetyl-CoA [21]. Compared with oxygen-treated conditions, carbon dioxide inhibited the activity of malonate-semialdehyde dehydrogenase. Triose phosphate isomerase (K01803) regulates the rapid balancing of dihydroxyacetone phosphate and glyceraldehyde-3-phosphate that are produced by aldolase in the glycolysis process [22]. Compared with the OOH condition, COH conditions will inhibit the activity of triose phosphate isomerase.
In conclusion, the COH condition increased the synthesis capacity for inositol phosphate compared to OOH conditions, which resulted in increased extracellular signal transmission. Thus, carbon dioxide treatments would lead to unfavorable factors against bacterial growth and reproduction, with cells needing to transmit increasing levels of signals to regulate growth and metabolism.

Analysis of Metabolic Pathways Differentially Expressed under COH vs CNH Conditions
A series of enzymes are needed to transform monosaccharides like L-sorbose and D-allose into fructose, mannose, and glucose. Sorbose reductase (K17742) converts L-sorbose into D-sorbitol (Fig. 10) [32]. When oil was added as the carbon source, sorbose reductase activity is enhanced and the conversion rate likely increases. Hexokinase (K00844) phosphorylates glucose [28] and catalyzes fructose and mannose conversion to fructose 6-phosphate and mannose 6-phosphate, respectively. When oil was added as the carbon source, hexokinase activity was inhibited. Mannose-1-phosphate guanylyltransferase (K00966) catalyzes the reaction of mannose-1-phosphate and GTP to produce GDP mannose [33]. When oil was added as the carbon source, transferase activity was inhibited. Mannose-6-phosphate isomerase (K01809) catalyzes the mutual conversion of mannose 6-phosphate (Man-6-P) and fructose 6-phosphate (Fru-6-P) [34], and adding oil as the carbon source inhibited the activity of the isomerase, thereby restricting this mutual conversion activity. Fructose 2,6-diphosphate is a signal molecule that controls glycolysis, and 6-phosphate fructose-2-kinase (K00900) catalyzes the synthesis of fructose 6-phosphate into fructose 2,6-diphosphate [35]. When oil was added as the carbon source, 6-phosphofructose-2-kinase activity was inhibited. Fructose-1,6-bisphosphatase I (K03841) catalyzes the conversion of fructose 1,6-diphosphate into fructose 6phosphate [36]. When oil was added as the carbon source, the activity of fructose-1,6-bisphosphatase I was inhibited and the conversion to fructose 6-phosphate would have thus been reduced. 6-phosphofructokinase 1 (K00850) catalyzes the conversion of 6-phosphate fructose to 1,6-diphosphate [30], but adding oil as the carbon source inhibited the activity of 6-phosphofructokinase 1. Fructose-bisphosphate aldolase (K01623) catalyzes the condensation of glucose-3-phosphate and dihydroxyacetone phosphate to form fructose 1,6diphosphate [37]. Under the oil addition treatment, the activity of fructose-bisphosphate aldolase was inhibited, resulting in a likely decrease of fructose 1,6-diphosphate products. Triose phosphate isomerase (K01803) regulates the rapid balancing of dihydroxyacetone phosphate and glyceraldehyde-3-phosphate produced by aldolase during glycolysis [22]. When oil was added as the carbon source, the activity of triose phosphate isomerase increased and the mutual conversion rate likely increased. Dihydroxyacetone kinase (K00863) phosphorylates fructose-derived glyceraldehyde to produce glyceraldehyde-3-phosphate [38]. When oil was added as the carbon source, the activity of dihydroxyacetone kinase was inhibited, likely leading to a decrease in product formation.
Inositol-1-phosphate synthase (K01858) catalyzes the conversion of D-glucose-6-phosphate to 1L-inositol-1phosphate (Fig. 11), with the intermediate product being 1D-inositol-3-phosphate [18]. When oil was added as the carbon source, inositol-1-phosphate synthase activity was inhibited, thereby reducing the amount of 1Dinositol-3-phosphate that was produced. Phosphatidylinositol 4-kinase A (K00888) catalyzes the conversion of phosphatidylinositol (PtdIns) into 4-phosphate PtdIns [19]. Upon oil addition treatment, inhibited activity of phosphatidylinositol 4-kinase A would result in decreased product levels. 1-phosphatidylinositol-4-phosphate 5-kinase (K00889) catalyzes the synthesis of 4-phosphate PtdIns to 4,5-bisphosphate PtdIns [39], and decreased nutrient concentrations inhibited the activity of 1-phosphatidylinositol-4-phosphate 5-kinase. Phosphatidylinositol 3-kinase (K00914) catalyzes the transformation of PtdIns to produce 3-phosphate PtdIns [40], while the addition of oil as a carbon source inhibited the activity of phosphatidylinositol 3-kinase, thereby likely decreasing the levels of the product PtdIns. 1-phosphatidylinositol-3-phosphate 5-kinase (K00921) catalyzes the conversion of 3-phosphate PtdIns to PtdIns-3,5-P(2) [20], and when oil was added as the carbon source, the activity of 1-phosphatidylinositol-3-phosphate 5-kinase was inhibited, likely resulting in a decrease in its product. Malonate-semialdehyde dehydrogenase (K00140) catalyzes the oxidation of malonate semialdehyde (MSA) to acetyl-CoA [21]. When oil was added as the carbon source, the activity of malonatesemialdehyde dehydrogenase was inhibited. Triose phosphate isomerase (K01803) regulates the rapid balancing of dihydroxyacetone phosphate and glyceraldehyde-3-phosphate that are produced by aldolase during glycolysis [22]. When oil was added as a carbon source, the activity of triose phosphate isomerase was enhanced. Inositol oxygenase (K00469) is the only mechanism to catabolize inositol, wherein it catalyzes the cleavage of the inositol ring and transfers an oxygen atom to it [41]. This metabolism catalyzes the decomposition of inositol into glucuronate and the addition of oil as a carbon source inhibited the activity of inositol oxygenase, thereby likely reducing the decomposition e ciency of inositol.
Overall, the addition of oil as a carbon source led to the inhibition of fructose and mannose metabolism and the concomitant decrease in fructose and mannose production. Thus, the ability of populations to consume sugar for survival will be lessened under such conditions, and oil will instead be degraded for energy conservation. Concomitantly, the addition of oil as the carbon source will inhibit the metabolism of inositol phosphate and reduce its synthesis, leading to the loss of extracellular signaling, thereby inhibiting cell growth along with metabolism and other activities. Thus, the addition of oil results in counterproductive effects on the growth and reproduction of bacteria.

Conclusions
This study investigated the transcriptomic responses of seawater microbial communities that were collected from near a drilling platform in Bohai Bay in response to varying enrichment incubations. We speci cally evaluated the transcription of enzyme-encoding genes and their related metabolic pathways that were associated with hydrocarbon metabolism and energy conservation. The enrichment culture cells and their metabolic activities exhibited differential adaptations to the enrichment conditions and exhibited different responses to aerobic and anaerobic culture conditions. Metabolic pathway transcription and functional gene analyses suggested that high-nutrient, oil-free, and aerobic culture conditions largely promoted the growth and reproduction of marine microbial populations. Understanding how these microorganisms may degrade hydrocarbons is an important focus for helping to remediate oil spill ecological problems. These results can help develop remediation protocols for oil spills.

Declarations
Biochemical Journal 360:313-320. https://doi.org/10.1042/bj3600313 Tables   Table 1 Setting of cultivation conditions for response of microbial communities near offshore drilling platforms to conditional changes  Table 3 The twenty most down-regulated genes in the transcriptomes of marine petroleum hydrocarbon-degrading bacterial populations under different enrichment conditions.  Figure 1 Comparisons of uorescence intensities for eight probe hybridization activities of cells in the presence of oil under high-and low-nutrient conditions. The x-axis shows cultivation time, while the y-axis shows uorescence intensity. The three treatments of air-ventilated, carbon dioxide-ventilated, and oxygen-ventilated conditions are shown as different vertical panels, while the eight horizontal sub-panels represent each of the eight gene probes. Red bars show values for high-nutrient conditions and blue bars show those for lownutrient conditions. Columns show average uorescence intensities, and the error bars represent the 95% con dence interval. Gene 1: znuA, gene 2: phoB, gene 3: nqrF, gene 4: rubB, gene 5: znuB, gene 6: modA, gene 7: gltX, and gene 8: ectA. Comparisons of uorescence intensities for eight probe hybridization activities of cells in the absence of oil under high-and low-nutrient conditions. The x-axis shows cultivation time, while the y-axis shows uorescence intensity. The three treatments of air-ventilated, carbon dioxide-ventilated, and oxygen-ventilated conditions are shown as different vertical panels, while the eight horizontal sub-panels represent each of the eight gene probes. Red bars show values for high-nutrient conditions and blue bars show those for lownutrient conditions. Columns show average uorescence intensities, and the error bars represent the 95% con dence interval. Gene 1: znuA, gene 2: phoB, gene 3: nqrF, gene 4: rubB, gene 5: znuB, gene 6: modA, gene 7: gltX, and gene 8: ectA.   Galactose metabolic pathways and differences in expression under the CNH vs ANH conditions. The color legend in the upper right corner indicates red values for level of gene upregulation and green for gene downregulation, as indicated for differentially expressed genes within the pathway map. Galactose metabolic pathways and differences in expression under the ONH vs ANH conditions. The color legend in the upper right corner indicates red values for level of gene upregulation and green for gene downregulation, as indicated for differentially expressed genes within the pathway map.