Notable

T. Sicheritz-Pontén, S.G. Andersson, "A phylogenomic approach to microbial evolution," Nucleic Acids Research, 29[2]:545-52, Jan. 15, 2001. F1000 Rating: Must Read "The paper describes methods and computer programs for automated phylogenetic analysis of complete genome datasets, as well as useful visualization tools for the results. The tools should be useful to those looking for genes that may have unusual evolutionary histories relative to other genes in the same genome." —Jonath

| 3 min read

Register for free to listen to this article
Listen with Speechify
0:00
3:00
Share
T. Sicheritz-Pontén, S.G. Andersson, "A phylogenomic approach to microbial evolution," Nucleic Acids Research, 29[2]:545-52, Jan. 15, 2001.


F1000 Rating: Must Read

"The paper describes methods and computer programs for automated phylogenetic analysis of complete genome datasets, as well as useful visualization tools for the results. The tools should be useful to those looking for genes that may have unusual evolutionary histories relative to other genes in the same genome."
—Jonathan A. Eisen,
The Institute for Genomic Research (TIGR), US

Structural Biology

J.E. Barrick et al., "Large libraries reveal diverse solutions to an RNA recognition problem," Proceedings of the National Academy of Sciences (PNAS), 98[22]: 12374-8, Oct. 23, 2001.

F1000 Rating: Recommended

"The development of tight-binding and highly selective small molecule ligands for RNA remains a very challenging problem, but this article demonstrates that combinatorial selection approaches such as the in vitro mRNA-peptide fusion systems offer promising possibilities for RNA recognition. Using a previously described in vitro mRNA-peptide fusion system, libraries of 150, 1600, and 9 trillion different peptide sequences were constructed based on the arginine-rich, RNA-binding domain of the lambda N protein. This sequence is known to recognize with high affinity the boxBR RNA hairpin containing a five-base RNA loop that adopts a tetraloop fold. In this work, several high affinity RNA-binding peptides were isolated (down to low nanomolar dissociation constants), demonstrating the usefulness of biological combinatorial libraries at targeting RNA."
—Dennis Hall,
University of Alberta, Canada

Genomics & Genetics

Y. Timsit, "Convergent evolution of MutS and topoisomerase II for clamping DNA crossovers and stacked Holliday junctions," Journal of Biomolecular Structure and Dynamics, 19[2]:215-8, October 2001.

F1000 Rating: Exceptional
"This study provides structural and evolutionary evidence for convergence at the protein structural level (between a DNA repair protein and a topoisomerase). This finding has major implications for molecular evolutionary studies, since it has been generally assumed by most researchers that structural similarity must be the result of homology (common ancestry) rather than analogy (e.g., convergence)."
—Jonathan A. Eisen,
TIGR, US

Neuroscience

S.K. Rehen et al., "Chromosomal variation in neurons of the developing and adult mammalian nervous system," PNAS, 98[23]:13361-6, Nov. 6, 2001.

F1000 Rating: Must Read

"The basic assumption that the normal mammalian nervous system contains neurons with identical genomes is challenged by this study, which suggests that the nervous system is a genetic mosaic. Multiple lines of evidence suggested that genomes of developing and adult neurons can be different at the level of whole chromosomes, i.e. neurons exhibit chromosomal aneuploidy. The biological consequences of neuronal aneuploidy might be similar to X-inactivation, imprinting or allelic inactivation. Aneuploid neurons with altered physiology might have significant consequences for establishment of neural networks."
—Marjori Matzke,
Institute of Molecular Biology, Austria

Bioinformatics

C. Kooperberg, et al., "Sequence analysis using logic regression," Genetic Epidemiology, 21[Suppl. 1]:S626-31, 2001.

F1000 Rating: Exceptional

"The authors develop a new adaptive regression methodology, called Logic Regression, that attempts to construct predictors as Boolean combinations of (binary) covariates; this methodology should be useful for finding associations between many genetic/environmental factors and disease outcomes. This is an exciting new approach to finding the few important predictors out of large pools of possible predictors, while allowing for complex interactions between the underlying predictors. For more details on this exciting and promising new methodology, see the authors' technical report on their Web page (bear.fhcrc.org/~clk/ref.html)."
—Daniel Weeks,
University of Pittsburgh, US

Cell Biology

C. Klein et al., "NMR spectroscopy reveals the solution dimerization interface of p53 core domains bound to their consensus DNA," Journal of Biological Chemistry, 276[52]:49020-7, Dec. 28, 2001.

F1000 Rating: Must Read

"The activation mechanism of the p53 tumor suppressor protein is still unclear - this paper adds experimental data to address this question, and derives a new model for the dimerization of p53 after DNA binding. In this model, the dimerization interface includes the short H1 helix, which contains "hot spots" for p53 mutations and comprises the binding site for a putative p53 inhibitor."
—Wolfgang Jahnke,
Novartis Pharma AG, Switzerland

Immunology

T. Sasada et al., "A naturally processed mitochondrial self-peptide in complex with thymic MHC molecules functions as a selecting ligand for a viral-specific T cell receptor," Journal of Experimental Medicine, 194[7]:883-92, Oct. 1, 2001.

F1000 Rating: Must Read

"This interesting paper describes the identification of a naturally processed thymic peptide involved in positive selection of a viral antigen specific T cell repertoire. The authors guide the biochemical isolation of the natural peptide with a functional assay involving TCR transgenic thymocytes. The peptide turned out to be derived from the widely expressed mitochondrial NADH ubiquinone oxidoreductase. Importantly, the peptide has little sequence homology with the cognate antigenic peptide, it is a weak agonist for mature specific T cells but induces functional differentiation of TCR transgenic thymocytes. Thus, this is the first naturally occurring ligand directly recovered from thymus that can mediate positive selection of immature T cells."
—Pedro Romero,
Ludwig Institute of Cancer Research,
Lausanne branch, Switzerland

Interested in reading more?

Become a Member of

The Scientist Logo
Receive full access to digital editions of The Scientist, as well as TS Digest, feature stories, more than 35 years of archives, and much more!
Already a member? Login Here

Keywords

Meet the Author

  • Jeffrey Perkel

    This person does not yet have a bio.

Published In

Share
Image of a woman in a microbiology lab whose hair is caught on fire from a Bunsen burner.
April 1, 2025, Issue 1

Bunsen Burners and Bad Hair Days

Lab safety rules dictate that one must tie back long hair. Rosemarie Hansen learned the hard way when an open flame turned her locks into a lesson.

View this Issue
Faster Fluid Measurements for Formulation Development

Meet Honeybun and Breeze Through Viscometry in Formulation Development

Unchained Labs
Conceptual image of biochemical laboratory sample preparation showing glassware and chemical formulas in the foreground and a scientist holding a pipette in the background.

Taking the Guesswork Out of Quality Control Standards

sartorius logo
An illustration of PFAS bubbles in front of a blue sky with clouds.

PFAS: The Forever Chemicals

sartorius logo
Unlocking the Unattainable in Gene Construction

Unlocking the Unattainable in Gene Construction

dna-script-primarylogo-digital

Products

Atelerix

Atelerix signs exclusive agreement with MineBio to establish distribution channel for non-cryogenic cell preservation solutions in China

Green Cooling

Thermo Scientific™ Centrifuges with GreenCool Technology

Thermo Fisher Logo
Singleron Avatar

Singleron Biotechnologies and Hamilton Bonaduz AG Announce the Launch of Tensor to Advance Single Cell Sequencing Automation

Zymo Research Logo

Zymo Research Launches Research Grant to Empower Mapping the RNome