GEORGY A. OSIPOV, NATAL’YA B. BOIKO, NATAL’YA F. FEDOSOVA, SVETLANA A. KASIKHINA & KONSTANTIN V. LYADOV
Research Center of Cardiovascular Surgery, Moscow andTreatment & Rehabilitation Center, Moscow, Russia
Gas chromatography-mass spectrometry analysis was used to determine fatty acids, the markers of microorganisms, in the feces, including neonatal transitional stool and meconium, and healthy adults of different ages. It revealed the markers of Eubacterium, Clostridium, Biﬁdobacterium, Lactobacillus, Enterococcus, Rhodococcus, Streptomyces, Enterobacteriaceae, Bacteroides, Helicobacter pylori, Alcaligenes, Peptostreptococcus, Candida, Streptococcus, Staphylococcus, Fusobacterium sp. and other bacteria, as well as yeast, microscopic fungi, and viruses. The fecal microbial concentration was estimated to be within (0.3–4) 1011/g depending on the examinees’ age and sex, which is in agreement with genetic and cultural ﬁndings in relation to both the total number of microorganisms and the dominant role of the bacteria of the genera Eubacterium, Bacteroides, Clostridium, and Biﬁdobacterium in the feces.
Key words: Fatty acids, meconium, microorganism, fecal microbiota
Conventional methods for determining intestinal microbiota composition rely on the cultivation of bacteria on selective media. However, many bacteria are difﬁcult to culture or are uncultivable and often media are not truly speciﬁc or are too selective for certain bacteria. Molecular tools introduced in microbial ecology have made it possible to study the composition of intestinal ﬂora in a culture-independent way based on the detection of rRNA (1).
The microbial detection technique using fatty acid (FA) markers is similar to the genetic one (polymerase chain reaction (PCR), 16S RNA sequence measurements, etc.) since the composition of FAs was determined in DNA and reproduced via replication of a genome portion by transfer RNA, followed by mitochondrial FA synthesis by messenger RNA. Therefore, the proﬁle of FA bacteria is their business card or ‘ﬁngerprint’ (2). It is as conservative as the structure of DNA, but it is also prone to mutations due to environmental factors. The stability of a set of the FAs that form microbial cells, as evidenced by bacteriological paleontological studies that show that FA composition of some microbes and the pool of their FAs as a whole, has remained constant for as long as 2.5 billion years (3).
Chemical methods for microbial differentiation are ﬁnding increasing use and they are frequently more rapid and universal than earlier approaches (4). For these purposes, gas chromatography (GC) and GC in combination with mass spectrometry (GC-MS) are in most common use, and provide unique information on the composition of monomer chemical components of a microbial cell and metabolites (5–7). Markers of this type may be determined and used to detect microorganisms in a complex environment matrix (8–11). Different applications of chemical marker analysis have been described (12,13). Chemo differentiation is widely employed as a method for identifying and conﬁrming the taxonomic position of microorganisms. The technique is used to work with microorganisms isolated in pure cultures and based on the application of very large databases containing information on the composition of FAs of several thousands of bacterial strains and microscopic fungi. This system is exempliﬁed by a specialized Microbial Identiﬁcation System chromatograph (‘Sherlock’; MIDI Inc., Newark, DE, USA (14). The speciﬁc features of the composition of FA are used along with other parameters in bacterial taxonomy and clinical bacterial diagnosis (15).
The capacities of GC-MS detection of microorganisms by their markers, including FAs, in practical medicine have been little studied. Attempts to detect bacteria from blood by using muramic (16–18) and
b-hydroxymyristic (19) acids as a markers have been reported. Control of meningococci from the presence of b-hydroxylauric acid in blood (20) and gonococci from the concomitant presence of b-hydroxylauric and b-hydroxymyristic acids (21) have been pro- posed. GC-MS potential for diagnosis and stud- ies on in clinical microbiology research have been discussed (5). Recently 3-hydroxy FAs in tissues
(22) and saliva (23) were investigated as diagnostic markers of endotoxin intraperitoneal injection and chronic periodontitis.
We have previously described examples of microbial detection in infectious processes by GC-MS (24). Homeostasis of small molecules of microbial origin has been found in human blood, which is impaired in inﬂammation (25).
The microbiota of intestine is extremely rarely studied in gastroenterology, mainly during surgical intervention. If so doing, the limited range of nosocomial pathogens is mainly detected by cultural and biochemical methods under aerobic cultivation. That is why changes in the normal intestinal microbiota are more frequently determined from the composition of fecal microorganisms (26), by using, among other techniques, GC of long chain FAs (27). However, the chromatographic techniques used to detect a signal from ﬂame ionization fail to provide adequate data on microbial markers due to the limited sensitivity, selectivity, and speciﬁcity of the technique in detecting a wide FA range required for analyzing such a complex microbial community as the intestinal microbiota.
This study has attempted to ﬁll this gap by measuring the quantitative and qualitative composition of the microbiota of feces (as the reference substrate) from the perspective of the intestinal wall (together with a mucosal layer) in healthy donors and in patients with irritable bowel syndrome (IBS) and associated antibiotic diarrhea (AAD). Our ﬁrst measurement of intestine mucosal microbiota was published in Russian (28). The present paper is an advanced version of that investigation and includes additional markers – fatty aldehydes – for monitoring intestinal dominants: Eubacterium, Propionibacterium, Biﬁdobacterium, Closyridium, and other plasmalogen-containing microbes. The concentrations of microbial FAs and aldehydes were measured by GC-MS in the mass-fragmentography mode, i.e. monitoring the speciﬁc ions of the mass spectrum of target substances (markers).
Material and methods
The averaged feces samples, 3–4 mg, were exposed to acid methanolysis in 1 M HCl in methanol at 80°C for 1 h. As a result of methanolysis, FAs were released as methyl esters. They were extracted twice with 200 μl of hexane, dried, and treated in 20 μl of N,O-bis(trimethylsilyl)-triﬂuoroacetamide at 80°C for 15 min to produce trimethylsilyl esters of hydroxy acids and sterols. A mixture of the esters in an amount of 2 μl was injected into the HP-5973 Hewlett-Packard GC-MS system (USA). The standard programs of the device were used to control and process data. The specimen was chromatographically separated on a capillary column with the methylsilicone chemically bonded phase HP-5ms Hewlett-Packard. The length of the column was 25 m; its internal diameter was 0.25 mm. The mode of an analysis was programmed; the rate of oven heating was 5°/min in the range of 130–320°C. The mass spectrometer was quadrupole with electron (70 Ev) ionization, it operated in the selective ion mode (SIM), regularly detecting 20 ions in each of 5 intervals. The intervals and ions were chosen so that the concentrations of marker FAs of detectable microbial species were selectively measured. The strong ion m/z 87 in the spectra of FAs was used to detect minor quantities of microbial acids of C12–C20. Ion 75 was used to detect fatty aldehyde as dimethyacetals (DMA). Ion 175 was constantly taken in each interval to detect b-hydroxy acids, which it is speciﬁc to and intensive in the spectrum. Intensive ions 301, 315, and further every 14 unit masses (of structure M-15) were chosen as witnesses of the molecular ion of hydroxy acids (tridecanoic, tetradecanoic, and the following acids in the homologous series). Ion 312 was taken as molecular to reveal the isomers of nonadecanoic acid, which are of importance in diagnosing staphylococci and enterococci. A total of 33 ions were entered into a monitoring program for SIM recording of a chromatogram. According to our estimates, this algorithm for detecting the mass spectral parameters of a biological specimen can detect about 200 known microbial FAs, alcohols, DMAs, and sterols, which is sufﬁcient to reveal and assay more than 170 taxons of clinically signiﬁcant microorganisms at the level of a genus or a species.
The preset program was applied to automatically integrate the peak areas of markers on the mass fragmentograms. Then these data were entered into the calculation program prepared in the EXCEL tables. The data were calibrated with deuterated tridecainoic acid as internal standard and elsewhere published data on FA composition of clinically important microorganisms and our clinical isolates as well. Biological reproducibility (accuracy of measurements) was calculated as 20% in statistical measurements (24,25).
Calculation of the composition and number of effective microbial cells
While drawing up a program of analysis, developing an algorithm for identifying and calculating the number of microorganisms, we were guided by the principle of a limited number of the members of a local microbial community, the recognition of the proﬁle of microbial FAs as an image during computerassisted identiﬁcation, and by the principle of a marker in the application only to the microbial com- munity under consideration (10).
Different microorganisms are known to contain about 200 FAs as components of cellular wall lipids, which distinguish them from human cells. In intestinal microorganisms some substances appeared to be speciﬁc to one taxon. The number of cells of these microorganisms was calculated by the concentration of a marker substance, by using the known data on the content of FA in the microbial cell, on the conditions for preparing a sample and calibrating a device.
The chromatographic peak area of a marker is in proportion to its concentration and thus to the con- centration of a respective microorganism, which is estimated as the number of cells N1 per unit of volume or weight of a sample, using the formula:
where the expression enclosed in brackets, the constant coefﬁcient
k Mst/q/Msam/Ast Mst(mg)/5.1 10(–15)g/ Msam(mg)/Ast
In these formulae, Ai is the peak area of a marker, Mst is the amount (mg) of the reference injected into the sample, Msam is the amount of the sample, Ast is the peak area of the reference, Ri1 is the proportion (%) of the marker with the index i in the proﬁle of FA of a detected microbe with number 1 (N1), q is the coefﬁcient equal to 5.1 10(–15)g, which contains the basic value calculated with reference to the number 5.9 1012 microbial cells available in 1 g of microbial biomass and the proportion of cellular FA, which is taken as, on the average, 3%.
The number of cells of any following microorganism may be calculated, by using the similar formula N2 Ai k/Ri2 and so on, by multiplying the peak area of a marker (Ai) that is used to make calculations, by the coefﬁcient k and dividing by the proportion of the marker as a part of total FA of this microorganism as a percentage.
The effective number (i.e. corresponding to the marker’s concentration measured at this moment) of bacteria including Clostridium ramosum group, C. perfringens, C. difﬁcile, Bacteroides fragilis, the yeast Candida albicans, bacteria of the genera Biﬁdobacterium, Eubacterium, Propionibacterium, Streptomyces, Nocardia, Alcaligenes, Pseudomonas, Enterococcus, Staphylococcus, the family Enterobacteriaceae, and others, as well as non-speciﬁc fungi from ergosterol (Aspergillus, Mucor, etc.) was estimated by the same procedure – one taxon, one marker. Some viruses are involved in the synthesis of sterols in human cells, which can be deter- mined from the product of transformation by their enzyme of human cholesterol to cholestendiol (herpes viruses), isomers of cholestadiene and cholestadienon (cytomegaloviruses). If the substance does not have the property of a marker, i.e. it may be referred to two taxons or more, here the contribution of each microorganism, if the solution of a system of equations for two substances (or, accordingly, more) is applied. We have described the procedure for calculating ecological microbial communities elsewhere (3,10,29).
Detection of taxonomic FA
By using the known data on the most common intestinal microorganisms (30) we formed a local database on the composition of FAs (Table I, database), which was used to identify markers and to make calculation formulae. Below is shown the substantiation of afﬁliation of markers to speciﬁc microorganisms that are putative intestinal wall inhabitants, as well as the choice of a speciﬁc marker or a scheme for calculation of their concentrations.
Biﬁdobacterium. The number of biﬁdobacteria was estimated from the component of the speciﬁc cellular membrane lipid plasmologen, wherein one of the Fas of glyceride is replaced by fatty aldehyde. The distinctive feature of biﬁdobacteria is 9-octadecenoic aldehyde (31) that was registered as a measure of their concentrations.
Lactobacillus. Lactobacilli have clear markers, such as lactobacillic acid (31) and cisvaccenic acid (18:1Ä11), which are also found in other bacteria, such as Pseudomonas and Enterobacteriaceae. However, Pseudomonas is rarely detectable in the intestine in noticeable concentrations and the cross determination with enterobacteria is taken into account in the equation of balance of FA concentrations, by using additional markers. Cisvaccenic acid was used here to control lactobacilli.
Table I. List of fatty acids, aldehydes, and sterols detected in the feces indicating the most likely microorganisms in whose cells they usually were found.
|No.||Abbreviation*||Chemical name||Most likely microorganisms|
|5||i14||iso-Tetradecanoic||Peptostreptococcus anaerobius, Streptomyces, Bacillus, Bacteroides|
|6||14:1ω7||7,8-Tetradecenoic||Haemophilus parahaemolyticus, Arcobacter|
|17||i16:0||iso-Hexadecanoic||Streptomyces, Corynebacterium betae, Curtobacterium, Cellulomonas|
|20||i17:1 I||iso-Heptadecenoic I||Campylobacter mucosalis|
|21||17:1||Heptadecenoic||Candida albicans, Mycobacterium|
|22||i17:0||iso-Heptadecanoic||Bacillus, Prevotella, Propionibacterium|
|23||a17:0||anteiso-Heptadecanoic||Corynebacterium CDC group|
|28||i18||iso-Octadecanoic||Clostridium difﬁcile, Bacillus subtilis,|
|29||10Me18||10-Methyl-octadecanoic||Mycobacterium, Nocardia, Corynebacterium bovis, C. xerosis group,
C. urealyticum, Actinomycetes
|31||20:1||Eicosenoic||Propionibacterium jensenii, Actinomyces|
|32||i19||iso-Nonadecanoic||Bacillus subtilis, Bacteroides hypermegas|
|40||hi15||Hydroxy-iso-pentadecanoic||Prevotella, Flavobacterium, Capnocytophaga|
|49||2h12||2-Hydroxy-lauric||Pseudomonas aeruginosa, Alcaligenes|
|52||2h16||2-Hydroxy-palmitic||Pseudomonas cepacea, Flexibacter|
|54||14a||Tetradecanoic||Eubacterium lentum, Biﬁdobacterium|
Table I. (Continued)
No. Abbreviation* Chemical name Most likely microorganisms
- 16a Hexadecanoic Non-speciﬁc
- 17a Heptadecanoic Propionibacteriumfreudenreichii
- i17a iso-Heptadecanoic Propionibacterium
- a17a anteiso-Heptadecanoic Eubacteriumlentum
- 18:1ω9a 9,10-Octadecenoic Biﬁdobacterium
- 18:1ω7a 11,12-Octadecenoic Eubacterium, Clostridiumramosum
- 19cyca cyclo-Nonadecanoic Enterococcus
- Coprostanol Dehydro-cholesterol Eubacterium
- Cholestendiol Herpesvirus
- Campesterol Microscopicfungi
- b-Sitosterol Microscopicfungi
- Cholestadienon Cytomegalovirus
- Ergosterol Microscopicfungi
*In 17:1, 17 is the number of carbon atoms, the ﬁgure after the colon denotes the number of double bonds; h, hydroxyacid; a,I, indicates methyl-branching; cyc, cyclopropanoic acid. For example, 2hi15 means 2-hydroxy-iso-pentadecanoic acid.
†3-Hydroxy-acids, if position of hydroxyl is not indicated.
Enterobacteriaceae family. Enterobacteriaceae are close in the proﬁle of FA, at the same time their genus-speciﬁc, occasionally species-speciﬁc, differentiation in the pure culture of cells is assumed, but they are barely distinguishable if they are simultaneously present in the community of microorganisms. Their markers are b-hydroxymyristic acid (h14), cycloheptadecanoic (17cyc), and cicvaccenic acids have a rank of a family, with multiple intersections with the representative of other families. Here in the absence of Pseudomonas, the number of enterobacteriaceae as a whole can be actually measured by the concentration of 17cyc (15,31).
Eubacterium. The representatives of this genus comprise one of the basic intestinal inhabitants. Their marker, dehydrocholesterol (coprostanol), is a product of the interactive metabolism of Eubacterium and cells of the host’s body (32). For differentiation of eubacteria at the level of a species and subspecies, their differences in the composition of fatty aldehydes (31) are used (see Table IV). Furthermore, the species of Eubacterium have been determined by speciﬁc fatty aldehydes, among them, E. lentum by iso-hexadecanoic aldehyde (i16a), a group of strains of this species, including E. lentum 7741, and others wherein tetradecanoic aldehyde (14a) are the leaders (33). The main group of species of the genus Eubacterium (E. moniliforme, E. nodatum, E. sabureum, and others) were separately determined by 11-octadecenoic (18:1w7a) aldehyde (31).Propionibacterium. Iso- and anteisoheptadecanoic (i17a and a17a) aldehyde were assigned to this genera according to ‘Sherlock’ (31) and our own measurements of Propionibacterium freudenreichii type culture from the All-Russian Collection of Microorganisms
Peptostreptococcus anaerobius. This microorganism is known to have less common even iso-acids with a number of carbon atoms from 10 to 16 in the proﬁle of FAs (34). We used iso-dodecanoic (i12) and iso- tetradecanoic (i14) acids as markers.
Ruminococcus. These were determined by 11-hexadecanoic acid found by use in the natural isolates of ruminococci (35).
Propionobacterium acnes. For identiﬁcation of this microorganism, iso-pentadecanoic aldehyde (i15a) (our own data) minus the contribution of Eubacterium spp. was used.
Bacillus. Bacilli of the species B. cereus and B. subtilis may be detected by speciﬁc branched acids with 13 carbon atoms: i13 and a13. B. megaterium was determined from the residue of anteiso-pentadecanoic (ai15) acid, using the balance equation (36).
Acinetobacter. It is convenient to use 2-hydroxy dodecanoic acid (15) as a generic sign in the presence of 3-hydroxydodecanoic acid.
Clostridium perfringens. They have clear markers that are characteristic of the clostridia group including, besides C.perfringens, C.histolyticum, and C.oedematiens. These are 10-hydroxystearic and 10-hydroxy- octadecenoic (10h18) acids readily detectable by speciﬁc ions in the mass spectrum [our data, published in Russian]. These substances are not cellular components of clostridia themselves, but they are associated with the breakdown of tissue cells of the organism by bacterial enzymes (37).
- difﬁcile and other clostridia. C. difﬁcile differs from other clostridia in that iso-octadecanoic (i18) acid (38)isin the composition of FA. C. histolyticum differs in that iso-tetradecenoic acid is present in FA proﬁle, and the C. ramosum group differs in that 7-hexadecenoic (16:1Ä7) acid (31) is in the FA proﬁle.
Bacteroides. The anaerobic bacteria of the group B. fragilis have a good marker – a pair of branched hydroxy acids: hydroxy-iso-heptadecanoic (hi17) and anteiso- heptadecanoic (ha17) ones (39). The number of the remaining bacteroides was estimated from the residue in the balance of hydroxy-hexadecanoic acid.
Streptococcus. Many streptococci are ‘invisible’ in the presence of biological ﬂuid components due to the coincidence of intrinsic FAs with the acids of a substrate. However, a group of oral or a-streptococci, such as Strep. mutans, Strep. salivarius, etc. is detectable from decanoic acid C10 (40) and the monounsaturated acids 16:1Ä7 and 18:1Ä11 (31). Strep. mutans was detected by its speciﬁc 11-eicosenoic acid – 20:1w9 (31).
Enterococcus. Enterococcus faecalis and E. faecium with their prevalence in the community may be also be detectable by cis-9,10-methylene-hexadecanoic acid (9,10-19cyc) acid (31).
Candida albicans, Mycobacterium. Heptadecenoic acid is a speciﬁc sign of the yeast C. albicans in the lipid fraction of human biological ﬂuids [our own data]. It cannot be ruled out that it may be also referred to mycobacteria (41).
Microscopic fungi. The non-speciﬁc marker of clinically signiﬁcant microscopic fungi (Aspergillus, Candida, Mucor, etc.) is ergosterol (42), as well as campesterol and b-sitosterol (43) [authors’ own measurements].
Flavobacterium (Sphingobacterium, Chriseobacterium). These bacteria have branched odd 2-hydroxy acids in the composition of cellular sphingolipids (2hi15, 2hi17) that may serve as markers in clinical tests (15).
Streptomyces, Nocardiopsis. The FA proﬁles of biological ﬂuids from patients contain a great amount of iso-hexadecanoic acid (i16), which substantially exceeds the possible proportion of P. anaerobius and Bacillus that have this substance as a constituent of the cellular membrane. The representatives of the genus Streptomyces and some other actinomycetes (such as Nocardiopsis dasonvilley isolated by us from an intestinal mucosal biopsy specimen) are rare organisms (of those we know) that have this sign. The strains of streptomycetes, which have as high as 40% of i16 in the proﬁle of FAs have been described in the literature (44). There is also evidence for the participation of streptomycetes in the colonization and inﬂammation of different human organs.
Actinomadura. They were determined by 10-methylheptadecanoic acid (10Me17) (44) minus the contribution of rhodococci.
Pseudonocardia. This genus determined by iso-hexadecenoic acid (i16:1) (44) minus the contribution of rhodococci to it’s measured value.
Rhodococcus. Rhodococci are likely to be responsible for the presence of 10-methyl-hexadecanoic acid (10Me16) (44) in the composition of FAs of all the samples we have studied.
Nocardia. They were determined by the tetradecenoic (presumably 14:1d11) acid isomer detected by us in the isolate of Nocardia from the patient’s blood. Nocardia asteroides and others were detected by trans-9,10-hexadecenoic acid (16:1w7t) (44).
Helicobacter pylori. Hydroxyoctadecanoic acid (h18) is usually present in the clinical samples. This hydroxy acid is characteristic of the genus Francisella and the species Helicobacter pylori (45). In our case it is logical to assign the presence of h18 to H. pylori or F. ﬁlomiragia. H. pylori is usually associated with chronic gastritis; however, it is detectable in the tissues of patients with oral aphthous ulcers (46), atherosclerotic plaques (47), and hepatic abscesses. Moreover, GC-MS analysis of the strains isolated from the intestinal biopsy specimens in this study indicated the presence of 11Me18:1, 2h18:1, 11-OMe-19, and cholesterol along with H. pylori-characteristic FA (18:1d11, 16:0, 19cyc, 3h16, 3h18). In the manual of non-fermenting gram-negative bacteria (15), the FA proﬁle of H. pylori showed 11Me18:1 (under the name of 19:1br).
Campylobacter mucosalis. This species has rare iso-heptadecenoic (i17:1) acid (31) as a component of FA, which was monitored by taking into account the contribution of bacteria of the genera Chriseobacterium and Flavobacterium, if their marker 2hi15 was present.
Fusobacterium. The only distinctive component in the cellular FA of these bacteria is 3-hydroxymyristic acid (3h14) (48), which also occurs in other clinically signiﬁcant gram-negative microorganisms, such as E. coli, Alcaligenes, Serratia, etc. Therefore, Fusobacterium and Haemophilus may be determined only from the residue, using the balance equation for 3h14.
Staphylococcus. Staphylococci are known to contain odd iso- and anteiso-branched acids with the number of carbon atoms 15, 17, and 19 (49). Anteiso-non-adecanoic (ai19) acid may be used as a generic marker in this community.
Corynebacterium CDC groups. A residue is frequently observed after consideration of all the microorganisms that have anteisoheptadecanoic acid in the composition of FA. This may be most likely to be attributable to C. betae, C. aquaticum, Listeria, and Brevibacterium, as well as individual groups of CDC A-3, A-4, A-5, B-1a, B-3a, B-1b, and B3b, which contain particularly high levels of the acids a15 II a17 .
Viruses. By comparing our data with the results of examination of patients with different diseases using immunological and genetic studies, we found a correlation in the appearance of the cholesterol metabolite cholestenediol in herpes virus infection and cholestadienone in cytomegalovirus infection.
The feces specimens were examined for the content of 135 microbial substances, which provide information on more than 170 taxons of microorganisms. All speciﬁc substances were conﬁrmed just in the objects studied using mass spectra in the direct scanning while comparing them with the standard libraries (NIST and Wiley) of the mass spectra of the GC-MS system.
GC-MS analysis of FA fractions in feces specimens revealed that the major components (at the level of
> 1% relative content) are even acids with 12–18 carbon atoms: C18:1, C16:0, C18:2, C18:0, C16:1
(in order of decreasing levels in the proﬁle of FAs), as well as polyunsaturated FAs (C20:n, C22:n), cholesterol, aldehydes, and 2-hydroxy acids. The level of long-chain acids (C23 and higher) is occasionally 1%. Each of the odd acids C15:0 and C17:0 forms about 1%.
The above substances are the lipid components of human cells and form the natural background against which the minor microbial components that are not characteristic of the human cells are detected in the examined samples. The chromatograms obtained by the selective ion method can conﬁdently detect microbial components in the presence of predominant human waste components. For the most part, the peaks of target substances are superposition-free, rather distant from the peak of a substrate and there- fore they may be accessible for automatic random integration in accordance with the standard program of the GC-MS system. The list of FAs, aldehydes, and sterols detected in feces specimens is given in Table I, indicating the most likely microorganisms in whose cells they usually were found.
The composition of intestinal microbiota has not been previously studied by GC-MS analysis. Moreover, there are no values of the composition of its microorganisms, measured by any routine procedure. In doing so, we cannot compare our results with the reference values.Therefore we also had to measure the microﬂora of feces in some samples from healthy persons of different ages and sex, as well as those of neonatal transitional stool and meconium (Table II). Since it had been thoroughly studied in the qualitative and quantitative senses, we used the fecal microﬂora as a reference material to substantiate the validity of the data of the future analysis of the microbiota of the intestinal wall and other objects by MS of microbial markers.
The whole number of microorganisms in feces varies from 3 1010 to 4 1011 in healthy adults and children. Minor values are speciﬁc for children and the elderly, which are consistent with known data. Really, the number of biﬁdobacteria is maximum in children and adults in comparison with newborn and older persons (Table II). In Table III, the microorgan- isms are distributed by groups: the ﬁrst entries show all anaerobes, with the leading ratio of Eubacterium. Next are clostridia, bacteroides, lactobacilli, and biﬁdobacteria. In persons with a formed intestinal microbiota, the proportion of anaerobes is 70–90% of the total number, as evidenced by our measurements. The aerobes are mainly represented by cocci and bacilli of different taxons (2.4–13.5%), as well as aerobic actinomycetes (actinobacteria) (1.1–15.3%) and microscopic fungi.Enterobacteria,pseudomonads, other gram-negative aerobes, and viruses are present in minor concentrations (0.1–7.3%).
To conﬁrm the reliability of these and subsequent measurements, we present their comparison with the known estimates obtained by cultural, biochemical, and genetic studies (Table IV) (51–53). The total number of microorganisms in the feces was in the range of 0.3–4 1011 cells/g, which agrees with the known literature measurements obtained by genetic and cultural and biochemical studies. The relative number of anaerobes, i.e. 70–90%, as shown by our data, is also in agreement with the known number. It is difﬁcult to compare the genus-speciﬁc distribution in this study with that available in the literature as the distribution has a wide range of values – within 36 orders of magnitude. Nevertheless, our data coincide with those on the priority of the genus Eubacterium, which numbered 0.3–3 1010 cells/g (109–1012, as shown by the data available in the literature), on the number of bacteroids, i.e. 0.2–2.4 1010 cells/g (1010–1012 according to the known data), Clostridium 109–1011cells/g (105–1011, respectively), Biﬁdobacterium 108–1010 cells/g (1010–1012).
Table II. Results of examination of the microbial composition (cell/g 106) of feces from healthy persons aged 12–60 years, neonatal meconium, and transitional stool of newborn and IBS patients before and after treatment.
Colonization level, cells/g 106, mean value
|IBS before treatment||IBS after treatment|
|No.||Microorganism||(n 2)||(n 2)||(n 7)||(n 1)||(n 5)||(n 3)|
|1 Eubacterium lentum||144||83||8213||2792||3223||978|
|2 Eubacterium||0||0||13 743||11 579||14 251||4693|
|3 Propionibacterium||18||0||13 442||7632||7875||4377|
|6 Clostridium histolyticum||6||45||112||6||78||5|
|7 Clostridium propionicum||0||828||4055||384||829||198|
|8 Clostridium ramosum||638||884||3281||2096||1635||706|
|9 Clostridium difﬁcile||1333||622||1046||820||390||377|
|10 Clostridium perfringens||6||34432||45470||9401||55209||11452|
|11 Bacteroides hypermegas||0||34||151||99||364||101|
|14 Bacteroides fragilis||0||0||1451||3223||2763||1575|
|15 Bacteroides ruminicola||52||0||2208||2130||6764||2822|
|18 Lactobacillus||1054||2102||26 354||4545||19 070||3549|
|19 Helicobacter pylori||33||251||9968||368||2427||505|
|20 Pseudomonas aeruginosa||0||0||21||42||5||4|
|25 Enterobacteriaceae spp.||0||365||359||0||138||19|
|27 Bacillus cereus||94||27||445||181||247||220|
|28 Bacillus megaterium||6||66||623||0||431||774|
|31 Streptococcus (oral)||160||1169||4503||0||421||443|
|32 Streptococcus mutans||455||44||818||0||542||601|
|33 Enterococcus faecalis||0||0||1573||3587||1927||0|
|34 Streptococcus intermedius||0||685||2659||0||1371||2322|
|35 Coryneform CDC group||0||306||521||0||221||172|
|36 Nocardia spp.||54||18||146||70||172||86|
|37 Actinomycetes 10Me15||69||42||48||34||78||61|
|43 Nocardia asteroides||235||126||868||0||159||56|
|44 Actinomycetes 10Me14||155||472||167||54||425||155|
|45 Microscopic fungi 1a||160||5350||2462||1173||783||500|
|46 Microscopic fungi 2b||290||6240||5118||8||1958||1526|
|48 Herpes virus||204||68||20||13||54||209|
Gas chromatography-mass spectrometry of microbial markers was used. Accuracy of measurements is 20% reproducible.
aMicroscopic fungi producing campesterol.
bMicroscopic fungi producing sitosterol.
These results conﬁrm that GC-MS analysis of the fecal microbiota yields valid data on their number. Therefore, any data on the composition of microorganisms in biopsy specimens or any other clinical, as well as environment samples, may also be considered valid.
Table III. Grouping of microorganisms (cell/g 106) of feces from healthy persons aged 12–60 years, neonatal meconium, and transitional stool of newborn, and IBS patients before and after treatment.
Colonization level, cells/g 106, mean
|IBS before treatment||IBS after treatment|
|Microorganism group||(n 2)||(n 2)||(n 7)||(n 1)||(n 5)||(n 3)|
|Aerobic gram-negative bacteria||271||1068||752||765||616||278|
|Cocci and bacilli||1281||3861||12 007||6680||5502||4690|
|Cocci and bacilli||9.3||9.8||7.2||9.8||4.7||7.3|
Accuracy of measurement is 20% reproducible.
Different investigations show that the fecal microbiota contains biﬁdobacteria almost 100 to 0.1% (Table III). The range of three orders of magnitude is unlikely to be due to the fact that human beings are different. Each study presents serious statistical data and a conscientious analytical procedure. The difference is more likely to be considered as the speciﬁc features of the comparable methods for measurements.Without going into details, it may be concluded that the effect of a predominance of Biﬁdobacterium is produced by the routine procedure for analyzing only Biﬁdobacterium and opportunistic microorganisms in studying disbiosis. Eubacterium, bacteroids, and Clostridium, which are at least several times more than Biﬁdobacterium are seen to be out of the view of a microbiologist. This delusion looks natural if we recall that it is practice to consider within general microbiology that not more than 20% of the microorganisms in any habitat are on the average cultured in the microbial community. Molecular genetic studies indicate that 60–80% of the fecal microbiocenosis cannot be determined by cultural techniques. Mass spectrometric data correlate with genetic data (within the comparability of microbiological estimates) and equally demonstrate that Eubacterium, bacteroids, and Clostridium alone and in combination are an order of magnitude higher than Biﬁdobacterium.
MS made it possible to measure the numbers of more than 50 taxons of intestinal microorganisms in the feces. These data show that Eubacterium spp. Are prevalent. The afﬁnity of Eubacterium for Clostridium should be noted. The ninth edition of Bergey’s manual (54) directly reads that the genus Eubacterium has been designed for convenience so that it should include weakly spore-forming clostridia. If the het- erogenicity of both genera, which is still known and unordered so far, is mentioned, it can be seen that the intestinal microbiota is a predominant continuum of strains and species of the genera Clostridium and Eubacterium in their present arrangement with the equivalent total amount of propionibacteria, bacteroids, biﬁdobacteria, and lactobacilli. The pro- portion of another biological diversity of intestinal microorganisms (as evidenced by MS) is as high as 10% in feces. The fact that the genera Clostridium and Eubacterium are closely genetically related is suggested by the current absence of speciﬁc probes for each genus. The probes designed for Clostridium determine Eubacterium in a cross-reaction and vice versa. Thus, in addition to Eubacterium, the probe proposed to determine a group of new clostridia headed by C. coccoides (intestinally detected in 1997) also includes ruminococci in this group.
The presented data suggest that the genus Eubacterium is of importance in the formation and functioning of the intestinal microbiota and we tend to consider them to be a digestively important group of peptolytic and cellulolytic organisms. The fundamental important feature of the representatives of the genus Eubacterium is noteworthy, i.e. the capacity to produce hydrogen.
Table IV. Comparison of data for analysis of fecal microbiota by genetic, cultural and biochemical, and mass-spectrometric studies.
Composition of adult fecal microbiota, cells/g wet weight
This is a key property of the microbial consortium that effects the digestion of an organic substrate during anaerobic processes in nature (in the marsh), in the rumen, and in biotechnology during the anaerobic fermentation of all kinds of waste products and the production of a biogas. The human intestinal mucosa is essentially a similar bioreactor. Methane is formed there and hence methanogenic archaebacteria, whose effectiveness strictly depends on the concentration of hydrogen in the system, are at work. In the methanogenic community, hydrogen-producing bacteria play a key regulatory role due to the feedback in the production and consumption of hydrogen in the primary process of carbohydrate cleavage to give rise to acetate.
There is no question that detection of a considerable amount of aerobic actinomycetes is an unexpected result. The speciﬁcity of their markers – branched FAs with a methyl group in the position Ä10 – gives no way of assuming some other taxonomic groups of microorganisms, other than the representatives of actinomycetales whose cell walls contain mycolic acids that are a source of 10Me-branched FAs. They are present in Mycobacterium, Nocardia, Rhodococcus, Actinomadura spp., and other actinomycetes, but they have not been found in higher organisms (fungi, plants, and animals). The presence of these molecules in human feces is sup- ported by mass spectra in the chromatographic peak and by relative retention time, as well as by their analysis in the composition of type cultures of respective microorganisms. The bacteria of the genera Streptomyces and Nocardiopsis are also conﬁrmed by the unique marker iso-hexadecanoic acid (i16). Further, the proﬁle of the branched FAs speciﬁc for streptomycetes was detected in the blood of septic patients in our practice (25). The list of actinobacteria should be extended by anaerobic actinomycetes and related microorganisms. These are Propionibacterium, Actinomyces, Brevibacterium, and corynebacteria. Finally, if we consider the fact that some manuals on microbiology, such as early ones (54), have assigned the genus Biﬁdobacterium to the family Actinomycetaceae so far, then it will turn out that actinomycetes are phylogenetically close to the traditionally known representatives of the intestinal parietal microbiota. With them, the intestinal micro- biota grows in importance for the host, since actinomycetes are superior to all other microorganisms in producing antibiotics and vitamins and have a powerful enzymatic apparatus. The high intestinal colonization by actinomycetes does not look an unusual phenomenon if we bear in mind that they occur widely in the environment – soil, water, air, on the inner walls of dwelling and industrial premises (55). Their habitation in the human body looks natural under such circumstances. The guides on clinical microbiology mention that actinomycetes and related organisms, such as Mycobacterium, Actinomadura, Propionibacterium, Actinomyces, Corynebacterium, Biﬁdobacterium, are detectable in the human intestine and other organs. They (including Biﬁdobacterium) are known to be participants in infectious and inﬂammatory processes. Recent study of the composition of the human GI microbiota of 23 healthy adult subjects was performed on a pooled fecal bacterial DNA sample by combining genomic %G+C-based proﬁling and fractioning with 16S rRNA gene cloning and sequencing. The orders Coriobacteriales, Biﬁdobacteriales, and Actinomycetales constituted the 65 actinobacterial phylotypes (56). Earlier, nucleotide sequencing and ampliﬁcation by PCR was done on the bacterial 16S ribosomal DNA present in a small bowel biopsy specimen taken from a patient with Whipple’s disease. A search by computer for similar rRNA sequences ﬁled in databases showed the Whipple’s-associated organism to be most similar to bacteria in the genera Rhodococcus, Streptomyces, and Arthrobacter, and more weakly related to mycobacteria (57). However, the pathogenicity of actinomycetes, their antibiotic sensitivity, and treatment of their associated diseases is the subject matter of single specialized laboratories and clinics around the world. Difﬁculties in their bacterial diagnosis and cultivation are a handicap to the wide popularity of these microorganisms in clinical practice, for instance in multiple diseases associated with the altered intestinal microbiota (44).
Microbial markers have also been found in meconium from newborns. This conﬁrms guesses and assumptions regarding prenatal intestinal colonization of the fetus. In fact, as reported some time ago (58), meconium dominant ﬂora was composed of either enterobacteria or of streptococci. Staphylococcus, Corynebacterium, Clostridium (C. perfringens), Bacteroides, Peptococcus represented a very small pro- portion of the total ﬂora. In the two children aged 48 h and more, the ﬂora was more complex and Bacteroides, Biﬁdobacterium, Veillonella, Peptostreptococcus, Clostridium, and Staphylococcus were associated with streptococci and enterobacteria. A very small number of lactobacilli were found in one child only. Later, the presence of bacteria in meconium of 21 healthy neonates was investigated. The identiﬁed isolates belonged predominantly to the genera Enterococcus and Staphylococcus (59). We found similar features in meconium microbiota in our analyses, which are in good agreement with molecular and culturing methods, as can be seen from Table II.
The microbiota of IBS patients differs in genera composition from that of healthy adults and coin- cides with the data obtained by a genetic method (26). However, the GC-MS method has the advantage of measuring the number of each taxon. That is why we can monitor the dynamic of quantitative changes in microbiota. It is clear from Tables II and III that in spite of small differences in the total amount of microorganisms, proportion of anaerobes, numbers of aerobic gram-negative bacteria and clostridia (Table III), the genera and species composition differ substantially in healthy persons and IBS patients. For instance, numbers of Biﬁdobacterium, Lactobacillus, Propionibacterium, C. propionicum, Enterobacteriaceae spp., Streptococcus, and microscopic fungi decreased, while the numbers of Ruminicoccus, Peptostreptococcus, Bacteroides, Fusobacterium, and Acinetobacter increased in patients as compared with healthy donors. We dare not speculate about the decrease in numbers of bacteria in feces after treatment. But we would like to admit that this is the same bacteria (Ruminicoccus, Bacteroides, Fusobacterium, Acinetobacter), which overgrows before treatment, as compared with healthy adults (Table II). We assume also, that the general microbiota deﬁciency is caused by reduction of microbes in the intestine after the termination of diarrhea.
The previous studies, which have relied almost exclusively on the use of culturing methods, have generated our current understanding of gut microbiology and ecology in infants. Gastrointestinal microbial ecology is experiencing a revival because of the development of molecular techniques, particularly techniques based on 16S rRNA genes, which are used to study complex bacterial ecosystems (60). So far,only a limited number of infant microbiota studies have been performed with molecular techniques, and very limited numbers of primers were used to characterize the diversity and quantity of fecal microbes. We demonstrate GC-MS as one more approach in studying microbiota in newborn and adults. This small number of experimental results could only demonstrate method and prove their compatibility with known ones both in genera composition in feces and tendency in age, health, and disease.
Declaration of interest: The authors report no conﬂicts of interest. The authors alone are responsible for the content and writing of the paper.
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G.A. Osipov, N.B. Boiko, N.F. Fedosova, S.A. Kasikhina and
K.V. Lyadov: Comparative gas chromatography-mass spectrometry study of the composition of microbial chemical markers in feces
This article is a part of a very ambitious project, challenging the genetic way of determining the composition of a mixture of known and unknown microorganisms. Instead of studying microbialderived genetic ﬁngerprints the authors are studying lipid ﬁngerprints in human fecal samples. Based upon an assumption that certain lipids are unique to certain species, the authors used gas chromatography-mass spectrometry technology for a qualitative and quantitative evaluation of lipids present in feces.
Both the reviewers are concerned about the speciﬁcity of the lipid markers in relation to speciﬁc microorganisms. As stated by one of the reviewers: ‘The authors’ statements that a certain microbe contains a certain lipid might be correct. The problem comes when they state that a certain lipid denotes a certain speciﬁc microbe. This is highly speculative.’ Surely, I am dealing with my reviewers’ concerns.
Why then accept a speculative paper with several weaknesses? Simply spoken: it represents a valuable approach to studying the human gut ﬂora and its possible inﬂuence upon the human body. Again to simplify: neither microbial genes nor microbial names cause any harm to the body, but microbial products may do. Many lipids are very active biological compounds indeed. The presence of such compounds in the gut may have physiological and pathophysiological consequences for the host. That represents Microbial Ecology in Health and Disease!
Tore Midtvedt Editor-in-Chief
(Received 20 August 2009; accepted 15 October 2009)
ISSN 0891-060X print/ISSN 1651-2235 online © 2009 Informa UK Ltd. (Informa Healthcare, Taylor & Francis AS) DOI: 10.3109/08910600903462657
Microbial Ecology in Health and Disease. 2009; 21: 159–171