The Ins and Outs of Cerebral Malaria Pathogenesis: Immunopathology, Extracellular Vesicles, Immunometabolism, and Trained Immunity

Complications from malaria parasite infections still cost the lives of close to half a million people every year. The most severe is cerebral malaria (CM). Employing murine models of CM, autopsy results, in vitro experiments, neuroimaging and microscopic techniques, decades of research activity have investigated the development of CM immunopathology in the hope of identifying steps that could be therapeutically targeted. Yet important questions remain. This review summarizes recent findings, primarily mechanistic insights on the essential cellular and molecular players involved gained within the murine experimental cerebral malaria model. It also highlights recent developments in (a) cell-cell communication events mediated through extracellular vesicles (EVs), (b) mounting evidence for innate immune memory, leading to “trained“ increased or tolerised responses, and (c) modulation of immune cell function through metabolism, that could shed light on why some patients develop this life-threatening condition whilst many do not

The BDNFVal66Met SNP modulates the association between beta-amyloid and hippocampal disconnection in Alzheimer’s disease

In Alzheimer’s disease (AD), a single-nucleotide polymorphism in the gene encoding brain-derived neurotrophic factor (BDNFVal66Met) is associated with worse impact of primary AD pathology (beta-amyloid, Aβ) on neurodegeneration and cognitive decline, rendering BDNFVal66Met an important modulating factor of cognitive impairment in AD. However, the effect of BDNFVal66Met on functional networks that may underlie cognitive impairment in AD is poorly understood. Using a cross-validation approach, we first explored in subjects with autosomal dominant AD (ADAD) from the Dominantly Inherited Alzheimer Network (DIAN) the effect of BDNFVal66Met on resting-state fMRI assessed functional networks. In seed-based connectivity analysis of six major large-scale networks, we found a stronger decrease of hippocampus (seed) to medial-frontal connectivity in the BDNFVal66Met carriers compared to BDNFVal homozogytes. BDNFVal66Met was not associated with connectivity in any other networks. Next, we tested whether the finding of more pronounced decrease in hippocampal-medial-frontal connectivity in BDNFVal66Met could be also found in elderly subjects with sporadically occurring Aβ, including a group with subjective cognitive decline (N = 149, FACEHBI study) and a group ranging from preclinical to AD dementia (N = 114, DELCODE study). In both of these independently recruited groups, BDNFVal66Met was associated with a stronger effect of more abnormal Aβ-levels (assessed by biofluid-assay or amyloid-PET) on hippocampal-medial-frontal connectivity decreases, controlled for hippocampus volume and other confounds. Lower hippocampal-medial-frontal connectivity was associated with lower global cognitive performance in the DIAN and DELCODE studies. Together these results suggest that BDNFVal66Met is selectively associated with a higher vulnerability of hippocampus-frontal connectivity to primary AD pathology, resulting in greater AD-related cognitive impairment

Systematic Collaborative Reanalysis of Genomic Data Improves Diagnostic Yield in Neurologic Rare Diseases

Altres ajuts: Generalitat de Catalunya, Departament de Salut; Generalitat de Catalunya, Departament d'Empresa i Coneixement i CERCA Program; Ministerio de Ciencia e Innovación; Instituto Nacional de Bioinformática; ELIXIR Implementation Studies (CNAG-CRG); Centro de Investigaciones Biomédicas en Red de Enfermedades Raras; Centro de Excelencia Severo Ochoa; European Regional Development Fund (FEDER).Many patients experiencing a rare disease remain undiagnosed even after genomic testing. Reanalysis of existing genomic data has shown to increase diagnostic yield, although there are few systematic and comprehensive reanalysis efforts that enable collaborative interpretation and future reinterpretation. The Undiagnosed Rare Disease Program of Catalonia project collated previously inconclusive good quality genomic data (panels, exomes, and genomes) and standardized phenotypic profiles from 323 families (543 individuals) with a neurologic rare disease. The data were reanalyzed systematically to identify relatedness, runs of homozygosity, consanguinity, single-nucleotide variants, insertions and deletions, and copy number variants. Data were shared and collaboratively interpreted within the consortium through a customized Genome-Phenome Analysis Platform, which also enables future data reinterpretation. Reanalysis of existing genomic data provided a diagnosis for 20.7% of the patients, including 1.8% diagnosed after the generation of additional genomic data to identify a second pathogenic heterozygous variant. Diagnostic rate was significantly higher for family-based exome/genome reanalysis compared with singleton panels. Most new diagnoses were attributable to recent gene-disease associations (50.8%), additional or improved bioinformatic analysis (19.7%), and standardized phenotyping data integrated within the Undiagnosed Rare Disease Program of Catalonia Genome-Phenome Analysis Platform functionalities (18%)

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly

Development of a Feature and Template-Assisted Assembler and Application to the Analysis of a Foot-and-Mouth Disease Virus Genotyping Microarray.

Several RT-PCR and genome sequencing strategies exist for the resolution of Foot-and-Mouth Disease virus (FMDV). While these approaches are relatively straightforward, they can be vulnerable to failure due to the unpredictable nature of FMDV genome sequence variations. Sequence independent single primer amplification (SISPA) followed by genotyping microarray offers an attractive unbiased approach to FMDV characterization. Here we describe a custom FMDV microarray and a companion feature and template-assisted assembler software (FAT-assembler) capable of resolving virus genome sequence using a moderate number of conserved microarray features. The results demonstrate that this approach may be used to rapidly characterize naturally occurring FMDV as well as an engineered chimeric strain of FMDV. The FAT-assembler, while applied to resolving FMDV genomes, represents a new bioinformatics approach that should be broadly applicable to interpreting microarray genotyping data for other viruses or target organisms

Comparison of different probe-level analysis techniques for oligonucleotide microarrays

Three different software packages for the probe-level analysis of high-density oligonucleotide microarray data were compared using an experiment-derived data set that was validated using real-time PCR. The efficiency with which these three programs could identify true positives in this data set was assessed. In addition, estimates of false-positive and false-negative rates were determined. The performance of the programs using very small data sets was also compared, and recommendations for use are suggested

Synthetic template scaffold build-up compared to native template selected by the algorithm.

<p>This is the comparison of the components of the synthetic template buildup for a chimeric FMDV, compared to the selected template compared to an individual scaffold template selection.</p

Consensus sequence buildup.

<p>Resolved sequence is selected by alignment of the candidate sequences for each of the thresholds. Sequence assembly is performed through selection of the individual resolved (non-ambiguous) nucleotides at the greatest MFI threshold.</p

Comparison of specific misidentified nucleotides when comparing a chimeric virus to a “native template” (upper alignment) assembled sequence versus a “synthetic template” (lower alignment) assembled sequence to illustrate predicted indels and nucleotide error call improvement using the synthetic scaffold template.

<p>Comparison of specific misidentified nucleotides when comparing a chimeric virus to a “native template” (upper alignment) assembled sequence versus a “synthetic template” (lower alignment) assembled sequence to illustrate predicted indels and nucleotide error call improvement using the synthetic scaffold template.</p

Effect of variable Mean Fluorescent Intensity (MFI) on the identification of nucleotides in the consensus output.

<p>(A) △ 85% Power (Correct); ▲ 85% Power (Unidentified); ◇ 70% Power (Correct); ◆ 70% Power (Unidentified); □ 35% Power (Correct); ■ 35% Power (Unidentified); ○ 20% Power (Correct); ● 20% Power (Unidentified). Decreasing average MFI results in an overall reduction of correct nucleotides with an inverse increase in ambiguous nucleotides; seen as a shift in the 50% correct:unidentified ratio to a lower threshold. (B) ▲ 85% Power (Incorrect); ◆ 70% Power (Incorrect); ■ 35% Power (Incorrect); ● 20% Power (Incorrect) Effect of variable MFI on the percent of incorrectly identified nucleotides at different threshold cutoffs.</p