Experimental Antiglomerular Basement Membrane GN Induced by a Peptide from Actinomyces.

BACKGROUND: Antiglomerular basement membrane (anti-GBM) disease is associated with HLA-DRB1*1501 (the major predisposing genetic factor in the disease), with α3127-148 as a nephritogenic T and B cell epitope. Although the cause of disease remains unclear, the association of infections with anti-GBM disease has been long suspected. METHODS: To investigate whether microbes might activate autoreactive T and B lymphocytes via molecular mimicry in anti-GBM disease, we used bioinformatic tools, including BLAST, SYFPEITHI, and ABCpred, for peptide searching and epitope prediction. We used sera from patients with anti-GBM disease to assess peptides recognized by antibodies, and immunized WKY rats and a humanized mouse model (HLA-DR15 transgenic mice) with each of the peptide candidates to assess pathogenicity. RESULTS: On the basis of the critical motif, the bioinformatic approach identified 36 microbial peptides that mimic human α3127-148. Circulating antibodies in sera from patients with anti-GBM recognized nine of them. One peptide, B7, derived from Actinomyces species, induced proteinuria, linear IgG deposition on the GBM, and crescent formation when injected into WKY rats. The antibodies to B7 also targeted human and rat α3127-148. B7 induced T cell activation from human α3127-148-immunized rats. T cell responses to B7 were detected in rats immunized by Actinomyces lysate proteins or recombinant proteins. We confirmed B7's pathogenicity in HLA-DR15 transgenic mice that developed kidney injury similar to that observed in α3135-145-immunized mice. CONCLUSIONS: Sera from patients with anti-GBM disease recognized microbial peptides identified through a bioinformatic approach, and a peptide from Actinomyces induced experimental anti-GBM GN by T and B cell crossreactivity. These studies demonstrate that anti-GBM disease may be initiated by immunization with a microbial peptide.

Heterosubtypic Protections against Human-Infecting Avian Influenza Viruses Correlate to Biased Cross-T-Cell Responses.

Against a backdrop of seasonal influenza virus epidemics, emerging avian influenza viruses (AIVs) occasionally jump from birds to humans, posing a public health risk, especially with the recent sharp increase in H7N9 infections. Evaluations of cross-reactive T-cell immunity to seasonal influenza viruses and human-infecting AIVs have been reported previously. However, the roles of influenza A virus-derived epitopes in the cross-reactive T-cell responses and heterosubtypic protections are not well understood; understanding those roles is important for preventing and controlling new emerging AIVs. Here, among the members of a healthy population presumed to have previously been infected by pandemic H1N1 (pH1N1), we found that pH1N1-specific T cells showed cross- but biased reactivity to human-infecting AIVs, i.e., H5N1, H6N1, H7N9, and H9N2, which correlates with distinct protections. Through a T-cell epitope-based phylogenetic analysis, the cellular immunogenic clustering expanded the relevant conclusions to a broader range of virus strains. We defined the potential key conserved epitopes required for cross-protection and revealed the molecular basis for the immunogenic variations. Our study elucidated an overall profile of cross-reactivity to AIVs and provided useful recommendations for broad-spectrum vaccine development.IMPORTANCE We revealed preexisting but biased T-cell reactivity of pH1N1 influenza virus to human-infecting AIVs, which provided distinct protections. The cross-reactive T-cell recognition had a regular pattern that depended on the T-cell epitope matrix revealed via bioinformatics analysis. Our study elucidated an overall profile of cross-reactivity to AIVs and provided useful recommendations for broad-spectrum vaccine development.

Hydrogen Bond Variations of Influenza A Viruses During Adaptation in Human.

Many host specific mutations have been detected in influenza A viruses (IAVs). However, their effects on hydrogen bond (H-bond) variations have rarely been investigated. In this study, 60 host specific sites were identified in the internal proteins of avian and human IAVs, 27 of which contained mutations with effects on H-bonds. Besides, 30 group specific sites were detected in HA and NA. Twenty-six of 36 mutations existing at these group specific sites caused H-bond loss or formation in at least one subtype. The number of mutations in isolations of 2009 pandemic H1N1, human-infecting H5N1 and H7N9 varied. The combinations of mutations and H-bond changes in these three subtypes of IAVs were also different. In addition, the mutations in isolations of H5N1 distributed more scattered than those in 2009 pandemic H1N1 and H7N9. Eight wave specific mutations in isolations of the fifth H7N9 wave were also identified. Three of them, R140K in HA, Y170H in NA, and R340K in PB2, were capable of resulting in H-bond loss. As mentioned above, these host or group or wave specific H-bond variations provide us with a new field of vision for understanding the changes of structural features in the human adaptation of IAVs.

Evolutionary genotypes of influenza A (H7N9) viruses over five epidemic waves in China.

Since the first human case of influenza A (H7N9) infection was identified in March 2013, five epidemics have emerged in China. Diverse H7N9 virus genotypes created through reassortments were already detected in the first epidemic wave, but how the H7N9 virus genetic diversities have evolved during the subsequent epidemics remained unclear. Here, to assess the ongoing genetic evolution of H7N9 viruses, we performed in-depth investigations of the dynamic H7N9 genotypes in these waves. We found that the H7N9 genotypes in the second and third epidemic waves are more diverse than those in the first wave, due to new reassortments that occurred during the second wave. However, the number of different H7N9 genotypes identified in the fourth and fifth waves decreased significantly. Furthermore, we found that different dominant genotypes existed in each of the five epidemic waves, and these wave-specific genotypes possess unique mutations that are enriched in the PB2 protein.

EF4 disengages the peptidyl-tRNA CCA end and facilitates back-translocation on the 70S ribosome.

EF4 catalyzes tRNA back-translocation through an unknown mechanism. We report cryo-EM structures of Escherichia coli EF4 in post- and pretranslocational ribosomes (Post- and Pre-EF4) at 3.7- and 3.2-Å resolution, respectively. In Post-EF4, peptidyl-tRNA occupies the peptidyl (P) site, but the interaction between its CCA end and the P loop is disrupted. In Pre-EF4, the peptidyl-tRNA assumes a unique position near the aminoacyl (A) site, denoted the A site/EF4 bound (A/4) site, with a large displacement at its acceptor arm. Mutagenesis analyses suggest that a specific region in the EF4 C-terminal domain (CTD) interferes with base-pairing between the peptidyl-tRNA 3'-CCA and the P loop, whereas the EF4 CTD enhances peptidyl-tRNA interaction at the A/4 site. Therefore, EF4 induces back-translocation by disengaging the tRNA's CCA end from the peptidyl transferase center of the translating ribosome.