Linda J. Magrum

Bio: Linda J. Magrum is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Ribosomal RNA & RNase P. The author has an hindex of 12, co-authored 14 publications receiving 5580 citations.

The Phylogeny of Prokaryotes

Abstract: For the first time a single experimental approach, 16S ribosomal RNA sequence characterization, has been used to develop an overview of phylogenetic relationships in the bacterial world. The techni...

Classification of methanogenic bacteria by 16S ribosomal RNA characterization.

Abstract: The 16S ribosomal RNAs from 10 species of methanogenic bacteria have been characterized in terms of the oligonucleotides produced by T(1) RNase digestion. Comparative analysis of these data reveals the methanogens to constitute a distinct phylogenetic group containing two major divisions. These organisms appear to be only distantly related to typical bacteria.

Secondary structure model for bacterial 16S ribosomal RNA: phylogenetic, enzymatic and chemical evidence

Abstract: We have derived a secondary structure model for 16S ribosomal RNA on the basis of comparative sequence analysis, chemical modification studies and nuclease susceptibility data. Nucleotide sequences of the E. coli and B. brevis 16S rRNA chains, and of RNAse T1 oligomer catalogs from 16S rRNAs of over 100 species of eubacteria were used for phylogenetic comparison. Chemical modification of G by glyoxal, A by m-chloroperbenzoic acid and C by bisulfite in naked 16S rRNA, and G by kethoxal in active and inactive 30S ribosomal subunits was taken as an indication of single stranded structure. Further support for the structure was obtained from susceptibility to RNases A and T1. These three approaches are in excellent agreement. The structure contains fifty helical elements organized into four major domains, in which 46 percent of the nucleotides of 16S rRNA are involved in base pairing. Phylogenetic comparison shows that highly conserved sequences are found principally in unpaired regions of the molecule. No knots are created by the structure.

16S ribosomal DNA amplification for phylogenetic study.

Abstract: A set of oligonucleotide primers capable of initiating enzymatic amplification (polymerase chain reaction) on a phylogenetically and taxonomically wide range of bacteria is described along with methods for their use and examples. One pair of primers is capable of amplifying nearly full-length 16S ribosomal DNA (rDNA) from many bacterial genera; the additional primers are useful for various exceptional sequences. Methods for purification of amplified material, direct sequencing, cloning, sequencing, and transcription are outlined. An obligate intracellular parasite of bovine erythrocytes, Anaplasma marginale, is used as an example; its 16S rDNA was amplified, cloned, sequenced, and phylogenetically placed. Anaplasmas are related to the genera Rickettsia and Ehrlichia. In addition, 16S rDNAs from several species were readily amplified from material found in lyophilized ampoules from the American Type Culture Collection. By use of this method, the phylogenetic study of extremely fastidious or highly pathogenic bacterial species can be carried out without the need to culture them. In theory, any gene segment for which polymerase chain reaction primer design is possible can be derived from a readily obtainable lyophilized bacterial culture.

Taxonomic Note: A Place for DNA-DNA Reassociation and 16S rRNA Sequence Analysis in the Present Species Definition in Bacteriology

Abstract: Because a natural entity “species” cannot be recognized as a group of strains that is genetically well separated from its phylogenetic neighbors, a pragmatic approach was taken to define a species by a polyphasic approach (L. G. Wayne, D. J. Brenner, R. R. Colwell, P. A. D. Grimont, O. Kandler, M. I. Krichevsky, L. H. Moore, W. E. C. Moore, R. G. E. Murray, E. Stackebrandt, M. P. Starr, and H. G. Truper, Int. J. Syst. Bacteriol. 37:463-464, 1987), in which a DNA reassociation value of about 70% plays a dominant role. With the establishment of rapid sequence analysis of 16S rRNA and the recognition of its potential to determine the phylogenetic position of any prokaryotic organism, the role of 16S rRNA similarities in the present species definition in bacteriology needs to be clarified. Comparative studies clearly reveal the limitations of the sequence analysis of this conserved gene and gene product in the determination of relationships at the strain level for which DNA-DNA reassociation experiments still constitute the superior method. Since today the primary structure of 16S rRNA is easier to determine than hybridization between DNA strands, the strength of the sequence analysis is to recognize the level at which DNA pairing studies need to be performed, which certainly applies to similarities of 97% and higher.

Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya.

Abstract: Molecular structures and sequences are generally more revealing of evolutionary relationships than are classical phenotypes (particularly so among microorganisms). Consequently, the basis for the definition of taxa has progressively shifted from the organismal to the cellular to the molecular level. Molecular comparisons show that life on this planet divides into three primary groupings, commonly known as the eubacteria, the archaebacteria, and the eukaryotes. The three are very dissimilar, the differences that separate them being of a more profound nature than the differences that separate typical kingdoms, such as animals and plants. Unfortunately, neither of the conventionally accepted views of the natural relationships among living systems--i.e., the five-kingdom taxonomy or the eukaryote-prokaryote dichotomy--reflects this primary tripartite division of the living world. To remedy this situation we propose that a formal system of organisms be established in which above the level of kingdom there exists a new taxon called a "domain." Life on this planet would then be seen as comprising three domains, the Bacteria, the Archaea, and the Eucarya, each containing two or more kingdoms. (The Eucarya, for example, contain Animalia, Plantae, Fungi, and a number of others yet to be defined). Although taxonomic structure within the Bacteria and Eucarya is not treated herein, Archaea is formally subdivided into the two kingdoms Euryarchaeota (encompassing the methanogens and their phenotypically diverse relatives) and Crenarchaeota (comprising the relatively tight clustering of extremely thermophilic archaebacteria, whose general phenotype appears to resemble most the ancestral phenotype of the Archaea.

Phylogenetic structure of the prokaryotic domain: The primary kingdoms

Abstract: A phylogenetic analysis based upon ribosomal RNA sequence characterization reveals that living systems represent one of three aboriginal lines of descent: (i) the eubacteria, comprising all typical bacteria; (ii) the archaebacteria, containing methanogenic bacteria; and (iii) the urkaryotes, now represented in the cytoplasmic component of eukaryotic cells.

Genetic algorithm approaches for the phylogenetic analysis of large biological sequence datasets under the maximum likelihood criterion

Abstract: Phylogenetic trees have a multitude of applications in biology, epidemiology, conservation and even forensics. However, the inference of phylogenetic trees can be extremely computationally intensive. The computational burden of such analyses becomes even greater when model-based methods are used. Model-based methods have been repeatedly shown to be the most accurate choice for the reconstruction of phylogenetic trees, and thus are an attractive choice despite their high computational demands. Using the Maximum Likelihood (ML) criterion to choose among phylogenetic trees is one commonly used model-based technique. Until recently, software for performing ML analyses of biological sequence data was largely intractable for more vi than about one hundred sequences. Because advances in sequencing technology now make the assembly of datasets consisting of thousands of sequences common, ML search algorithms that are able to quickly and accurately analyze such data must be developed if ML techniques are to remain a viable option in the future. I have developed a fast and accurate algorithm that allows ML phylogenetic searches to be performed on datasets consisting of thousands of sequences. My software uses a genetic algorithm approach, and is named GARLI (Genetic Algorithm for Rapid Likelihood Inference). The speed of this new algorithm results primarily from its novel technique for partial optimization of branch-length parameters following topological rearrangements. Experiments performed with GARLI show that it is able to analyze large datasets in a small fraction of the time required by the previous generation of search algorithms. The program also performs well relative to two other recently introduced fast ML search programs. Large parallel computer clusters have become common at academic institutions in recent years, presenting a new resource to be used for phylogenetic analyses. The P-GARLI algorithm extends the approach of GARLI to allow simultaneous use of many computer processors. The processors may be instructed to work together on a phylogenetic search in either a highly coordinated or largely independent fashion.