Genetic Methods of Classifying Microbes

There are three most prominent ‘genetic methods’ that are invariably employed for the methodi- cal arrangement of microbes based upon various taxonomic groups (i.e., Taxa), namely:

(i) Genetic relatedness (ii) The intuitive method, and (iii) Numerical taxonomy.

The aforesaid ‘genetic methods’ shall now be treated separately in the sections that follows.

3.3.3.1. Genetic Relatedness

It is regarded to be one of the most trustworthy and dependable method of classification based solely upon the critical extent of genetic relatedness occurring between different organisms. In addition this particular method is considered not only to be the utmost objective of all other techniques based upon the greatest extent pertaining to the fundamental aspect of organisms, but also their inherent he- reditary material (deoxyribonucleic acid, DNA).

It is, however, pertinent to state here that in actual practice the genetic relatedness may also be estimated by precisely measuring the degree of hybridization taking place either between denatured DNA molecules or between single stranded DNA and RNA species. The extent of homology* is as- sayed by strategically mixing two different, types of ‘single-stranded DNA’ or ‘single-stranded DNA

with RNA’ under highly specific and suitable experimental parameters; and subsequently, measuring

accurately the degree to which they are actually and intimately associated to give rise to the formation of the desired ‘double-stranded structures’ ultimately. The aforesaid aims and objectives may be accom- plished most precisely and conveniently by rendering either the DNA or RNA radioactive and measur- ing the radio activities by the help of Scintillation Counter or Geiger-Müller Counter.

Table 3.2, shows the extent of genetic relatedness of different microbes as assayed by the ensu- ing DNA-RNA hybridization. Nevertheless, it has been duly demonstrated and proved that the genetic relatedness can be estimated accurately by DNA-RNA hybridization; however, the DNA-DNA hybridi-

zation affords the most precise results, provided adequate precautions are duly taken to ascertain and

ensure that the prevailing hybridization between the two strands is perfectly uniform.

Table 3.2 : DNA Homologies amongst Some Microorganisms

S.No. Source of DNA Percent Relatedness to E. coli (%)

1 Acetobacter aerogenes 45 2 Bacillus subtilis 1 3 Escherichia coli 100 4 Proteus vulgaris 14 5 Salmonella typhimurium 35 6 Serratia marcescens 7 7 Shigella dysenteriae 71

3.3.3.2. The Intuitive Method

Various ‘microbiologists’ who have acquired enormous strength of knowledge, wisdom, and hands-on experience in the expanding field of ‘microbiology’ may at a particular material time vehe- mently decide and pronounce their ultimate verdict whether the microorganisms represent one or more species or genera. The most predominant and utterly important disadvantage of this particular method being that the characteristic features of an organism which may appear to be critical and vital to one researcher may not seem to be important to the same extent to another, and altogether different taxono- mists would ultimately decide on something quite different categorization at the end. Nevertheless, there are certain ‘classification schemes’ that are exclusively based upon the intuitive method and definitively proved to be immensely beneficial and useful in microbiology.

3.3.3.3. Numerical Taxonomy

The survey of literatures have amply proved that in the Nineteenth Century, microbes were categorically grouped strictly in proportion to their evolutionary affinities. Consequently, the systematic and methodical segregation and arrangement of microorganisms into the various organized groups was entirely on the specialized foundation of inherited and stable structural and physiological characteristic features. This arrangement is termed as the ‘Natural Classification’ or the ‘Phylogenetic Classifiction’. Interestingly, this particular modus operandi for the classification of microorganisms has now almost turned out to be absolutely redundant, and hence abandoned outright quite in favour of a rather more realistic empirical approach based exclusively on ‘precise quantification’ pertaining to close similarities and distinct dissimilarities prevailing amongst the various microbes. Michael Adanson was the first and foremost microbiologist who unequivocally suggested this magnanimous approach, which was termed as Adansonian Taxonomy or Numerical Taxonomy.

Salient Features: The various salient features of the Numerical Taxonomy (or Adansonian Taxonomy) are as enumerated below:

(1) The fundamental basis of Numerical Taxonomy is the critical assumption, that in the event when each phenotypic character is assigned even and equal weightage, it must be viable and feasible to express numerically the explicit taxonomic distances existing between microor- ganisms, with regard to the number of actual characters which are shared in comparison to the total number of characters being examined ultimately. The importance of the Numerical

Taxonomy is largely influenced by the number of characters being investigated. Therefore,

it would be absolutely necessary to accomplish precisely an extremely high degree of signifi- cance—one should examine an equally large number of characters.

(2) Similarity Coefficient and Matching Coefficient: The determination of the similarity co-

efficient as well as the matching coefficient of any two microbial strains, as characterized

with regard to several character variants viz., a, b, c, d etc., may be determined as stated under:

Number of characters + ve in both strains = a

Number of characters + ve in ‘strain-1’ and – ve in ‘Strain-2’ = b Number of characters, – ve in ‘Strain-1’ and + ve in ‘Strain-2’ = c

Number of characters – ve in both strain = d

Similarity coefficient [S_j] = a a+ +b c Matching coefficient [S_s] = a b a b c d + + + + .

Based on the results obtained from different experimental designs, it has been observed that the

similarity coefficient does not take into consideration the characters that are ‘negative’ for both organ-

isms; whereas, the matching coefficient essentially includes both positive and negative characters.

Similarity Matrix: The ‘data’ thus generated are carefully arranged in a ‘similarity matrix’

only after having estimated the similarity coefficient and the matching coefficient for almost all microor- ganisms under investigation duly and pair-wise, as depicted in Fig. 3.1 below. Subsequently, all these matrices may be systematically recorded to bring together the identical and similar strains very much close to one another.

1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Percent Similarity 100 90 99 80 89 70 79 60 69 50 59

Fig. 3.1. Similarity Matrix for Ten Strains of Microorganisms.

In actual practice, such data are duly incorporated and transposed to a ‘dandogram’* as illus- trated in Fig. 3.2 under, that forms the fundamental basis for establishing the most probable taxonomic

30 40 50 60 70 80 90 100 8 4 10 7 6 3 9 5 2 1 Similarity Levels Similarity levels Strain Number P er cent S im ila rity

Fig. 3.2. Dandogram Depicting Similarity Relationship Amongst Ten Microbial Strains.

arrangements. The ‘dotted line’ as indicated in (Fig. 3.2) a dandogram evidently shows ‘similarity

levels’ that might be intimately taken into consideration for recognizing two different taxonomic ranks, for instance: a genus and a species.

The ‘Numerical Taxonomy’ or ‘Adansonian Approach’ was thought and believed to be quite impractical and cumbersome in actual operation on account of the reasonably copious volume and mag- nitude of the ensuing numerical calculations involved directly. Importantly, this particular aspect has now almost been eliminated completely by the advent of most sophisticated ‘computers’ that may be programmed appropriately for the computation of the data, and ultimately, arrive at the degree of simi-

larity with great ease, simplicity, and precision. It is, however, pertinent to point out at this juncture that

though the ensuing ‘Numerical Taxonomy’ fails to throw any light with specific reference to the pre- vailing genetic relationship, yet it amply gives rise to a fairly stable fundamental basis for the articu-

lated categorization of the taxonomic distribution and groupings.

Limitations of Numerical Taxonomy: The various limitations of numerical taxonomy are as

enumerated under:

(1) It is useful to classify strains within a larger group which usually shares the prominent characteristic features in common.

(2) The conventional classification of organisms solely depends on the observations and knowledge of the individual taxonomist in particular to determine the ensuing matching similarities existing between the bacterial strains; whereas, numerical taxonomy exclusively depends upon the mathematical figures plotted on paper.

(3) The actual usage of several tests reveals a good number of phenotypes, thereby more genes are being screened; and, therefore, no organism shall ever be missed in doing so.

* This is a way to express the similarity between the different Operational Taxonomic Units (OTUs). It is also known as Hierarchic Taxonomic Tree. It is prepared from the similarity matrix data for the strains under test. The result is presented in the form of a figure when a line joins all similar OTUs to one another.

(4) One major limitation of the numerical analysis is that in some instances, a specific strain may be grouped with a group of strains in accordance to the majority of identical characteristic features, but certainly not to all the prevailing characters. However, simultaneously the particu- lar strain may possess a very low ebb of similarity with certain other members of the cluster. (5) The exact location of the taxon is not yet decided, and hence cannot be grouped or related to

any particular taxonomic group, for instance : genes or species.

(6) Evidently, in the numerical analysis, the definition of a species is not acceptable as yet, whereas some surveys do ascertain that a 65% single-linkage cluster distincly provides a 75% approximate idea of the specific species.