A spatiotemporally resolved single-cell atlas of the Plasmodium liver stage

Plasmodium berghei liver stage parasites exploit host GABARAP proteins for TFEB activation

Plasmodium, the causative agent of malaria, infects hepatocytes prior to establishing a symptomatic blood stage infection. During this liver stage development, parasites reside in a parasitophorous vacuole (PV), whose membrane acts as the critical interface between the parasite and the host cell. It is well-established that host cell autophagy-related processes significantly impact the development of Plasmodium liver stages. Expression of genes related to autophagy and lysosomal biogenesis is orchestrated by transcription factor EB (TFEB). In this study, we explored the activation of host cell TFEB in Plasmodium berghei-infected cells during the liver stage of the parasite. Our results unveiled a critical role of proteins belonging to the Gamma-aminobutyric acid receptor-associated protein subfamily (GABARAP) of ATG8 proteins (GABARAP/L1/L2 and LC3A/B/C) in recruiting the TFEB-blocking FLCN-FNIP (Folliculin-Folliculin-interacting protein) complex to the PVM. Remarkably, the sequestration of FLCN-FNIP resulted in a robust activation of TFEB, reliant on conjugation of ATG8 proteins to single membranes (CASM) and GABARAP proteins. Our findings provide novel mechanistic insights into host cell signaling occurring at the PVM, shedding light on the complex interplay between Plasmodium parasites and the host cell during the liver stage of infection.

Disentanglement of single-cell data with biolord

Biolord is a deep generative method for disentangling single-cell multi-omic data to known and unknown attributes, including spatial, temporal and disease states, used to reveal the decoupled biological signatures over diverse single-cell modalities and biological systems. By virtually shifting cells across states, biolord generates experimentally inaccessible samples, outperforming state-of-the-art methods in predictions of cellular response to unseen drugs and genetic perturbations. Biolord is available at https://github.com/nitzanlab/biolord .

Spatial Transcriptomic Study Reveals Heterogeneous Metabolic Adaptation and a Role of Pericentral PPARα/CAR/Ces2a Axis During Fasting in Mouse Liver

Spatial heterogeneity and plasticity of the mammalian liver are critical for systemic metabolic homeostasis in response to fluctuating nutritional conditions. Here, a spatially resolved transcriptomic landscape of mouse livers across fed, fasted and refed states using spatial transcriptomics is generated. This approach elucidated dynamic temporal-spatial gene cascades and how liver zonation-both expression levels and patterns-adapts to shifts in nutritional status. Importantly, the pericentral nuclear receptor Nr1i3 (CAR) as a pivotal regulator of triglyceride metabolism is pinpointed. It is showed that the activation of CAR in the pericentral region is transcriptionally governed by Pparα. During fasting, CAR activation enhances lipolysis by upregulating carboxylesterase 2a, playing a crucial role in maintaining triglyceride homeostasis. These findings lay the foundation for future mechanistic studies of liver metabolic heterogeneity and plasticity in response to nutritional status changes, offering insights into the zonated pathology that emerge during liver disease progression linked to nutritional imbalances.

Type-I IFNs induce GBPs and lysosomal defense in hepatocytes to control malaria

Plasmodium parasites undergo development and replication within the hepatocytes before infecting the erythrocytes and initiating clinical malaria. Although type-I interferons (IFNs) are known to hinder Plasmodium infection within the liver, the underlying mechanisms remain unclear. Here, we describe two IFN-I-driven hepatocyte antimicrobial programs controlling liver-stage malaria. First, oxidative defense by NADPH oxidases 2 and 4 triggers a pathway of lysosomal fusion with the parasitophorous vacuole (PV) to help clear Plasmodium . Second, guanylate-binding protein (GBP) 1 disruption of the PV activates caspase-1 inflammasome, inducing pyroptosis to remove the infected host cells. Remarkably, both human and mouse hepatocytes enlist these cell-autonomous immune programs to eliminate Plasmodium ; their pharmacologic or genetic inhibition led to profound malarial susceptibility, and are essential in vivo . In addition to identifying the IFN-I-mediated cell-autonomous immune circuits controlling Plasmodium infection in the hepatocytes, this study extends our understanding of how non-immune cells are integral to protective immunity against malaria.

Unraveling the intricacies of host-pathogen interaction through single-cell genomics

Single-cell genomics provide researchers with tools to assess host-pathogen interactions at a resolution previously inaccessible. Transcriptome analysis, epigenome analysis, and immune profiling techniques allow for a better comprehension of the heterogeneity underlying both the host response and infectious agents. Here, we highlight technological advancements and data analysis workflows that increase our understanding of host-pathogen interactions at the single-cell level. We review various studies that have used these tools to better understand host-pathogen dynamics in a variety of infectious disease contexts, including viral, bacterial, and parasitic diseases. We conclude by discussing how single-cell genomics can advance our understanding of host-pathogen interactions.

Host-pathogen interactions in the Plasmodium-infected mouse liver at spatial and single-cell resolution

Upon infecting its vertebrate host, the malaria parasite initially invades the liver where it undergoes massive replication, whilst remaining clinically silent. The coordination of host responses across the complex liver tissue during malaria infection remains unexplored. Here, we perform spatial transcriptomics in combination with single-nuclei RNA sequencing over multiple time points to delineate host-pathogen interactions across Plasmodium berghei-infected liver tissues. Our data reveals significant changes in spatial gene expression in the malaria-infected tissues. These include changes related to lipid metabolism in the proximity to sites of Plasmodium infection, distinct inflammation programs between lobular zones, and regions with enrichment of different inflammatory cells, which we term 'inflammatory hotspots'. We also observe significant upregulation of genes involved in inflammation in the control liver tissues of mice injected with mosquito salivary gland components. However, this response is considerably delayed compared to that observed in P. berghei-infected mice. Our study establishes a benchmark for investigating transcriptome changes during host-parasite interactions in tissues, it provides informative insights regarding in vivo study design linked to infection and offers a useful tool for the discovery and validation of de novo intervention strategies aimed at malaria liver stage infection.

Hepatocytes and the art of killing Plasmodium softly

The Plasmodium parasites that cause malaria undergo asymptomatic development in the parenchymal cells of the liver, the hepatocytes, prior to infecting erythrocytes and causing clinical disease. Traditionally, hepatocytes have been perceived as passive bystanders that allow hepatotropic pathogens such as Plasmodium to develop relatively unchallenged. However, now there is emerging evidence suggesting that hepatocytes can mount robust cell-autonomous immune responses that target Plasmodium, limiting its progression to the blood and reducing the incidence and severity of clinical malaria. Here we discuss our current understanding of hepatocyte cell-intrinsic immune responses that target Plasmodium and how these pathways impact malaria.

A spatiotemporal atlas of mouse liver homeostasis and regeneration

The mechanism by which mammalian liver cell responses are coordinated during tissue homeostasis and perturbation is poorly understood, representing a major obstacle in our understanding of many diseases. This knowledge gap is caused by the difficulty involved with studying multiple cell types in different states and locations, particularly when these are transient. We have combined Stereo-seq (spatiotemporal enhanced resolution omics-sequencing) with single-cell transcriptomic profiling of 473,290 cells to generate a high-definition spatiotemporal atlas of mouse liver homeostasis and regeneration at the whole-lobe scale. Our integrative study dissects in detail the molecular gradients controlling liver cell function, systematically defining how gene networks are dynamically modulated through intercellular communication to promote regeneration. Among other important regulators, we identified the transcriptional cofactor TBL1XR1 as a rheostat linking inflammation to Wnt/β-catenin signaling for facilitating hepatocyte proliferation. Our data and analytical pipelines lay the foundation for future high-definition tissue-scale atlases of organ physiology and malfunction.

Exploiting integrative metabolomics to study host-parasite interactions in Plasmodium infections

Despite years of research, malaria remains a significant global health burden, with poor diagnostic tests and increasing antimalarial drug resistance challenging diagnosis and treatment. While 'single-omics'-based approaches have been instrumental in gaining insight into the biology and pathogenicity of the Plasmodium parasite and its interaction with the human host, a more comprehensive understanding of malaria pathogenesis can be achieved through 'multi-omics' approaches. Integrative methods, which combine metabolomics, lipidomics, transcriptomics, and genomics datasets, offer a holistic systems biology approach to studying malaria. This review highlights recent advances, future directions, and challenges involved in using integrative metabolomics approaches to interrogate the interactions between Plasmodium and the human host, paving the way towards targeted antimalaria therapeutics and control intervention methods.

Bacterial phenotypic heterogeneity through the lens of single-cell RNA sequencing

Bacterial transcription is not monolithic. Microbes exist in a wide variety of cell states that help them adapt to their environment, acquire and produce essential nutrients, and engage in both competition and cooperation with their neighbors. While we typically think of bacterial adaptation as a group behavior, where all cells respond in unison, there is often a mixture of phenotypic responses within a bacterial population, where distinct cell types arise. A primary phenomenon driving these distinct cell states is transcriptional heterogeneity. Given that bacterial mRNA transcripts are extremely short-lived compared to eukaryotes, their transcriptional state is closely associated with their physiology, and thus the transcriptome of a bacterial cell acts as a snapshot of the behavior of that bacterium. Therefore, the application of single-cell transcriptomics to microbial populations will provide novel insight into cellular differentiation and bacterial ecology. In this review, we provide an overview of transcriptional heterogeneity in microbial systems, discuss the findings already provided by single-cell approaches, and plot new avenues of inquiry in transcriptional regulation, cellular biology, and mechanisms of heterogeneity that are made possible when microbial communities are analyzed at single-cell resolution.

VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center in 2023

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) is a Bioinformatics Resource Center funded by the National Institutes of Health with additional funding from the Wellcome Trust. VEuPathDB supports >600 organisms that comprise invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Since 2004, VEuPathDB has analyzed omics data from the public domain using contemporary bioinformatic workflows, including orthology predictions via OrthoMCL, and integrated the analysis results with analysis tools, visualizations, and advanced search capabilities. The unique data mining platform coupled with >3000 pre-analyzed data sets facilitates the exploration of pertinent omics data in support of hypothesis driven research. Comparisons are easily made across data sets, data types and organisms. A Galaxy workspace offers the opportunity for the analysis of private large-scale datasets and for porting to VEuPathDB for comparisons with integrated data. The MapVEu tool provides a platform for exploration of spatially resolved data such as vector surveillance and insecticide resistance monitoring. To address the growing body of omics data and advances in laboratory techniques, VEuPathDB has added several new data types, searches and features, improved the Galaxy workspace environment, redesigned the MapVEu interface and updated the infrastructure to accommodate these changes.

Analysis of codon usage bias of thioredoxin in apicomplexan protozoa

BACKGROUND

Apicomplexan protozoa are a diverse group of obligate intracellular parasites causing many diseases that affect humans and animals, such as malaria, toxoplasmosis, and cryptosporidiosis. Apicomplexan protozoa possess unique thioredoxins (Trxs) that have been shown to regulate various cellular processes including metabolic redox regulation, parasite survival, and host immune evasion. However, it is still unknown how synonymous codons are used by apicomplexan protozoa Trxs.

METHODS

Codon usage bias (CUB) is the unequal usage of synonymous codons during translation which leads to the over- or underrepresentation of certain nucleotide patterns. This imbalance in CUB can impact a variety of cellular processes including protein expression levels and genetic variation. This study analyzed the CUB of 32 Trx coding sequences (CDS) from 11 apicomplexan protozoa.

RESULTS

The results showed that both codon base composition and relative synonymous codon usage (RSCU) analysis revealed that AT-ended codons were more frequently used in Cryptosporidium spp. and Plasmodium spp., while the Eimeria spp., Babesia spp., Hammondia hammondi, Neospora caninum, and Toxoplasma gondii tended to end in G/C. The average effective number of codon (ENC) value of these apicomplexan protozoa is 46.59, which is > 35, indicating a weak codon preference among apicomplexan protozoa Trxs. Furthermore, the correlation analysis among codon base composition (GC1, GC2, GC3, GCs), codon adaptation index (CAI), codon bias index (CBI), frequency of optimal codons (FOP), ENC, general average hydropathicity (GRAVY), aromaticity (AROMO), length of synonymous codons (L_sym), and length of amino acids (L_aa) indicated the influence of base composition and codon usage indices on CUB. Additionally, the neutrality plot analysis, PR2-bias plot analysis, and ENC-GC3 plot analysis further demonstrated that natural selection plays an important role in apicomplexan protozoa Trxs codon bias.

CONCLUSIONS

In conclusion, this study increased the understanding of codon usage characteristics and genetic evolution of apicomplexan protozoa Trxs, which expanded new ideas for vaccine and drug research.

Miniature spatial transcriptomics for studying parasite-endosymbiont relationships at the micro scale

Several important human infectious diseases are caused by microscale-sized parasitic nematodes like filarial worms. Filarial worms have their own spatial tissue organization; to uncover this tissue structure, we need methods that can spatially resolve these miniature specimens. Most filarial worms evolved a mutualistic association with endosymbiotic bacteria Wolbachia. However, the mechanisms underlying the dependency of filarial worms on the fitness of these bacteria remain unknown. As Wolbachia is essential for the development, reproduction, and survival of filarial worms, we spatially explored how Wolbachia interacts with the worm's reproductive system by performing a spatial characterization using Spatial Transcriptomics (ST) across a posterior region containing reproductive tissue and developing embryos of adult female Brugia malayi worms. We provide a proof-of-concept for miniature-ST to explore spatial gene expression patterns in small sample types, demonstrating the method's ability to uncover nuanced tissue region expression patterns, observe the spatial localization of key B. malayi - Wolbachia pathway genes, and co-localize the B. malayi spatial transcriptome in Wolbachia tissue regions, also under antibiotic treatment. We envision our approach will open up new avenues for the study of infectious diseases caused by micro-scale parasitic worms.

Liver in infections: a single-cell and spatial transcriptomics perspective

The liver is an immune organ that plays a vital role in the detection, capture, and clearance of pathogens and foreign antigens that invade the human body. During acute and chronic infections, the liver transforms from a tolerant to an active immune state. The defence mechanism of the liver mainly depends on a complicated network of intrahepatic and translocated immune cells and non-immune cells. Therefore, a comprehensive liver cell atlas in both healthy and diseased states is needed for new therapeutic target development and disease intervention improvement. With the development of high-throughput single-cell technology, we can now decipher heterogeneity, differentiation, and intercellular communication at the single-cell level in sophisticated organs and complicated diseases. In this concise review, we aimed to summarise the advancement of emerging high-throughput single-cell technologies and re-define our understanding of liver function towards infections, including hepatitis B virus, hepatitis C virus, Plasmodium, schistosomiasis, endotoxemia, and corona virus disease 2019 (COVID-19). We also unravel previously unknown pathogenic pathways and disease mechanisms for the development of new therapeutic targets. As high-throughput single-cell technologies mature, their integration into spatial transcriptomics, multiomics, and clinical data analysis will aid in patient stratification and in developing effective treatment plans for patients with or without liver injury due to infectious diseases.

Novel systems to study vector-pathogen interactions in malaria

Some parasitic diseases, such as malaria, require two hosts to complete their lifecycle: a human and an insect vector. Although most malaria research has focused on parasite development in the human host, the life cycle within the vector is critical for the propagation of the disease. The mosquito stage of the Plasmodium lifecycle represents a major demographic bottleneck, crucial for transmission blocking strategies. Furthermore, it is in the vector, where sexual recombination occurs generating "de novo" genetic diversity, which can favor the spread of drug resistance and hinder effective vaccine development. However, understanding of vector-parasite interactions is hampered by the lack of experimental systems that mimic the natural environment while allowing to control and standardize the complexity of the interactions. The breakthrough in stem cell technologies has provided new insights into human-pathogen interactions, but these advances have not been translated into insect models. Here, we review in vivo and in vitro systems that have been used so far to study malaria in the mosquito. We also highlight the relevance of single-cell technologies to progress understanding of these interactions with higher resolution and depth. Finally, we emphasize the necessity to develop robust and accessible ex vivo systems (tissues and organs) to enable investigation of the molecular mechanisms of parasite-vector interactions providing new targets for malaria control.

The nutrient games - Plasmodium metabolism during hepatic development

Malaria is a febrile illness caused by species of the protozoan parasite Plasmodium and is characterized by recursive infections of erythrocytes, leading to clinical symptoms and pathology. In mammals, Plasmodium parasites undergo a compulsory intrahepatic development stage before infecting erythrocytes. Liver-stage parasites have a metabolic configuration to facilitate the replication of several thousand daughter parasites. Their metabolism is of interest to identify cellular pathways essential for liver infection, to kill the parasite before onset of the disease. In this review, we summarize the current knowledge on nutrient acquisition and biosynthesis by liver-stage parasites mostly generated in murine malaria models, gaps in knowledge, and challenges to create a holistic view of the development and deficiencies in this field.

Delineating Plasmodium liver infection across space and time

The liver is a major entry point and gatekeeper for invasive pathogens. However, high-resolution, spatiotemporal transcriptomic analysis of host-pathogen interactions has remained challenging. Afriat et al. have deconvoluted Plasmodium berghei liver-stage maturation at an unprecedented scale and discovered molecular signatures of heterogeneity during pre-erythrocytic development of malarial parasites.