Nucleic Acids Research最新文献

Genome-wide identification of binding profiles for DNA-binding proteins from the limited number of intracellular pathogens in infection studies is crucial for understanding virulence and cellular processes but remains challenging, as the current ChIP-exo is designed for high-input bacterial cells (>1010). Here, we developed an optimized ChIP-mini method, a low-input ChIP-exo utilizing a 5,000-fold reduced number of initial bacterial cells and an analysis pipeline, to identify genome-wide binding dynamics of DNA-binding proteins in host-infected pathogens. Applying ChIP-mini to intracellular Salmonella Typhimurium, we identified 642 and 1,837 binding sites of H-NS and RpoD, respectively, elucidating changes in their binding position and binding intensity during infection. Post-infection, we observed 21 significant reductions in H-NS binding at intergenic regions, exposing the promoter region of virulence genes, such as those in Salmonella pathogenicity islands-2, 3 and effectors. Furthermore, we revealed the crucial phenomenon that novel and significantly increased RpoD bindings were found within regions exhibiting diminished H-NS binding, thereby facilitating substantial upregulation of virulence genes. These findings markedly enhance our understanding of how H-NS and RpoD simultaneously coordinate the transcription initiation of virulence genes within macrophages. Collectively, this work demonstrates a broadly adaptable tool that will enable the elucidation of DNA-binding protein dynamics in diverse intracellular pathogens during infection.

RNA-binding proteins (RBPs) are central components of gene regulatory networks. The differentiation of heterocysts in filamentous cyanobacteria is an example of cell differentiation in prokaryotes. Although multiple non-coding transcripts are involved in this process, no RBPs have been implicated thus far. Here we used quantitative mass spectrometry to analyze the differential fractionation of RNA-protein complexes after RNase treatment in density gradients yielding 333 RNA-associated proteins, while a bioinformatic prediction yielded 311 RBP candidates in Nostoc sp. PCC 7120. We validated in vivo the RNA-binding capacity of six RBP candidates. Some participate in essential physiological aspects, such as photosynthesis (Alr2890), thylakoid biogenesis (Vipp1) or heterocyst differentiation (PrpA, PatU3), but their association with RNA was unknown. Validated RBPs Asl3888 and Alr1700 were not previously characterized. Alr1700 is an RBP with two oligonucleotide/oligosaccharide-binding (OB)-fold-like domains that is differentially expressed in heterocysts and interacts with non-coding regulatory RNAs. Deletion of alr1700 led to complete deregulation of the cell differentiation process, a striking increase in the number of heterocyst-like cells, and was ultimately lethal in the absence of combined nitrogen. These observations characterize this RBP as a master regulator of the heterocyst patterning and differentiation process, leading us to rename Alr1700 to PatR.

Increasing antifungal drug resistance is a major concern associated with human fungal pathogens like Aspergillus fumigatus. Genetic mutation and epimutation mechanisms clearly drive resistance, yet the epitranscriptome remains relatively untested. Here, deletion of the A. fumigatus transfer RNA (tRNA)-modifying isopentenyl transferase ortholog, Mod5, led to altered stress response and unexpected resistance against the antifungal drug 5-fluorocytosine (5-FC). After confirming the canonical isopentenylation activity of Mod5 by liquid chromatography-tandem mass spectrometry and Nano-tRNAseq, we performed simultaneous profiling of transcriptomes and proteomes to reveal a comparable overall response to 5-FC stress; however, a premature activation of cross-pathway control (CPC) genes in the knockout was further increased after antifungal treatment. We identified several orthologues of the Aspergillus nidulans Major Facilitator Superfamily transporter nmeA as specific CPC-client genes in A. fumigatus. Overexpression of Mod5-target tRNATyrGΨA in the Δmod5 strain rescued select phenotypes but failed to reverse 5-FC resistance, whereas deletion of nmeA largely, but incompletely, reverted the resistance phenotype, implying additional relevant exporters. In conclusion, 5-FC resistance in the absence of Mod5 and i6A likely originates from multifaceted transcriptional and translational changes that skew the fungus towards premature CPC-dependent activation of antifungal toxic-intermediate exporter nmeA, offering a potential mechanism reliant on RNA modification to facilitate transient antifungal resistance.

The DdmDE antiplasmid system, consisting of the helicase-nuclease DdmD and the prokaryotic Argonaute (pAgo) protein DdmE, plays a crucial role in defending Vibrio cholerae against plasmids. Guided by DNA, DdmE specifically targets plasmids, disassembles the DdmD dimer, and forms a DdmD-DdmE handover complex to facilitate plasmid degradation. However, the precise ATP-dependent DNA translocation mechanism of DdmD has remained unclear. Here, we present cryo-EM structures of DdmD bound to single-stranded DNA (ssDNA) in nucleotide-free, ATPγS-bound, and ADP-bound states. These structures, combined with biochemical analysis, reveal a unique "gate-clamp" mechanism for ssDNA translocation by DdmD. Upon ATP binding, arginine finger residues R855 and R858 reorient to interact with the γ-phosphate, triggering HD2 domain movement. This shift repositions the gate residue Q781, causing a flip of the 3' flank base, which is then clamped by residue F639. After ATP hydrolysis, the arginine finger releases the nucleotide, inducing HD2 to return to its open state. This conformational change enables DdmD to translocate along ssDNA by one nucleotide in the 5' to 3' direction. This study provides new insights into the ATP-dependent translocation of DdmD and contributes to understanding the mechanistic diversity within SF2 helicases.

Machine learning (ML) has shown great potential in the adaptive immune receptor repertoire (AIRR) field. However, there is a lack of large-scale ground-truth experimental AIRR data suitable for AIRR-ML-based disease diagnostics and therapeutics discovery. Simulated ground-truth AIRR data are required to complement the development and benchmarking of robust and interpretable AIRR-ML methods where experimental data is currently inaccessible or insufficient. The challenge for simulated data to be useful is incorporating key features observed in experimental repertoires. These features, such as antigen or disease-associated immune information, cause AIRR-ML problems to be challenging. Here, we introduce LIgO, a software suite, which simulates AIRR data for the development and benchmarking of AIRR-ML methods. LIgO incorporates different types of immune information both on the receptor and the repertoire level and preserves native-like generation probability distribution. Additionally, LIgO assists users in determining the computational feasibility of their simulations. We show two examples where LIgO supports the development and validation of AIRR-ML methods: (i) how individuals carrying out-of-distribution immune information impacts receptor-level prediction performance and (ii) how immune information co-occurring in the same AIRs impacts the performance of conventional receptor-level encoding and repertoire-level classification approaches. LIgO guides the advancement and assessment of interpretable AIRR-ML methods.