Exploring Microorganisms Associated to Acute Febrile Illness and Severe Neurological Disorders of Unknown Origin: A Nanopore Metagenomics Approach

Abstract

Acute febrile illness (AFI) and severe neurological disorders (SNDs) often present diagnostic challenges due to their potential origins from a wide range of infectious agents. Nanopore metagenomics is emerging as a powerful tool for identifying the microorganisms potentially responsible for these undiagnosed clinical cases. In this study, we aim to shed light on the etiological agents underlying AFI and SND cases that conventional diagnostic methods have not been able to fully elucidate. Our approach involved analyzing samples from fourteen hospitalized patients using a comprehensive nanopore metagenomic approach. This process included RNA extraction and enrichment using the SMART-9N protocol, followed by nanopore sequencing. Subsequent steps involved quality control, host DNA/cDNA removal, de novo genome assembly, and taxonomic classification. Our findings in AFI cases revealed a spectrum of disease-associated microbes, including Escherichia coli, Streptococcus sp., Human Immunodeficiency Virus 1 (Subtype B), and Human Pegivirus. Similarly, SND cases revealed the presence of pathogens such as Escherichia coli, Clostridium sp., and Dengue virus type 2 (Genotype-II lineage). This study employed a metagenomic analysis method, demonstrating its efficiency and adaptability in pathogen identification. Our investigation successfully identified pathogens likely associated with AFI and SNDs, underscoring the feasibility of retrieving near-complete genomes from RNA viruses. These findings offer promising prospects for advancing our understanding and control of infectious diseases, by facilitating detailed genomic analysis which is critical for developing targeted interventions and therapeutic strategies.

Keywords: acute febrile illness; metagenomics; nanopore sequencing; severe neurological disorders.

Figure 1

Metagenomic workflow analysis of AFI and SND in hospitalized patients. (1) Sample collection: Collection of biological samples from hospitalized patients diagnosed with acute febrile illness [AFI] or severe neurological disorder [SND] of unidentified origin. (2) Laboratory Processing: Samples underwent RNA extraction using the SMART-9N protocol, followed by metagenomic sequencing employing nanopore technology. (3) Data Analysis: Sequences were subjected to quality control, the removal of host genetic material, and the generation of contigs through de novo genome assembly. These contigs were then classified taxonomically. (4) Pathogen Identification and Further Analysis: Identified pathogens with coverage exceeding 80% were used to assemble a consensus genome. The completeness of these genomes was assessed, culminating in the construction of a phylogenetic tree.

Figure 2

Overview of the proportion of cases per classification and microorganisms identified. (A) Percentage of cases per clinical classification. (B) Proportion of SND-associated microorganisms in the samples. (C) SND-associated microorganisms identified: Clostridium sp. (light green), E. coli (dark green) and DENV-2 (light orange). (D) Proportion of AFI-associated microorganisms in the samples. (E) AFI-associated microorganisms identified: E. coli (dark green), Streptococcus sp. (light green), HIV (orange) and HPgV (dark orange).

Figure 3

Genome coverage of the viral pathogens identified. (A) The genome coverage of the HIV genome, (B) the genome coverage of the HPgV genome, and (C) the genome coverage of the Dengue virus 2 genome.

Figure 4

Phylogenetic tree of the HIV genome analysis. The sample from the study is the highlighted sample grouped with subtype B.

Figure 5

Phylogenetic tree of the HPgV genome analysis. The study’s sample is the one that is highlighted in the human clade.

Figure 6

Phylogenetic tree of the DENV2 genome analysis. Comparing the detected genotypes of DENV2 in Brazil, the sample from the study is the highlighted sample that is grouped in genotype II.