Many proteins populate collapsed intermediate states during folding. In order to elucidate the nature and importance of these species, we have mapped the structure of the on-pathway intermediate of the four-helix protein, Im7, together with the conformational changes it undergoes as it folds to the native state. Kinetic data for 29 Im7 point mutants show that the intermediate contains three of the four helices found in the native structure, packed around a specific hydrophobic core. However, the intermediate contains many non-native interactions; as a result, hydrophobic interactions become disrupted in the rate-limiting transition state before the final helix docks onto the developing structure. The results of this study support a hierarchical mechanism of protein folding and explain why the misfolding of Im7 occurs. The data also demonstrate that non-native interactions can play a significant role in folding, even for small proteins with simple topologies.

We conducted a serological study to define correlates of immunity against SARS-CoV-2. Relative to mild COVID-19 cases, individuals with severe disease exhibited elevated virus-neutralizing titers and antibodies against nucleocapsid (N) and the receptor binding domain (RBD) of spike protein. Age and sex played lesser roles. All cases, including asymptomatic individuals, seroconverted by 2 weeks post-PCR confirmation. Spike RBD and S2 and neutralizing antibodies remained detectable through 5-7 months post-onset, whereas α-N titers diminished. Testing of 5882 members of the local community revealed only 1 sample with seroreactivity to both RBD and S2 that lacked neutralizing antibodies. This fidelity could not be achieved with either RBD or S2 alone. Thus, inclusion of multiple independent assays improved the accuracy of antibody tests in low seroprevalence communities and revealed differences in antibody kinetics depending on the antigen. We conclude that neutralizing antibodies are stably produced for at least 5-7 months after SARS-CoV-2 infection.

Cells regulate gene expression using a complex network of signaling pathways, transcription factors and promoters. To gain insight into the structure and function of these networks we analyzed gene expression in single and multiple mutant strains to build a quantitative model of the Hog1 MAPK-dependent osmotic stress response in budding yeast. Our model reveals that the Hog1 and general stress (Msn2/4) pathways interact, at both the signaling and promoter level, to integrate information and create a context-dependent response. This study lays out a path to identifying and characterizing the role of signal integration and processing in other gene regulatory networks.A full understanding of gene regulation will require the construction of detailed circuit diagrams that describe how signals influence transcription factor (TF) activity and how these TFs cooperate to regulate mRNA levels1,2. However, current experimental approaches used to examine these networks, such as chromatin immunoprecipitation (ChIP) and microarray analysis of strains with a single network component deleted3-6, provide only a limited view of their structure and function.For example, when single mutant analysis is used, an interaction between two network components is inferred if they regulate overlapping gene-sets (e.g. HΔ and MΔ, Fig. 1a). However, it is not possible to tell from single-mutant data if two factors act fully cooperatively, independently, or partially cooperatively to regulate gene expression (Potential Mechanisms, Fig. 1a). Moreover, the nature of the interaction could vary from one * To whom correspondence should be addressed: erin_oshea@harvard.edu. ChIP AnalysisChIP on chip analysis was preformed using a custom peak-fitting algorithm described in the supplement and http:// compbio.cs.huji.ac.il/HOG/. URLsThe supplementary datasets and figures are available at http://compbio.cs.huji.ac.il/HOG/ Accession CodesThe microarray data for this study have been deposited in the GEO database and have accession number GSE 12270.Published as: Nat Genet. 2008 November ; 40(11): 1300-1306. HHMI Author ManuscriptHHMI Author Manuscript HHMI Author Manuscript target gene to another. As a result, network models derived from such data are incomplete and likely inaccurate.To overcome this problem, and distinguish between possible regulatory mechanisms, double mutant (or epistasis) analysis can be applied7. Here, if two network components H and M act cooperatively to regulate a gene, then the single mutants (HΔ and MΔ) and double mutants (HΔMΔ) will have identical expression defects (Cooperative Mechanism, Fig. 1b). By contrast, if H and M act independently, then the expression defect in the double mutant will be the sum of the defects found in the single mutants (Independent Mechanism, Fig. 1b). In mechanisms with partial cooperativity, the observed behavior will lie between that found for cooperative and independent mechanisms (Partially Cooperative Mechanism, Fig. 1b). This approach has been used previously in conjunction with microa...