How Genomics Solved a Typhoid Fever Mystery in Papua New Guinea
Unraveling the secrets of Salmonella Typhi through whole-genome sequencing
In the rugged highlands of Papua New Guinea (PNG), where access to clean water and proper sanitation remains limited, a silent threat has lurked for decades—typhoid fever. Caused by the bacterium Salmonella enterica serovar Typhi, this potentially fatal disease has plagued communities, particularly affecting children and young adults 1 3 .
What puzzled researchers most wasn't just the prevalence of typhoid in PNG—which ranks among the highest in the world—but why some patients succumbed to the infection while others recovered. The answer to this medical mystery would eventually be found not through traditional diagnostic methods, but by reading the complete genetic blueprints of the bacteria themselves through whole-genome sequencing 1 3 .
For years, scientists suspected that antimicrobial resistance (AMR) might explain the fatal cases, as drug-resistant typhoid strains have emerged in many parts of the world. But when researchers began unraveling the genetic code of PNG's typhoid bacteria, they discovered something surprising: these pathogens were largely susceptible to antibiotics. This revelation launched a genuine genetic detective story that would ultimately transform our understanding of typhoid in the Pacific region and provide valuable insights for global typhoid control efforts 1 7 .
Papua New Guinea has one of the highest typhoid fever incidence rates in the world, with reports of 1,208 cases per 100,000 population in the mid-1990s 1 .
Typhoid fever is a life-threatening systemic infection caused by the bacterium Salmonella enterica serovar Typhi. Spread through contaminated food and water, the disease remains a significant public health threat in many low- and middle-income countries where sanitation infrastructure is limited 2 7 .
The effectiveness of antibiotics is increasingly threatened by the emergence of antimicrobial resistance. Multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains have emerged globally, complicating treatment efforts 1 8 .
Whole-genome sequencing (WGS) has revolutionized how scientists track and understand infectious diseases. By decoding the complete genetic blueprint of pathogens, researchers can identify subtle variations that help them trace transmission patterns and detect resistance genes 4 8 .
Papua New Guinea has long been recognized as a high-burden setting for typhoid fever. In the mid-1990s, the incidence rate was reported as 1,208 cases per 100,000 population—among the highest rates in the world at that time. More recent diagnostic studies have confirmed that typhoid remains a common diagnosis in febrile patients in the PNG highlands 1 .
What made PNG's typhoid situation particularly intriguing was the puzzle of why some patients died while others recovered. Initial hypotheses centered on antibiotic resistance, but early studies had noted that PNG's S. Typhi appeared largely susceptible to first-line antibiotics. This contrasted sharply with trends in South Asia, where drug-resistant strains had become dominant 1 3 .
Initial hypothesis: Antimicrobial resistance
Surprising finding: PNG strains were largely susceptible to antibiotics
To solve this mystery, researchers embarked on a comprehensive whole-genome sequencing study comparing bacterial isolates from fatal and nonfatal cases. Their investigation would span isolates collected over three decades (1980-2010), providing an unprecedented window into the evolution of typhoid in this unique setting 1 .
The research team, led by scientists from the Papua New Guinea Institute of Medical Research (PNGIMR), analyzed 86 S. Typhi isolates collected between 1980 and 2010. The isolates came from both fatal and nonfatal cases across multiple regions of PNG 1 .
Frozen bacterial isolates were carefully revived from the PNGIMR culture collection. Each isolate was cultured on nutrient agar, and PCR confirmation was performed to verify their identity as S. Typhi 1 .
The researchers performed standardized antibiotic susceptibility testing using agar breakpoint dilution methods. They tested sensitivity to multiple antibiotics including chloramphenicol, ampicillin, co-trimoxazole, fluoroquinolones, third-generation cephalosporins, and macrolides 1 .
High-quality genomic DNA was extracted from each isolate using commercial kits. Most samples were sequenced using Illumina technology, which provides short but highly accurate reads. For selected isolates, the team also used Oxford Nanopore technology to generate long reads that help assemble complete genomes 1 3 .
The sequenced reads were mapped to a reference genome (CT18) to identify genetic variations. Researchers used the GenoTyphi framework to assign each isolate to a specific genotype and sublineage. They also screened for known antimicrobial resistance determinants and virulence factors 1 3 .
| Feature | Fatal Cases | Nonfatal Cases |
|---|---|---|
| Genotype Distribution | Predominantly 2.1.7 | Predominantly 2.1.7 |
| AMR Determinants | No acquired resistance genes | No acquired resistance genes |
| Virulence Genes | Complete complement | Complete complement |
| Plasmids/Prophages | None detected | None detected |
| Unique Genetic Features | None identified | None identified |
The absence of genetic differences between isolates from fatal and nonfatal cases led researchers to consider alternative explanations for the varying disease outcomes:
Cutting-edge typhoid genomics research relies on a sophisticated array of laboratory reagents and bioinformatic tools. Here are some of the key components that enabled this research:
| Reagent/Tool | Function | Application in PNG Study |
|---|---|---|
| Illumina HiSeq Platform | High-throughput sequencing | Generated short-read sequences for most isolates |
| Nanopore MinION | Long-read sequencing | Provided complete genomes for selected isolates |
| DNeasy Blood & Tissue Kit | DNA extraction | Isolated high-quality genomic DNA from bacterial cultures |
| CT18 Reference Genome | Reference for mapping | Provided a standard for read alignment and variant calling |
| GenoTyphi Framework | Genotype classification | Enabled standardized lineage assignment and global comparisons |
| Pathogenwatch Platform | Genomic analysis | Facilitated AMR determinant detection and phylogenetic analysis |
The TyphiNET platform, developed by the Global Typhoid Genomics Consortium, represents an important innovation in making genomic data accessible to public health decision-makers. This interactive online dashboard allows users to explore country-level summaries of typhoid genotypes and AMR patterns 4 .
The story of typhoid fever in Papua New Guinea illustrates how genomic technologies are transforming our understanding of infectious diseases. By decoding the complete genetic blueprints of bacterial pathogens, scientists can unravel mysteries that defy solution through conventional approaches.
In PNG's case, genomics revealed that the difference between life and death for typhoid patients wasn't written in the bacteria's genes but likely resulted from a complex interplay of host factors, healthcare access, and social determinants of health. This understanding helps focus public health efforts on improving overall health systems, nutrition, and access to care while maintaining effective antibiotic treatments.
Perhaps most importantly, the study offers hope for typhoid control in PNG and similar settings. With susceptible bacteria and effective vaccines available, there is real potential to reduce the devastating burden of this ancient disease through coordinated public health efforts informed by genomic surveillance.
As genomic technologies become more accessible and affordable, their application to public health challenges in low- and middle-income countries will undoubtedly increase, leading to more personalized and effective approaches to disease control. The PNG typhoid story represents just the beginning of this exciting transformation in global health.