Non-cultural methods of human microflora evaluation for the benefit of crew medical control in confined habitat

  • Главная
  • Статьи

Current control of human microflora is a great problem not only for the space medicine but also for practical health care. Due to many reasons its realization by classical bacteriological method is difficult in practical application or cannot be done.
To evaluate non-cultural methods of microbial control of crews in a confined habitat we evaluated two different methods. The first method is based on digital treatment of microbial visual images, appearing after gram staining of microbial material from natural sample. This way the rate between gram-positive and gram-negative microbe could be gained as well as differentiation of rods and cocci could be attained, which is necessary for primary evaluation of human microbial cenosis in remote confined habitats.
The other non-culture method of human microflora evaluation is gas chromatomass spectrometry (gcms) analysis of swabs gathered from different body sites. Gc-ms testing of swabs allows one to validate quantitative and special microflora based on specific lipid markers analysis.
Keywords: Human microflora, Gas chromatography, Mass spectrometry, Confined habitat, Digital treatment of microbial images

  1. Introduction

Long space flights inevitably entail risks of various natures. The most significant factors for preservation of life, health and normal working capacity of crew members includes curbing the risk of infectious diseases. The concept of periodic accumulation of potential pathogenicity by microorganisms in the long time action of space flight factors, formulated earlier, solves this problem to a significant extent.
Diagnostics of the microflora condition-generated commensal microorganisms is one of the most rational ways of preventing the infection of cosmonauts onboard a space vehicle. In standard practice the classical bacteriological method is applied to receive similar information on a condition of a barrier colonization resistance, based on cultivation of bacteria allocated from integumentary tissues and their subsequent definition to species. However in conditions of space flight its use is impossible. The decision of microflora condition control problem demands creation of systems and the methods excluding necessity of bacteria cultivation.
The computer analysis of microbial cells images is based on automated analysis. It allows obtaining information on critical parameters (morphological, tinctorial, quantitative) and on the definite quantitative ratio of microorganism groups in the investigated material. The given method assumes analyzing open biotopes of human organism as the covering tissues (skin and mucous) are in the closest direct contact to the environment.
The normal ratio of researched microorganisms groups is known for every biotope. So knowledge of qualitative and quantitative structure of their microflora can give a complete representation about the current condition of immunity. This, in turn, allows predicting the risk of development of an infectious disease. The developed method yields live data about human microflora without separating and cultivating microorganisms on media, which reduces the test time from 2-5 days to 1.5-3 h. It permits one to give timely recommendation on correction of the immune status.
GC-MS permits one to obtain unique information regarding the composition of specific monomeric chemical compounds of a microbial cell. These markers can be detected in the mass of other chemical compounds in total biomass constituencies of biological objects and can be used for determining microorganisms in corresponding genera or species. The root cause of the problem lies in the direct extraction of Fatty Acids (FAs) from examined specimens by a chemical procedure by dividing them in the capillary column of gas chromatography and analyzing the compounds in a dynamic rate on massspectrometry. This procedure takes only 30 min as the chromatograph is combined with mass-spectrometry and provided by PC with corresponding programs of automatic analysis and taking into account the time of sample preparation and quantification of data (not more than 3 h). Result involves quantification determining of microorganisms’ constituencies.
Today the FAs of the most significant microorganisms have been well investigated regarding its repeatability and its special and genera specificity have been estimated [1,2].
Diagnostic possibility of the method to detect microbial

Fig. 1. The system for automated microbial analysis of native swab.

Fig. 2. An example of objects segmentation on vision field of native smear image.
markers in clinical materials seems promising. Introduction of GC-MS permits one to reduce time but increase value of investigation, passing the stages of recurring replanting of primary colonies and test fermentations, which are particularly difficult, laborious and prolonged processes for anaerobic microorganisms. This method permits not only detecting marker compounds (FAs, aldehydes, alcohols and sterines) in pure cultures of microorganisms, isolated from clinic material, but also determining and calculating the composition of microbial community, which is encoded in markers of the concrete sample [5,6]. The material for investigation in clinic is blood, saliva, urine, liquor, synovial or ascetic liquid, mucosa, phlegm, throat, nose and ear swabs, secretion from genitals, tissue sampling, skin smears, depending on the aim of investigation. The skin biotopes could be selected in accordance with the concrete experimental task [4].
Samples of biological liquid or tissue should be treated immediately or frozen and stored at — 5/ -18 °C in case it is impossible to immediately analyze. Transportation of samples at normal temperature for five hours can be permitted. Storing in dried form is needed in case the samples need distant transportation or need to be sent by post (dry at 70-85 °C).

  1. Materials and methods
    • The automated analysis of native swab

By means of automated analysis method the laboratory researched 10 samples prepared from each of the 12 biotopes of five volunteers-participants of long-term experiment in confined habitat. Swabs from mucous membranes of the top respiratory ways were investigated.
The object of research for the automated analysis is smears prepared by means of centrifugation using a DiffSpin 2 Slide Spinner (model M 701-22, StatSpin, USA). The analysis was carried out by automatic scanning of the preparation under the microscope equipped with the automated subject table and a video camera. The system automatically focuses by the microscope, inputs the images of the microscopic vision field in computer memory, segments the image (allocation of objects from a background) and recognises it as gram-positive and gramnegative cocci and rods. Further the system counts quantity of microbial objects in groups (types) on all areas of scanning and calculates the number ratio between groups and the common microbial number (CFU/sample).
For verification of the data received by means of the automated analysis, bacteriological research was carried out.

Fig. 3. The vision field of Gram-positive cocci smear image processing

Fig. 4. The vision field of Gram-positive rod bacteria smear image processing.

Fig. 5. The vision field of yeastlike mycoses smear image processing

The material from biotope was passed through a rinsing solution and further crop from the received cultivations on nutrient mediums a blood agar of 5%, a mannitol hydrochloric agar, Endo and Sauburaud was spent. Crops incubated in thermostat at 37 °C for 2 days, then calculation of the evolved colonies and their specific definition was spent.
Also smears were investigated by means of immersion microscopy (1000 x ). The common condition of swab was estimated on the following scale: ‘‘low», ‘‘average», and ‘‘high» contamination level. ‘‘Low» semination corresponded to 1-2 microbial objects on all smear areas,“average» — in fields of vision of a microscope on a regular basis there are microbial objects, ‘‘high” — microbial objects meet almost each field of vision of a microscope.
The scheme of the investigation equipment is shown in Fig. 1. An example of objects segmentation on vision field of native smear is given in Fig. 2. Examples of vision field with different types of microbial objects processing are given in Figs. 3-5.

  • Gas chromatomass spectrometry

We investigated microflora of cosmonauts, participants of one of the ISS mission one day prior to launch and on the 7th day of the flight. Material was taken with the use of standard packs including 12 biotopes and 1 control.
We investigated nose, mouth, tongue, teeth-mucosa of organism, ear, forehead, cheek, neck, chest, armpit, groin, and arm-skin of organism. Material was taken before flight and on the 7th day of flight.
Tampons with smears were divided into two subsamples, the first of which was directed to GC-MS investigation and the second was analyzed by the classic bacteriological method.
Samples preparation.
Samples in Teflon-lined glass test tubes were heated in 400 ml of 2 M methanolic HCL at 80 1C for one hour.
Subsequently 400ml of hexane was added to the reaction mixture. The mixture was vortexed and stored until division ofphases for 5min at room temperature. The upper hexane fraction was evaporated for 5-7min at 801C.
The dried residuum was treated with 20 mlofN, O-bysftoracetamide for 15 min at 801C in a closed vial.
80 ml hexane was added to the reaction mixture and the mixture was transferred to the closed vial. The mixture of esters of 2 mkl was injected into the capillary column of system AT-5973N Agilent Technologies by an autosampler. For treatment of the results the standard programs of the unit were used. GC-MS extracting of sample was on a capillary column with methylsilicon phase HP-5MS Agilent. The regimen of analyzing and detecting microorganisms by markers was implemented as described above. The analysis protocol and compatibility of markers to known microbial specia were performed in accordance with the description in [3,4].
Areas of markers ‘‘peaks»were integrated automatically by special program with an internal standard. Subsequently these data were involved in the quantification program, made in electron tables EXEL. Dates of calibration on dateric tridecan acide and pure cultures of clinical isolated microorganisms were used for quantification analyses.

  • Calculation of composition and amount of effective cells of microorganisms.

This mode is described for estimating ecological microbial communities in general view from m compounds and n specimens ofmicroorganisms by composing system of m equation for n unknowns.

Fig. 6. The image of Gram-positive cocci.

Fig. 7. The image of Gram-positive rod bacteria.

The area of GC-MS marker peak is in proportion to its concentration. Therefore it is in proportion to concentrations of corresponding microorganisms, which is defined as the member of N cells in the unit of volume or weight of sample by the following formula:
N1 — Ai[Mst/(q2 x Msam x Ast)]/Ri1;
where the form in square brackets is constant k — Mst/q2/M sam /Ast — Mst(mg)/5; 1
In these formulae Ai is the area of markers peak, Mst the quantity of standard, injected into the sample (mg), Msam the corresponding quantity of the sample, Ast the area of standard peak, Ril the portion(%) of marker with index i in FAs profile of the determined microbe number 1 (N1),
q2 the coefficient that is equal to 5.1 x 1015g, where value 5.9 x 10 cells of microbes contained in 1 g of microbial biomass and part of FAs in cell, averaging 3%.
Correspondingly, the number of cells of any further microorganism can be calculated by the analogous formula N2=Ai x k/Ri2, multiplying areas of marker peak Ai on the k coefficient and dividing on the portion of markers (in %) in composition FAs of this microorganism.
By this mode an effective number of bacteria species, namely Clostridium perfringens, Cl. difficile, Prevotella, Stenotrophomonas, Klebsiella, Eubacterium, Rhodococcus, Nocardia, Sphingobacterium, Pseudomonas, Enterococcus, Staphylococcus, Enterobacteriaceae, etc., were detected. Some bacteria interfere in the synthesis of stearines in human cells, and it allows us to determine bacteria Eubacterium by the product of transformation of human cholesterol by its fermentation in coprostanol.
Some compounds do not have the property of marker, i.e. can be concerned with two or more taxons; therefore in this case part of the contribution of each microorganism should be determined, using conclusion of equation‘ system for two compounds.
Investigation was done by the classic bacteriologic method (plating microscopy, estimation of results by quantitative method, estimation of results) according to the method described in order MZ Ao 535 22.04.1985. Also isolated cultures were identified (using corresponding methods and media) according to the order MZ Ao535 22.04.1985. Biochemical identification was carried out using commercial test systems LACHEMA, according to the instruction of the manufacturer.

  1. Results and discussion
    • The automated analysis of native swab

The results received by means of the automated analysis were compared with received cultural method and with expert estimations. These researches have shown good correlation with previously mentioned methods. It was shown that results of the automated analysis are authentic at number 104 CFU/sample and above. Such accuracy is sufficient and allows revealing the threat of an infection in time. Results of the researches are presented in Table 1. The image of gram-positive cocci and rod bacteria are shown in Figs. 6 and 7.

  • Gas chromatomass spectrometry

The results obtained by GC-MS are presented in Tables 2 and 3.
The dates of GC-MS analyses in most cases compared with bacteriological indexes:
increasing of quantitative compounds of protective groups:

  • Growth of Pseudomonas aeruginosa,
  • Reduction of Enterococcus spp.

Certain deviations from bacteriological studies occur in quantitative characteristics of tested cultures. There was no distinguishing of S aureus from Staphylococcus spp. pool. Also there is a problem with distinguishing Protea from Providencia and detection of Klebsiella. Anyway it was the first attempt to use GC-MS method for covering tissues microflora detection and the obtained results were satisfactory in general.
The chromatograms obtained by the selective ion method (Fig. 8) can confidently detect microbial components in the presence of predominant human wastes components. For the most part, the peaks of target substances are superposition-free, rather distant from the peak of a substrate and therefore they may be accessible for automatic random integration in accordance with the standard program of the GC-MS system. The list of fatty acids, aldehydes and sterols detected in specimens is given elsewhere [7], by indicating the most likely microorganisms in whose cells they usually were found. For instance, i16 (iso-hexadecanoic acid) is a marker of Streptomyces spp., 18:1o7 refer to Lactobacillus spp., h14 (3-hydroxy-tetra- decanoic acid) is a well-known summed feature of family Enterobacteriaceae, genera Haemophylus, Fusobacterium and other gram-negative microbes, whose endotoxine contains this substance.

  1. Conclusions

The proposed 2 non-cultural methods could be a good perspective for these purposes.
With the aid of chromatomass-spectrometry method testing it was confirmed that on the 7th day of flight there is

Fig. 8. Single ion monitoring chromatograms represent fractions of a cavity of nose fatty acids (ion 87, upper plot), fatty aldehydes (ion 75, in the middle) and hydroxyl FA (ion 175, lower plot). Marking: 18:1o7a-18- is the number of carbon atoms, the figure after colon denotes the number of double bonds; o7 — double bond position from carboxyl head of molecule h — 3-hydroxy-acid, back a — aldehyde, front i — iso-branched. For example, hi17 means 3 -hydroxy-iso-heptadecanoic acid.
an increase of pathogenicity potential, i.e. quantitative increase of conventional pathogens and decrease of protective groups. The method allows one to increase the spectrum of the controlled list of microbial specie. The data in majority are comparable with bacteriology indices: quantitative increase of Pseudomonas aeruginosa, decrease of enterococci. This determines the necessity of maintaining a portable chromatomass spectrometer for diagnostics of disbacteriosis.
Problems that should be solved concern the problems of differentiation of certain microbial groups: differentiation of S. aureus from the other staphylococci, detection of Proteus spp., Klebsiella spp. Quantitative characteristics of microbial content should be revised. Also one and the same markers are used for detection ofdifferent specie. As a result in some cases ‘‘false detection» occurs.

  • E. Stead, J.E. Sellwood, J. Wilson, et al., Evaluation of a commercial microbial identification system based on fatty acid profiles for rapid, accurate identification of plant pathogenic bacteria, J. Appl. Bacteriol. 72 (1992) 315-321.
  • S. Weyant, C.W. Moss, R.E. Weaver, et al., Identification of Unusual Pathogenic Gram-Negative Aerobic and Facultative Anaerobic bacteria, second ed., Williams and Wilkins, Aaaaa, 1996.
  • A. Osipov, E.S. Turova, Studying species composition of microbial communities with the use of gas chromatography-mass spectrometry. Microbial community of kaolin, FEMS Microbiol. Rev. 20 (1997) 437-446.
  • V. Polesko, U.S. Butov, G.A. Osipov, T.I. Kabaeva, V.V. Parfenov, N.V. Delenyan, Composition of sebum, microecology of skin and intestine of patients with dermatitis and acne. (investigation by GC-MS method),, Russ. J. Skin Venerology Dis. 1 (2) (2007) 43.
  • Ju-Hyeong Park, Bogumila Szponar, Lennart Larsson, Diane R. Gold, Donald K. Milton, Characterization of Lipopolysaccharides present in settled house dust, Appl. Microbiol. 70 (1) (2004) 262-267.
  • Aleksandra Sebastian, Lennart Larsson, Characterization of the microbial community in indoor environments: a chemical-analytical approach, Appl. Microbiol. 69 (6) (2003) 3103-3109.
  • V. Beloborodova, G.A. Osipov, Small molecules originating from microbes (SMOM) and their role in microbes-host relationship, Microb. Ecol. Health Dis. SCUP 12 (2000) 12-21.

© Ilyin Viacheslav , Moukhamedieva Lana, Osipov Georgy, Batov Aleksey, Soloviova Zoya,
Mardanov Robert, Panina Yana, Gegenava Anna
Institute for Biomedical Problems, Sanitary chemical and microbial safety, Khoroshevskoye shosse 76a, 123007 Moscow, Russian Federation
I   Viacheslav et al. Acta Astronautica 68 (2011) 1529-1536

Добавить комментарий