Studying Composition of Bacteriobenthic Communities in the Sediments of Water Ecosystems by Fatty Acid Markers

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ISSN 1995-0829, Inland Water Biology, 2015, Vol. 8, No. 3, pp. 242–249. © Pleiades Publishing, Ltd., 2015.


Studying Composition of Bacteriobenthic Communities

in the Sediments of Water Ecosystems by Fatty Acid Markers

  1. G. Sheryshevaa, G. A. Osipovb, and V. V. Khalkoc

aInstitute of Ecology of the Volga River Basin, Russian Academy of Sciences, ul. Komzina 10, Togliatti, 445003, Russia

bGroup of Academician Y.F. Isakov, Bakoulev Center for Cardiovascular Surgery, Academy of Medical Sciences,

Rublevskoe shosse 135, Moscow, 121552 Russia

cInstitute for Biology of Inland Waters, Borok, 152742 Russia

Received April 18, 2014



The structure and function of bacterial communities in sediments of aquatic ecosystems have been considered using the molecular method of gas chromatography—mass spectrometry (GC–MS). Specific substances of microbial origin have been discovered in the samples and assigned to most probable genera or species. The local bank of microbial markers has been designed for lake silts. The composition of bacteri- obenthic community is determined quantitatively using the algebra algorithm of decomposition of the total fatty acids profile into individual taxonomic components.

Keywords: bottom microbial community, taxonomic composition, fatty acid markers, lake sediments
DOI: 10.1134/S1995082915030128


In studies of the structure and functioning of benthic bacterial communities of aquatic ecosystems, the use of methods of quantitative estimation is urgent. One that is promising in this respect and intensively elaborated over the last few years is the method of gas chromatography–mass spectrometry (GC–MS) making it possible—by the composition of fatty acids, aldehydes, and hydroxy acids of the cellular wall of microorganisms—to estimate their taxonomic belonging.
The method of mass spectrometry of microbial markers (MSMM) is widely used in studies of the tax- onomic diversity of different microbial communities. Bacteria differ in composition of fatty acids and alde- hydes from plants and animals, as well as from organic substance of the habitation medium. The genus and species specificity of the composition of fatty acids, as well as its interlaboratory reproducibility, are shown. The results of studies on identifying and characterizing ecologically significant procaryotes of the oil sub- strate, sediments of freshwater lakes and marine eco- systems, and microbial mats have been published  [7, 12, 20, 22].
The considered method (GC–MS) is based on a highly accurate determination of marker molecules entering the composition of cellular lipids of microor- ganisms. The presence of specific substances from the number of cellular components and metabolites of microorganisms allows not only qualitative, but also a quantitative estimation of the structure of bacterial communities [2, 19].
The considerable advantage of GC–MS when identifying the taxonomic composi- tion of microbiocenoses is that they do not require the isolation of viable cells from the sample and their cul- tivation on selective media. The species composition of the microbial community is determined by analyz- ing the lipid fraction of the total biomass.
Using the GC–MS method, studies of quantitative characteristics of silty communities of microorgan- isms of magnetic model systems on natural material from water bodies of Astrakhan oblast were performed [9]. Recently, the GC–MS method has been used to determine the structure of microbial communities of marine bottom sediments of the Sea of Japan [25]. Different groups of microorganisms of deepwater lips and bottom sediments in Lake Baikal were identified [1]. Previously we studied the enrichment cultures of iron-reducing bacteria and experimentally revealed leading ecological-trophic groups of bacteria exercis- ing anaerobic Fer(III) reduction at the oxidation of glucose, hydrogen, and methane [5, 10, 11].
The purpose of the study is to determine the taxo- nomic composition of bacterial communities in bot- tom sediments of lake ecosystems using GC–MS.


Samples of silts were taken from polytypic water bodies of Samara oblast—the bend of the Volga River in its middle current and Volzhsko-Kama State Nature Biosphere Reserve. Sulfur, karst lakes, and meromictic water bodies with different contents of iron, humus, sulfates, and organic matter in silts were studied.
To study the taxonomic structure of bacteri- obenthic communities, GC–MS with the reconstruc- tion of the composition of microorganisms (MSMM) was used, making it possible to determine the genus (and sometimes species) of bacteria with numbers of >10 cells per 1 g of dry silt. Analysis was performed on an AT 6850/5973 gas chromatograph–mass spec- trometer of the company Agilent Technologies in the laboratory of the academic group of Academician of the Russian Academy of Medical Sciences Yu.F. Isa- kov. The mass spectrometer is quadrupole, with a mass range  2–550  amu,  and  has  a  resolving  power  of 0.5 amu in the entire operating range. Ionization by electrons is 70 eV. Sensitivity of the device is 0.01 ng by methyl stearate. For chromatographic separation of the sample, a capillary column from molten quarts with a length of 25 m and inner diameter of 0.25 μm was used. The immobile phase of HP-Sins Hewlett- Packard has a layer thickness of 0.25 μm. Chromatog- raphy was performed in the mode of temperature pro- gramming from 120 to 320°C with a rate of 7°/min. Temperature of injector and interface was 280°C. Data were processed using regular programs of the device. Upon identification of substances in chromatographic peaks, library programs with data files of mass spectra of NIST were used. The composition of microbial communities was calculated in EXCEL electron tables using an elaborated algorithm of calculation [2, 19].
For a microbiological confirmation of express- method MSMM of the identification of the composi- tion of bacteriobenthos, inoculations were performed for the target separation of isolates of organotrophic microorganisms from communities of polytypic lake silts located on the territory of Samarskaya Luka. Enrichment bacterial cultures were prepared using anaerobic cultivation [13]: 10% of silt was placed from the ground column immediately before the selection of the samples into small bottles with anaerobically prepared nutrient media for ammonificating, fermen- tary, and lactate- and acetate-oxidizing bacteria [4, 6]. Pure cultures of bacteria were obtained from enrich- ment cultures as a result of the repeated transplanta- tion of isolated colonies. The purity of bacterial cul- tures was controlled microscopically [8]. The isolated microorganisms were identified by the composition of cellular fatty acids on a Sherlock bacterial analyzer (Sherlock Microbial Identification System, MIDI Inc., Delaware, United States). Bacterial biomass (40–60 mg) from the agar surface was subjected to acid methanolysis in 1 M HCl (0.4 mL) for 1 h at a temperature of 80°C. As a result of methanolysis, fatty acids were freed from lipids of cellular membrane and liposaccharids of the cellular wall as methyl ethers. They were twice extracted by 200 μL of hexane and the solution was boiled up to 60 μL. Identification of the species of microorganisms was performed automati- cally according to the program of the device upon a comparison of the obtained profile of fatty acids with the data base including ~2000 strains of microorganisms. A total of 22 analyses of enrichment and pure cultures of iron-reducing microorganisms with the subsequent identification of taxonomic belonging were performed.


Composition of fatty acids and aldehydes of the total biomass of the silty bacterial community. An analysis of fatty-acid composition of biomass of polytypic silts of lakes revealed the presence of several substances typi- cal for bacteria. They are presented in Table 1 with the assignment to taxa of microorganisms in which these substances are present in the composition of cellular lipids. The main components of methanolysate of the lipid fraction of the studied samples were saturated and unsaturated straight-chain and branched fatty acids.
Markers BeggiatoaThiobacillusSpirochaeta, and Sphaerotilus were obtained as a result of joint studies with G.A. Dubinina. Cyanobacteria of the genera Anabaena, Aphanizomenon, and Microcystis were revealed.
Analysis of fatty-acid composition of iron-reducing bacteria. For an estimation of the amount of iron- reducing bacteria, the composition of seven species of pure cultures (FeRB Lovley) from the collection of Lovley (University of Massachusetts, United States)werestudied. They included Shewanella alga Smith et al., 1990 emend. Nozue et al., 1992, Desulfu- romonas palmitatis Coates et al., 2000, Geobacter humireducens Holmes D.E. et al., 2003, G. sukfurre- ducens Caccavo et al., 1995, G. metallireducens Lovley et al., 1995, Geothrix fermentas Coates et al., 1999, and Geovibrio ferrireducens Caccavo et al., 2000. It was found that all of them contain 2 to 5% of 11-hexade- canoic acid (16 : 1ω5), which can serve as their com- mon marker.
Analysis of isolates of organotrophic microorgan- isms cultivated on nutrient media. For a microbiologi- cal confirmation of the express method of microbial markers for the identification of the genus-composi- tion of microbial communities, an analysis of isolates of amonificating, fermenting, lactate-oxidizing, and acetate-oxidizing bacteria on agarized nutrient media was performed. Results of analysis are given in Table 2. The fatty-acid profiles of isolates are included into a database of microbial markers.


Finding biomass of fatty acids with a number of carbon atoms 12 to 19 in silt is considered a sign of bacterial biomass [24]. Some specific substances (markers) turned out typical for large taxonomic groups of microorganisms. For instance, 8-hexanode- canoic (16 : 1ω8) is mainly inherent to methanotrophic bacteria [3] and cyclotropane heptadecanoic (17cyc) to representatives of the fam.

Lipid componentTypical microorganisms
Fatty acids:
decanoic (10:0)Rhodococcus terrae
dodecanoic (12:0)Flexibacter
dodecenoic (12:1)Rhodobacter
iso-tridecanoic (i13)Xanthomonas, Bacillus subtilis
anteiso-tridecanoic (a13)Bacillus cereus, Cellulomonas
tridecanoic (13:0)No direct assignment to microorganism
iso-meristic (i14)Streptomyces, Bacillus, Spirochaeta
anteiso-meristic (a14)
9-tetradecenoic (14:1 ω7)
11-tetradecenoic (14:1 ω5)
Anabaena, Aphanizomenon, Microcystis Sphaerotilus, Clostridium
Acetobacterium, Iron reducer KM-2 (Lebedeva)
tetradecanoic (14:0)Many species of microorganisms
10-methyltetradecanoic (10Me14)Actinobacteria
iso-pentadecanoic (i15)Many species of microorganisms, Arthrobacter
anteiso-pentadecanoic (a15)Many species of microorganisms, Azotobacter, Micrococcus
pentadecenoic (15:1)Clostridium putrefaciens, Cl. sporogenes, Cl. propionicum, Geodacter humireducens
pentadecanoic (15:0)Cytophaga, Pseudomonas stutzeri
iso-hexadecenoic (i16:1)Pseudonocardia
iso-hexadecanoic (i16)Streptomyces rimosus, Bacillus coagulans
anteiso-hexadecanoic (a16) 7-hexadecenoic (16:1 ω9) 8-hexadecenoic (16:1 ω8)
cis-9-hexadecenoic (16:1 ω7c) trans-9-hexadecenoic (16:1 ω7t)
11-hexadecenoic (16:1ω5)
Anabaena Methylococcus
Methylomonas, Methylomicrobium
Many species of microorganisms, Aquaspirillum, Thiotrix, Macromonas, Leptothrix Nocardia carnea
Iron reducers
10-methylhexadecenoic (10Me16)Desulfobacter, Rhodococcus equi
iso-heptadecenoic (i17:1)Desulfovibrio, Heliobacterium
iso-heptadecanoic (i17)Bacillus, Propionibacterium
heptadecenoic (17:1)Mycobacterium (rapidly growing), Clostridium, Aquaspirillum
cyclopropane-heptadecanoic (17cyc)@. Enterobacteriaceae
anteiso-heptadecanoic (a17)Corynebacterium aquaticum, Nocardia, Micromonospora
heptadecanoic (17:0)Many species of microorganisms,
minor component
10-methyl-heptadecanoic (10Me17)Actinomadura roseola
iso-octadecanoic (i18)Sulfobacillus, Clostridium difficile
octadecadianoic (18:2)Fungi, yeast, protozoans
alpha-octadecenoic (alfa18:3)Oscillatoria, Anabaena, Aphanizomenon
gamma-octadecenoic (gamma18:3) 9-octadecenoic (18:1ω9)
cis-11-octadecenoic (18:1ω7c)
Many species of microorganisms
Pseudomonas, Caulobacter, Nitrobacter, Beggiatoa
octadecanoic (18:0)Many species of microorganisms
iso-nonadecanoic (i19)Bacillus subtilis
anteiso-nonadecanoic (a19)Caulobacter
cyclonodecanoic (19cyc)Agrobacterium radiobacter, Ectothiorhodospira
nonadecanoic (19:0)Nitrobacter, Bacillus, Burkholderia cepacia

Table 1. (Contd.)

Lipid componentTypical microorganisms
9-eicosenoic (20:1ω9) 11-eicosenoic (20:1ω11)Actinomyces, Thiobacillus Propionibacterium, Actinomyces
hydroxydecanoic (h10)Leptothrix
3-hydroxydecanoic (3h10)Pseudomonas putida, Hydrogenophaga
3-hydroxydodecanoic (3h11)Iron reducer FeRed (Turova, 1996)
3-hydroxydodecanoic (3h12)Pseudomonas, Beggiatoa
2-hydroxydodecanoic (2h12)Pseudomonas
3-hydroxy-iso-tridecanoic (3hi13)Xanthomonas
3-hydroxy-anteiso-tridecanoic (3ha13)No direct assignment to microorganism
3-hydroxytridecanoic (3h13)Bacteroides hypermegas
3-hydroxy-iso-tetradecanoic (3hi14)No direct assignment to microorganism
3-hydroxy-tetradecanoic (3h14)Aeromonas, Burkholderia
3-hydroxy-iso-pentadecanoic (3hi15)Flavobacterium, Cytophaga, Flexibacter
3-hydroxy-anteiso-pentadecanoic (3ha15)Cytophaga, Flexibacter
2-hydroxy-iso-pentadecanoic (2hi15)Azospirillum, Flexibacter
3-hydroxy-pentadecanoic (3h15)Strains ZOR-1/Zor-2
2-hydroxy-pentadecanoic (2h15)Sphingomonas
3-hydroxy-hexadecanoic (3h16)Cytophaga, Flexibacter; Cyanobacteria
3-hydroxy-iso-heptadecanoic (3hi17)Flexibacter, Cytophaga
3-hydroxy-heptadecanoic (3h17)Bacteroides
3-hydroxy-octadecanoic (3h18)Acetobacter, Macromonas; Cyanobacteria
10-hydroxy-octadecanoic (10h18)Clostridium, Nocardia
3-hydroxy-iso-eicosanoic (3hi20)Chlamydia
Fatty aldehydes:
tetradecanoic (14a)Spirochaeta, Clostridium
anteiso-pentadecanoic (a15a)Butyrivibrio, Eubacterium
iso-pentadecanoic (i15a)Butyrivibrio, Propionibacteri um
iso-hexadecanoic (i16a)Eubacterium
hexadecanoic (16a)Clostridium, Acetobacterium
anteiso-heptadecanoic (a17a)Propionibacterium freudenreichii
iso-heptadecanoic (i17a)Propionibacterium, Clostridium
heptadecanoic (17a)Propionibacterium
pentadecanoic (15a)Butyrivibrio
octadecanoic (18a)Protozoa
octadecenoic (18:1а)Desulfotomaculum

Component abbreviation is given in parentheses. For instance, 16:1ω7t. Here 16 is the number of carbon atoms, the figure after the colon is the number of double bonds, and ω7t is location of double bond and molecule configuration; h is hydroacid, a and i is branch- ing, and cyc is cyclopropane acid. (For instance, 3ha15-3-hydroxy-anteiso-pentadecanoic acid).
Enterobacteraceae [2, 19]. One should particularly note the pres- ence of 2- and 3-hydroacids in biomass, indicating the presence in the community of gram-negative bacteria.
An analysis of lipid components of the sample demonstrates that some of them can be assigned to quite definite genera or even species of microorganisms. For instance, the presence of hydroaxids with 12 atoms of carbon (2-, 3-hydrodecanoic) indicates the presence of representatives of the genus Pseudomo- nas [23]. For the biomass of cyanobacteria, 5-hydrox- yhexadecanoic (3h16) and 3-hydrooxyoctadecanoic (3h18) acids are typical. As an additional marker in
Table 2. Species assignment of strains of microorganisms according to profiles of fatty acids

LakeSiltIdentified microorganismsSubstrate
Maloe Karstovoe Serebryanka
Klyukvennoe Zolotenka
Bolshoe Shelekhmetskoe Uzhinoe
Zolotenka Kharovoe
Peaty Pelitic Aleuritic
Peaty Silty sand Black silt Sandy
Silty sand Detrital silt
Burkholderia (Pseudomonas cepacia) Salmonella (@, Escherichia coli)
Streptomyces rimosus
@: S. rimosus, Pseudomonas, @. Enterobacteriaceae
Bacillus Streptomyces rimosus Bacillus
@: Bacillus, @. Enterobacteriaceae
Bacillus coagulans
Corinebacterium aquaticum
Lactate FPB
Acetate FPB
Glucose FPB

FPB is fish-peptone broth.
cyanobacteria of the genera AnabaenaAphanizome- nonMicrocystis, and Oscillatoria, fatty acids anteiso- miristine (a14), anteiso-hexalene  (a16),  and alfa18:3 and gamma18:3 octadecenoic were distin- guished [15]. The presence of branched hydroacids with 15 atoms of carbon suggests the presence of gen- era Azospirillum (our data) and Cytophaga [14]. 3-hydroxy-iso-tridecanoic (3hi13) acid is known for organisms of the genus Xanthomonas; 10-hydroxyoc- tadecanoic (10h18) acid was found in metabolites of Clostridium perfringens (Veillon and Zuber, 1898) Hau- duroy et al., 1957 and some other bacteria (including nocardia).
Of other typical fatty acids, one should note 10-methylhexadecanoic (10Me16), specific marker Rhodococcus equi (Magnusson, 1923) Goodfellow and Alderson, 1977 [18]. For another group of rhodococcs with a typical species R. terrae (Tsukamura, 1971) Tsukamura, 1974, decanoic (10 : 0) acid is typical. In the composition of silt biomass, there is a unique iso- heptadecenoic (i17 : 1) acid known in the genus Helio- bacterim and sulfate reducers of the genus Desuk- fovibrio. 10-methyl-hexadecanoic (10Me16) acid alternatively can be a marker of the genus Desulfo- bacter [21]. Using traditional microbiological meth- ods, the presence of viable bacteria Desulfovibrio vul- garis Postgate and Campbell, 1966 and Desulfobacter sp. was confirmed [19]. Branched acids (iso-miris- tine–i14, iso-hexadecanoic–i16, io-nanodecanoic– i19) with regard of their ratio should be assigned to bacteria of genera Streptomyces and Bacillus [16, 18]. Of other rare fatty acids, one should note 9-eicosenoic (20 : 1ω9), which is present in cells of actinomycetes [17] and thiobacilli (our data).
The measure of content of iron reducers in the community of microorganisms of silt can be 11-hexa- decenoic acid (16 : 1ω5) that we discovered in the composition of fatty acids mainly of lake silts. Another dissimilation iron reducer–strain Felked [19] is determined according to specific component–3-hydroxi- undecanoic (3h11) and 3-hydrotridecanoic (3h13) acids. Strain FeRed KM-2 isolated from river  silt  (I. Lebedeva, private collection) was identified according to content of 11-tetradecenoic acid 14:1ω5. The presence of iron bacterium of the genus Leptodrix in the structure of community of silts was established from the superposition of cis-9-hexadecenoic (16:1ω7c) and hydrodecanoic (h10) acids.
The remaining most probable assignments of the fatty acids to bacteria that contain them are given in Table 1.
Parallel to fatty acids and oxyacids, a large group of marker substances that significantly increase specific- ity of chemodifferentiation of microorganisms are aldehydes. For instance, anteiso-ptadecanoic (a15a) and iso-peptadecanoic (i15a) aldehydes indicate the presence of genera Butyrivibrio. Representatives of the genus Desulfotomaculum are characterized by octade- cenoic (18 : 1a) aldehyde. Other than the bacterial and actinomycetic complex, samples contain markers (aldehydes and sterols) indicating the presence of rep- resentatives of protozoans, fungi, yeast, and algae.
The list of bacteria given in Table 1 is a guiding basis for revealing possible species corresponding to one or another marker. The determination of the actual com- position of the sample of lake silt was performed by separating the aggregate profile of fatty acids into gen- era and species of organisms that compose it using the technology of reconstruction of the microbial com- munity (MCMM). This reconstruction is exemplified by the calculated composition of bacterial community (Fig. 1) dwelling in the coastal biotope of Lake Sere- bryanka–karst water body of round shape (length 42 m, area 0.11 ha, depth <1 m) on the territory of Samarskaya Luka. Bottom sediments of the lake are represented by gray oily aleuritic silt with black streaks in denser lower layers. On the top, silt is covered by a Cells × 106/g

Fig. 1. Genus (species) composition and numbers of bacteriobenthos (cells 106/g) of aleurite silt in Lake Serebryanka (Samar- skaya Luka). On the abscissa: (1) Acetobacter, (2) Acetobacterium, (3) Actinomadura roseola, (4) Actinomyces, (5) Azospirillum, (6) Bacillus subtilis, (7) Bacillus/Cellulomonas, (8) Bacteriodes hypermegas, (9) Burkholderia, (10) Butyrivibrio 1-2-13,)11) Butyr- ivibrio  1-4-11,  (12) Butyrivibrio  7S-14-3, (13)  Caulobacter,  (14) Chlamydia,  (15)  Clostridium,  (16)   Clostridium  butyricum, (17) Clostridium difficile, (18) Clostridium/Nocardia, (19) Cyanobacteria, (20) Cytophaga, (21) Desulfotomaculum, (22) Des- ulfovibrio, (23) fam. Enterobacteriaceae, (24) Eubacterium, (25) FeRB (Lovley), (26) FeRed (Turova), (27) FeRed KM-2, (28) Flexibacter, (20) Methylcoccus, (30) Micrcocus/Arthrobacter, (31) Nitrobacter, (32) Nocardia cornea, (33) Propionbacterim freudenreichii, (34) Pseudomonas fluorescens, (35) Pseudomonas putida, (36) Pseudomonas sp., (37) Pseudonocardia, (38) Rhodo- bacter, (39) Rhodococcus, (40) Rhodococcus terrae, (41) Sphingomonas, (42) Spirochata, (43) Streptomyces rimosus, (44) Xanth- omonas, and (45) ZOR-1/ZOR-2.
layer of brown oxidized detritus. Silt contains abun- dant semidecomposed fragments of aquatic vegetation and litter. In the microscopic structure of surface layer of the silt, thin detritus of plant and animal origin dominates. Ground temperature during sampling was 24.5°C, active medium reaction (pH) was 6.1, and redox potential (Eh) was +60.
The necessity in special algorithm of reconstruc- tion of the composition of microbial community stems from the fact that most marker substances (Table 1) are typical for more than two bacterial taxa; therefore, it is impossible to calculate the numbers of each of them according to one marker. In the bacteriobenthic com- munity, the superposition of profiles of fatty acids of component bacteria when there is a contribution from two or several organisms in the determined concentra- tion of substance is inevitable. Superposition can be solved by setting up for each revealed substance (fatty acid or aldehyde) an equation that quantitatively sums up contributions of all microorganisms that contain this substance. We considered the superposition of three microorganisms, FeRed KM-2 (Lebedeva), Azospirillum and Bacillus subtilis (Ehrenberg, 1935) Cohn, 1872, with different profiles of fatty acids culation is performed in the fatty-acid profile of the determined microbe (Fig. 2).
In the given example we obtain numbers of FeRed KM-2:
XFeRed KM-2 = A14:1ω5S/3.66, XFeRed KM-2 = Aa15S/2.54;
numbers of Azospirillum:
XAzospirillum = A2hi15S/6.51; numbers of Bacillus subtilis:

  1. X subtilis=Ai13S/8.10, XB. subtilis Ai19S/6.10.

In case of superposition of peaks (i.e., when the same substance is present in different members of the community), we solve the inverse task: determining the area of GC-peak via the concentration of the microbe and the proportion of fatty acid (substance) in its profile.
In general for m substances of the aggregate biom- ass of community including as members n genera (spe- cies) of microorganisms, one can set up a system of m equations for n unknown quantities. We obtain a matrix in which each unknown quantity is a number of one of the taxa of microbial community:
(Fig. 2) in the community of silt in Lake Serebryanka.
A1q X1R1 1 + X2R1 2 + X3R1 3 + …….. + XnR ,
According to the concentration of markers, it is possible to calculate the number of cells of these species in
A2q X1R2 1 + X2R2 2 + X3R2 3 + …….. + XnR ,
the community using the formula
A3q X1R3 1 + X2R3 2 + X3R3 3 + …….. + XnR , 
Xj AiS/Rij. (1)
This formula stems from the obvious linear (proportional) dependence between the number of cells of microbe Xj and area of peak Ai of belonging only to it
Am=  X1Rm 1 + X2Rm 2 + X3Rm 3 + + XnRm n,
substance in the chromatogram. In this formula, S is a constant coefficient of proportionality considering conditions of analysis and device sensitivity, Rij is the proportion of i-substance according to which the cal-
where A is area of chromatographic peak of aggregate biomass; q is the coefficient of proportionality consid- ering conditions of sample preparation and device sensitivity; X with indices 1, 2, and 3 is the amount of %.

Fig. 2. Proportion of species in microbial community (%) consisting of three microorganisms with different profiles of fatty acids (abscissa): (a) FeRed KM-2, (b) Azospirillum, (c) Bacillus subtilis, and (d) total sum for each substance: FeRed KM-2 + Azospir- illum Bacillus subtilis. The lower diagram is a superposition of the profiles of individual species of bacteria above it, simulating their position in real communities.
cells of microorganism in 1 g of the sample; and R is the proportion of the substance according to which the calculation is performed in the fatty-acid profile of the determined microorganism. The areas of peaks were determined from chromatogram; magnitudes of R were determined from the data bank on pure cultures. The system has an actually acceptable approximate solution for local microbial community (sediments of bottom, soil, compost, active silt, etc.) that is formed as a group of formulas in EXCEL tables [2, 19].


On the basis of data of literature sources and our investigations, when using GC–MS method of analy- sis of lake silts, ~100 compounds from the class of fatty acids, oxyacids, and aldehydes were revealed, on the
basis of which a local bank of bacterial markers for lake silts was compiled. The creation of such a bank will allow us to considerably extend the study of the struc- tural–functional organization of bacteriobenthos in aquatic ecosystems. Fatty-acid marking can be an effi- cient express method for the study of bacterial bottom communities in ecological investigations. The GC–MS method makes it possible to perform a quantitative estimation of the taxonomic composition of bacteriobenthos, which makes it indispensable for solving several of the most important tasks, such as determining the taxonomic diversity of bottom communities of micro- organisms, a study of the structure of dominant complex, establishing the regularities of spatiotemporal development of bacteriobenthic populations on the basis of revealing relations with abiotic components of the ecosystem, a study of trophic interactions, a comparative analysis of the structure of bacteriobenthos of polytypic water bodies, and an estimation of hydrobiological indices of bacteiobenthic communities (for instance, indices of biological diversity, domination, etc.).

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Translated by I. Pogosyants

INLAND WATER BIOLOGY    Vol. 8 No. 3 2015

SPELL: 1. ok

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