John M. Richardson

Noncharged amino acid residues at the solvent‐exposed positions in the middle and at the C terminus of the α‐helix have the same helical propensity

It was established previously that helical propensities of different amino acid residues in the middle of α‐helix in peptides and in proteins are very similar. The statistical analysis of the protein helices from the known three‐dimensional structures shows no difference in the frequency of noncharged residues in the middle and at the C terminus. Yet, experimental studies show distinctive differences for the helical propensities of noncharged residues in the middle and in the C terminus in model peptides. Is this a general effect, and is it applicable to protein helices or is it specific to the model alanine‐based peptides? To answer this question, the effects of substitutions at positions 28 (middle residue) and 32 (C2 position at the C terminus) of the α‐helix of ubiquitin on the stability of this protein are measured by using differential scanning calorimetry. The two data sets produce similar values for intrinsic helix propensity, leading to a conclusion that noncharged amino acid residues at the solvent‐exposed positions in the middle and at the C terminus of the α‐helix have the same helical propensity. This conclusion is further supported with an excellent correlation between the helix propensity scale obtained for the two positions in ubiquitin with the experimental helix propensity scale established previously and with the statistical distribution of the residues in protein helices.

Primary structure determinants of the pH- and temperature-dependent aggregation of thioredoxin

Thioredoxins are small proteins found in all living organisms. We have previously reported that Chlamydomonas reinhardtii thioredoxin h exhibited differences both in its absorption spectrum and its aggregation properties compared to thioredoxin m. In this paper, we demonstrate, by site-directed mutagenesis, that the particularity of the absorption spectrum is linked to the presence of an additional tryptophan residue in the h isoform. The pH and temperature dependence of the aggregation of both thioredoxins has been investigated. Our results indicate that the aggregation of TRX is highly dependent on pH and that the differences between the two TRX isoforms are linked to distinct pH dependencies. We have also analyzed the pH and temperature dependence of 12 distinct variants of TRX engineered by site-directed mutagenesis. The results obtained indicate that the differences in the hydrophobic core of the two TRX isoforms do not account for the differences of aggregation. On the other hand, we show the importance of His-109 as well as the second active site cysteine, Cys-39 in the aggregation mechanism.

Autoinhibition of Mint1 adaptor protein regulates amyloid precursor protein binding and processing

Mint adaptor proteins bind to the amyloid precursor protein (APP) and regulate APP processing associated with Alzheimer’s disease; however, the molecular mechanisms underlying Mint regulation in APP binding and processing remain unclear. Biochemical, biophysical, and cellular experiments now show that the Mint1 phosphotyrosine binding (PTB) domain that binds to APP is intramolecularly inhibited by the adjacent C-terminal linker region. The crystal structure of a C-terminally extended Mint1 PTB fragment reveals that the linker region forms a short α-helix that folds back onto the PTB domain and sterically hinders APP binding. This intramolecular interaction is disrupted by mutation of Tyr633 within the Mint1 autoinhibitory helix leading to enhanced APP binding and β-amyloid production. Our findings suggest that an autoinhibitory mechanism in Mint1 is important for regulating APP processing and may provide novel therapies for Alzheimer’s disease.

Using microbial genome annotation as a foundation for collaborative student research

We used the Integrated Microbial Genomes Annotation Collaboration Toolkit as a framework to incorporate microbial genomics research into a microbiology and biochemistry course in a way that promoted student learning of bioinformatics and research skills and emphasized teamwork and collaboration as evidenced through multiple assessment mechanisms. Student teams in microbiology used bioinformatics tools to identify and characterize gene products from Mucilaginibacter paludis necessary for the synthesis of specific amino acids and then designed and carried out growth experiments to determine if the organism could indeed synthesize the amino acids. Students in biochemistry worked to characterize one of the amino acid biosynthetic pathways reconstructed by a previous microbiology class through amplification and cloning of the M. paludis genes and complementation analysis of Escherichia coli mutants.