Protein fingerprinting may serve as a complementary tool for the phylogenetic classification of heterocystous (Nostoc, Anabaena, Cylindrospermum, Aulosira and Tolypothrix) Cyanobacteria
S Mishra, P Bhargava, R Rai, Y Mishra, T Zotta, E Parente, L Rai
16s rrna gene, cyanobacteria, maximum-parsimony, protein fingerprinting sodium-dodecyl sulphate polyacrylamide gel electrophoresis
S Mishra, P Bhargava, R Rai, Y Mishra, T Zotta, E Parente, L Rai. Protein fingerprinting may serve as a complementary tool for the phylogenetic classification of heterocystous (Nostoc, Anabaena, Cylindrospermum, Aulosira and Tolypothrix) Cyanobacteria. The Internet Journal of Microbiology. 2008 Volume 7 Number 2.
A combination of morphology, SDS-PAGE, 16S rRNA gene and the fuzzy approach has been used for the first time to attest the phylogenetic affiliation of the cyanobacterial species such as
Cyanobacteria are the most widespread, photosynthetic prokaryotes with remarkable degrees of morphological and developmental diversity. Among the heterocystous cyanobacteria, Nostocalean strains are considered to be the most important component of the N2-fixing community in nutrient poor, arid and semiarid soils world wide (Doods
Cyanobacteria have been traditionally classified on the basis of their morphological and physiological characteristics (Gietler, 1932; Desikachary, 1959). However, morphology of the strains may change depending on environmental conditions and the diversity of the strains can be altered by selective culture conditions (Palinska
SDS-PAGE whole cell protein pattern analysis has emerged as a powerful tool for bacterial identification having the advantages of being fairly fast and easy and, when performed under highly standardized conditions, it offers a better taxonomic resolution at species or subspecies level (Vandamme
The logistic weighting function is a procedure which transforms complex electrophoretic patterns consisting of two vectors of data (molecular weight and band intensities) with varying length into a single vector of fixed length consisting of band intensities accumulated in classes of molecular weight. This data reduction by logistic weighting function provides better cluster pattern as compared to commercial software like diversity database. This approach has already been utilized in case of bacteria (Piraino
Materials and methods
Strains, media and culture conditions
Twenty-one strains used in the study were isolated from paddy fields of Eastern Uttar Pradesh.
Morphological assessment and phylogenic tree construction
Morphological characterization of 21cyanobacterial strains were conducted using trinocular microscope (Kyowa Getner, Opto-Plan, 2KT, Japan, Model No. 90116) equipped with high resolution Nikon digital camera (model no. DXm 1200). Morphological characters were described according to traditional criteria (Desikachary, 1959; Geitler, 1932). All the (16) morphological characters used to prepare a matrix for WINCLADA are listed in Table 1 and described in detail in Appendix 1.
Among the characters only the presence and absence of sheath and hormogones were codified as binary data, while the remainings were codified as multivariate data. Composite coding was used in preference to binary coding in order to minimize the occurrence of inapplicable or missing entries. Unknown determinations of the true state or missing data, are represented in the matrix by a “?”. Primary causes of missing data include character states being not visible in the material available. The order of appearance of the characters in the matrix is functional facilitating future data addition.
The phylogenetic tree was constructed using WINCLADA version 1.00.008 (Nixon, 1999). The maximum parsimony analysis of above mentioned characters was done selecting
Protein extraction and SDS-PAGE analysis
Protein extraction was performed using a modified protocol of Wagener
SDS-PAGE data processing and statistical analysis
The image analysis was performed using the Quantity one software (Bio-Rad, USA). The protein fingerprinting patterns were compared using the information on apparent molecular masses of bands, band intensity, normalized quantity, trace intensity, and Gauss intensity.
SDS-PAGE patterns were processed as described by Piraino
Genomic DNA extraction, 16S rRNA gene amplification and Sequencing
Total genomic DNA was extracted by the phenol free method of Srivastava
Alignment and Phylogenetic analysis
The 16S rRNA gene sequences of the twenty-one local isolates were multiple aligned using CLUSTAL X (1.83) (Thompson
Results and discussion
Cyanobacterial taxonomy has remained problematic for many years because of its dependence on morphological and ecological characters (Geitler, 1932; Desikachary, 1959). Taxonomic revisions are required to be done by a multidisciplinary approach including molecular, morphological, physiological, cytological and ecological (Suda
Morphology based phylogenetic tree
The cluster analysis carried out on the morphological characters grouped the strains in three major clusters (Fig. 2).
Further, cluster 3 emerged as a pure
SDS-PAGE based phylogenetic tree
The hierarchical cluster analysis (Unweighted Pair Group Method Using Average Linkage, UPGMA) carried out using the logistic weighted SDS-PAGE data set generated five major clusters at a similarity level (Pearson product-moment coefficient) of 0.7 (Fig. 3). Only four strains (position 1a, 2a, 3a and 4a) failed to group in any major cluster because their SDS-PAGE profile was different from the other strains. Most of the strain replicates grouped together at a similarity level ranging from 0.99 to 0.85 showing that the analysis was reproducible. Cluster C1 and C2, in the upper section of the dendrogram, were very near. Cluster C1 grouped
the strains of
16S rRNA gene based phylogenetic tree
In contrast to SDS-PAGE analysis the deepest nodes of the phylogenetic tree with only partial support by the bootstrap values separated the twenty-one strains in two large clades (Fig. 4). Clade 1 that included clusters I and II corresponded to
The large cluster I, included maximum number of nostocalean strains except few like
Thus the 16S rRNA gene data supports the grouping of the species indicated that
The small cluster II and III are composed of
The lowest clade of the phylogenetic tree corresponded to the wide radiation including the genera
All the three approaches were used together not only to find out the congruencies /incongruencies of the three systems in classifying the cyanobacterial isolates but also to check as how far the polyphasic approach is reliable as compared to single approach. Cluster C1 grouped
It may be thus proposed that the strains were phylogenetically linked and are of same genetic make up but appear quite different under different physiological conditions as a result of differential gene expression. Morphological differences suggest that they might have undergone different environmental pressures.
The grouping of
The coherent positioning of
The largest cluster C4 was quite congruent with the cluster 3 of 16S rRNA gene based MP tree. This exclusively harboured the species of
The present study reveals that the phenotypically diverse genera are closely related at their genetic level and represent their realistic phylogenetic relationship at the class and up to the genera level. It is also suggested that the clustering of strains in SDS-PAGE and 16S rRNA gene analyses is congruent and illustrates complementarity. Despite a few incongruities the clustering pattern of taxa in SDS-PAGE and 16S rRNA gene analyses are quite complementary to each other. The SDS-PAGE and 16S rRNA gene based phylogenetic analysis affirm the heterogeneity but monophyletic origin of nostocalean strains. Merging of
In conclusion, single-dimensional SDS-PAGE phylogeny may be used as a complementary tool for the 16S rRNA gene based analysis to identify the nitrogen-fixing species at the molecular level. This shows immense importance of the classical cyanobacterial taxonomic systems. Molecular methods should be used in parallel or as a supplement to the phenotypic characterization but never replace it otherwise the more precise and probably more reliable molecular data would produce confusing results concerning the occurrence of cyanobacterial genera and species in nature.
Appendix 1. Morphological character descriptions, arranged in an order conducive to minimal handling of cyanobacterial taxa during character scoring.
Lal Chand Rai is thankful to ICAR, New Delhi for financial support. Poonam Bhargava is thankful to UGC for the award to SRF and Rashmi Rai and Yogesh Mishra to CSIR for JRF and SRF respectively. We are also thankful to Head and Program Coordinator, CAS in Botany, BHU for facilities.