Journal: Cell reports

Article Title: Extensive natural variation in bacterial ribosomal drug-binding sites.

doi: 10.1016/j.celrep.2025.115878

Figure Lengend Snippet: Figure 5. Actinobacteria bearing divergent ribosomal drug-binding sites are intrinsi cally resistant to antibiotics (A) Schematic phylogenetic tree showing three closely related branches of Actinobacteria. Each branch exhibits nucleotide variations in the 16S rRNA sequence at the binding sites for two ribo some-targeting antibiotics—spectinomycin and paromomycin. (B–D) Comparison of minimum inhibitory concen trations (MICs) for pactamycin and spectinomycin across representative Actinobacteria, including S. fradiae (bears identical drug-binding residues to E. coli), M. smegmatis (bears A694G substitution in the pactamycin-binding site), and K. subterranea (bears C1192G substitution in the spectinomycin- binding site compared to E. coli). The images show that 16S rRNA nucleotide alterations—previously characterized as resistance conferring in model organisms—correlate with intrinsic drug suscepti bility. Specifically, K. subterranea, which carries the C1192G substitution in spectinomycin-binding site, exhibits intrinsic resistance to spectinomycin (MIC = 20,000 μg/mL), while M. smegmatis (lacking this substitution) exhibits spectinomycin sensitivity (MIC = 20 μg/mL). Conversely, M. smegmatis (bearing A694G substitution in the pactamycin- binding site) can tolerate pactamycin at 62.5 μg/mL concentration, which is 500× higher compared to the concentration required to inhibit the growth of K. subterranea (as shown in Figure S3).

Article Snippet: Freeze-dried cell pellets of S. fradiae (DSM 40063), obtained from the German Collection of Microorganisms and Cell Cultures (DSMZ), were rehydrated in 1 mL of distilled water.

Techniques: Binding Assay, Sequencing, Comparison, Concentration Assay

Journal: Cell reports

Article Title: Extensive natural variation in bacterial ribosomal drug-binding sites.

doi: 10.1016/j.celrep.2025.115878

Figure Lengend Snippet: Figure 6. rRNA substitutions that cause drug resistance in model organisms are widespread among natural bacterial species (A) rRNA secondary structure diagrams illustrate divergence in the evernimicin-binding pocket between S. fradiae and E. coli ribosomes. (B) Cryo-EM map of S. fradiae shows the divergent drug-binding site. (C) Comparison of experimental and AlphaFold3-predicted structures of S. fradiae’s evernimicin-binding pocket reveals nearly identical conformations (all-atom RMSD = ∼0.3 A˚ ), validating AlphaFold’s utility for assessing rRNA substitution effects. (D) Superposition of vacant S. fradiae ribosome with evernimicin-bound E. coli structure. (E–P) Comparisons of wild-type E. coli binding sites with AlphaFold3-predicted divergent sites across species demonstrate how rRNA variation alters pocket conformation, with each box summarizing the reported drug affinity impacts of substitutions and phylogenetic distribution of variants. Asterisks indicate sequence variants that have a variable impact on drug affinity that depends on the surrounding context in rRNA. (E)–(J) correspond to the large subunit and (K)–(P) to the small subunit. Overall, (E)–(P) show that changes at the direct ribosome-drug interface—even in the absence of apparent steric clashes or disrupted hydrophobic stacking interactions—typically lead to resistance.

Article Snippet: Freeze-dried cell pellets of S. fradiae (DSM 40063), obtained from the German Collection of Microorganisms and Cell Cultures (DSMZ), were rehydrated in 1 mL of distilled water.

Techniques: Binding Assay, Cryo-EM Sample Prep, Comparison, Sequencing

Journal: Cell reports

Article Title: An Aurora kinase A-BOD1L1-PP2A B56 axis promotes chromosome segregation fidelity

doi: 10.1016/j.celrep.2025.115317

Figure Lengend Snippet:

Article Snippet: The following antibodies were used for immunofluorescence (IF) and/or immunoblotting (IB): human anti-ACA (Geisel School of Medicine; IF at 1:2000), mouse anti-Hec1 (Santa Cruz C-11; IF,IB at 1:1000), mouse anti-PP2AR1A (Santa Cruz SC-74580; IB at 1:500), mouse anti-PP2AC (Santa Cruz SC-166034; IB at 1:500), rabbit anti-PP2A B56 Alpha ( MyBioSource.com MBS8524809; IB at 1:500), mouse anti-PP2A B56 Beta (Santa Cruz E–6; IB at 1:500), mouse anti-PP2A B56 Gamma (Santa Cruz A-11; IB at 1:500), mouse anti-PP2A B56 Delta (Santa Cruz H-11; IB at 1:500), rabbit anti-PP2A B56 Epsilon (Aviva Systems Biology RP56694_P050; IB at 1:500), rabbit anti-Hec1 pS44 (gift of Jennifer DeLuca; IF at 1:500), rabbit anti DSN1 pS100 (gift of Iain Cheeseman; IF at 1:250), rabbit anti-KNL1 pT943/pT1155 (Cell Signaling #40758), mouse anti-α-Tubulin DM1α (Sigma-Aldrich; IF at 1:4000–1:10,000), mouse anti-Aurora A (Cell Signaling Technology 1F8; IF at1:1000), Rabbit anti-Aurora A pT288 (Cell Signaling Technology C39D8; IF at 1:500), Rabbit anti-TACC3 (gift of Jordan Raff; IF at 1:1000), mouse anti-TPX2 (Cell Signaling Technology D9Y1V; IF at 1:1000), rabbit anti-Aurora B pT232 (Rockland 600–401-677; IF/IB at 1:1000), rabbit anti-MCAK pS95 (Abcam #AB74146; IF/IB at 1:500), rabbit anti-Hec1 pT31 (IF at 1:100,000, WB at 1:1000), rabbit anti-BOD1L1 (IF at 1:1000) (gift of Grant Stewart ), rabbit anti-BOD1L1 (Genetex #GTX119946; WB at 1:500), rabbit anti-GST (Molecular Probes #A-5800; WB at 1:1000).

Techniques: Virus, Recombinant, Staining, shRNA, Cloning, Plasmid Preparation, Software