Journal Club: Microbiology, Cell Biology, and Microbiology & Computational Biology

Graduate Division

MICROBIOLOGY: Use of 16S rRNA gene for identification of a broad range of clinically relevant bacterial pathogens. Srinivasan, R., et al. (Lynch, S.V.). PLoS One. 2015. 10(2):e0117617.

Definitive diagnosis of infectious diseases frequently rests on growing a culture of the offending organism—this can be a time-consuming process and not all bacteria can be successfully cultured.

In recent years, much research has looked to improve up on this situation by developing means for diagnosis by sequencing. In this paper, the authors evaluated the reliability of sequencing 16S rRNA as a means of identifying bacterial species.

They examined hundred of isolates representing a few dozen pathogenic species and found a large amount of agreement between unbiased analysis of the sequencing and clinical identification, with 96 percent genus-level concordance and nearly 90 percent species concordance. In other words, the genetic classification system agrees well with an observation-derived system, suggesting this may be a useful way to identify bacteria in the clinical setting.

CELL BIOLOGY: A CaMKII/PDE4D negative feedback regulates cAMP signaling. Mika, D., Richter, W., and Conti, M. PNAS. 2015. Epub ahead of print.

A pounding heart is due to the activity of the sympathetic nervous system on the cells of the heart, especially the pacemaker cells. The binding of norepinephrine to adrenergic receptors, which are G-protein coupled receptors, initiates signaling cascades that lead to the more frequent and forceful contractions.

The best-known signaling route resulting from these receptors involves cAMP and PKA. Here, however, Mika and colleagues focus on another signaling route in these cells involving CaMKII, a calcium-dependent protein kinase.

The researchers find that CaMKII acts to rein in cAMP at both baseline and in the presence of adrenergic stimulation. They also find that the phosphodiesterase PDE4D plays an important role in this negative feedback loop; phosphodiesterases break down cyclic nucleotides such as cAMP. .

CELL BIOLOGY: Compartmentalization of GABA synthesis by GAD67 differs between pancreatic beta cells and neurons. Kanaani, J., et al. (Baekkeskov, S.). PLoS One. 2015. 10(2):e0117130.

Pancreatic beta cells and neurons both act to regulate cells throughout the body, but otherwise might not seem to have much in common.

It has long been known, however, that another similarity is that both produce and use GABA, an inhibitory neurotransmitter. The key enzyme in this process is GAD, which exists in two isoforms: GAD65 and GAD67. The means by which GAD67 is targeted to vesicles has been determined for neurons but not beta cells. In this article, these researchers provide an answer.

In neurons, there is both a GAD65-dependent and a GAD65-independent mechanism of GAD67 targeting. By examining pancreatic islets and insulinoma cells in vitro, the authors determined that only the GAD65-dependent pathway is active in beta cells.

MICROBIOLOGY & COMPUTATIONAL BIOLOGY: Experimentally guided models reveal replication principles that shape the mutation distribution of RNA viruses. Schulte, M.B., et al. (Andino, R.). Elife

Viral genomes, especially those of RNA viruses, acquire mutations quite frequently. This is advantageous for the virus in that it provides the potential of rapid evolution. At the same time, since a mutation is more likely to be deleterious than helpful, it is important to not have too many mutations at once.

Here, Schulte and colleagues studied the genetics of a poliovirus population arising within a single infected cell.  They found that poliovirus as new copies of the genome are produced from the infecting virus, they are not released to infect new cells but serve as templates for new virus. The average viral particle that does emerge from the cell is about five generations removed from the infecting virus.  This method of replication provides multiple opportunities for the introduction of mutations in the genome.

The authors have also developed a mathematical model, drawing on these experimental results. This model aligns better with experimentally observed results than previous models have.