Biology subjects

Park, H.

Publications and source records attributed to Park, H..

At least 109 records · Page 6Linked to original sources

bioRxiv2023

Single tissue proteomics in Caenorhabditis elegans reveals proteins resident in intestinal lysosome-related organelles

The nematode intestine is the primary site for nutrient uptake and storage as well as the synthesis of biomolecules; lysosome-related organelles known as gut granules are important for many of these functions. Aspects of intestine biology are not well understood, including the export of the nutrients it imports and the molecules it synthesizes, as well as the complete functions and protein content of the gut granules. Here, we report a mass spectrometry-based proteomic analysis of the intestine of the Caenorhabditis elegans and of its gut granules. Overall, we identified approximately 5,000 proteins each in the intestine and the gonad and showed that most of these proteins can be detected in samples extracted from a single worm, suggesting the feasibility of individual-level genetic analysis using proteomes. Comparing proteomes and published transcriptomes of the intestine and the gonad, we identified proteins that appear to be synthesized in the intestine and then transferred to the gonad. To identify gut granule proteins, we compared the proteome of individual intestines deficient in gut granules to the wild-type. The identified gut granule proteome includes proteins known to be exclusively localized to the granules and additional putative novel gut granule proteins. We selected two of these putative gut granule proteins for validation via immunohistochemistry, and our successful confirmation of both suggests that our strategy was effective in identifying the gut granule proteome. Our results demonstrate the practicability of single tissue mass-spectrometry- based proteomic analysis in small organisms and in its utility for making discoveries. Significance statementWe show that tissue-specific proteomic analysis is achievable and can be done efficiently at an individual level in a small nematode, with resolution sufficient for genetic analysis on a single animal basis. With data collected from single animals, we produced high-quality sets of proteins that described the proteomes of the gonad and the intestine. Comparison of these proteomes with the organs transcriptomes improved our understanding of interorgan protein transport. We applied single-tissue proteomic to describe the proteome of the gut granules in the nematode intestine, a specialized lysosome-related organelle with important functions but which is not well characterized, identifying proteins not previously known to be associated with LROs and verifying two by subcellular localization.

cell biology↗

bioRxiv2023

Functional implication of the homotrimeric multidomain vacuolar sorting receptor 1 (VSR1) from Arabidopsis thaliana

The vacuolar sorting receptors (VSRs) are specific to plants and are responsible for sorting and transporting particular proteins from the trans-Golgi network to the vacuole. This process is critically important for various cellular functions, including storing nutrients during seed development. Despite many years of intense studies on VSRs, a complete relation between function and structure has not yet been revealed. For the first time, the crystal structure of the full-length luminal part of glycosylated VSR1 from Arabidopsis thaliana (AtVSR1) has been determined. The structure provides insights into the tertiary and quaternary structures of VSR1, which are composed of an N-terminal protease-associated (PA) domain, a unique central region, and one epidermal growth factor (EGF) domain followed by two disordered EGF domains. The structure of VSR1 exhibits unique characteristics, the significance of which is yet to be fully understood.

plant biology↗

bioRxiv2023

Topological Learning Approach to Characterizing Biological Membranes

Biological membranes play key roles in cellular compartmentalization, structure, and its signaling pathways. At varying temperatures, individual membrane lipids sample from different configurations, a process that frequently leads to higher-order phase behavior and phenomena. Here we present a persistent homology-based method for quantifying the structural features of individual and bulk lipids, providing local and contextual information on lipid tail organization. Our method leverages the mathematical machinery of algebraic topology and machine learning to infer temperature-dependent structural information of lipids from static coordinates. To train our model, we generated multiple molecular dynamics trajectories of DPPC membranes at varying temperatures. A fingerprint was then constructed for each set of lipid coordinates by a persistent homology filtration, in which interactions spheres were grown around the lipid atoms while tracking their intersections. The sphere filtration formed a simplicial complex that captures enduring key topological features of the configuration landscape, using homology, yielding persistence data. Following fingerprint extraction for physiologically relevant temperatures, the persistence data were used to train an attention-based neural network for assignment of effective temperature values to selected membrane regions. Our persistence homology-based method captures the local structural effects, via effective temperature, of lipids adjacent to other membrane constituents, e.g. sterols and proteins. This topological learning approach can predict lipid effective temperatures from static coordinates across multiple spatial resolutions. The tool, called MembTDA, can be accessed at https://github.com/hyunp2/Memb-TDA.

biophysics↗

bioRxiv2023

Exploring connectivity of resting-state EEG between BCI-literate and -illiterate groups

Although Motor Imagery-based Brain-Computer Interface (MI-BCI) holds significant potential, its practical application faces challenges attributable to the phenomenon known as BCI-illiteracy. BCI researchers have attempted to predict BCI-illiteracy to mitigate this issue. As connectivitys significance in neuroscience has grown, BCI researchers have applied connectivity to predict BCI-illiteracy with resting-state data. However, connectivity metrics use and interpretation of the results can be challenging for several reasons. Firstly, there are various connectivity metrics, each with its own advantages and disadvantages based on their underlying hypotheses and perspectives. These pros and cons are shaped by several factors, increasing the complexity of their application and interpretation. Secondly, it is unclear whether they are as acceptable as their developers have claimed. Thirdly, it is not evident which factor may influence the estimation of connectivity and which metric is suitable for this research. Therefore, this study conducted an empirical test to provide BCI researchers with a better understanding of connectivity. We analyzed three large public datasets using three functional connectivity (FC) and three effective connectivity (EC) metrics. Additionally, the structural difference in the resting-state network between BCI-literate and illiterate groups was examined. Our analysis revealed that the appropriate frequency range to measure connectivity varies depending upon the metric used. The alpha range was found to be suitable for FC, while the alpha, alpha + theta, and beta ranges were found to be appropriate for EC. Further, the results of estimating connectivity varied depending upon the dataset and metric used. Although we observed that BCI-literacy had stronger connections between nodes, no other significant structural differences were found between the two groups. However, BCI-literacys resting-state network displayed higher network efficiency compared to BCI-illiteracy, regardless of the metrics and dataset used. Therefore, it seems reasonable to use resting-state connectivity to predict BCI-illiteracy. Our conclusion is that each metric has its own specific hypothesis and perspective to measure connectivity under certain conditions.

neuroscience↗

bioRxiv2023

Depletion of SMN Protein in Mesenchymal Progenitors Impairs the Development of Bone and Neuromuscular Junction in Spinal Muscular Atrophy

Spinal Muscular Atrophy (SMA) is a neuromuscular disorder characterized by the deficiency of the survival motor neuron (SMN) protein, which leads to motor neuron dysfunction and muscle atrophy. In addition to the requirement for SMN in motor neurons, recent studies suggest that SMN deficiency in peripheral tissues plays a key role in the pathogenesis of SMA. Using limb mesenchymal progenitor cells (MPCs)-specific SMN-depleted mouse models, we reveal that SMN reduction in chondrocytes and fibro-adipogenic progenitors (FAPs) derived from limb MPCs causes defects in the development of bone and neuromuscular junction (NMJ), respectively. We showed that impaired growth plate homeostasis, which causes skeletal growth defects in SMA, is due to reduced IGF signaling from chondrocytes rather than the liver. Furthermore, the reduction of SMN in FAPs resulted in abnormal NMJ maturation, altered release of neurotransmitters, and NMJ morphological defects. Transplantation of healthy FAPs rescued the morphological deterioration. Our findings highlight the significance of mesenchymal SMN in neuromusculoskeletal pathogenesis in SMA and provide insights into potential therapeutic strategies targeting mesenchymal cells for the treatment of SMA.

neuroscience↗

bioRxiv2023

Hypoxia increases the methylated histones to prevent histone clipping and redistribution of heterochromatin during Raf-induced senescence

Hypoxia increases histone methylation by inhibiting O2- and -ketoglutarate- dependent histone lysine demethylases (KDMs). This study is the first to demonstrate how the hypoxic increment of methylated histones cross-talks with other epigenetic changes, such as histone clipping, and heterochromatin redistribution (senescence-associated heterochromatin foci, SAHF) found during oncogene-induced senescence (OIS). Raf activation in primary human fibroblasts IMR90 increased cathepsin L (CTSL)-mediated clipping of histone 3 (H3), H2B and H4 at H3 A21/T22, H2B T19/K20, and H4 G11/K12, respectively. Hypoxia protected H3 from CTSL by increasing histone methylation, especially at H3K23me3 without reducing the activity of CTSL. The maintenance of methylated histones is sufficient for protecting histones from CTSL, not sufficient but necessary for inhibiting SAHFs. Expression of cleaved H3 induces senescence even under hypoxia, suggesting that hypoxia disrupts this positive feedback loop of OIS by increasing histone methylation. Thus, hypoxia protects histones and chromatin from dramatic epigenetic changes by increasing histone methylation. Highlights{checkmark} Raf activation in primary fibroblasts increases cathepsin L-mediated cleavage of H3, H2B, and H4. {checkmark}Hypoxia inhibits OIS-induced histone clipping by maintaining methylated histones. {checkmark}Cleaved H3 induces senescence, even under hypoxia.

molecular biology↗

bioRxiv2023

Massively parallel identification of sequence motifs triggering ribosome-associated mRNA quality control

Decay of mRNAs can be triggered by ribosome slowdown at stretches of rare codons or positively charged amino acids. However, the full diversity of sequences that trigger co-translational mRNA decay is poorly understood. To comprehensively identify sequence motifs that trigger mRNA decay, we use a massively parallel reporter assay to measure the effect of all possible combinations of codon pairs on mRNA levels in S. cerevisiae. In addition to known mRNA-destabilizing sequences, we identify several dipeptide repeats whose translation reduces mRNA levels. These include combinations of positively charged and bulky residues, as well as proline-glycine and proline-aspartate dipeptide repeats. Genetic deletion of the ribosome collision sensor Hel2 rescues the mRNA effects of these motifs, suggesting that they trigger ribosome slowdown and activate the ribosome-associated quality control (RQC) pathway. Deep mutational scanning of an mRNA-destabilizing dipeptide repeat reveals a complex interplay between the charge, bulkiness, and location of amino acid residues in conferring mRNA instability. Finally, we show that the mRNA effects of codon pairs are predictive of the effects of endogenous sequences. Our work highlights the complexity of sequence motifs driving co-translational mRNA decay in eukaryotes, and presents a high throughput approach to dissect their requirements at the codon level.

molecular biology↗

bioRxiv2023

Linking Gba1 E326K mutation to microglia activation and mild age-dependent dopaminergic Neurodegeneration

Mutations in the GBA1 gene have been identified as a prevalent genetic risk factor for Parkinsons disease (PD). GBA1 mutations impair enzymatic activity, leading to lysosomal dysfunction and elevated levels of -synuclein (-syn). While most research has primarily focused on GBA1s role in promoting synucleinopathy, emerging evidence suggests that neuroinflammation may be a key pathogenic alteration caused by GBA1 deficiency. To examine the molecular mechanism underlying GBA1 deficiency-mediated neuroinflammation, we generated Gba1 E326K knock-in (KI) mice using the CRISPR/Cas9 technology, which is linked to an increased risk of PD and dementia with Lewy bodies (DLB). In the ventral midbrain and hippocampus of 24-month-old Gba1 E326K KI mice, we found a moderate decline in GBA1 enzymatic activity, a buildup of glucosylceramide, and an increase in microglia density. Furthermore, we observed increased levels of pro-inflammatory cytokines and formation of reactive astrocytes in primary microglia and astrocytes, respectively, cultured from Gba1 E326K KI mice following treatment with pathologic -syn preformed fibrils (PFF). Additionally, the gut inoculation of -syn PFF in Gba1 E326K KI mice significantly enhanced the accumulation of Lewy bodies in the dentate gyrus of the hippocampus, accompanied by aggravated neuroinflammation and exacerbated non-motor symptoms. This research significantly enhances our understanding of the Gba1 E326K mutations involvement in neuroinflammation and the cell-to-cell transmission of pathogenic -syn in the brain, thereby opening new therapeutic avenues.

neuroscience↗

bioRxiv2023

Neural correlates of model-based behavior in internet gaming disorder and alcohol use disorder

BackgroundAn imbalance between model-based and model-free decision-making systems is a common feature in addictive disorders. However, little is known about whether similar decision-making deficits appear in internet gaming disorder (IGD). This study compared neurocognitive features associated with model-based and model-free systems in IGD and alcohol use disorder (AUD). MethodParticipants diagnosed with IGD (n=22) and AUD (n=22), and healthy controls (n=30) performed the two-stage task inside the functional magnetic resonance imaging (fMRI) scanner. We used computational modeling and hierarchical Bayesian analysis to provide a mechanistic account of their choice behavior. Then, we performed a model-based fMRI analysis and functional connectivity analysis to identify neural correlates of the decision-making processes in each group. ResultsThe computational modeling results showed similar levels of model-based behavior in the IGD and AUD groups. However, we observed distinct neural correlates of the model-based reward prediction error (RPE) between the two groups. The IGD group exhibited insula-specific activation associated with model-based RPE, while the AUD group showed prefrontal activation, particularly in the orbitofrontal cortex and superior frontal gyrus. Furthermore, individuals with IGD demonstrated hyper-connectivity between the insula and brain regions in the salience network in the context of model-based RPE. Discussion and ConclusionsThe findings suggest potential differences in the neurobiological mechanisms underlying model-based behavior in IGD and AUD, albeit shared cognitive features observed in computational modeling analysis. As the first neuroimaging study to compare IGD and AUD in terms of the model-based system, this study provides novel insights into distinct decision-making processes in IGD.

neuroscience↗

bioRxiv2023

Protein Ensemble Generation through VariationalAutoencoder Latent Space Sampling

Mapping the ensemble of protein conformations that contribute to function and can be targeted by small molecule drugs remains an outstanding challenge. Here we explore the use of soft-introspective variational autoencoders for reducing the challenge of dimensionality in the protein structure ensemble generation problem. We convert high-dimensional protein structural data into a continuous, low-dimensional representation, carry out search in this space guided by a structure quality metric, then use RoseTTAFold to generate 3D structures. We use this approach to generate ensembles for the cancer relevant protein K-Ras, training the VAE on a subset of the available K-Ras crystal structures and MD simulation snapshots, and assessing the extent of sampling close to crystal structures withheld from training. We find that our latent space sampling procedure rapidly generates ensembles with high structural quality and is able to sample within 1 angstrom of held out crystal structures, with a consistency higher than MD simulation or AlphaFold2 prediction. The sampled structures sufficiently recapitulate the cryptic pockets in the held-out K-Ras structures to allow for small molecule docking.

biochemistry↗

bioRxiv2023

Changes in spatial self-consciousness elicit grid cell-like representation in entorhinal cortex

Grid cells in entorhinal cortex (EC) encode an individuals location in space and rely on environmental cues and multisensory bodily cues. Body-derived signals are also primary signals for the sense of self as the continuous application of visuo-tactile bodily stimuli elicits illusory drifts in perceived self-location. It is unknown whether illusory changes in self-location are sufficient to elicit grid cell like representation (GCLR) in EC and how this compares to GCLR during conventional virtual navigation. Our results show that illusory changes in perceived self-location (independent of changes in environmental navigation cues and explicit imagined navigation) evoke entorhinal GCLR, correlating in strength with the magnitude of perceived self-location, and characterized by similar grid orientation as during conventional virtual navigation. These data demonstrate that the same grid-like representation is recruited when navigating based on environmental, mainly visual cues, or when experiencing illusory forward drifts in self-location, driven by perceptual multisensory bodily cues.

neuroscience↗

bioRxiv2023

Nanobead-based single-molecule pulldown for single cells

Investigation of cell-to-cell variability holds critical physiological and clinical implications. Thus, numerous new techniques have been developed for studying cell-to-cell variability, and these single-cell techniques can also be used to investigate rare cells. Moreover, for studying protein-protein interactions (PPIs) in single cells, several techniques have been developed based on the principle of the single-molecule pulldown (SiMPull) assay. However, the applicability of these single-cell SiMPull (sc-SiMPull) techniques is limited because of their high technical barrier and special requirements for target cells and molecules. Here, we report a highly innovative nanobead-based approach for sc-SiMPull that is based on our recently developed microbead-based, improved version of SiMPull for cell populations. In our sc-SiMPull method, single cells are captured in microwells and lysed in situ, after which commercially available, pre-surface-functionalized magnetic nanobeads are placed in the microwells to specifically capture proteins of interest together with their binding partners from cell extracts; subsequently, the PPIs are examined under a microscope at the single-molecule level. Relative to previously published methods, nanobead-based sc-SiMPull is considerably faster, easier to use, more reproducible, and more versatile for distinct cell types and protein molecules, and yet provides similar sensitivity and signal-to-background ratio. These crucial features should enable universal application of our method to the study of PPIs in single cells. Statement of SignificanceHeterogeneity between single cells holds critical physiological and clinical implications. Characterization of protein-protein interactions (PPIs) and identification of the interacting partners of a specific protein are critical for elucidating the function and regulation of the protein. However, the applicability of the currently available techniques for studying PPIs in single cells is limited by their high technical barrier and special requirements for cell/proteins types. Our single-cell single-molecule pulldown (sc-SiMPull) assay in this study is not only substantially simpler and faster than existing sc-SiMPull methods, but also considerably more widely applicable--to all cell types and to both soluble and transmembrane proteins. These two crucial features should enable universal application of our method to the study of PPIs in single cells.

bioengineering↗

bioRxiv2023

The Salivary Microbiome and Predicted Metabolite Production are Associated with Progression from Barrett's Esophagus to Esophageal Adenocarcinoma

Esophageal adenocarcinoma (EAC) is rising in incidence and associated with poor survival, and established risk factors do not explain this trend. Microbiome alterations have been associated with progression from the precursor Barretts esophagus (BE) to EAC, yet the oral microbiome, tightly linked to the esophageal microbiome and easier to sample, has not been extensively studied in this context. We aimed to assess the relationship between the salivary microbiome and neoplastic progression in BE to identify microbiome-related factors that may drive EAC development. We collected clinical data and oral health and hygiene history and characterized the salivary microbiome from 250 patients with and without BE, including 78 with advanced neoplasia (high grade dysplasia or early adenocarcinoma). We assessed differential relative abundance of taxa by 16S rRNA gene sequencing and associations between microbiome composition and clinical features and used microbiome metabolic modeling to predict metabolite production. We found significant shifts and increased dysbiosis associated with progression to advanced neoplasia, with these associations occurring independent of tooth loss, and the largest shifts were with the genus Streptococcus. Microbiome metabolic models predicted significant shifts in the metabolic capacities of the salivary microbiome in patients with advanced neoplasia, including increases in L- lactic acid and decreases in butyric acid and L-tryptophan production. Our results suggest both a mechanistic and predictive role for the oral microbiome in esophageal adenocarcinoma. Further work is warranted to identify the biological significance of these alterations, to validate metabolic shifts, and to determine whether they represent viable therapeutic targets for prevention of progression in BE.

microbiology↗

bioRxiv2023

Dysregulated Platelet Function and Thrombosis in Patients with Post-Acute Sequelae of COVID-19

BackgroundPost-acute sequelae of COVID-19 (PASC), also referred as Long-COVID, sometimes follows COVID-19, a disease caused by SARS-CoV-2. While SARS-CoV-2 is well-known to promote a prothrombotic state, less is known about the thrombosis risk in PASC. AimOur objective was to evaluate the platelet function and thrombotic potential in patients following recovery from SARS-CoV-2 with clear symptoms of PASC. MethodsPASC patients and matched healthy controls were enrolled in the study on average 15 months after documented SARS-CoV-2 infection. Platelet activation was evaluated by Light Transmission Aggregometry (LTA) and flow cytometry in response to platelet surface receptor agonists. Thrombosis in platelet-deplete plasma was evaluated by Factor Xa activity. A microfluidics system assessed thrombosis in whole blood under shear stress conditions. ResultsA mild increase in platelet aggregation in PASC patients through the thromboxane receptor was observed and platelet activation through the glycoprotein VI (GPVI) receptor was decreased in PASC patients compared to age- and sex-matched healthy controls. Thrombosis under shear conditions as well as Factor Xa activity were reduced in PASC patients. Plasma from PASC patients was an extremely potent activator of washed, healthy platelets - a phenomenon not observed when stimulating healthy platelets after incubation with plasma from healthy individuals. ConclusionsPASC patients show dysregulated responses in platelets and coagulation in plasma, likely caused by a circulating molecule that promotes thrombosis. A hitherto undescribed protective response appears to exists in PASC patients to counterbalance ongoing thrombosis that is common to SARS-CoV-2 infection.

pharmacology and toxicology↗

bioRxiv2023

Direct Relationship between Protein Expression and Progeny Yield of Herpes Simplex Virus 1 Unveils a Rate-limiting Step for Virus Production

Although viral protein expression and progeny virus production were independently shown to be highly heterogenous in individual cells, their direct relationship, analyzed by considering their heterogeneities, has not been investigated to date. This study established a system to fractionate cells infected with a herpesvirus based on the levels of the global expression of viral late proteins, which are largely virion structural proteins, and to titrate virus yields in these fractions. This system demonstrated a direct relationship and indicated there was a threshold for the levels of viral late protein expression for progeny virus production and suggested that viral DNA cleavage/packaging was a rate-limiting step for progeny virus production. These findings, which were masked in previous studies performed at the entire population level, have uncovered a sophisticated viral strategy for efficient progeny virus production and shed new light on an effective target for the development of anti-viral drugs.

microbiology↗

bioRxiv2023

Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation for analyzing extracellular viral markers

Chronic infection of hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. The quantifying and understanding dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, it requires a liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because of the ethical aspect. We here aimed to develop a non-invasive method for quantifying cccDNA in the liver using surrogate markers present in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations (PDEs), integrates experimental data from in vitro and in vivo investigations. By applying this model, we successfully predicted the amount and dynamics of intrahepatic cccDNA using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The non-invasive quantification of cccDNA using our proposed methodology holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.

microbiology↗

bioRxiv2023

A semiconductor 96-microplate platform for real-time impedance-based high-throughput screening

Profiling compounds and genetic perturbations via high-content imaging has become increasingly popular for drug discovery, but the technique is limited to endpoint images of fixed cells. In contrast, electronic-based devices offer label-free, functional information of live cells, yet current approaches suffer from low-spatial resolution or single-well throughput. Here, we report a semiconductor 96-microplate platform designed for high-resolution real-time impedance "imaging" at scale. Each well features 4,096 electrodes at 25 {micro}m spatial resolution while a miniaturized data interface allows 8x parallel plate operation (768 total wells) within each incubator for enhanced throughputs. New electric field-based, multi-frequency measurement techniques capture >20 parameter images including tissue barrier, cell-surface attachment, cell flatness, and motility every 15 min throughout experiments. Using these real-time readouts, we characterized 16 cell types, ranging from primary epithelial to suspension, and quantified heterogeneity in mixed epithelial and mesenchymal co-cultures. A proof-of-concept screen of 904 diverse compounds using 13 semiconductor microplates demonstrates the platforms capability for mechanism of action (MOA) profiling with 25 distinct responses identified. The scalability of the semiconductor platform combined with the translatability of the high dimensional live-cell functional parameters expands high-throughput MOA profiling and phenotypic drug discovery applications.

bioengineering↗

bioRxiv2023

Mapping the genomic landscape of multidrug resistance in Plasmodium falciparum and its impact on parasite fitness

Drug-resistant Plasmodium falciparum parasites have swept across Southeast Asia and now threaten Africa. By implementing a P. falciparum genetic cross using humanized mice, we report the identification of key determinants of resistance to artemisinin (ART) and piperaquine (PPQ) in the dominant Asian KEL1/PLA1 lineage. We mapped k13 as the central mediator of ART resistance and identified secondary markers. Applying bulk segregant analysis, quantitative trait loci mapping and gene editing, our data reveal an epistatic interaction between mutant PfCRT and multicopy plasmepsins 2/3 in mediating high-grade PPQ resistance. Susceptibility and parasite fitness assays implicate PPQ as a driver of selection for KEL1/PLA1 parasites. Mutant PfCRT enhanced susceptibility to lumefantrine, the first-line partner drug in Africa, highlighting a potential benefit of opposing selective pressures with this drug and PPQ. We also identified that the ABCI3 transporter can operate in concert with PfCRT and plasmepsins 2/3 in mediating multigenic resistance to antimalarial agents.

genomics↗