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Patel, A.

Publications and source records attributed to Patel, A..

At least 109 records · Page 6Linked to original sources

An Open-Source Rodent Chronic EEG Array System with High Density MXene-Based Skull Surface Electrodes

Electroencephalography (EEG) is an indispensable tool in epilepsy, sleep, and behavioral research. In rodents, EEG recordings are typically performed with metal electrodes that traverse the skull into the epidural space. In addition to requiring a major surgery, this intracranial EEG technique is difficult to perform for more than a few electrodes, is time-intensive, and confounds experiments studying traumatic brain injury. Here, we describe an open-source cost-effective refinement of this technique for chronic mouse EEG recording. Our alternative two channel (EEG2) and sixteen channel high-density EEG (HdEEG) arrays use electrodes made of the novel, flexible 2D nanomaterial titanium carbide (Ti3C2Tx) MXene. The MXene electrodes are placed on the surface of the intact skull and establish electrical connection without conductive gel or paste. Fabrication and implantation times of MXene EEG electrodes are significantly shorter than the standard approach and recorded resting baseline and epileptiform EEG waveforms are similar to those obtained with traditional epidural electrodes. Applying HdEEG to a mild traumatic brain injury (mTBI) model in mice of both sexes revealed that mTBI significantly altered awake resting state spectral density with a spatiospectral region of interest in the {beta} spectral band (12-30 Hz) in the central and posterior regions. These findings indicate that fabrication of MXene electrode arrays is a cost effective, efficient technology for multichannel EEG recording in rodents that obviates the need for skull-penetrating surgery. Moreover, increased {beta} spectral power may contribute to the development of early post-mTBI seizures. Significance StatementElectroencephalography (EEG) is a critical technique used to study neurological activity in rodents. Commonly used EEG procedures require time-consuming skull-penetrating surgeries that may confound the experiments. Here we provide a cost-effective solution for obtaining two channel (EEG2) and high-density EEG (HdEEG) recordings on the skull surface thus avoiding major surgery. We compared this HdEEG system to traditional EEG recordings and then used it to determine the effects of mild traumatic brain injury on awake resting state spectral density. This novel open-source EEG system will contribute the electrophysiological characterization of rodent behaviors and seizure activity.

neuroscience↗

Lab evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance

Relationships between the genome, transcriptome, and metabolome underlie all evolved phenotypes. However, it has proved difficult to elucidate these relationships because of the high number of variables measured. A recently developed data analytic method for characterizing the transcriptome can simplify interpretation by grouping genes into independently modulated sets (iModulons). Here, we demonstrate how iModulons reveal deep understanding of the effects of causal mutations and metabolic rewiring. We use adaptive laboratory evolution to generate E. coli strains that tolerate high levels of the redox cycling compound paraquat, which produces reactive oxygen species (ROS). We combine resequencing, iModulons, and metabolic models to elucidate six interacting stress tolerance mechanisms: 1) modification of transport, 2) activation of ROS stress responses, 3) use of ROS-sensitive iron regulation, 4) motility, 5) broad transcriptional reallocation toward growth, and 6) metabolic rewiring to decrease NADH production. This work thus reveals the genome-scale systems biology of ROS tolerance. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/521246v1_ufig1.gif" ALT="Figure 1"> View larger version (83K): org.highwire.dtl.DTLVardef@187f455org.highwire.dtl.DTLVardef@ba0798org.highwire.dtl.DTLVardef@148b175org.highwire.dtl.DTLVardef@17a8f8c_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

Molecular basis of SARS-CoV-2 Omicron variant evasion from shared neutralizing antibody response

A detailed understanding of the molecular features of the neutralizing epitopes developed by viral escape mutants is important for predicting and developing vaccines or therapeutic antibodies against continuously emerging SARS-CoV-2 variants. Here, we report three human monoclonal antibodies (mAbs) generated from COVID-19 recovered individuals during first wave of pandemic in India. These mAbs had publicly shared near germline gene usage and potently neutralized Alpha and Delta, but poorly neutralized Beta and completely failed to neutralize Omicron BA.1 SARS-CoV-2 variants. Structural analysis of these three mAbs in complex with trimeric spike protein showed that all three mAbs are involved in bivalent spike binding with two mAbs targeting class-1 and one targeting class-4 Receptor Binding Domain (RBD) epitope. Comparison of immunogenetic makeup, structure, and function of these three mAbs with our recently reported class-3 RBD binding mAb that potently neutralized all SARS-CoV-2 variants revealed precise antibody footprint, specific molecular interactions associated with the most potent multi-variant binding / neutralization efficacy. This knowledge has timely significance for understanding how a combination of certain mutations affect the binding or neutralization of an antibody and thus have implications for predicting structural features of emerging SARS-CoV-2 escape variants and to develop vaccines or therapeutic antibodies against these.

immunology↗

Metamorphic proteins at the basis of human autophagy initiation and lipid transfer

Autophagy is a conserved intracellular degradation pathway that uses de novo doublemembrane vesicle (autophagosome) formation to target a wide range of cytoplasmic material for lysosomal degradation. In multicellular organisms, autophagy initiation requires the timely assembly of a contact site between the ER and the nascent autophagosome. Here, we report the in vitro reconstitution of a full-length sevensubunit human autophagy initiation supercomplex and found at its core ATG13-101 and transmembrane protein ATG9. Assembly of this core complex requires the rare ability of ATG13 and ATG101 to adopt topologically distinct folds. The slow spontaneous conversion between folds creates a rate-limiting step to regulate selfassembly of the super-complex. The interaction of the core complex with ATG2-WIPI4 enhances tethering of membrane vesicles and accelerates lipid transfer of ATG2 by both ATG9 and ATG13-101. Our work uncovers the molecular basis of the contact site and its assembly mechanisms imposed by the metamorphosis of ATG13-101 to regulate autophagosome biogenesis in space and time.

biochemistry↗

Is adiposity associated with white matter microstructural health and intelligence differently in men and women?

The role of vascular risk in age-related brain degeneration has long been the subject of intense study. As a sub-category of vascular risk, obesity has an increasingly recognized role in influencing brain health and health-care strategies, but its association with brain health remains under-studied. Notably, no prior study has addressed sex differences in the association between adiposity and white-matter microstructural integrity, an important early marker of brain degeneration, despite known sex differences in fat storage and usage. This study focuses on the associations between adiposity (abdominal fat ratio: AFR, and liver proton density fat fraction: PDFF) and brain microstructural health (measures of white-matter microstructure using diffusion-tensor imaging, DTI). We found that fluid intelligence and reaction time are indeed associated with body fat differently in men and women. We also found significant differences in the associations of AFR with DTI metrics between sexes. These sex differences are mirrored in the associations of SBP and age with DTI metrics. Moreover, these sex differences in the AFR and SBP associations with DTI metrics persist when controlling for age. Taken together, these findings suggest that there are inherent sex-driven differences in how brain health is associated with vascular risk factors such as obesity.

systems biology↗

Automated prediction of site and sequence of protein modification with ATRP initiators

One of the most straightforward and commonly used chemical modifications of proteins is to react surface amino groups (lysine residues) with activated esters. This chemistry has been used to generate protein-polymer conjugates, many of which are now approved therapeutics. Similar conjugates have also been generated by reacting activated ester atom transfer polymerization initiators with lysine residues to create biomacromolecular initiators for polymerization reactions. The reaction between activated esters and lysine amino groups is rapid and has been consistently described in almost every publication on the topic as a "random reaction". A random reaction implies that every accessible lysine amino group on a protein molecule is equally reactive, and as a result, that the reaction is indiscriminate. Nonetheless, the literature contradicts itself by also suggesting that some lysine amino groups are more reactive than others (as a function of pKa, surface accessibility, temperature, and local environment). If the latter assumption is correct, then the outcome of these reactions cannot be random at all, and we should be able to predict the outcome from the structure of the protein. Predicting the non-random outcome of a reaction between surface lysines and reactive esters could transform the speed at which active bioconjugates can be developed and engineered. Herein, we describe a robust integrated tool that predicts the activated ester reactivity of every lysine in a protein, thereby allowing us to calculate the non-random sequence of reaction as a function of reaction conditions. Specifically, we have predicted the intrinsic reactivity of each lysine in multiple proteins with a bromine-functionalised N-hydroxysuccinimide initiator molecule. We have also shown that the model applied to PEGylation. The rules-based analysis has been coupled together in a single Python program that can bypass tedious trial and error experiments usually needed in protein-polymer conjugate design and synthesis.

bioinformatics↗

Salivary exosomal miR-1307-5p predicts disease aggressiveness and poor prognosis in oral squamous cell carcinoma patients

BackgroundSalivary exosomal miRNAs as biomarkers facilitate repeated sampling, real-time disease monitoring and assessment of therapeutic response. This study identifies a single salivary exosomal miRNA prognosticator that will aid in improved patient outcome using a liquid biopsy approach. MethodSmall RNA and transcriptome sequencing profiles of tumour tissues and salivary exosomes from oral cancer patients were compared to their non-cancerous counterparts. We validated these results using the Cancer Genome Atlas database and performing Real-time PCR on a larger patient cohort. Potential target genes, miRNA-mRNA networks and enriched biological pathways regulated by this microRNA were identified using computational tools. ResultsSalivary exosomes (size: 30-50nm) demonstrated a strong expression of CD47 and detectable expression of tetraspanins CD63, CD81 and CD9 by flow cytometry. miR-1307-5p was exclusively overexpressed in tissues and salivary exosomes of oral cancer patients compared to their non-cancerous counterparts. Enhanced expression of miR-1307-5p clinically correlated with poor patient survival, disease progression, aggressiveness and chemo-resistance in these patients. Transcriptome analysis suggested that miRNA-1307-5p could promote oral cancer progression by suppressing THOP1, EHF, RNF4, GET4, and RNF114. ConclusionSalivary exosomal miRNA-1307-5p is a potential prognosticator for predicting poor survival and poor patient outcome in oral cancers.

cancer biology↗

Drug-induced adaptation along a resistance continuum in cancer cells

Advancements in rational drug design over the past decades have consistently produced new cancer therapies, but such treatments are inevitably countered through an adaptive process that fosters therapy resistance. Malignant cells achieve drug resistance through intrinsic and acquired mechanisms, rooted in genetic and non-genetic determinants. In particular, recent work has highlighted the role of intrinsic cellular heterogeneity in the emergence of transient drug-tolerant persister cells that survive drug treatment, as well as non-genetically driven cell plasticity toward stable resistance. However, these models do not account for the role of dose and treatment duration as extrinsic forces in eliciting cancer cell adaptation. Here, we show that these two components together drive the resistance of ovarian cancer cells to targeted therapy along a trajectory of cellular adaptation, that we denote the resistance continuum. We report that gradual dose exposure and prolonged treatment promote a continuous increase in fitness, and show that this process is mediated by evolving transcriptional, epigenetic and genetic changes that promote multiple cell state transitions. The resistance continuum is underpinned by the assembly of gene expression programs and epigenetically reinforced stress response regulation. Using both in vivo and in vitro models, we found that this process involves widespread reprogramming of cell survival pathways, including interferon response, lineage reprogramming, metabolic rewiring and oxidative stress regulation. Together, the resistance continuum reveals the dynamic nature of cellular adaptation, and carries implications for cancer therapies, as initial exposure to lower doses primes cells over time for increased resistance to higher doses. Beyond cancer, such continuous adaptation exposes a basic aspect of cellular plasticity, which may also be deployed in other biological systems such as development, immune response and host-pathogen interactions.

cancer biology↗

A novel 4 miRNA signature from salivary exosomes regulates multiple signalling pathways and predicts tumour progression in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is often diagnosed late, leading to poor patient outcomes. This study aims to identify potential miRNA-based biomarkers for predicting disease progression using salivary exosomes derived from OSCC patients. Further, we identify crucial miRNA-mRNA networks involved in tumorigenesis and uncover the underlying mechanism responsible for OSCC progression. Small RNA (n=23) sequencing analysis along with data available from The Cancer Genome Atlas (TCGA) (n=114) identified 12 differentially expressed miRNAs in OSCC patients as compared to controls. Validating these findings, miR-140-5p, miR-143-5p, and miR-145-5p were significantly downregulated in a larger cohort of OSCC patients (n=70). This 3-miRNA signature demonstrated higher efficacy of salivary exosomes (p<0.0001) in early detection and clinically correlated with disease progression and overall survival of OSCC patients (p<0.05). Further, analysis of the transcriptome, TCGA datasets and miRNA-mRNA networks, identified top hub genes (HIF1a, CDH1, CD44, EGFR, and CCND1) which were regulated by a 3-miRNA signature. Based on pathway analysis, these miRNA-mRNA interactions were found to be involved in regulating epithelial-mesenchymal transition (EMT). Further, transfection-mediated upregulation of the 3-miRNA signature significantly decreased cell proliferation, induced apoptosis, resulted in G2/M phase cell cycle arrest and reduced the invasive and migratory potential by reversing the EMT process in OECM-1 cell line. Thus, this study identifies a 3-miRNA signature that can be utilized as a potential biomarker for early detection of OSCC and uncovers the underlying mechanisms responsible for converting a normal epithelial cell into a malignant phenotype.

cancer biology↗

In vivo selection reveals long non-coding RNAs implicated in colon to liver metastasis

Colorectal cancer (CRC) is the third most common malignancy in both American men and women. Most of the deaths attributed to CRC are a result of metastatic spread to the liver. In this study, colon cancer cells that highly metastasized to liver in vivo were compared to less metastatic parental cells to investigate the role for long non-coding RNAs (lncRNAs) in CRC metastasis. The highly metastatic daughter cells (LS-3B) were found to be 63-fold more metastatic than the parental cell line (LS-PAR) in vivo. A lncRNA microarray comparing LS-PAR and LS-3B cells revealed that 104 lncRNAs had fold changes > 2.0 and an FDR < 0.05. Real time PCR mediated validation revealed many lncRNAs exhibited high fold changes such as a 60-fold increase in LOC101448202, a 20-fold increase in MRPL23-AS1 and 50-fold decreases in GNAS-AS1 and LOC101928131. In vivo metastasis differences could be recapitulated in vitro as LS-3B cells closed wounds faster than their parental LS-PAR cells. However, intestinal epithelial cancer cells with robust downregulation of MRPL23-AS1, C1QTNF1-AS1, GNAS-AS1, LINCR-0002 and LOC101448202 failed to display differences in comparison to controls in in vitro migration assays. Three of the five lncRNAs with microarray probes for currently available GEO-datasets were significantly altered in liver CRC-associated tumor biopsies as compared to the primary tumor of non-metastatic CRC. Further studies on the lncRNAs identified will better define their roles in metastasis and how they might be useful if targeted therapeutically.

cancer biology↗

Structural insights for neutralization of BA.1 and BA.2 Omicron variants by a broadly neutralizing SARS-CoV-2 antibody

The SARS-CoV-2 BA.1 and BA.2 (Omicron) variants contain more than 30 mutations within the spike protein and evade therapeutic monoclonal antibodies (mAbs). Here, we report a receptor-binding domain (RBD) targeting human antibody (002-S21F2) that effectively neutralizes live viral isolates of SARS-CoV-2 variants of concern (VOCs) including Alpha, Beta, Gamma, Delta, and Omicron (BA.1 and BA.2) with IC50 ranging from 0.02 - 0.05 g/ml. This near germline antibody 002-S21F2 has unique genetic features that are distinct from any reported SARS-CoV-2 mAbs. Structural studies of the full-length IgG in complex with spike trimers (Omicron and WA.1) reveal that 002-S21F2 recognizes an epitope on the outer face of RBD (class-3 surface), outside the ACE2 binding motif and its unique molecular features enable it to overcome mutations found in the Omicron variants. The discovery and comprehensive structural analysis of 002-S21F2 provide valuable insight for broad and potent neutralization of SARS-CoV-2 Omicron variants BA.1 and BA.2.

immunology↗

VAP-A intrinsically disordered regions enable versatile tethering at membrane contact sites

Membrane contact sites (MCSs) between organelles are heterogeneous in shape, composition and dynamics. Despite this diversity, VAP proteins act as receptors for multiple FFAT motif-containing proteins and drive the formation of most MCSs involving the endoplasmic reticulum (ER). Although the VAP-FFAT interaction is well characterized, no model explains how VAP adapts to its partners in various MCSs. We report here that VAP-A localization to different MCSs depends on its intrinsically disordered regions (IDRs). We show that VAP-A interaction with PTPIP51 and VPS13A at ER-mitochondria MCS conditions mitochondria fusion by promoting lipid transfer and cardiolipin buildup. VAP-A also enables lipid exchange at ER-Golgi MCS by interacting with OSBP and CERT. However, removing IDRs from VAP-A restricts its distribution and function to ER- mitochondria MCS, at the expense of ER-Golgi MCS. Our data suggest that IDRs of VAP-A do not modulate its preference towards specific partners, but adjust its geometry to the constraints linked to different MCS organization and lifetime. Thus, VAP-A conformational flexibility mediated by its IDRs ensures membrane tethering plasticity and efficiency.

cell biology↗

Targeted Sequencing of Alzheimers Disease Genes in Gujarat Cohort

Alzheimers Disease (AD) is the most common type of dementia affecting cognitive and behavioural functions. Its a complex disease that results from the modest effect of gene interaction and environmental factors, as a result of which its exact pathogenesis is still unknown. In the present study, we have performed an association study of exonic regions of 94 genes with AD using the Haloplex target enrichment method and genotyping of 4 genes NOTCH4(rs367398), NEP(rs61760379), APOE (rs121918398), and ATP7B(rs1801243) using PCR RFLP technique. In this study, we screened 32 AD cases and 11 control samples. We have identified 19 variants assigned to 16 genes that were significantly associated with AD with a p-value < 0.05. However, no variants have passed multiple test corrections except NOTCH4/rs367398 genotyped using the PCR-RFLP approach. The functional enrichment analysis of the significant genes for the disease indicates that the genes are significantly involved in AD. Also, functional enrichment analysis for biological processes using ClueGo and network analysis using the STRING database indicated that the genes are directly and indirectly playing a role in AD pathogenesis. The eQTL analysis of the variants with GTEx dataset indicate that out of 19 variants ACHE/rs1799806 and NOTCH4/rs367398 variants is showing significant eQTL for the neighbouring genes for different brain regions and whole blood. Regardless, additional studies with a large cohort are required to establish the role and prevalence of these variants in the local population of Gujarat.

genomics↗

Laboratory evolution of synthetic electron transport system variants reveals a larger metabolic respiratory system and its plasticity

Respiration requires organisms to have an electron transport system (ETS) for the generation of proton motive force across the membrane that drives ATP synthase. Although the molecular details of the ETS are well studied and constitute textbook material, few studies have appeared to elucidate its systems biology. The most thermodynamically efficient ETS consists of two enzymes, an NADH: quinone oxidoreductase (NqRED) and a dioxygen reductase (O2RED), which facilitate the shuttling of electrons from NADH to oxygen. However, evolution has produced variations within ETS which modulate the overall energy efficiency of the system even within the same organism 1-3. The system-level impact of these variations and their individual physiological optimality remain poorly determined. To mimic varying ETS efficiency we generated four Escherichia coli deletion strains (named ETS-1H, 2H, 3H, and 4H) harboring unbranched ETS variants that pump 1, 2, 3, or 4 proton(s) per electron respectively. We then used a combination of synergistic methods (laboratory evolution, multi-omic analyses, and computation of proteome allocation) to characterize these ETS variants. We found that: (a) all four ETS variants evolved to a similar optimized growth rate, (b) the evolution of ETS variants was enabled by specific rewiring of major energy-generating pathways that couple to the ETS to optimize their ATP production capability, (c) proteome allocation per ATP generated was the same for all the variants, (d) the aero-type, that designates the overall ATP generation strategy 4 of a variant, remained conserved during its laboratory evolution, with the exception of the ETS-4H variant, and (e) integrated computational analysis of then data supported a proton-to-ATP ratio of 10 protons per 3 ATP for ATP synthase for all four ETS variants. We thus have defined the Aero-Type System (ATS) as a generalization of the aerobic bioenergetics, which is descriptive of the metabolic systems biology of respiration and demonstrates its plasticity.

systems biology↗

Hyperbolic Geometry-Based Deep Learning Methods to Produce Population Trees from Genotype Data

The production of population-level trees using the genomic data of individuals is a fundamental task in the field of population genetics. Typically, these trees are produced using methods like hierarchical clustering, neighbor joining, or maximum likelihood. However, such methods are non-parametric: they require all data to be present at the time of tree formation, and the addition of new data points necessitates the regeneration of the entire tree, a potentially expensive process. They also do not easily integrate with larger workflows. In this study, we aim to address these problems by introducing parametric deep learning methods for tree formation from genotype data. Our models specifically create continuous representations of population trees in hyperbolic space, which has previously proven highly effective in embedding hierarchically structured data. We present two different architectures - a multi-layer perceptron (MLP) and a variational autoencoder (VAE) - and we analyze their performance using a variety of metrics along with comparisons to established tree-building methods. Both models tested produce embedding spaces that reflect human evolutionary history. In addition, we demonstrate the generalizability of these models by verifying that addition of new samples to an existing tree occurs in a semantically meaningful manner. Finally, we use Dasguptas Cost to compare the quality of trees generated by our models to those produced by established methods. Despite the fact that the benchmark methods are directly fit on the evaluation data, our models are able to outperform some of these and achieve highly comparable performance overall. Author summaryTree production is a vital task in population genetics, but current approaches fall prey to several common shortfalls. Most notably, they lack the ability to add new data points after tree generation, and they are often difficult to use in larger pipelines. By leveraging cutting-edge advances pairing deep learning with hyperbolic geometry, we develop multiple models designed to rectify these issues. Through experiments on a dataset of humans from globally widespread ancestries, we demonstrate the generalizability of our models to new data, and we also show strong empirical performance with respect to currently used methods. In addition, we show that the data representations produced by our models are semantically meaningful and reflect known facts about human evolutionary history. Finally, we discuss the additional benefits our models could provide, including improved visualization, greater privacy preservation, and improved integration with downstream machine learning tasks. In conclusion, we present models that are accurate, flexible, and generalizable, with the potential to facilitate a variety of further applications.

evolutionary biology↗

KAT5 activity regulates G0-like states in human gliomas

In solid tumors, G0-like states are likely critical for maintaining developmental hierarchies and cellular heterogeneity and promoting tumor growth/recurrence, yet little is known about tumor G0 states or regulation of their ingress/egress. To discover G0-like states and their regulators for glioblastoma (GBM), we analyzed G0 populations in an orthotopic model of GBM using single cell RNA-seq and performed a genome-wide CRISPR-Cas9 screen in patient-derived GBM stem-like cells (GSCs) for genes that trap cells in G0 when inhibited. We identify the protein acetyltransferase KAT5 as a key regulator of transcriptional, epigenetic, and proliferative heterogeneity impacting transitions into G0-like states. KAT5 activity suppresses the emergence of non-dividing subpopulations with oligodendrocyte progenitor and radial glial cell characteristics both in vitro and in a human GSC brain tumor model. In primary gliomas, KAT5 activity is dynamic with KAT5low tumor cells displaying quiescent properties, while KAT5 activity overall increases from low to high grade tumors and is associated with worse patient outcomes.

cancer biology↗

Single-cell multiome of the human retina and deep learning nominate causal variants in complex eye diseases

Genome-wide association studies (GWAS) of eye disorders have identified hundreds of genetic variants associated with ocular disease. However, the vast majority of these variants are noncoding, making it challenging to interpret their function. Here, we present a joint single-cell atlas of gene expression and chromatin accessibility of the adult human retina with >50,000 cells, which we used to analyze noncoding single-nucleotide polymorphisms (SNPs) implicated by GWAS of age-related macular degeneration, glaucoma, diabetic retinopathy, myopia, and type 2 macular telangiectasia. We integrate this atlas with a HiChIP enhancer connectome, expression quantitative trait loci (eQTL) data, and base-resolution deep learning models to predict noncoding SNPs with causal roles in eye disease, assess SNP impact on transcription factor binding, and define their known and novel target genes. Our efforts nominate pathogenic SNP-target gene interactions for multiple vision disorders and provide a potentially powerful resource for interpreting noncoding variation in the eye.

genomics↗

CDC50 orthologues in Plasmodium falciparum have distinct roles in merozoite egress and trophozoite maturation

In model organisms P4-ATPases require cell division control protein 50 (CDC50) chaperones for their phospholipid flipping activity. In the malaria parasite, P. falciparum, guanylyl cyclase alpha (GC) is an integral membrane protein that is essential for release (egress) of merozoites from their host erythrocytes. GC is unusual in that it contains both a C-terminal cyclase domain and an N-terminal P4-ATPase domain of unknown function. We sought to investigate whether any of the three CDC50 orthologues (denoted A, B and C) encoded by P. falciparum are required for GC function. Using gene tagging and conditional gene disruption, we demonstrate that both CDC50B and CDC50C are expressed in the clinically important asexual blood stages and that CDC50B is a binding partner of GC whereas CDC50C is the binding partner of another putative P4-ATPase, ATP2. Our findings indicate that CDC50B has no essential role for intraerythrocytic parasite maturation but modulates the rate of parasite egress by interacting with GC for optimal cGMP synthesis. In contrast, CDC50C is essential for blood stage trophozoite maturation. Additionally, we find that the CDC50C-ATP2 complex may influence parasite endocytosis of host cell haemoglobin and consequently hemozoin formation.

molecular biology↗