Method for detecting corrosive microorganisms that induce microbiological corrosion using set of synthetic oligonucleotides

Abstract

FIELD: biotechnology.SUBSTANCE: method for detecting dominant strains of corrosive microorganisms Desulfobulbus propionicus, Desulfovibriovulgaris, Desulfomicrobiumbaculatum, Desulfobacterpostgatei, Desulfotomaculumruminis, Desulfovibriodesulfuricans is described. It consists of the stages of extraction of total genomic DNA of samples, quantitative PCR amplification using synthesized pairs of oligonucleotide sequences and fluorescence detection.EFFECT: ability to detect these strains using unique oligonucleotide sequences for fragments of the 16S ribosomal RNA gene.2 cl, 4 tbl, 2 ex

Description

[0001] Field of technology to which the invention relates

[0002] The invention relates to the field of biotechnology, namely to a method for the quantitative detection of dominant strains of corrosive microorganisms characteristic of objects of production, transportation and storage of oil and petroleum products.

[0003] Technology Level

[0004] Classical approaches to detecting corrosive microorganisms are culture-based methods, which primarily involve qualitative analysis to detect iron sulfide precipitates formed on selective nutrient media as a result of the microorganisms' activity. It should be noted that this method is effective only for cultured forms of microorganisms, eliminating the specificity of the analysis for non-cultured forms. The transition of industrial practice for monitoring corrosive microorganisms to accurate and relatively rapid molecular genetic analysis requires the selection of an optimal detection method that combines analytical precision and relative ease of implementation in industrial practice.

[0005] Methods for monitoring microbiologically induced corrosion are known using a specialized high-performance platform for analyzing culture media inoculated with samples of corrosive microorganisms, using colorimetric measurement (US patent 20150119286 A1, published April 30, 2015) and electrochemical measurement (CN patent 211871940 U, ​​published November 6, 2020). A disadvantage of these methods is the lack of species identification of corrosion-active strains, which complicates the subsequent selection of a bactericide effective against a specific strain.

[0006] A monitoring method (US Patent 11035009 B2, published June 15, 2021) is known, which also aims to achieve high analytical throughput, but in this case, using biochips. A distinctive feature of the process is the inclusion of microorganisms in the target list that not only induce microbiological corrosion but also inhabit the same consortium. A disadvantage of this method is the relative high cost of biochips for routine analysis of a thousand or more samples.

[0007] A known monitoring method (patent CN 103088133 B, published May 20, 2015) utilizes polymerase chain reaction for the rapid quantitative detection of corrosive microorganisms. However, this method is only applicable to a single sulfate-reducing thermophilic bacterium, limiting its applicability to other corrosive strains.

[0008] Among the closest analogs, a method for monitoring microbiologically induced corrosion (patent WO 2016145329 A1, published September 15, 2016) stands out as a prototype technological approach. This method involves quantitative PCR analysis of a wide range of corrosion-active strains with unique oligonucleotide sequences serving as PCR primers. However, this monitoring method is labor-intensive for industrial use due to the large number of targets to be detected. Furthermore, this method lacks the ability to interpret the obtained quantitative data to determine the level of corrosion stress and select strain-specific bactericides.

[0009] The proposed invention solves the problem of optimizing quantitative monitoring of corrosive microorganisms typical of oil wells by implementing quantitative PCR analysis for several of the most common (dominant, target) strains. The technical result of the invention is a method for detecting these strains using unique oligonucleotide sequences for fragments of the 16S ribosomal RNA gene.

[0010] Essence of the invention

[0011] The invention provides an optimal method for detecting corrosive microorganisms typical of the oil industry for routine use. To regularly assess the level of corrosion load on a large number of samples and quickly decide on the initiation of bactericidal treatment, a method is needed to identify microbiologically induced corrosion by the dominant (target) strains typical of oil production, transportation, and storage facilities. The proposed method is less labor-intensive and more accurate in identifying the identified strains.

[0012] The present invention involves the use of a method based on quantitative PCR analysis with unique synthetic oligonucleotides (forward and reverse primers, oligonucleotide probes) followed by detection by fluorescence or hybridization-fluorescence detection. The claimed nucleotide sequences for fragments of the 16S ribosomal RNA gene of Desulfobulbus propionicus, Desulfovibrio vulgaris, Desulfomicrobium baculatum, Desulfobacter postgatei, Desulfotomaculum ruminis, Desulfovibrio desulfuricans exclude the risk of dimer formation and are presented in Table 1 and in the Sequence Listing.

[0013]

[0014]

[0015] The method is implemented by preliminary extraction of total genomic DNA of 6 declared corrosive microorganisms from the aqueous phase of samples collected at oil production, transportation, and storage facilities (produced water, water washouts). The isolated DNA is used as a template for real-time quantitative polymerase chain reaction and fluorescence or hybridization-fluorescence detection. Interpretation is based on the obtained threshold cycle value and the value obtained by calibration according to Table 2.

[0016]

[0017]

[0018] Information confirming the possibility of implementing the invention

[0019] Example 1

[0020] The invention was validated on samples of formation water collected from oil production sites. The invention can be implemented sequentially: with bacterial culture lysis, total genomic DNA extraction, amplification, and detection of target strains.

[0021] At the first stage, the bacterial culture was lysed using buffer solution A (sodium dodecyl sulfate, 1.5% (w / v); Triton X-100, 7% (v / v); dissolved in TE buffer). 180 μl of lysis buffer solution A were added to one 300 μl sample, and the solution was incubated at 70°C for 7 minutes in a solid-state thermostat. The resulting lysate was used to isolate total genomic DNA by magnetic separation. The lysate was transferred to tubes with a suspension of magnetic particles, and binding buffer solution B (sodium chloride, 1.25 M; PEG-400, 10%; dissolved in TE buffer) was added. The solution was incubated at room temperature for 5 minutes to adsorb DNA onto the particles, the DNA pellet with magnetic particles was immobilized using a magnetic stand, and the resulting supernatant was removed.Genomic DNA was purified using wash solutions C1 and C2 (95% and 70% ethyl alcohol, respectively), and a DNA pellet with magnetic particles was immobilized. The supernatant was removed, and the pellet was dried for 5 minutes at room temperature. Genomic DNA was eluted with elution buffer D (TAE buffer, 1X). After incubation for 1 minute at room temperature, the DNA pellet with magnetic particles was immobilized, the supernatant (eluate) was collected, and used as a template in the second step.

[0022] The second stage involved real-time PCR amplification using the intercalating fluorescent dye SYBR Green in a PCR mix with hot-start polymerase (Lumiprobe, Russia). Reaction mixture components for each dominant (target) strain were prepared in separate tubes with the calculated amount of nuclease-free water added, as shown in Table 3. Working solutions for synthetic oligonucleotides were prepared by dilution in TE buffer.

[0023]

[0024]

[0025]

[0026]

[0027] Quantitative PCR analysis was performed using a real-time amplifier with fluorescence detection mode in the SYBR channel according to the program indicated in Table 4.

[0028]

[0029] At the third stage, an evaluation of the obtained threshold cycle value was carried out with the corrosion load level stated earlier in Table 2.

[0030] Example 2

[0031] The method is similar to example 1, but with the addition of oligonucleotide probes SEQ ID NO: 3 to reaction mixture No. 1, SEQ ID NO: 6 - No. 2, SEQ ID NO: 9 - No. 3, SEQ ID NO: 12 - No. 4, SEQ ID NO: 15 - No. 5, SEQ ID NO: 18 - No. 6.

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[0384] <insdqualifier id="q50">

[0385] <INSDQualifier_name>organism< / INSDQualifier_name>

[0386] <INSDQualifier_value>synthetic construct< / INSDQualifier_value>

[0387] < / insdqualifier>

[0388] < / INSDFeature_quals>

[0389] < / insdfeature>

[0390] < / INSDSeq_feature-table>

[0391] <INSDSeq_sequence> tcagcatcctccaccgac< / INSDSeq_sequence>

[0392] < / insdseq>

[0393] < / sequencedata>

[0394] <sequencedata sequenceidnumber="15">

[0395] <insdseq>

[0396] <INSDSeq_length> 23< / INSDSeq_length>

[0397] <INSDSeq_moltype> DNA< / INSDSeq_moltype>

[0398] <INSDSeq_division> PAT< / INSDSeq_division>

[0399] <INSDSeq_feature-table>

[0400] <insdfeature>

[0401] <INSDFeature_key>source< / INSDFeature_key>

[0402] <INSDFeature_location>1..23< / INSDFeature_location>

[0403] <INSDFeature_quals>

[0404] <insdqualifier>

[0405] <INSDQualifier_name>mol_type< / INSDQualifier_name>

[0406] <INSDQualifier_value>other DNA< / INSDQualifier_value>

[0407] < / insdqualifier>

[0408] <insdqualifier id="q51">

[0409] <INSDQualifier_name>organism< / INSDQualifier_name>

[0410] <INSDQualifier_value>synthetic construct< / INSDQualifier_value>

[0411] < / insdqualifier>

[0412] < / INSDFeature_quals>

[0413] < / insdfeature>

[0414] < / INSDSeq_feature-table>

[0415] <INSDSeq_sequence> agattatgcgaaccggtgtggat< / INSDSeq_sequence>

[0416] < / insdseq>

[0417] < / sequencedata>

[0418] <sequencedata sequenceidnumber="16">

[0419] <insdseq>

[0420] <INSDSeq_length>23< / INSDSeq_length>

[0421] <INSDSeq_moltype>DNA< / INSDSeq_moltype>

[0422] <INSDSeq_division>PAT< / INSDSeq_division>

[0423] <INSDSeq_feature-table>

[0424] <insdfeature>

[0425] <INSDFeature_key>source< / INSDFeature_key>

[0426] <INSDFeature_location>1..23< / INSDFeature_location>

[0427] <INSDFeature_quals>

[0428] <insdqualifier>

[0429] <INSDQualifier_name>mol_type< / INSDQualifier_name>

[0430] <INSDQualifier_value>other DNA< / INSDQualifier_value>

[0431] < / insdqualifier>

[0432] <insdqualifier id="q52">

[0433] <INSDQualifier_name>organism< / INSDQualifier_name>

[0434] <INSDQualifier_value>synthetic construct< / INSDQualifier_value>

[0435] < / insdqualifier>

[0436] < / INSDFeature_quals>

[0437] < / insdfeature>

[0438] < / INSDSeq_feature-table>

[0439] <INSDSeq_sequence>ttgactagctacattgcccagac< / INSDSeq_sequence>

[0440] < / insdseq>

[0441] < / sequencedata>

[0442] <sequencedata sequenceidnumber="17">

[0443] <insdseq>

[0444] <INSDSeq_length> 19< / INSDSeq_length>

[0445] <INSDSeq_moltype> DNA< / INSDSeq_moltype>

[0446] <INSDSeq_division> PAT< / INSDSeq_division>

[0447] <INSDSeq_feature-table>

[0448] <insdfeature>

[0449] <INSDFeature_key>source< / INSDFeature_key>

[0450] <INSDFeature_location>1..19< / INSDFeature_location>

[0451] <INSDFeature_quals>

[0452] <insdqualifier>

[0453] <INSDQualifier_name>mol_type< / INSDQualifier_name>

[0454] <INSDQualifier_value>other DNA< / INSDQualifier_value>

[0455] < / insdqualifier>

[0456] <insdqualifier id="q53">

[0457] <INSDQualifier_name>organism< / INSDQualifier_name>

[0458] <INSDQualifier_value>synthetic construct< / INSDQualifier_value>

[0459] < / insdqualifier>

[0460] < / INSDFeature_quals>

[0461] < / insdfeature>

[0462] < / INSDSeq_feature-table>

[0463] <INSDSeq_sequence> ttattcccagggcgctttg< / INSDSeq_sequence>

[0464] < / insdseq>

[0465] < / sequencedata>

[0466] <sequencedata sequenceidnumber="18">

[0467] <insdseq>

[0468] <INSDSeq_length>20< / INSDSeq_length>

[0469] <INSDSeq_moltype>DNA< / INSDSeq_moltype>

[0470] <INSDSeq_division>PAT< / INSDSeq_division>

[0471] <INSDSeq_feature-table>

[0472] <insdfeature>

[0473] <INSDFeature_key>source< / INSDFeature_key>

[0474] <INSDFeature_location>1..20< / INSDFeature_location>

[0475] <INSDFeature_quals>

[0476] <insdqualifier>

[0477] <INSDQualifier_name>mol_type< / INSDQualifier_name>

[0478] <INSDQualifier_value>other DNA< / INSDQualifier_value>

[0479] < / insdqualifier>

[0480] <insdqualifier id="q54">

[0481] <INSDQualifier_name>organism< / INSDQualifier_name>

[0482] <INSDQualifier_value>synthetic construct< / INSDQualifier_value>

[0483] < / insdqualifier>

[0484] < / INSDFeature_quals>

[0485] < / insdfeature>

[0486] < / INSDSeq_feature-table>

[0487] <INSDSeq_sequence>tcgacgcgatcgcccgtaat< / INSDSeq_sequence>

[0488] < / insdseq>

[0489] < / sequencedata>

[0490]

[0491] <---

Claims

1. A method for detecting dominant strains of the corrosion-active microorganisms Desulfobulbus propionicus, Desulfovibrio vulgaris, Desulfomicrobium baculatum, Desulfobacter postgatei, Desulfotomaculum ruminis, Desulfovibrio desulfuricans, consisting of the stages of extraction of total genomic DNA of samples, quantitative PCR amplification using synthesized pairs of oligonucleotide sequences of SEQ ID NO: 1 - SEQ ID NO: 2; SEQ ID NO: 4 - SEQ ID NO: 5; SEQ ID NO: 7 - SEQ ID NO: 8; SEQ ID NO: 10 - SEQ ID NO: 11; SEQ ID NO: 13 - SEQ ID NO: 14; SEQ ID NO: 16 - SEQ ID NO: 17; respectively, by real-time fluorescence detection using the intercalating dye SYBR and determining the corrosion load level by comparing the obtained threshold cycle value and the value obtained by calibration.

2. The method according to paragraph 1, characterized in that hybridization-fluorescence detection is carried out with the additional use of probes for each dominant strain according to paragraph 1 with the sequences SEQ ID NO: 3, SEQ ID NO: 6, SEQ ID NO: 9, SEQ ID NO: 12, SEQ ID NO: 15, SEQ ID NO: 18, respectively.

Images