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Adhesion to host cells is an initial and important step in Acinetobacter baumannii pathogenesis. However, there is relatively little information on the mechanisms by which A. baumannii binds to and interacts with host cells. Adherence to extracellular matrix proteins, such as fibronectin, affords pathogens with a mechanism to invade epithelial cells. Here, we found that A. baumannii adheres more avidly to immobilized fibronectin than to control protein. Free fibronectin used as a competitor resulted in dose-dependent decreased binding of A. baumannii to fibronectin. Three outer membrane preparations (OMPs) were identified as fibronectin binding proteins (FBPs): OMPA, TonB-dependent copper receptor, and 34 kDa OMP. Moreover, we demonstrated that fibronectin inhibition and neutralization by specific antibody prevented significantly the adhesion of A. baumannii to human lung epithelial cells (A549 cells). Similarly, A. baumannii OMPA neutralization by specific antibody decreased significantly the adhesion of A. baumannii to A549 cells. These data indicate that FBPs are key adhesins that mediate binding of A. baumannii to human lung epithelial cells through interaction with fibronectin on the surface of these host cells.

Computing plays a critical role in the biological sciences but faces increasing challenges of scale and complexity. Quantum computing, a computational paradigm exploiting the unique properties of quantum mechanical analogs of classical bits, seeks to address many of these challenges. We discuss the potential for quantum computing to aid in the merging of insights across different areas of biological sciences.

We used single-cell genomic approaches to map DNA copy number variation (CNV) in neurons obtained from human induced pluripotent stem cell (hiPSC) lines and postmortem human brains. We identified aneuploid neurons, as well as numerous subchromosomal CNVs in euploid neurons. Neurotypic hiPSC-derived neurons had larger CNVs than fibroblasts, and several large deletions were found in hiPSC-derived neurons but not in matched neural progenitor cells. Single-cell sequencing of endogenous human frontal cortex neurons revealed that 13 to 4 1% of neurons have at least one mega base-sea le de novo CNV, that deletions are twice as common as duplications, and that a subset of neurons have highly aberrant genomes marked by multiple alterations. Our results show that mosaic CNV is abundant in human neurons.

Single-cell sequencing methods have emerged as powerful tools for identification of heterogeneous cell types within defined brain regions. Application of single-cell techniques to study the transcriptome of activated neurons can offer insight into molecular dynamics associated with differential neuronal responses to a given experience. Through evaluation of common whole-cell and single-nuclei RNA-sequencing (snRNA-seq) methods, here we show that snRNA-seq faithfully recapitulates transcriptional patterns associated with experience-driven induction of activity, including immediate early genes (IEGs) such as Fos , Arc and Egr1 . SnRNA-seq of mouse dentate granule cells reveals large-scale changes in the activated neuronal transcriptome after brief novel environment exposure, including induction of MAPK pathway genes. In addition, we observe a continuum of activation states, revealing a pseudotemporal pattern of activation from gene expression alone. In summary, snRNA-seq of activated neurons enables the examination of gene expression beyond IEGs, allowing for novel insights into neuronal activation patterns in vivo. The molecular dynamics associated with neuronal activation patterns in vivo are unclear. Lacar et al . perform single-nuclei RNA-sequencing of hippocampal neurons from mice exposed to a novel environment, and identify large-scale transcriptome changes in individual neurons associated with the experience.

This protocol describes how to sequence the transcriptome from a single nucleus. It is particularly suited to cell types that are difficult to isolate as intact whole cells, such as neurons. A protocol is described for sequencing the transcriptome of a cell nucleus. Nuclei are isolated from specimens and sorted by FACS, cDNA libraries are constructed and RNA-seq is performed, followed by data analysis. Some steps follow published methods (Smart-seq2 for cDNA synthesis and Nextera XT barcoded library preparation) and are not described in detail here. Previous single-cell approaches for RNA-seq from tissues include cell dissociation using protease treatment at 30 °C, which is known to alter the transcriptome. We isolate nuclei at 4 °C from tissue homogenates, which cause minimal damage. Nuclear transcriptomes can be obtained from postmortem human brain tissue stored at −80 °C, making brain archives accessible for RNA-seq from individual neurons. The method also allows investigation of biological features unique to nuclei, such as enrichment of certain transcripts and precursors of some noncoding RNAs. By following this procedure, it takes about 4 d to construct cDNA libraries that are ready for sequencing.

► Acinetobacter baumannii produces OMVs that contain immunogenic outer membrane proteins. ► Immunization of mice with A. baumannii OMVs produces a robust antibody response against proteins of the bacterial outer membrane. ► Immunization with A. baumannii protects against infection in an experimental mouse model of infection. Acinetobacter baumannii produces different types of infections including pneumonia, meningitis, and bloodstream infections. The optimal treatment of these infections has been complicated by the global emergence of multidrug resistant strains, requiring the development of novel approaches for treatment and prevention. Outer membrane vesicles are outpouchings of the bacterial outer membrane that are secreted from numerous pathogenic Gram-negative bacteria. In the present study, we describe the isolation of outer membrane vesicles from A. baumannii and their use as a vaccine in a mouse model of disseminated sepsis. Immunization produced a robust antibody response against multiple bacterial antigens which consisted of antigen-specific IgG and IgM. In addition, both IgG1 and IgG2c subtypes were produced by immunization. Immunized mice had lower tissue bacterial loads and lower serum levels of the pro-inflammatory cytokines IL-6 and IL-1β post-infection compared to control mice. Importantly, vaccination protected mice from challenge with the ATCC 19606 strain and provided protection against two clinical isolates, including a pan-resistant strain. These results indicate that vaccination with outer membrane vesicles may be a viable strategy for preventing A. baumannii infection.

Vaccines and monoclonal antibodies are promising approaches for preventing and treating infections caused by multidrug resistant Acinetobacter baumannii . However, only partial protection has been achieved with many previously tested protein antigens, which suggests that vaccines incorporating multiple antigens may be necessary in order to obtain high levels of protection. Several aspects that use the wealth of omic data available for A. baumannii have not been fully exploited for antigen identification. In this study, the use of fractionated proteomic and computational data from ~4,200 genomes increased the number of proteins potentially accessible to the humoral response to 8,824 non-redundant proteins in the A. baumannii panproteome. Among them, 59% carried predicted B-cell epitopes and T-cell epitopes recognized by two or more alleles of the HLA class II DP supertype. Potential cross-reactivity with human proteins was detected for 8.9% of antigens at the protein level and 2.7% at the B-cell epitope level. Individual antigens were associated with different infection types by genomic, transcriptomic or functional analyses. High intra-clonal genome density permitted the identification of international clone II as a “vaccitype”, in which 20% of identified antigens were specific to this clone. Network-based centrality measurements were used to identify multiple immunologic nodes. Data were formatted, unified and stored in a data warehouse database, which was subsequently used to identify synergistic antigen combinations for different vaccination strategies. This study supports the idea that integration of multi-omic data and fundamental knowledge of the pathobiology of drug-resistant bacteria can facilitate the development of effective multi-antigen vaccines against these challenging infections.

It has recently been established that synthesis of double-stranded cDNA can be done from a single cell for use in DNA sequencing. Global gene expression can be quantified from the number of reads mapping to each gene, and mutations and mRNA splicing variants determined from the sequence reads. Here we demonstrate that this method of transcriptomic analysis can be done using the extremely low levels of mRNA in a single nucleus, isolated from a mouse neural progenitor cell line and from dissected hippocampal tissue. This method is characterized by excellent coverage and technical reproducibility. On average, more than 16,000 of the 24,057 mouse protein-coding genes were detected from single nuclei, and the amount of gene-expression variation was similar when measured between single nuclei and single cells. Several major advantages of the method exist: first, nuclei, compared with whole cells, have the advantage of being easily isolated from complex tissues and organs, such as those in the CNS. Second, the method can be widely applied to eukaryotic species, including those of different kingdoms. The method also provides insight into regulatory mechanisms specific to the nucleus. Finally, the method enables dissection of regulatory events at the single-cell level; pooling of 10 nuclei or 10 cells obscures some of the variability measured in transcript levels, implying that single nuclei and cells will be extremely useful in revealing the physiological state and interconnectedness of gene regulation in a manner that avoids the masking inherent to conventional transcriptomics using bulk cells or tissues.

Expression of MHC class I molecules on motor neurons protects them from astrocyte-induced toxicity in ALS. Astrocytes isolated from individuals with amyotrophic lateral sclerosis (ALS) are toxic to motor neurons (MNs) and play a non–cell autonomous role in disease pathogenesis. The mechanisms underlying the susceptibility of MNs to cell death remain unclear. Here we report that astrocytes derived from either mice bearing mutations in genes associated with ALS or human subjects with ALS reduce the expression of major histocompatibility complex class I (MHCI) molecules on MNs; reduced MHCI expression makes these MNs susceptible to astrocyte-induced cell death. Increasing MHCI expression on MNs increases survival and motor performance in a mouse model of ALS and protects MNs against astrocyte toxicity. Overexpression of a single MHCI molecule, HLA-F, protects human MNs from ALS astrocyte–mediated toxicity, whereas knockdown of its receptor, the killer cell immunoglobulin-like receptor KIR3DL2, on human astrocytes results in enhanced MN death. Thus, our data indicate that, in ALS, loss of MHCI expression on MNs renders them more vulnerable to astrocyte-mediated toxicity.

Reverse vaccinology (RV) was originally conceived to leverage genomic information for antigen selection and promised a paradigm change in vaccine design. After a steady increment since 2000 and surge in 2021, RV-related publications have recently plateaued, accompanied by declining journal impact factors and a shift from immunology and microbiology to more technical and general categories. Despite its potential and a favorable data science scenario, the impact of RV on the vaccine portfolio concerning pandemics, antimicrobial resistant pathogens and calendar campaigns remains almost negligible. The lack of multidisciplinary collaboration in many RV studies has led to a predominance of purely theoretical studies without experimental validation, likely contributing to waning interest within the broader vaccinology community. For instance, a growing fraction of RV studies focuses on multi-epitope constructs, which limited successful antecedents make their performance questionable in practice. Additionally, target pathogens are increasingly redundant with existing vaccines or of marginal immediate relevance, further fueling skepticism about RV’s real-world value. This decoupling underscores the need to renew the original idea by integrating RV with complementary frameworks such as systems vaccinology, network vaccinology, and artificial intelligence, as well as embedding RV within higher-order experimental and translational efforts. Furthermore, policymakers and the pharmaceutical sector have relied almost exclusively on classical antigenic elements such as attenuated or inactivated microorganisms, capsular components and fimbria proteins. Importantly, alignment with key stakeholders is essential to bridge early computational insights with late-stage vaccine development. Without this integration to cover the whole vaccine lifecycle, RV risks losing relevance.