Although severe malaria presents in different clinical forms – such as cerebral malaria or severe malarial anemia – a new study reveals that all severe cases have one thing in common: a shared inflammatory signature

Transcript

Whilst most cases of malaria are mild, some take a dangerous turn. In severe cases, the malaria parasite can overwhelm the body, disrupting the blood-brain barrier and leading to cerebral malaria, or destroying so many red blood cells that it triggers life-threatening anemia. Now, a new study has taken a closer look at this progression – from uncomplicated malaria to severe disease.

Researchers looked at three factors: Transcriptomics, the genes being expressed; proteomics, the proteins being produced; and metabolomics, the metabolites and small molecules present. Using a matched-pairs design, they compared blood samples of children with severe malaria versus children with uncomplicated disease.

The finding? Although different types of severe malaria can be distinguished by other factors, they all share a ‘common signalling pattern.’

Two proteins stood out: MMP8 and MMP9 – and those proteins are both involved, in different ways, in the breakdown of the extracellular matrix – the scaffolding between cells. The finding gives researchers new clues into how malaria becomes deadly, and may open the door to better-targeted treatments – or even a vaccine against severe malaria - in the future.

Source

A shared inflammatory signature across severe malaria syndromes manifested by transcriptomic, proteomic and metabolomic analyses [Nature Communications]

About The Podcast

The Johns Hopkins Malaria Minute podcast is produced by the Johns Hopkins Malaria Research Institute to highlight impactful malaria research and to share it with the global community.

Dr. Alexandra Probst discusses a breakthrough in malaria prevention: bed nets coated with anti-parasitic drugs that stop transmission by curing infected mosquitoes.

With Alexandra Probst, former graduate student at Harvard University.

About The Podcast

The Johns Hopkins Malaria Minute is produced by the Johns Hopkins Malaria Research Institute to highlight impactful malaria research and to share it with the global community.

How next-generation bed nets could stop malaria by killing the parasites inside mosquitoes, not just the mosquitoes themselves.

Transcript

Bed nets have long been a cornerstone of vector control. Coated with insecticide, they serve a dual purpose: preventing bites and killing mosquitoes. But what if those nets could do more – not only kill the mosquitoes, but for those they don’t kill because of increasing insecticide resistance, at least kill the parasites hidden inside them?

Researchers assembled a library of antiparasitic compounds active against the form of the parasite in the mosquito midgut. They identified 81 promising compounds, some of which were already in clinical development. Of those, 22 were found to be effective against these early stages of parasite development in the mosquito and, therefore, capable of preventing onward transmission.

One class of compound stood out: ELQs, or endochin-like quinolones. These could be absorbed through the mosquito’s legs in tests, therefore viable for use in a mosquito net. The researchers suggest that ELQs could offer a promising new strategy for malaria control, working alongside traditional methods to reduce malaria cases and deaths.

Source

In vivo screen of Plasmodium targets for mosquito-based malaria control (Nature)

About The Podcast

The Johns Hopkins Malaria Minute podcast is produced by the Johns Hopkins Malaria Research Institute to highlight impactful malaria research and to share it with the global community.

The extent to which malaria vaccines reduce cases and deaths is a key consideration. But there’s another factor, too.

with Dr. Lemu Golassa, Head of Medical Parasitology at Addis Ababa University.

About The Podcast

The Johns Hopkins Malaria Minute is produced by the Johns Hopkins Malaria Research Institute to highlight impactful malaria research and to share it with the global community.

A recent study in Ethiopia reveals that local malaria parasite strains differ genetically from those targeted by current vaccines, potentially reducing their effectiveness.

Transcript

The recent introduction of two malaria vaccines in sub-Saharan Africa represents a major success in global health, and the culmination of decades of research and development. The two jabs – RTS,S and R21 – target a protein on the surface of the malaria parasite as it enters the skin, called the circumsporozoite protein, or CSP. The vaccines are based on a specific form of CSP. The challenge is that there are many forms of CSP – called haplotypes – across regions. Vaccine efficacy, therefore, may in part depend on how closely local CSP haplotypes match those used to develop the vaccine. If they’re a close match, the vaccine should work well, but if there’s a mismatch, the vaccine may be less effective.

A recent study in Ethiopia collected blood samples from malaria-infected children over the age of five from three health centres in different parts of the country. Of the 120 blood samples collected, CSP was successfully sequenced in 85. Whilst there was little variation in samples from the same region, there was significant variation between regions, highlighting the genetic polymorphism of CSP. Importantly, none of the Ethiopian CSP haplotypes matched the vaccine haplotype, indicating the jabs may not achieve optimal efficacy in the country.

Source

Unveiling mismatch of RTS S AS01 and R21 Matrix M malaria vaccines haplotype among Ethiopian Plasmodium falciparum clinical isolates (Scientific Reports)

About The Podcast

The Johns Hopkins Malaria Minute podcast is produced by the Johns Hopkins Malaria Research Institute to highlight impactful malaria research and to share it with the global community.

The podcast explores the importance of advocacy for malaria research and control. It follows over 120 advocates gathering in Washington, DC, as part of the ‘United to Beat Malaria’ campaign, urging Congress to continue supporting global malaria efforts.

Key topics include:

• The US President’s Malaria Initiative (PMI), founded in 2005, which provides bed nets, test kits, and treatments to combat malaria

• The role of global partnerships, including the Global Fund, in distributing resources efficiently.

• How Uganda’s malaria response is supported by international funding for the dissemination of key public health interventions.

• The importance of sustained funding for malaria research, with US agencies like NIH, CDC, and PMI contributing to vaccine development and disease surveillance.
  
  

Featuring: Margaret Reilly McDonnell (United to Beat Malaria), Dr David Walton (formerly PMI), Dr Jimmy Opigo (Uganda National Malaria Control Program), Jamie Bay Nishi (ASTMH) and Ed Royce (former House Foreign Affairs Committee (HFAC) Chairman).

With a shortage of entomologists in malaria-endemic regions, could AI fill the gap? We explore VectorCam, an offline tool powered by a Convolutional Neural Network that aims to support local vector surveillance.

with Dr. Soumya Acharya and Sunny Patel of Johns Hopkins University.

About The Podcast

The Johns Hopkins Malaria Minute is produced by the Johns Hopkins Malaria Research Institute to highlight impactful malaria research and to share it with the global community.

Can AI identify mosquito species? VectorCAM, a pocket-sized device, uses machine learning to differentiate species with 95% accuracy, enhancing malaria surveillance efforts

Transcript

Not all mosquitoes are created equal. Of the more than three thousand species, only a limited number of the Anopheles genus can transmit malaria. Even within that subset, subtle physiological differences affect how malaria spreads. Some mosquitoes prefer to bite indoors, while others outdoors. Some need large bodies of water to breed, while others only need a small puddle. Distinguishing these species is critical for effective malaria control—whether using bed nets, indoor spraying, or outdoor larval management. But identifying them by eye takes expert, entomological knowledge. Could AI help? The VectorCAM team at Johns Hopkins is working on just that. Their pocket-sized device uses a small light and magnifying lens, allowing a phone camera to capture close-up images of mosquitoes placed on slides. With up to 95% accuracy, it can identify mosquito species based on morphology in seconds. The hope is that VectorCAM will help health teams better understand mosquito populations, paving the way for more targeted and relevant malaria control efforts.

Source

Towards transforming malaria vector surveillance using VectorBrain: a novel convolutional neural network for mosquito species, sex, and abdomen status identifications (Scientific Reports)

About The Podcast

The Johns Hopkins Malaria Minute podcast is produced by the Johns Hopkins Malaria Research Institute to highlight impactful malaria research and to share it with the global community.